The Role of Trust in Narrowing Protection Gaps

The Geneva Association 2018 Customer Survey in 7 mature economies reveals that for half of the respondents, increased levels of trust in insurers and intermediaries would encourage additional insurance purchases, a consistent finding across all age groups. In emerging markets this share is expected to be even higher, given a widespread lack of experience with financial institutions, the relatively low presence of well-known and trusted insurer brands and a number of structural legal and regulatory shortcomings.

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Against this backdrop, a comprehensive analysis of the role and nature of trust in insurance, with a focus on the retail segment, is set to offer additional important insights into how to narrow the protection gap—the difference between needed and available protection—through concerted multi-stakeholder efforts.

The analysis is based on economic definitions of trust, viewed as an ’institutional economiser’ that facilitates or even eliminates the need for various procedures of verification and proof, thereby cutting transaction costs.

In the more specific context of insurance, trust can be defined as a customer’s bet on an insurer’s future contingent actions, ranging

  • from paying claims
  • to protecting personal data
  • and ensuring the integrity of algorithms.

Trust is the lifeblood of insurance business, as its carriers sell contingent promises to pay, often at a distant and unspecified point in the future.

From that perspective, we can explore the implications of trust for both insurance demand and supply, i.e. its relevance to the size and nature of protection gaps. For example, trust influences behavioural biases such as customers’ propensity for excessive discounting, or in other words, an irrationally high preference for money today over money tomorrow that dampens demand for insurance. In addition, increased levels of trust lower customers’ sensitivity to the price of coverage.

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Trust also has an important influence on the supply side of insurance. The cost loadings applied by insurers to account for fraud are significant and lead to higher premiums for honest customers. Enhanced insurer trust in their customers’ prospective honesty would enable

  • lower cost loadings,
  • less restrictive product specifications
  • and higher demand for insurance.

The potential for lower cost loadings is significant. In the U.S. alone, according to the Insurance Information Institute (2019), fraud in the property and casualty sector is estimated to cost the insurance industry more than USD 30 billion annually, about 10% of total incurred losses and loss adjustment expenses.

Another area where trust matters greatly to the supply of insurance coverage is asymmetric information. A related challenge is moral hazard, or the probability of a person exercising less care in the presence of insurance cover. In this context, however, digital technologies and modern analytics are emerging as potentially game-changing forces. Some pundits herald the end of the age of asymmetric information and argue that a proliferation of information will

  • counter adverse selection and moral hazard,
  • creating transparency (and trust) for both insurers and insureds
  • and aligning their respective interests.

Other experts caution that this ‘brave new world’ depends on the development of customers’ future privacy preferences.

One concrete example is the technology-enabled rise in peer-to-peer trust and the amplification of word-of-mouth. This general trend is now entering the world of insurance as affinity groups and other communities organise themselves through online platforms. In such business models, trust in incumbent insurance companies is replaced with trust in peer groups and the technology platforms that organise them. Another example is the blockchain. In insurance, some start-ups have pioneered the use of blockchain to improve efficiency, transparency and trust in unemployment, property and casualty, and travel insurance, for example. In more advanced markets, ecosystem partners can serve as another example of technology-enabled trust influencers.

These developments are set to usher in an era in which customer data will be a key source of competitive edge. Therefore, gaining and maintaining customers’ trust in how data is used and handled will be vitally important for insurers’ reputations. This also applies to the integrity and interpretability of artificial intelligence tools, given the potential for biases to be embedded in algorithms.

In spite of numerous trust deficits, insurers appear to be in a promising position to hold their own against technology platforms, which are under increasing scrutiny for dubious data handling practices. According to the Geneva Association 2018 Customer Survey, only 3% of all respondents (and 7% of the millennials) polled name technology platforms as their preferred conduits for buying insurance. Insurers’ future performance, in terms of responsible data handling and usage as well as algorithm building, will determine whether their current competitive edge is sustainable. It should not be taken for granted, as—especially in high-growth markets—the vast majority of insurance customers would at least be open to purchasing insurance from new entrants.

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In order to substantiate a multi-stakeholder road map for narrowing protection gaps through fostering trust, we propose a triangle of determinants of trust in insurance.

  1. First, considering the performance of insurers, how an insurer services a policy and settles claims is core to building or destroying trust.
  2. Second, regarding the performance of intermediaries, it is intuitively plausible that those individuals and organisations at the frontline of the customer interface are critically important to the reputation and the level of trust placed in the insurance carrier.
  3. And third, taking into account sociodemographic factors, most recent research finds that trust in insurance is higher among females.

This research also suggests that trust in insurance decreases with age, and insurance literacy has a strong positive influence on the level of trust in insurance.

Based on this paper’s theoretical and empirical findings, we propose the following road map for ensuring that insurance markets are optimally lubricated with trust. This road map includes 3 stakeholder groups that need to act in concert: insurers (and their intermediaries), customers, and regulators/ lawmakers.

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In order for insurers and their intermediaries to bolster customer trust—and enhance their contribution to society—we recommend they do the following:

  • Streamline claims settlement with processes that differentiate between honest and (potentially) dishonest customers. Delayed claims settlement, which may be attributable to procedures needed for potentially fraudulent customer behaviour, causes people to lose trust in insurers and is unfair to honest customers.
  • Increase product transparency and simplicity, with a focus on price and value. Such efforts could include aligning incentives through technology-enabled customer engagement and utilising data and analytics for simpler and clearer underwriting procedures. This may, however, entail delicate trade-offs between efficiency and privacy.
  • ‘Borrow’ trust: As a novel approach, insurers may partner with non-insurance companies or influencers to access new customers through the implied endorsement of a trusted brand or individual. Such partnerships are also essential to extending the business model of insurance beyond its traditional centre of gravity, which is the payment of claims.

Customers and their organisations are encouraged to undertake the following actions:

  • Support collective action against fraud. Insurance fraud hinders mutual trust and drives cost loadings, which are unfair to honest customers and lead to suboptimal levels of aggregate demand.
  • Engage with insurers who leverage personal data for the benefit of the customer. When insurers respond to adverse selection, they increase rates for everyone in order to cover their losses. This may cause low-risk customers to drop out of the company’s risk pool and forego coverage. ‘Real time’ underwriting methods and modern analytics are potential remedies to the undesirable effects of adverse selection.

Recommendations for policymakers and regulators are the following:

  • Protect customers. Effective customer protection is indispensable to lubricating insurance markets with trust. First, regulators should promote access to insurance through regulations that interfere with the market mechanism for rate determination or through more subtle means, such as restrictions on premium rating factors. Second, regulators should make sure that insurers have the ability to pay claims and remain solvent. This may involve timely prudential regulatory intervention.
  • Promote industry competition. There is a positive correlation between an insurance market’s competitiveness and levels of customer trust. In a competitive market, the cost to customers for switching from an underperforming insurance carrier to a more favourable competitor is relatively low. However, the cost of customer attrition for insurers is high. Therefore, in a competitive market, the onus is on insurers to perform well and satisfy customers.

Click here to access Geneva Association’s Research Debrief

 

Overview on EIOPA Consultation Paper on the Opinion on the 2020 review of Solvency II

The Solvency II Directive provides that certain areas of the framework should be reviewed by the European Commission at the latest by 1 January 2021, namely:

  • long-term guarantees measures and measures on equity risk,
  • methods, assumptions and standard parameters used when calculating the Solvency Capital Requirement standard formula,
  • Member States’ rules and supervisory authorities’ practices regarding the calculation of the Minimum Capital Requirement,
  • group supervision and capital management within a group of insurance or reinsurance undertakings.

Against that background, the European Commission issued a request to EIOPA for technical advice on the review of the Solvency II Directive in February 2019 (call for advice – CfA). The CfA covers 19 topics. In addition to topics that fall under the four areas mentioned above, the following topics are included:

  • transitional measures
  • risk margin
  • Capital Markets Union aspects
  • macroprudential issues
  • recovery and resolution
  • insurance guarantee schemes
  • freedom to provide services and freedom of establishment
  • reporting and disclosure
  • proportionality and thresholds
  • best estimate
  • own funds at solo level

EIOPA is requested to provide technical advice by 30 June 2020.

Executive summary

This consultation paper sets out technical advice for the review of Solvency II Directive. The advice is given in response to a call for advice from the European Commission. EIOPA will provide its final advice in June 2020. The call for advice comprises 19 separate topics. Broadly speaking, these can be divided into three parts.

  1. Firstly, the review of the long term guarantee measures. These measures were always foreseen as being reviewed in 2020, as specified in the Omnibus II Directive. A number of different options are being consulted on, notably on extrapolation and on the volatility adjustment.
  2. Secondly, the potential introduction of new regulatory tools in the Solvency II Directive, notably on macro-prudential issues, recovery and resolution, and insurance guarantee schemes. These new regulatory tools are considered thoroughly in the consultation.
  3. Thirdly, revisions to the existing Solvency II framework including in relation to
    • freedom of services and establishment;
    • reporting and disclosure;
    • and the solvency capital requirement.

Given that the view of EIOPA is that overall the Solvency II framework is working well, the approach here has in general been one of evolution rather than revolution. The principal exceptions arise as a result either of supervisory experience, for example in relation to cross-border business; or of the wider economic context, in particular in relation to interest rate risk. The main specific considerations and proposals of this consultation paper are as follows:

  • Considerations to choose a later starting point for the extrapolation of risk-free interest rates for the euro or to change the extrapolation method to take into account market information beyond the starting point.
  • Considerations to change the calculation of the volatility adjustment to risk-free interest rates, in particular to address overshooting effects and to reflect the illiquidity of insurance liabilities.
  • The proposal to increase the calibration of the interest rate risk submodule in line with empirical evidence. The proposal is consistent with the technical advice EIOPA provided on the Solvency Capital Requirement standard formula in 2018.
  • The proposal to include macro-prudential tools in the Solvency II Directive.
  • The proposal to establish a minimum harmonised and comprehensive recovery and resolution framework for insurance.

A background document to this consultation paper includes a qualitative assessment of the combined impact of all proposed changes. EIOPA will collect data in order to assess the quantitative combined impact and to take it into account in the decision on the proposals to be included in the advice. Beyond the changes on interest rate risk EIOPA aims in general for a balanced impact of the proposals.

The following paragraphs summarise the main content of the consulted advice per chapter.

Long-term guarantees measures and measures on equity risk

EIOPA considers to choose a later starting point for the extrapolation of risk-free interest rates for the euro or to change the extrapolation method to take into account market information beyond the starting point. Changes are considered with the aim to avoid the underestimation of technical provisions and wrong risk management incentives. The impact on the stability of solvency positions and the financial stability is taken into account. The paper sets out two approaches to calculate the volatility adjustment to the risk-free interest rates. Both approaches include application ratios to mitigate overshooting effects of the volatility adjustment and to take into account the illiquidity characteristics of the insurance liabilities the adjustment is applied to.

  • One approach also establishes a clearer split between a permanent component of the adjustment and a macroeconomic component that only exists in times of wide spreads.

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  • The other approach takes into account the undertakings-specific investment allocation to further address overshooting effects.

EIOPA3

Regarding the matching adjustment to risk-free interest rates the proposal is made to recognise in the Solvency Capital Requirement standard formula diversification effects with regard to matching adjustment portfolios. The advice includes proposals to strengthen the public disclosure on the long term guarantees measures and the risk management provisions for those measures.

EIOPA1

The advice includes a review of the capital requirements for equity risk and proposals on the criteria for strategic equity investments and the calculation of long-term equity investments. Because of the introduction of the capital requirement on long-term equity investments EIOPA intends to advise that the duration-based equity risk sub-module is phased out.

Technical provisions

EIOPA identified a larger number of aspects in the calculation of the best estimate of technical provisions where divergent practices among undertakings or supervisors exist. For some of these issues, where EIOPA’s convergence tools cannot ensure consistent practices, the advice sets out proposals to clarify the legal framework, mainly on

  • contract boundaries,
  • the definition of expected profits in future premiums
  • and the expense assumptions for insurance undertakings that have discontinued one product type or even their whole business.

With regard to the risk margin of technical provisions transfer values of insurance liabilities, the sensitivity of the risk margin to interest rate changes and the calculation of the risk margin for undertakings that apply the matching adjustment or the volatility adjustment were analysed. The analysis did not result in a proposal to change the calculation of the risk margin.

Own funds

EIOPA has reviewed the differences in tiering and limits approaches within the insurance and banking framework, utilising quantitative and qualitative assessment. EIOPA has found that they are justifiable in view of the differences in the business of both sectors.

EIOPA4

Solvency Capital Requirement standard formula

EIOPA confirms its advice provided in 2018 to increase the calibration of the interest rate risk sub-module. The current calibration underestimates the risk and does not take into account the possibility of a steep fall of interest rate as experienced during the past years and the existence of negative interest rates. The review

  • of the spread risk sub-module,
  • of the correlation matrices for market risks,
  • the treatment of non-proportional reinsurance,
  • and the use of external ratings

did not result in proposals for change.

Minimum Capital Requirement

Regarding the calculation of the Minimum Capital Requirement it is suggested to update the risk factors for non-life insurance risks in line with recent changes made to the risk factors for the Solvency Capital Requirement standard formula. Furthermore, proposals are made to clarify the legal provisions on noncompliance with the Minimum Capital Requirement.

EIOPA5

Reporting and disclosure

The advice proposes changes to the frequency of the Regular Supervisory Report to supervisors in order to ensure that the reporting is proportionate and supports risk-based supervision. Suggestions are made to streamline and clarify the expected content of the Regular Supervisory Report with the aim to support insurance undertakings in fulfilling their reporting task avoiding overlaps between different reporting requirements and to ensure a level playing field. Some reporting items are proposed for deletion because the information is also available through other sources. The advice includes a review of the reporting templates for insurance groups that takes into account earlier EIOPA proposals on the templates of solo undertakings and group specificities.

EIOPA proposes an auditing requirement for balance sheet at group level in order to improve the reliability and comparability of the disclosed information. It is also suggested to delete the requirement to translate the summary of that report.

Proportionality

EIOPA has reviewed the rules for exempting insurance undertakings from the Solvency II Directive, in particular the thresholds on the size of insurance business. As a result, EIOPA proposes to maintain the general approach to exemptions but to reinforce proportionality across the three pillars of the Solvency II Directive.

Regarding thresholds EIOPA proposes to double the thresholds related to technical provisions and to allow Member States to increase the current threshold for premium income from the current amount of EUR 5 million to up to EUR 25 million.

EIOPA had reviewed the simplified calculation of the standard formula and proposed improvements in 2018. In addition to that the advice includes proposals to simplify the calculation of the counterparty default risk module and for simplified approaches to immaterial risks. Proposals are made to improve the proportionality of the governance requirements for insurance and reinsurance undertakings, in particular on

  • key functions (cumulation with operational functions, cumulation of key functions other than the internal audit, cumulation of key and AMSB function)
  • own risk and solvency assessment (ORSA) (biennial report),
  • written policies (review at least once every three years)
  • and administrative, management and supervisory bodies (AMSB) ( evaluation shall include an assessment on the adequacy of the composition, effectiveness and internal governance of the administrative, management or supervisory body taking into account the nature, scale and complexity of the risks inherent in the undertaking’s business)

Proposals to improve the proportionality in reporting and disclosure of Solvency II framework were made by EIOPA in a separate consultation in July 2019.

Group supervision

EIOPA proposes a number of regulatory changes to address the current legal uncertainties regarding supervision of insurance groups under the Solvency II Directive. This is a welcomed opportunity as the regulatory framework for groups was not very specific in many cases while in others it relies on the mutatis mutandis application of solo rules without much clarifications.

In particular, there are policy proposals to ensure that the

  • definitions applicable to groups,
  • scope of application of group supervision
  • and supervision of intragroup transactions, including issues with third countries

are consistent.

Other proposals focus on the rules governing the calculation of group solvency, including own funds requirements as well as any interaction with the Financial Conglomerates Directive. The last section of the advice focuses on the uncertainties related to the application of governance requirements at group level.

Freedom to provide services and freedom of establishment

EIOPA further provides suggestions in relation to cross border business, in particular to support efficient exchange of information among national supervisory authorities during the process of authorising insurance undertakings and in case of material changes in cross-border activities. It is further recommended to enhance EIOPA’s role in the cooperation platforms that support the supervision of cross-border business.

Macro-prudential policy

EIOPA proposes to include the macroprudential perspective in the Solvency II Directive. Based on previous work, the advice develops a conceptual approach to systemic risk in insurance and then analyses the current existing tools in the Solvency II framework against the sources of systemic risk identified, concluding that there is the need for further improvements in the current framework.

EIOPA7

Against this background, EIOPA proposes a comprehensive framework, covering the tools initially considered by the European Commission (improvements in Own Risk and Solvency Assessment and the prudent person principle, as well as the drafting of systemic risk and liquidity risk management plans), as well as other tools that EIOPA considers necessary to equip national supervisory authorities with sufficient powers to address the sources of systemic risk in insurance. Among the latter, EIOPA proposes to grant national supervisory authorities with the power

  • to require a capital surcharge for systemic risk,
  • to define soft concentration thresholds,
  • to require pre-emptive recovery and resolution plans
  • and to impose a temporarily freeze on redemption rights in exceptional circumstances.

EIOPA8

Recovery and resolution

EIOPA calls for a minimum harmonised and comprehensive recovery and resolution framework for (re)insurers to deliver increased policyholder protection and financial stability in the European Union. Harmonisation of the existing frameworks and the definition of a common approach to the fundamental elements of recovery and resolution will avoid the current fragmented landscape and facilitate cross-border cooperation. In the advice, EIOPA focuses on the recovery measures including the request for pre-emptive recovery planning and early intervention measures. Subsequently, the advice covers all relevant aspects around the resolution process, such as

  • the designation of a resolution authority,
  • the resolution objectives,
  • the need for resolution planning
  • and for a wide range of resolution powers to be exercised in a proportionate way.

The last part of the advice is devoted to the triggers for

  • early intervention,
  • entry into recovery and into resolution.

EIOPA9

Other topics of the review

The review of the ongoing appropriateness of the transitional provisions included in the Solvency II Directive did not result in a proposal for changes. With regard to the fit and proper requirements of the Solvency II Directive EIOPA proposes to clarify the position of national supervisory authorities on the ongoing supervision of propriety of board members and that they should have effective powers in case qualifying shareholders are not proper. Further advice is provided in order to increase the efficiency and intensity of propriety assessments in complex cross-border cases by providing the possibility of joint assessment and use of EIOPA’s powers to assist where supervisors cannot reach a common view.

Click here to access EIOPA’s detailed Consultation Paper

Mastering Financial Customer Data at Multinational Scale

Your Customer Data…Consolidated or Chaotic?

In an ideal world, you know your customers. You know

  • who they are,
  • what business they transact,
  • who they transact with,
  • and their relationships.

You use that information to

  • calculate risk,
  • prevent fraud,
  • uncover new business opportunities,
  • and comply with regulatory requirements.

The problem at most financial institutions is that customer data environments are highly chaotic. Customer data is stored in numerous systems across the company. Most, if not all of which, has evolved over time in siloed environments according to business function. Each system has its

  • own management team,
  • technology platform,
  • data models,
  • quality issues,
  • and access policies.

Tamr1

This chaos prevents the firms from fully achieving and maintaining a consolidated view of customers and their activity.

The Cost of Chaos

A chaotic customer data environment can be an expensive problem in a financial institution. Customer changes have to be implemented in multiple systems, with a high likelihood of error or inconsistency because of manual processes. Discrepancies with the data leads to inevitable remediation activities that are widespread, and costly.

Analyzing customer data within one global bank required three months to compile and validate its correctness. The chaos leads to either

  1. prohibitively high time and cost of data preparation or
  2. garbage-in, garbage-out analytics.

The result of customer data chaos is an incredibly high risk profile — operational, regulatory, and reputational.

Eliminating the Chaos 1.0

Many financial services companies attempt to eliminate this chaos and consolidate their customer data.

A common approach is to implement a master data management (MDM) system. Customer data from different source systems is centralized into one place where it can be harmonized. The output is a “golden record,” or master customer record.

A lambda architecture permits data to stream into the centralized store and be processed in realtime so that it is immediately mastered and ready for use. Batch processes run on the centralized store to perform periodic (daily, monthly, quarterly, etc.) calculations on the data.

First-generation MDM systems centralize customer data and unify it by writing ETL scripts and matching rules.

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The harmonizing often involves:

  1. Defining a common, master schema in which to store the consolidated data
  2. Writing ETL scripts to transform the data from source formats and schemas into the new common storage format
  3. Defining rule sets to deduplicate, match/cluster, and otherwise cleanse within the central MDM store

There are a number of commercial MDM solutions available that support the deterministic approach outlined above. The initial experience with those MDM systems, integrating the first five or so large systems, is often positive. Scaling MDM to master more and more systems, however, becomes a challenge that grows exponentially, as we’ll explain below.

Rules-based MDM, and the Robustness- Versus-Expandability Trade Off

The rule sets used to harmonize data together are usually driven off of a handful of dependent attributes—name, legal identifiers, location, and so on. Let’s say you use six attributes to stitch together four systems, A and B, and then the same six attributes between A and C, then A and D, B and C, B and D, and C and D. Within that example of 4 systems, you would have twenty four potential attributes that you are aligning. Add a fifth system, it’s 60 attributes; a sixth system, 90 attributes. So the effort to master additional systems grows exponentially. And in most multinational financial institutions, the number of synchronized attributes is not six; it’s commonly 50 to 100.

And maintenance is equally burdensome. There’s no guarantee that your six attributes maintain their validity or veracity over time. If any of these attributes need to be modified, then rules need to be redefined across the systems all over again.

The trade off for many financial institutions is robustness versus expandability. In other words, you can have a large-scale data mastering implementation and have it wildly complex, or you can do something small and have it highly accurate.

This is problematic for most financial institutions, which have very large-scale customer data challenges.

Customer Data Mastering at Scale

In larger financial services companies, especially multinationals, the number of systems in which customer data resides is much larger than the examples above. It is not uncommon to see financial companies with over 100 large systems.

Among those are systems that have been:

  • Duplicated in many countries to comply with data sovereignty regulations
  • Acquired via inorganic growth, purchased companies bringing in their own infrastructure for trading, CRM, HR, and back office. Integrating these can take a significant amount of time and cost

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When attempting to master a hundred sources containing petabytes of data, all of which have data linking and matching in different ways across a multitude of attributes and systems, you can see that the matching rules required to harmonize your data together gets incredibly complex.

Every incremental source added to the MDM environment can take thousands of rules to be implemented. Within just a mere handful of systems, the complexity gets to a point where it’s unattainable. As that complexity goes up, the cost of maintaining a rules-based approach also scales wildly, requiring more and more data stewards to make sure all the stitching rules remain correct.

Mastering data at scale is one of the riskiest endeavors a business can take. Gartner reports that 85% of MDM projects fail. And MDM budgets of $10M to $20M per year are not uncommon in large multinationals. With such high stakes, making sure that you get the right approach is critical to making sure that this thing is a success.

A New Take on an Old Paradigm

What follows is a reference architecture. The approach daisy chains together three large tool sets, each with appropriate access policies enforced, that are responsible for three separate steps in the mastering process:

  1. Raw Data Zone
  2. Common Data Zone
  3. Mastered Data Zone

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Raw Data Zone The first sits on a traditional data lake model—a landing area for raw data. Data is replicated from source systems to the centralized data repository (often built on Hadoop). Data is replicated in real time (perhaps via Kafka) wherever possible so that data is most up to date. For source systems that do not support real-time replication, nightly batch jobs or flat-file ingestion are used.

Common Data Zone Within the Common Data Zone, we take all of the data from the Raw Zone—with the various different objects, in different shapes and sizes, and conform that into outputs that look and feel the same to the system, with the same column headers, data types, and formats.

The toolset in this zone utilizes machine learning models to categorize data that exists within the Raw Data Zone. Machine learning models are trained on what certain attributes look like—what’s a legal entity, or a registered address, or country of incorporation, or legal hierarchy, or any other field. It does so without requiring anyone having to go back to the source system owners to bog them down with questions about that, saving weeks of effort.

This solution builds up a taxonomy and schema for the conformed data as raw data is processed. Unlike early-generation MDM solutions, this substantially reduces data unification time, often by months per source system, because there is:

  • No need to pre-define a schema to hold conformed data
  • No need to write ETL to transform the raw data

One multinational bank implementing this reference architecture reported being able to conform the raw data from a 10,000-table system within three days, and without using up source systems experts’ time defining a schema or writing ETL code. In terms of figuring out where relevant data is located in the vast wilderness this solution is very productive and predictable.

Mastered Data Zone In the third zone, the conformed data is mastered, and the outputs of the mastering process are clusters of records that refer to the same real-world entity. Within each cluster, a single, unified golden, master record of the entity is configured. The golden customer record is then distributed to wherever it’s needed:

  • Data warehouses
  • Regulatory (KYC, AML) compliance systems
  • Fraud and corruption monitoring
  • And back to operational systems, to keep data changes clean at the source

As with the Common Zone, machine learning models are used. These models eliminate the need to define hundreds of rules to match and deduplicate data. Tamr’s solution applies a probabilistic model that uses statistical analysis and naive Bayesian modeling to learn from existing relationships between various attributes, and then makes record-matching predictions based on these attribute relationships.

Tamr matching models require training, which usually takes just a few days per source system. Tamr presents a data steward with its predictions, and the steward can either confirm or deny them to help Tamr perfect its matching.

With the probabilistic model, Tamr looks at all of the attributes on which it has been trained, and based on the attribute matching, the solution will indicate a confidence level of a match being accurate. Depending on a configurable confidence level threshold, It will disregard entries that fall below the threshold from further analysis and training.

As you train Tamr and correct it, it becomes more accurate over time. The more data you throw at te solution, the better it gets. Which is a stark contrast to the rules-based MDM approach, where the more data you throw at it, it tends to break because the rules can’t keep up with the level of complexity.

Distribution A messaging bus (e.g., Apache Kafka) is often used to distribute mastered customer data throughout the organization. If a source system wants to pick up the master copy from the platform, it subscribes to that topic on the messaging bus to receive the feed of changes.

Another approach is to pipeline deltas from the MDM platform into target system in batch.

Real-world Results

This data mastering architecture is in production at a number of large financial institutions. Compared with traditional MDM approaches, the model-driven approach provides the following advantages:

70% fewer IT resources required:

  • Humans in the entity resolution loop are much more productive, focused on a relatively small percentage (~5%) of exceptions that the machine learning algorithms cannot resolve
  • Eliminates ETL and matching rules development
  • Reduces manual data synchronization and remediation of customer data across systems

Faster customer data unification:

  • A global retail bank mastered 35 large IT systems within 6 months—about 4 days per source system
  • New data is mastered within 24 hours of landing in the Raw Data Zone
  • A platform for mastering any category of data—customer, product, suppler, and others

Faster, more complete achievement of data-driven business initiatives:

  • KYC, AML, fraud detection, risk analysis, and others.

 

Click here to access Tamr’s detailed analysistamr4

An Animal Kingdom Of Disruptive Risks -How boards can oversee black swans, gray rhinos, and white elephants

Where was the board? As a corporate director, imagine you find yourself in one of these difficult situations:

  • Unexpected financial losses mount as your bank faces a sudden collapse during a 1-in-100-year economic crisis.
  • Customers leave and profits drop year after year as a new technology start-up takes over your No. 1 market position.
  • Negative headlines and regulatory actions besiege your company following undesirable tweets and other belligerent behavior from the CEO.

These scenarios are not hard to imagine when you consider what unfolded before the boards of Lehman Brothers, Blockbuster, Tesla, and others. In the context of disruptive risks, these events can be referred to as black swans, gray rhinos, and white elephants, respectively. While each has unique characteristics, the commonality is that all of these risks can have a major impact on a company’s profitability, competitive position, and reputation.

In a VUCA (volatile, uncertain, complex, and ambiguous) world, boards need to expand their risk governance and oversight to include disruptive risks. This article addresses three fundamental questions:

  • What are black swans, gray rhinos, and white elephants?
  • Why are they so complex and difficult to deal with?
  • How should directors incorporate these disruptive risks as part of their oversight?

Why are companies so ill prepared for disruptive risks? There are three main challenges:

  1. standard enterprise risk management (ERM) programs may not capture them;
  2. they each present unique characteristics and complexities;
  3. and cognitive biases prevent directors and executives from addressing them.

Standard tools used in ERM, including risk assessments and heat maps, are not timely or dynamic enough to capture unconventional and atypical risks. Most risk quantification models—such as earnings volatility and value-at-risk models—measure potential loss within a 95 percent or 99 percent confidence level. Black swan events, on the other hand, may have a much smaller than 0.1 percent chance of happening. Gray rhinos and white elephants are atypical risks that may have no historical precedent or operational playbooks. As such, disruptive risks may not be adequately addressed in standard ERM programs even if they have the potential to destroy the company. The characteristics and complexities of each type of disruptive risk are unique. The key challenge with black swans is prediction. They are outliers that were previously unthinkable. That is not the case with gray rhinos, since they are generally observable trends. With gray rhinos the main culprit is inertia: companies see the megatrends charging at them, but they can’t seem to mitigate the risk or seize the opportunity. The key issue with white elephants is subjectivity. These no-win situations are often highly charged with emotions and conflicts. Doing nothing is usually the easiest choice but leads to the worst possible outcome. While it is imperative to respond to disruptive risks, cognitive biases can lead to systematic errors in decision making. Behavioral economists have identified dozens of biases, but several are especially pertinent in dealing with disruptive risks:

  • Availability and hindsight bias is the underestimation of risks that we have not experienced and the overestimation of risks that we have. This bias is a key barrier to acknowledging atypical risks until it is too late.
  • Optimism bias is a tendency to overestimate the likelihood of positive outcomes and to underestimate the likelihood of negative outcomes. This is a general issue for risk management, but it is especially problematic in navigating disruptive risks.
  • Confirmation bias is the preference for information that is consistent with one’s own beliefs. This behavior prevents us from processing new and contradictory information, or from responding to early signals.
  • Groupthink or herding occurs when individuals strive for group consensus at the cost of objective assessment of alternative viewpoints. This is related to the sense of safety in being part of a larger group, regardless if their actions are rational or not.
  • Myopia or short-termism is the tendency to have a narrow view of risks and a focus on short-term results (e.g., quarterly earnings), resulting in a reluctance to invest for the longer term.
  • Status quo bias is a preference to preserve the current state. This powerful bias creates inertia and stands in the way of appropriate actions.

To overcome cognitive biases, directors must recognize that they exist and consider how they impact decision making. Moreover,

  • board diversity,
  • objective data,
  • and access to independent experts

can counter cognitive biases in the boardroom.

Recommendations for Consideration

How should directors help their organizations navigate disruptive risks? They can start by asking the right questions in the context of the organization’s business model and strategy. The chart below lists 10 questions that directors can ask themselves and management.

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In addition, directors should consider the following five recommendations to enhance their risk governance and oversight:

  1. Incorporate disruptive risks into the board agenda. The full board should discuss the potential impact of disruptive risks as part of its review of the organization’s strategy to create sustainable long-term value. Disruptive risks may also appear on the agenda of key committees, including the risk committee’s assessment of enterprise risks, the audit committee’s review of risk disclosures, the compensation committee’s determination of executive incentive plans, and the governance committee’s processes for addressing undesirable executive behavior. The key is to explicitly incorporate disruptive risks into the board’s oversight and scope of work.
  2. Ensure that fundamental ERM practices are effective. Fundamental ERM practices—risk policy and analytics, management strategies, and metrics and reporting—provide the baseline from which disruptive risks can be considered. As an example, the definition of risk appetite can inform discussions of loss tolerance relative to disruptive risks. As an early step, the board should ensure that the overall ERM framework is robust and effective. Otherwise, the organization may fall victim to “managing risk by silo” and miss critical interdependencies between disruptive risks and other enterprise risks.
  3. Consider scenario planning and analysis. Directors should recognize that basic ERM tools may not fully capture disruptive risks. They should consider advocating for, and participating in, scenario planning and analysis. This is akin to tabletop exercises for cyber-risk events, except much broader in scope. Scenario analysis can be a valuable tool to help companies put a spotlight on hidden risks, generate strategic insights on performance drivers, and identify appropriate actions for disruptive trends. The objective is not to predict the future, but to identify the key assumptions and sensitivities in the company’s business model and strategy. In addition to scenario planning, dynamic simulation models and stress-testing exercises should be considered.
  4. Ensure board-level risk metrics and reports are effective. The quality of risk reports is key to the effectiveness of board risk oversight. Standard board risk reports often are comprised of insufficient information: historical loss and event data, qualitative risk assessments, and static heat maps. An effective board risk report should include quantitative analyses of risk impacts to earnings and value, key risk metrics measured against risk appetite, and forwardlooking information on emerging risks. By leveraging scenario planning, the following reporting components can enhance disruptive risk monitoring:
    • Market intelligence data that provides directors with useful “outside-in” information, including key business and industry developments, consumer and technology trends, competitive actions, and regulatory updates.
    • Enterprise performance and risk analysis including key performance and risk indicators that quantify the organization’s sensitivities to disruptive risks.
    • Geo-mapping that highlights global “hot spots” for economic, political, regulatory, and social instability. This can also show company-specific risks such as third-party vendor, supply chain, and cybersecurity issues.
    • Early-warning indicators that provide general or scenariospecific signals with respect to risk levels, effectiveness of controls, and external drivers.
    • Action triggers and plans to facilitate timely discussions and decisions in response to disruptive risks.
  5. Strengthen board culture and governance. To effectively oversee disruptive risks, the board must be fit for purpose. This requires creating a board culture that considers nontraditional views, questions key assumptions, and supports continuous improvement. Good governance practices should be in place in the event a white elephant appears. For example, what is the board protocol and playbook if the CEO acts inappropriately? In the United States, the 25th Amendment and impeachment clauses are in place ostensibly to remove a reprehensible president. Does the organization have procedures to remove a reprehensible CEO?

The following chart summarizes the key characteristics, examples, indicators, and strategies for identifying and addressing black swans, gray rhinos, and white elephants. The end goal should be to enhance oversight of disruptive risks and counter the specific challenges that are presented. To mitigate the unpredictability of black swans, the company should develop contingency plans with a focus on preparedness. To overcome inertia and deal with gray rhinos, the company needs to establish organizational processes and incentives to increase agility. To balance subjectivity and confront white elephants, directors should invest in good governance and objective input that will support decisiveness.

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The Opportunity for Boards

In a VUCA world, corporate directors must expand their traditional risk oversight beyond well-defined strategic, operational, and financial risks. They must consider atypical risks that are hard to predict, easy to ignore, and difficult to address. While black swans, gray rhinos, and white elephants may sound like exotic events, directors could enhance their recognization of them by reflecting on their own experiences serving on boards.

Given their experiences, directors should provide a leading voice to improve oversight of disruptive risks. They have a comparative advantage in seeing the big picture based on the nature of their work— part time, detached from day-to-day operations, and with experience gained from serving different companies and industries. Directors can add significant value by providing guidance to management and helping them see the forest for the trees. Finally, there is an opportunity side to risk. There are positive and negative black swans. A company can invest in the positive ones and be prepared for the negative ones. For every company that is trampled by a gray rhino, another company is riding it to a higher level of performance. By addressing the white elephant in the boardroom, a company can remediate an unspoken but serious problem. In the current environment, board oversight of disruptive risks represents both a risk management imperative and a strategic business opportunity.

Click here to access NACD’s summary

EIOPA outlines key financial stability risks of the European insurance and pensions sector

The global and European economic outlook has deteriorated in the past months with weakening industrial production and business sentiment and ongoing uncertainties about trade disputes and Brexit. In particular, the “low for long” risk has resurfaced in the EU, as interest rates reached record lows in August 2019 and an increasing number of countries move into negative yield territory for their sovereign bonds even at longer maturities in anticipation of a further round of monetary easing by central banks and a general flight to safety. Bond yields and swap rates have since slightly recovered again, but protracted low interest rates form the key risk for both insurers and pension funds and put pressure on both the capital position and long-term profitability. Large declines in interest rates can also create further incentives for insurers and pension funds to search for yield, which could add to the build-up of vulnerabilities in the financial sector if not properly managed.

Despite the challenging environment, the European insurance sector remains overall well capitalized with a median SCR ratio of 212% as of Q2 2019. However, a slight deterioration could be observed for life insurers in the first half of 2019 and the low interest rate environment is expected to put further pressures on the capital positions of life insurers in the second half of 2019. At the same time, profitability improved in the first half of 2019, mainly due to valuation gains in the equity and bond portfolios of insurers. Nevertheless, the low yield environment is expected to put additional strains on the medium to long term profitability of insurers as higher yielding bonds will have to be replaced by lower yielding bonds, which may make it increasingly difficult for insurers to make investment returns in excess of guaranteed returns issued in the past, which are still prevalent in many countries.

THE EUROPEAN INSURANCE SECTOR

The challenging macroeconomic environment is leading insurance undertakings to further adapt their business models. In order to address the challenges associated with the low yield environment and improve profitability, life insurers are lowering guaranteed rates in traditional products and are increasingly focusing on unit-linked products. On the investment side, insurers are slowly moving towards more alternative investments and illiquid assets, such as unlisted equity, mortgages & loans, infrastructure and property. For non-life insurers, the challenge is mostly focused on managing increasing losses stemming from climate-related risks and cyber events, which may not be adequately reflected in risk models based on historical data, and continued competitive pressures.

Despite the challenging environment, the European insurance sector overall gross written premiums slightly grew by 1.6% on an annual basis in Q2 2019. This growth is particularly driven by the increase in non life GWP (3.7%), in comparison to a slightly decrease in life (-0.5%). This reduction growth rate in life GWP is associated to the slowdown in the economic growth; however this does not seem to have affected the growth of non-life GWP to the same extent. Overall GWP as a percentage of GDP slightly increased from 9% to 11% for the European insurance market, likewise total assets as a share of GDP improved from 70% to 74%. The share of unit-linked business has slightly declined notwithstanding the growth expectations. Even though insurers are increasingly trying to shift towards unit-linked business in the current low yield environment, the total share of unit-linked business in life GWP has slightly decreased from 42% in Q2 2018 to 40% in Q2 2019, likewise the share for the median insurance company declined from 34% in Q2 2018 to 31% in Q2 2019. Considerable differences remain across countries, with some countries still being plagued by low trust due to misselling issues in the past. Overall, the trend towards unit-lead business means that investment risks are increasingly transferred to policyholders with potential reputational risks to the insurance sector in case investment returns turn out lower than anticipated.

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The liquid asset ratio slightly deteriorated in the first half of 2019. The median value for liquid asset increased by 1.5% from 63.3% in 2018 Q2 to 64.8% in 2018 Q4, and after slightly decreased to 63.8% in Q2 2019. Furthermore,  the distribution moved down (10th percentile reduced in the past year by 6 p.p. to 47.9%). Liquid assets are necessary in order to meet payment obligations when they are due. Furthermore, a potential increase in interest rate yields might directly impact the liquidity needs of insurers due to a significant increase in the lapse rate as policyholders might look for more attractive alternative investments.

EIOPA2

Lapse rates in the life business remained stable slightly increased in the first half of 2019. The median value increased from 1.34% in Q2 2018 to 1.38% in Q2 2019. Moreover, a potential sudden reversal of risk premia and abruptly rising yields could trigger an increase in lapse rates and surrender ratios as policyholders might look  for more attractive investments. Although several contractual and fiscal implications could limit the impact of lapses and surrenders in some countries, potential lapses by policyholders could add additional strains on insurers’ financial position once yields start increasing.

The return on investment has substantially declined further over 2018. The investment returns have significantly deteriorated for the main investment classes (bonds, equity and collective instruments). The median return on investment decreased to only 0.31% in 2018, compared to 2.83% in 2016 and 1.95% in 2017. In particular the four main investment options (government and corporate bonds, equity instruments and collective investment undertakings) – which approximately account for two-thirds of insurers’ total investment portfolios – have generated considerably lower or even negative returns in 2018. As a consequence, insurers may increasingly look for alternative investments, such as unlisted equities, mortgages and infrastructure to improve investment returns. This potential search for yield behaviour might differ per country and warrants close monitoring by supervisory authorities as insurers may suffer substantial losses on these more illiquid investments when markets turn sour.

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Despite the challenging investment climate, overall insurer profitability improved in the first half of 2019. The median return on assets (ROA) increased from 0.24% in Q2 2018 to 0.32% in Q2 2019, whereas the median return on excess of assets over liabilities (used as a proxy of return on equity), increased from 2.8% in Q2 2018 to 4.9 % in Q2 2019. The improvement in overall profitability seems to stem mainly from valuation gains in the investment portolio of insurers driven by a strong rebound in equity prices and declining yields (and hence increasing values of bond holdings) throughout the first half of 2019, while profitability could be further supported by strong underwriting results and insurers’ continued focus on cost optimisation. However, decreased expected profits in future premiums (EPIFP) from 11% in Q1 2019 to 10.3% in Q2 2019 suggest expectations of deteriorating profitability looking ahead. Underwriting profitability remained stable and overall positive in the first half of 2019. The median Gross Combined Ratio for non-life business remained below 100% in the first half of 2019 across all lines of business, indicating that most EEA insurers were able to generate positive underwriting results (excluding profits from investments). However, significant outliers can still be observed across lines of business, in particular for credit and suretyship insurance, indicating that several insurers have experienced substantial underwriting losses in this line of business. Furthermore, concerns of underpricing and underreserving remain in the highly competitive motor insurance markets.

EIOPA4

Solvency positions slightly deteriorated in the first half of 2019 and the low interest rate environment is expected to put further pressures on the capital positions in the second half of the year, especially for life insurers. Furthermore, the number of life insurance undertakings with SCR ratios below the 100% threshold increased in comparison with the previous year from 1 in Q2 2018 to 4 in Q2 2019 mainly due to the low interest rate environment, while the number of non-life insurance undertakings with SCR ratios below 100% threshold decreased from 9 in Q2 2018 to 7 in Q2 2019. The median SCR ratio for life insurers is still the highest compared to non-life insurers and composite undertakings. However, the SCR ratio differs substantially among countries.

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The impact of the LTG and transitional measures varies considerably across insurers and countries. The long term guarantees (LTG) and transitional measures were introduced in the Solvency II Directive to ensure an appropriate treatment of insurance products that include long-term guarantees and facilitate a smooth transition of the new regime. These measures can have a significant impact on the SCR ratio by allowing insurance undertakings, among others, to apply a premium to the risk free interest rate used for discounting technical provions. The impact of applying these measures is highest in DE and the UK, where the distribution of SCR ratios is signicantly lower without LTG and transitional measures (Figure 2.16). While it is important to take the effect of LTG measures and transitional measures into account when comparing across insurers and countries, the LTG measures do provide a potential financial stability cushion by reducing overall volatility.

On October 15th 2019, EIOPA launched a public consultation on an Opinion that sets out technical advice for the 2020 review of Solvency II. The call for advice comprises 19 separate topics. Broadly speaking, these can be divided into three parts.

  1. The review of the LTG measures, where a number of different options are being consulted on, notably on extrapolation and on the volatility adjustment.
  2. The potential introduction of new regulatory tools in the Solvency II framework, notably on macro-prudential issues, recovery and resolution, and insurance guarantee schemes. These new regulatory tools are considered thoroughly in the consultation.
  3. Revisions to the existing Solvency II framework including in relation to
    • freedom of services and establishment;
    • reporting and disclosure;
    • and the solvency capital requirement.

The main specific considerations and proposals of this consultation are as follows:

  • Considerations to choose a later starting point for the extrapolation of risk-free interest rates for the euro or to change the extrapolation method to take into account market information beyond the starting point.
  • Considerations to change the calculation of the volatility adjustment to risk-free interest rates, in particular to address overshooting effects and to reflect the illiquidity of insurance liabilities.
  • The proposal to increase the calibration of the interest rate risk sub-module in line with empirical evidence, in particular the existence of negative interest rates. The proposal is consistent with the technical advice EIOPA provided on the Solvency Capital Requirement standard formula in 2018.
  • The proposal to include macro-prudential tools in the Solvency II Directive.
  • The proposal to establish a minimum harmonised and comprehensive recovery and resolution framework for insurance.

The European Supervisory Authorities (ESAs) published on the 4th October 2019 a Joint Opinion on the risks of money laundering and terrorist financing affecting the European Union’s financial sector. In this Joint Opinion, the ESAs identify and analyse current and emerging money laundering and terrorist financing (ML/ TF) risks to which the EU’s financial sector is exposed. In particular, the ESAs have identified that the main cross-cutting risks arise from

  • the withdrawal of the United Kingdom (UK) from the EU,
  • new technologies,
  • virtual currencies,
  • legislative divergence and divergent supervisory practices,
  • weaknesses in internal controls,
  • terrorist financing and de-risking;

in order to mitigate these risks, the ESAs have proposed a number of potential actions for the Competent Authorities.

Following its advice to the European Commission on the integration of sustainability risks in Solvency II and the Insurance Distribution Directive on April 2019, EIOPA has published on 30th September 2019 an Opinion on Sustainability within Solvency II, which addresses the integration of climate-related risks in Solvency II Pillar I requirements. EIOPA found no current evidence to support a change in the calibration of capital requirements for “green” or “brown” assets. In the opinion, EIOPA calls insurance and reinsurance undertakings to implement measures linked with climate change-related risks, especially in view of a substantial impact to their business strategy; in that respect, the importance of scenario analysis in the undertakings’ risk management is highlighted. To increase the European market and citizens’ resilience to climate change, undertakings are called to consider the impact of their underwriting practices on the environment. EIOPA also supports the development of new insurance products, adjustments in the design and pricing of the products and the engagement with public authorities, as part of the industry’s stewardship activity.

On the 15th July 2019 EIOPA submitted to the European Commission draft amendments to the Implementing technical standards (ITS) on reporting and the ITS on public disclosure. The proposed amendments are mainly intended to reflect the changes in the Solvency II Delegated Regulation by the Commission Delegated Regulation (EU) 2019/981 and the Commission Delegated Regulation 2018/1221 as regards the calculation of regulatory capital requirements for securitisations and simple, transparent and standardised securitisations held by insurance and reinsurance undertakings. A more detailed review of the reporting and disclosure requirements will be part of the 2020 review of Solvency II.

On 18th June 2019 the Commission Delegated Regulation (EU) 2019/981 amending the Solvency II Delegated Regulation with respect to the calculation of the SCR for standard formula users was published. The new regulation includes the majority of the changes proposed by EIOPA in its advice to the Commission in February 2018 with the exception of the proposed change regarding interest rate risk. Most of the changes are applicable since July 2019, although changes to the calculation of the loss-absorbing capacity of deferred taxes and non-life and health premium and reserve risk will apply from 1 January 2020.

RISK ASSESSMENT

QUALITATIVE RISK ASSESSMENT

EIOPA conducts twice a year a bottom-up survey among national supervisors to determine the key risks and challenges for the European insurance and pension fund sectors, based on their probability and potential impact.

The EIOPA qualitative Autumn 2019 Survey reveals that low interest rates remain the main risks for both the insurance and pension fund sectors. Equity risks also remain prevalent, ranking as the 3rd and 2nd biggest risk for the insurance and pension funds sectors respectively. The cyber risk category is now rank as the 2nd biggest risk for the insurance sector, as insurers need to adapt their business models to this new type of risk both from an operational risk perspective and an underwriting perspective. Geopolitical risks have become more significant for both markets, along with Macro risks, which continue to be present in the insurance and pension fund sectors, partially due to concerns over protectionism, trade tensions, debt sustainability, sudden increase in risk premia and uncertainty relating to the potential future post-Brexit landscape.

The survey further suggests that all the risks are expected to increase over the coming year. The increased risk of the low for long interest rate environment is in line with the observed market developments, particulary after the ECB’s announcement of renewed monetary easing in September 2019. The significant expected raise of cyber, property, equity, macro and geopolitical risks in the following year is also in line with the observed market developments, indicating increased geopolitical uncertainty, trade tensions, stretched valuations in equity and real estate markets and more frequent and sophisticated cyber attacks which could all potentially affect the financial position of insurers and pension funds. On the other hand, ALM risks and Credit risk for financials are expected to increase in the coming year, while in the last survey in Spring 2019 the expectations were following the opposite direction.

EIOPA6

Although cyber risk is ranking as one of the top risks and expected to increase in the following year, many jurisdictions also see cyber-related insurance activities as a growth opportunity. The rapid pace of technological innovation and digitalisation is a challenge for the insurance market and insurers need to be able to adapt their business models to this challenging environment, nonetheless from a profitability perspective, increased digitalisation may offer significant cost-saving and revenue-increasing opportunities for insurance companies. The increase of awareness of cyber-risk and higher vulnerability to cyber threats among undertakings due to the increased adoption of digital technologies could drive a growth in cyber insurance underwriting.

The survey shows the exposure of an sudden correction of the risk premia significantly differs across EU countries. In the event of a sudden correction in the risk premia, insurance undertakings and pension funds with ample exposure to bonds and real estate, could suffer significant asset value variations that could lead to forced asset sales and potentially amplify the original shock to asset prices in less liquid markets. Some juridictions, however, confirm the limited exposure to this risk due to the low holding of fixed income instruments and well diversified portfolios.

The survey further indicates that national authorities expect the increase of investments in alternative asset classes and more illiquid assets. Conversely, holdings of governement bonds are expected to decrease in favour of corporate bonds within the next 12 months. Overall this might indicate potential search for yield behaviour and a shift towards more illiquid assets continues throughout numerous EU jurisdictions. Property investments – through for instance mortgages and infrastructure investment – are also expected to increase in some jurisdictions, for both insurers and pension funds. A potential downturn of real estate markets could therefore also affect the soundness of the insurance and pension fund sectors.

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QUANTITATIVE RISK ASSESSMENT EUROPEAN INSURANCE SECTOR

This section further assesses the key risks and vulnerabilities for the European insurance sector identified in this report. A detailed breakdown of the investment portfolio and asset allocation is provided with a focus on specific country exposures and interconnectedness with the banking sector. The chapter also analyses in more detail the implications of the current low yield environment for insurers.

INVESTMENTS

Insurance companies’ investments remain broadly stable, with a slight move towards less liquid investment. Government and corporate bonds continue to make up the majority of the investment portfolio, with only a  slight movement towards more non-traditional investment instruments such as unlisted equity and mortgage and loans. Life insurers in particular rely on fixed-income assets, due to the importance of asset-liability matching of their long-term obligations. At the same time, the high shares of fixed-income investments could give rise to significant reinvestment risk in the current low yield environment, in case the maturing fixed-income securities can only be replaced by lower yielding fixed-income securities for the same credit quality.

The overall credit quality of the bond portfolio is broadly satisfactory, although slight changes are observed in 2018. The vast majority of bonds held by European insurers are investment grade, with most rated as CQS1 (AA). However, the share of CQS2 has increased in the first half of 2019, and significant differences can be observed for insurers across countries.

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INTERCONNECTEDNESS BETWEEN INSURERS AND BANKS

The overall exposures towards the banking sector remain significant for insurers in certain countries, which could be one potential transmission channel in case of a sudden reassessment of risk premia. The interconnectedness between insurers and banks could intensify contagion across the financial system through common risk exposures. A potential sudden reassessment of risk premia may not only affect insurers directly, but also indirectly through exposures to the banking sector. This is also a potential transmission channel of emerging markets distress, as banks have on average larger exposures to emerging markets when compared to insurers.

Another channel of risk transmission could be through different types of bank instruments bundled together and credited by institutional investors such as insurers and pension funds.

Insurers’ exposures towards banks are heterogeneous across the EU/EEA countries, with different levels of home bias as well. Hence, countries with primary banks exposed to emerging markets or weak banking sectors could be impacted more in case of economic distress. On average, 15.95% of the EU/EEA insurers’ assets are issued by the banking sector through different types of instruments, mostly bank bonds.

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Click here to access EIOPA’s Dec 2019 Financial Stability Report

Fit for the Future: An Urgent Imperative for Board Leadership

It is a truism that the only constant in business is change. But that statement does not remotely do justice to the scale and scope of the multiple changes confronting business in the first half of the twenty-first century:

  • Rapid and far-reaching advances in technology are reshaping competition and the process of value creation in every business sector.
  • The struggle to deal with climate change is beginning to transform the economics of extractive industries and others.
  • Global supply chains are challenged by geopolitical and mercantile conflicts.
  • Investor scrutiny is more demanding than ever.
  • Society’s expectations of business are increasing as governments struggle to address mounting challenges—income inequality, threats to data privacy, crumbling infrastructure, global warming, and so forth.

Each of these changes in itself is seismic. But what makes the current epoch uniquely unpredictable and hard to navigate is the fact that these changes are happening concurrently, interacting with and amplifying each other, as illustrated in the figure below. As a result, companies may find it extremely difficult to anticipate the full impact or the second- or third-order effects of these disruptions in the next few years. This is especially true for boards of directors and their leaders, whose job it is to secure the long-term success of their companies. It is a challenge that is not going away any time soon—indeed, all indications are that it will become more acute.

NACD 1

AN EXISTENTIAL THREAT

As last year’s Blue Ribbon Commission report on board oversight of disruptive risks pointed out, these trends

  • “have the potential to change industry structure or operating conditions,
  • make existing business models obsolete,
  • derail growth,
  • or otherwise pose a fundamental threat [or transformative opportunity] to the long-term strategy of the organization.”

But while the threats are clearly existential, it is far from clear that all companies and their boards are adequately equipped to respond, because many of the big issues facing business are in new or uncharted territories. Technology is one obvious disruptor which is reshaping industries and forcing companies to consider new forms of collaboration that would have been unimaginable a few years ago. For example, the car industry is having to retool its entire production system to meet rising projected demand for electric vehicles while forming partnerships and joint ventures with leading software providers to exploit the emerging markets for autonomous cars. The competitive battleground and source of value creation has shifted rapidly and radically from the vehicles’ hardware to the systems driving it. Another challenge is the complex issue of climate change, where companies are feeling their way toward a response to fundamental market shifts involving international politics, governmental regulation, and investor expectations while considering the economic impact of climate risk. Boards need to bolster their capacity to navigate this labyrinth. A third and rapidly-moving set of challenges is emerging from tectonic shifts in geopolitics and in particular from the rise of great-power rivalry, trade protectionism, and mercantilism—notably in the domain of technology, where the United States and China are engaged in what some see as a new arms race for control over the systems of the future.

Overarching all of these trends is another relatively new pressure: the pressure for companies to articulate and justify their broader purpose, in terms of how they address society’s unmet needs in an era of great social change, activism, and political uncertainty. This is certainly the message from some of the largest institutional investors. As Larry Fink, CEO of BlackRock, put it in his 2019 CEO letter to portfolio companies, “Companies that fulfill their purpose and responsibilities to stakeholders reap rewards over the long-term. Companies that ignore them stumble and fail. This dynamic is becoming increasingly apparent as the public holds companies to more exacting standards. And it will continue to accelerate as millennials—who today represent 35 percent of the workforce—express new expectations of the companies they work for, buy from, and invest in.”

CREATIVE DESTRUCTION ACCELERATES

One important inference from these trends is that the formula for past success matters even less to companies considering their future. Research conducted in 2018 for the Fortune Future 500 initiative (the public companies with the best long-term growth outlook) shows that for large companies, there is now less correlation than there was before between past and future financial and competitive performance over multiple years. This means that companies can no longer hope to prosper merely by sticking to their historical growth strategies and competitive advantages. Relying on past success can engender complacency—itself an existential threat.

It is certainly true that the process Joseph Schumpeter called “creative destruction” is accelerating, and in consequence corporate lifespans are shrinking. A 2018 Innosight study showed that, based on recent trends, nearly half of the corporate constituents of the S&P 500 could be expected to be replaced over the next 10 years. While companies in the S&P 500 had an average tenure of 33 years in 1964, tenures had narrowed to 24 years by 2016 and are forecasted to shrink to just 12 years by 2027. This accelerating churn is to be seen also among very young firms—for example, five-year survival rates for newly-listed firms have declined by nearly 30 percentile points (dropping from 92 percent to 63 percent) since the 1960s. In a parallel trend, the median CEO tenure for large-cap companies has been shrinking steadily over time—indeed, it dropped by one full year between 2013 and 2017. Median tenure is now five years.

Structural change and industry consolidation are also impacting the nature of competition, creating a “winnertakes-most” dynamic in an increasing number of business sectors. Recent research based on analysis of 5,750 of the world’s largest companies shows just how unevenly the fruits of success are now distributed in terms of economic profit (a measure of a company’s invested capital times its return above its weighted cost of capital). The top 10 percent of these companies captured fully 80 percent of positive economic profit between 1994 and 2016.

All of these implications are brought into sharper focus by the increasing shareholder scrutiny which companies are now under, not only from activist investors but also increasingly from institutional investors who wield their significant influence to demand change. Stephen Murray, the president and CEO of private equity firm CCMP Capital, goes so far as to say, “The whole activist industry exists because public boards are often seen as inadequately equipped to meet shareholder interests.” So the challenges for boards and management teams are stark—probably more so now than at any time since the birth of the modern corporation a little more than a century ago. They mean that some, though by no means all, of these individuals’ accumulated experience in strategy development and execution may be less relevant in the future than in the past. And they suggest that board leaders in particular need to adopt a new mind-set and consider a different modus operandi attuned to the demands of this rapidly-changing environment.

IMPLICATIONS FOR BOARDS

Three years ago, in its Report of the Blue Ribbon Commission on Building the Strategic-Asset Board, NACD first pointed out that a new leadership mandate for boards was emerging, driven by “an operating environment . . . that is characterized by increased complexity and uncertainty and includes new sources of risk and opportunity.” It highlighted the role of the board leader in driving a continuous improvement ethos to ensure that the board remains fit for its purpose. Yet performance expectations for boards continue to rise. In a 2019 NACD survey, 73 percent of directors reported that board leadership is more challenging now than it was three years ago, and 84 percent reported that performance expectations had gone up for all board members. Directors admit that they find it really challenging to keep up with change. In the same NACD survey, 36 percent of directors cited the struggle to stay abreast of the changing speed of business as one of the key impediments to the effectiveness of board leaders. Commissioners for this report echoed that concern and highlighted it as a challenge for the entire board. “Many directors don’t feel comfortable talking about emerging technologies, cybersecurity, and other complex topics,” said one Commissioner. “As a result, they tend to defer to others, which can become an abdication of their responsibility to be active board members.”

In the view of the Commission, this shifting business paradigm has profound and immediate implications for boards, and these implications will intensify dramatically over the next 5 to 10 years. They cover

  • board engagement with management,
  • board renewal,
  • operations,
  • transparency,
  • and accountability.

Some of these implications are not new—indeed, boards have been grappling with all of them with greater or lesser success for some time. But there is no doubt that all of them have recently become more acute, and now pose an urgent challenge to board leaders.

  1. IMPLICATION 1: Boards must engage more proactively, deeply, and frequently on entirely new and fast-changing drivers of strategy and risk.
  2. IMPLICATION 2: Boards must approach their own renewal through the lens of shifting strategic needs to ensure longterm competitive advantage.
  3. IMPLICATION 3: Boards must adopt a more dynamic operating model and structure.
  4. IMPLICATION 4: Boards must be much more transparent about how they govern.
  5. IMPLICATION 5: Boards must hold themselves more accountable for individual director and collective performance.

NACD 2

SETTING EXPECTATIONS FOR THE NEW BOARD LEADER

The fundamental role of board leadership stays the same: building and maintaining high-performing boards that build long-term value. Here is how NACD has described board leaders and their role in its past Blue Ribbon Commission reports:

Board leaders are the linchpins on many key issues, including the board-CEO relationship, board dynamics and culture, setting the board agenda, information flows between the board and management, and stakeholder relations (especially board-shareholder engagement).

Many NACD principles and positions about what constitutes good board practice are contingent upon having a strong and effective leader in this role. Strong, qualified individuals in this role “[have] the ability to give the board a competitive advantage.”

As seen in the infographic that follows, based on 2019 NACD analysis of S&P 500 chairs and lead directors, board leaders today have extensive tenure on the boards they serve, bringing with them strong institutional memory, and they almost always have past experience in business leadership roles and a proven track record in strategy and execution.

NACD 3

PRIORITY RESPONSIBILITIES FOR BOARD LEADERS OF TODAY
Lead the setting and monitoring of board performance goals that are regularly synchronized with the (shifting) business strategy.

  • Drive alignment and connectivity. This includes staying connected on material new initiatives and strengthening alignment in how committees and the full board engage on crucial, but now fast-changing, issues such as strategy, risk, disruption, talent, corporate culture, incentives, and technology.
  • Lead the setting of shared values and expectations for a well-functioning board, including the use of a fully candid board, committee, and individual-director performance evaluation.
  • Pay continuous attention to (a) what’s working and why, (b) what’s not working and why, and (c) how the board can use this knowledge to improve its effectiveness.
  • Spend considerable time in one-on-one discussions on key topics with other board members, the CEO, and the management team, with a focus on ensuring openness of discussion and constructive group dynamics.

DESIRED ATTRIBUTES FOR BOARD LEADERS OF TODAY
Fortitude and vigilance to ensure that changes in board processes and practices change behaviors over time

  • Adaptability—a willingness to recognize a board’s new needs and responsibilities and adjust board practices, processes, agenda setting, and structures accordingly
  • Superb communication skills, especially with regard to difficult communications, including sensitive messages to the CEO and to fellow directors
  • Aptitude for relationship building, not just with the board, the CEO, and the senior team, but also with key shareholders, stakeholders, and regulators
  • Inclusiveness—ensuring that the growing diversity of the boardroom is optimized, and enhancing collaboration that is inclusive of different, unconventional thinking
  • Humility—placing a high premium on listening and seeking to understand the (contrasting) views of others. The successful board leader presents himself/herself as “last among equals”

STRENGTHENING BOARD ENGAGEMENT

Board leaders will need to orchestrate more meaningful board engagement to help inform strategic choices and to understand the risks being taken in a much more uncertain and fast-changing environment. Earlier, we described the pressures for boards to become more actively engaged with their companies, without falling into the trap of micromanagement or losing the objectivity required to oversee the business. We suggest that this requires collaboration and candid dialogue between boards and management teams about respective roles and responsibilities.

  • Clarifying where the board would like to seek deeper involvement and why this creates better governance. Examples might be earlier and more in-depth understanding/verification of strategy development and underlying assumptions, preparations for responding to disruption, and plans for major corporate transformations.
  • Creating a shared picture of the present, and of the future, and of where the industry and the competition are headed, and of what that means for strategy.
  • Enhancing board focus on innovation and change. Here is another shift made imperative by the speed of business change. Where in the past a board’s typical posture may have been to act as a brake on management’s ambitions, an equally important goal should now be to work with management to ensure that they embrace innovation and can successfully drive change in the organization.
  • Assessing how well management is maintaining critical alignments among key determinants of performance (e.g., strategy, risk management, innovation, controls, incentives, culture, and talent). This becomes increasingly important as strategies are more frequently being recalibrated.
  • Establishing a framework for more frequent, focused management communication with the board between formal meetings. This can help streamline the meetings themselves, freeing up time to focus on the most critical strategic matters.

DRIVING STRATEGIC BOARD RENEWAL

In order to deliver more meaningful and deeper engagement on entirely new issues, the board leader and the chair of the nominating and governance committee should thoroughly assess whether the board has the right human capital to fulfill its mandate and deliver ongoing value. One of the key questions will be whether the board’s existing composition is aligned with the challenges likely to face the business in the future sketched out together with the management team, and if not, how it should best be renewed. One useful way of thinking about this task could be a “clean-sheet” approach to board diversity and composition, which NACD first recommended in its Blue Ribbon Commission report on building the strategic-asset board. In particular, nominating and governance committees should consider asking the following questions:

  • If we were to create a board from scratch today, what would it look like holistically, from the standpoint of skills, leadership styles, and backgrounds? What will we need in three, five, or more years?
  • Have we sufficiently mapped out our strategy and risks into the future to understand what profiles we need?
  • How should our board composition represent the characteristics of the company’s current and future customer base as well as its workforce?
  • If we are anticipating adding one or more new directors in the next couple of years, have we vetted our recruitment profile to ensure criteria are relevant and that they are not unnecessarily restricting access to appropriate candidates (e.g., requiring CEO or prior board experience)?

BUILDING AN INCLUSIVE BOARD CULTURE

Boards already know how to be purposeful in seeking out individuals who bring a variety of backgrounds, perspectives, and skills. Now they need to be just as purposeful in creating an environment that enables those diverse voices to be heard. The board leader has a critical role to play in activating diversity in the boardroom by recognizing that the aim is not “hiring for diversity and then managing for assimilation.” The goal of the board leader after bringing in new board members is not assimilation but rather enhancing collaboration that is inclusive of different, unconventional thinking. With higher levels of diversity in the boardroom—whether this is diversity in experience, skills, gender, race, ethnicity, or age—it’s critical for board leaders to create a culture that facilitates constructive and candid interactions between board members and that ensures that each director is heard from on important issues.

FOSTERING CONTINUOUS LEARNING

“Continuous lifelong learning’’ is such an oft-heard phrase that it’s close to becoming a cliché. But it’s nonetheless a worthwhile approach for boards and management teams to adopt—because when the pace of change is accelerating, “the fastest-growing companies and most resilient workers will be those who learn faster than their competition.”

This, too, will function most effectively as a collaborative effort between the board and the management team. It’s the role of management to help educate the board about the future and its impact on strategy. The board leader should help the C-suite understand the board’s expectations for the learning process, the time line, and the board’s information needs. At the same time, the board leader should set the expectation that directors not rely solely on management for all of the information they receive, but rather seek out other external sources proactively to deepen their understanding of the business. The agenda for potential learning is vast and constantly growing. “Some learning opportunities may be specific to individual directors; others may be common to all members of a committee or to the entire board (e.g., raising the board’s collective knowledge about cyber threats). Individual, committee, or board-level learning agendas might include

  • industry-specific topics;
  • emerging economic and technology trends;
  • governance matters;
  • regulatory developments;
  • shareholder/stakeholder issues;
  • and/or team dynamics and decision making.”

Commissioners offered a number of observations about the pursuit of structured board learning:

  • First, that it is not just a matter for board leaders and committee chairs—it is a collective task for the whole board to stay “constantly curious.” This can be assisted through experiential learning, where the board visits company sites or meets local managers.
  • Second, there is a constant need to focus collective learning on new technologies—not just the features of emerging technologies but also the reasons why they are so disruptive and how competitors have succeeded in commercializing them.
  • Third, longer-serving directors will benefit from periodically refreshing their knowledge of the basics—for example, by joining new director orientation in order to understand how management’s presentation of the issues may have changed.
  • Finally, the learning imperative applies equally to management. To this end, selected executives should be encouraged to take board positions with companies that are not competitors.

BUILDING AGILITY INTO BOARD OPERATIONS AND STRUCTURE

As stated earlier, the dynamic external environment requires boards to be more careful than before about how they allocate their time, but also more flexible in responding to events. The starting point is effective agenda setting for board meetings.

Agendas

The Commissioners offered a number of specific ideas for enhancing board meeting effectiveness:

  1. First, think holistically about the entire cycle of meetings throughout the year and not just about the agenda for individual meetings. The objective is to ensure the highest return on the time that the board spends together and with management—including what happens outside, around, and in between the actual board meetings.
  2. Second, make a deliberate effort to ensure that board meetings are not predominantly focused on the past and on compliance—on the rear-view mirror, so to speak. Create “white space” time for open conversation and time to delve into identified issues of importance. Foster dialogue and minimize time spent on formal presentations.
  3. Third, take a strategic and almost mathematical approach to time allocation. One Commissioner described how the board tracks how it is spending its time in meetings, then asks board members their opinions about how the board should be spending time, and periodically optimizes the mix.
  4. Fourth, try to maximize one-on-one time with the CEO and the board. It is important to spend time with the CEO without other managers present. An hour and sometimes more at the start of every meeting, and then again at the end, coupled with a CEO/director-only dinner, is an effective way “to get everything that needs airing out on the table.”

NACD 4 (2)

 

Click here to access NACD’s entire report

Incumbents and InsurTechs must embrace each other’s unique strengths and work together

Executive summary

New challenges, changing business dynamics have set off a tectonic shift in the insurance industry

  • Customer expectations are evolving, offers are becoming more innovative, and new players are making their presence known.
  • Fundamental and significant challenges will require insurers’ immediate and considered attention.
  • As a result of these changing dynamics, incumbents and InsurTechs agree that collaboration with other industry players is necessary to create an integrated portfolio of offerings.

Insurers must support a platform that serves a broad spectrum of customer needs

  • The future marketplace will showcase a bouquet of offerings that caters to customers’ financial and non-financial needs.
  • Insurers need a structured approach to marketplace development that includes proper identification of customer preferences and relevant offerings, evaluation of best-fit partners, and an effective GTM strategy.
  • Today’s operating model will undergo a fundamental transformation as part of the inevitable path forward.

Experience-led digital offerings and seamless collaboration with ecosystem players will drive marketplace success

  • Insurers will need to tear down internal silos, seamlessly connect with ecosystem players, and be more inventive.
  • Our Inventive Insurer profile includes key characteristics:
    • intelligent insurer,
    • open insurer,
    • deep customer,
    • and product agility.

Incumbent-InsurTech collaboration can shore up competencies in preparation for the future

  • InsurTechs’ unique capabilities and agility make them ideal partners for incumbents aiming to carve out a substantive role in the new marketplace.
  • A successful holistic collaboration will focus on long-term benefits.

New ecosystem roles will evolve as the industry transitions toward the marketplace model

  • Industry players must decide how to successfully and profitably contribute to the new ecosystem based on their most compelling competencies, as well as market needs and the external environment.

There’s no looking back for today’s digitally-empowered consumers

Throughout the past decade, as smart technology tools became mainstream, consumer interaction with the world changed dramatically. Changing lifestyles, behavior, and preferences have created a digital-age paradigm. As smartphones and the internet unlock information and decision power, interconnectivity, personalization, and seamless omnichannel access have become must-haves.

So, what does this mean for insurers?

Policyholders seek new offerings: Traditional insurance policies may not fully meet customers’ changing needs and desire for add-on services, personalization, and flexible offerings. In fact, for nearly half of policyholders, the decision to continue with their insurer is influenced by the availability of these features and benefits, according to the World Insurance Report (WIR) 2019.1

The demand for digital transaction channels is up: The popularity of digital channels is gradually growing. More than half of insurance customers (nearly 52%) interviewed as part of the WIR 2018 placed high importance on the mobile and internet or a website channel for conducting insurance transactions.

Simplicity is the rationale behind genuinely digital products

Digital channels work best when insurers streamline and standardize products and processes so customers easily understand features and benefits and can make direct purchases online with ease. In short, insurers must simplify offerings to create genuinely
digital products.

  • Easy to understand: Policy details should be redesigned and reformatted for straightforward interpretation so customers can quickly make a buy/ no-buy decision. For example, Berkshire Hathaway’s Insurance Group (BiBerk) launched a comprehensive insurance product for small businesses that combines multiple coverages. Dubbed THREE, the new product is three-pages long and links coverage for workers compensation, liability (including general liability, errors and omissions, and cyber), property, and auto.
  • Automated processes: Straight-through processing and other ease-of-use tools can simplify underwriting, claims processing, and more across the value chain. Cake Insure, a subsidiary of Colorado-based Pinnacol Assurance, launched in late 2017 with an algorithm that produces a bindable quote in less than a minute and a bound policy in fewer than five minutes for small businesses seeking workers’ compensation insurance. New York-based property and casualty InsurTech Lemonade uses artificial intelligence to automate claims processing. Lemonade showcases a 2016 case in which it crossreferenced a claim against a user’s policy, ran 18 anti-fraud algorithms, approved the claim, and sent wiring instructions to the bank in three seconds to demonstrate ease of use.
  • Straightforward policy wording: Descriptions of policy coverage and expenses (which ones are payable and which do not qualify) must be explained clearly in everyday language. Similarly, insurance industry players should work together to standardize definitions, exclusions, and processes.
  • Interactive customer education: Gamification, interactive videos, and social channels are ways to educate customers about risks, their need for coverage, and policy details. Interaction can also improve customer engagement and experience.

The marketplace of the future can holistically focus on customer needs

HomeFlix is a virtual assistant offering renters and homeowners insurance underwritten by Zurich Connect, the digital arm of Zurich Italy, and powered by on-demand digital broker Yolo, a Milan-based InsurTech. In addition to insurance coverage, the policy, introduced in July 2019, offers laundry service – washed and ironed after a few days and paid directly on delivery. Access to concierge maintenance services such as plumbing and electric also is available. Next, HomeFlix plans home delivery, babysitting, and cleaning services.

New York-based Generali Global Assistance (a division of Italy’s Generali Group, which provides travel insurance-related services) strategically partnered with San Francisco-based rideshare company Lyft in late 2017 to improve customer service and contain costs for clientele of its insurance companies and multinational corporations. Later, Lyft
collaborated with CareLinx, a US professional caregiver marketplace that helps find, hire, manage and pay caregivers online, to create CareRides, a door-to-door transportation service for special-needs individuals in 50 US metro areas. Generali Global Assistance also partnered with CareLinx to provide value-added services for existing policyholders in times of need.

The marketplace of the future can offer emerging-risk coverage

Working with Cisco, Apple, and Aon, Allianz launched a comprehensive cyber insurance product for businesses in early 2018. The product includes a solution comprised of cyber-resilience evaluation services from Aon, secure technologies from Cisco and Apple, and options for enhanced cyber insurance coverage from Allianz. The product aims to help a broader range of organizations manage and protect themselves better from cyber risks associated with ransomware and malware-related threats.

The marketplace of the future can deliver simple to understand, easy-access offerings

Berlin-based startup FRIDAY offers innovative, digital automotive insurance with features like kilometeraccurate billing, the option to terminate at month’s end, and paperless administration. The InsurTech’s technologies and partnerships include:

  • Telematics support from the BMW CarData platform and from TankTaler, which tracks vehicle location as well as data such as battery voltage, mileage, and other statistics
  • Automotive services through the mobility hub of ATU, a German chain of vehicle repair franchises
  • Drivy, a peer-to-peer car rental marketplace that enables consumers to lease vehicles from private individuals
  • Friendsurance, a peer-to-peer InsurTech that pays out a percentage to customers who do not use (or use very little) annual insurance also sells FRIDAY policies

Prudential Singapore and StarHub partnered to create FastTrackTrade (FTT), Singapore’s first digital trade platform for small and midsized business (SMBs) that uses blockchain technology. FTT helps SMBs find business partners and distributors, buy and sell goods, track shipments, receive and make payments, access financing, and buy insurance via a single platform. FinTech startup Cités Gestion developed the pioneering platform with funding from Prudential.

CG1

Structure supports success

Insurer success in the future marketplace will rely on a structured approach (see Figure 3).

  • Understanding customer preferences and conceptualizing product portfolios: Insurers can tap new data sources such as social media channels and use behavioral analytics for better understanding and more accurate estimation of their customer’s preferences and risk profile. With a deeper understanding of customers, they can conceptualize personalized product portfolios for each customer segment.
  • Recruiting the right partners: Once the product portfolio is finalized, insurers should look for partners that align with their business objectives and strategic vision. Cultural fit, ease of integration of systems, and seamless channels of communication are key success factors.
  • Structuring the offerings portfolio: Insurers should closely collaborate with partners while assembling their portfolio. A winning product/service mix offers a hyper-personalized one-stop solution for all the needs of the customer.
  • A compelling go-to-market strategy: Insurers should be able to communicate the value of the marketplace by touting human-centric offerings that customers find simple to understand and easy to access.
  • Capturing feedback: Through advanced analysis of sales data, direct customer input, social media, etc., insurers can capture feedback about their offerings. The process should be continuous rather than on an ad-hoc basis. More importantly, the input should be immediately acted upon to enhance current products or to conceptualize a new product.

CG2

To realize the full potential of the structured approach, four fundamental shifts in the current operating model are critical

For an insurer to realize the full potential of the structured approach and ensuring the successful creation of the marketplace of the future, four fundamental shifts in the current operating model are critical (see Figure 4). The importance of these areas is borne out by the research. For example:

  1. Experience: More than 70% of insurers and InsurTechs said a focus on holistic risk solutions for customers was critical to establishing a future-state insurance marketplace.
  2. Data: More than 70% said advanced data management capabilities are critical.
  3. Partnerships: 90% of InsurTechs said partnerships were critical while 70% of incumbents said the same. Both insurers and InsurTechs have a hearty appetite for collaboration with other sectors, such as healthcare providers and players from the travel, transportation, and hospitality space (see Figure 5).
  4. Shared access: However, an emerging area in which views are evolving is the transition to a shared economy. Here, less than 40% of established insurers and InsurTechs say they consider shared ownership of assets to be critical.

Industry players should understand that the four shifts – focus on experience, data, partnership, and shared access – are interrelated and critical for partnering with other entities to develop bundled offerings. Concentrating on one at the expense of others may stymie the overall efficiency of the marketplace.

CG3

Digital maturity does not match aspiration

While insurers realize the importance of these fundamental shifts, there is a significant gap between their expectations and their current digital maturity. Lack of digital maturity is the biggest concern for incumbents. While 68% of insurers said they believe partnerships are critical, only 32% are currently collaborating with ecosystem partners (see Figure 6).

Less than 40% of insurers have a holistic digital transformation strategy and are collaborating with ecosystem players to provide value-added services. Only 11% of insurers say they leverage open architecture, which is critical for working with other industry players.

CG4

CG5

Experience-led digital offerings and seamless collaboration with ecosystem players will drive marketplace success

We call firms prepared to excel in the future marketplace Inventive Insurers because they have strategically updated their product portfolios, operating models, and distribution methods. They have outlined their distinctive capabilities as well as their competency gaps and are ready to deliver end-to-end solutions in the manner customers prefer.

Pragmatic assessment (and subsequent enhancement) of a firm’s digital maturity is critical to connecting with ecosystem players seamlessly. Figure 7 shows the steps companies need to take to establish the marketplace of the future.

CG6

1. Prioritize digital agility

The critical first step in the future marketplace journey is boosting digital agility. The more quickly initiatives are implemented, the more quickly firms will enhance their digital maturity and actively participate within a connected ecosystem. Insurers must holistically adopt these critical capabilities to optimize their digital agility and seamlessly connect with partners to develop digitallyintegrated ecosystems (see Figure 8).

  • Real-time data gathering
  • Advanced analytics
  • Re-engineering complex processes and automating them

CG7

2. Build an integrated ecosystem

Seamless collaboration between insurers and their strategic partners is the backbone of a digitally integrated ecosystem. As new players enter the insurance value chain (aggregators, original equipment manufacturers (OEMs), one-stop policy management apps, and third parties such as repair stores), incumbents must strengthen their position through strategic partnerships.

Our proposed digitally-integrated ecosystem seamlessly interconnects insurers with customers and partners to enable the efficient flow of information and services (see Figure 9).

CG8

In the digitally-integrated ecosystem, customers can access insurers over various channels through extended multi-device, multi-platform, and mobility offerings. Digital integration with partners will play a crucial role as insurers seek to increase their reach and provide customers with convenient and seamless services.

Integration with aggregators and intermediaries offers insurers a choice of distribution channels. As insurers connect with individual customers through devices, real-time data can be captured and used to provide personalized offerings and value-added services.

Insurers will move beyond traditional touchpoints to become their customers’ constant risk control advisory and partner. For that to happen, however, insurers will need to join forces with third-party vendors for efficient claims management and payout, and with OEMs for real-time customer data.

APIs, cloud-based storage, and blockchain can foster insurance ecosystem integration by enabling the seamless and secure transfer of data between diverse systems. A digitally-integrated ecosystem – both within and outside the organization – will support the real-time, personalized services that customers already demand. Digital mastery can benefit top- and bottom lines and propel insurers forward.

Grasping the art of teamwork with close ecosystem players – and relevant offerings based on core capabilities – will lay the groundwork for insurers to partner profitably.

3. Create tomorrow’s marketplace

Firms must develop Inventive Insurer competencies to contribute to the successful development of tomorrow’s marketplace. These competencies include intelligent processes, open platforms, customer centricity, and an innovative mindset among team members ( see Figure 10).

CG9

Intelligent insurer. Automation, analytics, and artificial intelligence can prioritize customer experience within all operations.

  • Process efficiencies can support top-notch service with quick turnaround times.
  • Analytical competencies help insurers understand customer needs and act swiftly.
  • Robust digital governance provides monitoring and ensures compliance within today’s dynamic regulatory environment.

Open insurers leverage open platforms to build an ecosystem of partners through seamless collaboration with third parties and enable firms to participate in the value chain of third parties. Insurers with open platforms can access and integrate new data streams to cater to customers’ evolving needs, reaching them in the way they prefer via new distribution channels. Modern platform with open architecture for providing bouquet of offerings also allow firms to take a fail-fast approach to product development and innovate at a faster pace.

Deep customer competencies allow insurers to leverage data and channels for enhancing the customer experience across all touchpoints. Deep customer insights generated using advanced analytics and AI enable insurers to keep the customer at the center of all decisions.

Product agility is crucial for insurers to create new products at a faster pace and gain a competitive edge from an increased speed-to-market. Creative culture and ability to innovate at scale are critical components for achieving product agility. A creative culture
encourages novel thinking from employees and spurs openness to change.

Innovation labs and design thinking can encourage a fresh approach, especially within cultures that are hard-wired with conventional processes and culture.

Leadership support and vision are also critical. While Inventive Insurer status may be an aspirational future state, each firm’s journey is unique. An open platform used as a sandbox is an excellent place to begin developing new competencies and learning how to innovate at scale. Inventive Insurers create digital, experience-led offerings by collaborating seamlessly with other ecosystem players.

Incumbents and InsurTechs will benefit from strategic collaboration

For the most part, the industry sees InsurTech collaboration only as a means to drive growth and transform the customer experience. For example, 84% of insurers and 80% of InsurTechs say they are focusing on “developing new offerings.”

However, when it comes to the critical building blocks for the new insurance marketplace – such as developing holistic technology infrastructure and advanced data management capabilities – there are significant gaps in the expectations of insurers and InsurTechs. For example, fewer than 40% of incumbent insurers want to build holistic technology infrastructure by collaborating with InsurTech firms, while more than 60% of InsurTechs wish to work with insurers to create such a foundation.

What’s more, while data security remains a crucial concern when establishing partnerships with other industries, only around 10% of incumbents and 25% of InsurTechs say they want to focus collaborative efforts on data security.

Industry players should focus on a holistic approach while venturing into an insurer-InsurTech collaboration to prepare for the future and consider tactical plans for quick wins that may offer short-term benefits.

External partners can facilitate incumbent-InsurTech collaboration

After clearly outlining collaboration objectives, insurers must select a partner. The World InsurTech Report 2018 took a deep dive into the InsurTech landscape and offered ways in which incumbents can assess the success potential of short-to-medium term partnerships with InsurTech firms as well as longterm relationship feasibility. Finding a partner that can address technology capability gaps may require specialized third-party support.

Incumbents and InsurTechs can optimize their structured collaborative efforts by keeping four guiding pillars in mind: People, Finance, Business, and Technology (Figure 13).

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People (The right individuals in the best-fit positions): Employees are a firm’s most essential assets when it comes to driving innovation, growth, expansion, and fruitful collaboration. Both partnering entities must be flexible and strive for a balance between the hierarchical nature of many traditional insurers and the flat organizational structure favored by InsurTechs.

Finance (Allocate optimal capital, realistically forecast returns): Without a defined investment and revenue model, it may be difficult to articulate a compelling value proposition. Participants need adequate capital to invest in the partnership and a proven revenue generating model to maintain positive cash flow in the not-too-distant future.

Business (Early traction, measurable success): Business traction, a proven business model, customer adoption, and value creation are must-meet goals for any potential collaboration. A new business model should solve the needs and challenges that were difficult to tackle independently. A collaborative partnership should produce a value proposition with quantifiable results.

Technology (Collaboration tools and technologies): Technology tools should be secure and enable frictionless collaboration, as well as scalability. Partner systems should securely integrate with the help of technology. Accessed information must be accurate, timely, and be regulatorily compliant. It should be scalable without affecting current systems.

New ecosystem roles will evolve as the industry transitions toward the marketplace model

As the insurance industry advances, new specialist roles are developing. In addition to the traditional integrated business role, new functions include that of Supplier, Aggregator, and Orchestrator. Close collaboration will enable incumbents and InsurTechs to maximize opportunities in each.

These roles are not business-model exclusive but business-case specific. Each ecosystem entity may mix and match positions depending on the business model in play (see Figure 15).

Established insurers and InsurTechs can also play multiple roles within an ecosystem. For example, a firm can act as both supplier and orchestrator. Similarly, one firm may be a supplier in an ecosystem, but be an orchestrator in another ecosystem.

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Click here to access Cap Gemini’s entire report

 

Building your data and analytics strategy

When it comes to being data-driven, organizations run the gamut with maturity levels. Most believe that data and analytics provide insights. But only one-third of respondents to a TDWI survey said they were truly data-driven, meaning they analyze data to drive decisions and actions.

Successful data-driven businesses foster a collaborative, goal-oriented culture. Leaders believe in data and are governance-oriented. The technology side of the business ensures sound data quality and puts analytics into operation. The data management strategy spans the full analytics life cycle. Data is accessible and usable by multiple people – data engineers and data scientists, business analysts and less-technical business users.

TDWI analyst Fern Halper conducted research of analytics and data professionals across industries and identified the following five best practices for becoming a data-driven organization.

1. Build relationships to support collaboration

If IT and business teams don’t collaborate, the organization can’t operate in a data-driven way – so eliminating barriers between groups is crucial. Achieving this can improve market performance and innovation; but collaboration is challenging. Business decision makers often don’t think IT understands the importance of fast results, and conversely, IT doesn’t think the business understands data management priorities. Office politics come into play.

But having clearly defined roles and responsibilities with shared goals across departments encourages teamwork. These roles should include: IT/architecture, business and others who manage various tasks on the business and IT sides (from business sponsors to DevOps).

2. Make data accessible and trustworthy

Making data accessible – and ensuring its quality – are key to breaking down barriers and becoming data-driven. Whether it’s a data engineer assembling and transforming data for analysis or a data scientist building a model, everyone benefits from trustworthy data that’s unified and built around a common vocabulary.

As organizations analyze new forms of data – text, sensor, image and streaming – they’ll need to do so across multiple platforms like data warehouses, Hadoop, streaming platforms and data lakes. Such systems may reside on-site or in the cloud. TDWI recommends several best practices to help:

  • Establish a data integration and pipeline environment with tools that provide federated access and join data across sources. It helps to have point-and-click interfaces for building workflows, and tools that support ETL, ELT and advanced specifications like conditional logic or parallel jobs.
  • Manage, reuse and govern metadata – that is, the data about your data. This includes size, author, database column structure, security and more.
  • Provide reusable data quality tools with built-in analytics capabilities that can profile data for accuracy, completeness and ambiguity.

3. Provide tools to help the business work with data

From marketing and finance to operations and HR, business teams need self-service tools to speed and simplify data preparation and analytics tasks. Such tools may include built-in, advanced techniques like machine learning, and many work across the analytics life cycle – from data collection and profiling to monitoring analytical models in production.

These “smart” tools feature three capabilities:

  • Automation helps during model building and model management processes. Data preparation tools often use machine learning and natural language processing to understand semantics and accelerate data matching.
  • Reusability pulls from what has already been created for data management and analytics. For example, a source-to-target data pipeline workflow can be saved and embedded into an analytics workflow to create a predictive model.
  • Explainability helps business users understand the output when, for example, they’ve built a predictive model using an automated tool. Tools that explain what they’ve done are ideal for a data-driven company.

4. Consider a cohesive platform that supports collaboration and analytics

As organizations mature analytically, it’s important for their platform to support multiple roles in a common interface with a unified data infrastructure. This strengthens collaboration and makes it easier for people to do their jobs.

For example, a business analyst can use a discussion space to collaborate with a data scientist while building a predictive model, and during testing. The data scientist can use a notebook environment to test and validate the model as it’s versioned and metadata is captured. The data scientist can then notify the DevOps team when the model is ready for production – and they can use the platform’s tools to continually monitor the model.

5. Use modern governance technologies and practices

Governance – that is, rules and policies that prescribe how organizations protect and manage their data and analytics – is critical in learning to trust data and become data-driven. But TDWI research indicates that one-third of organizations don’t govern their data at all. Instead, many focus on security and privacy rules. Their research also indicates that fewer than 20 percent of organizations do any type of analytics governance, which includes vetting and monitoring models in production.

Decisions based on poor data – or models that have degraded – can have a negative effect on the business. As more people across an organization access data and build  models, and as new types of data and technologies emerge (big data, cloud, stream mining), data governance practices need to evolve. TDWI recommends three features of governance software that can strengthen your data and analytics governance:

  • Data catalogs, glossaries and dictionaries. These tools often include sophisticated tagging and automated procedures for building and keeping catalogs up to date – as well as discovering metadata from existing data sets.
  • Data lineage. Data lineage combined with metadata helps organizations understand where data originated and track how it was changed and transformed.
  • Model management. Ongoing model tracking is crucial for analytics governance. Many tools automate model monitoring, schedule updates to keep models current and send alerts when a model is degrading.

In the future, organizations may move beyond traditional governance council models to new approaches like agile governance, embedded governance or crowdsourced governance.

But involving both IT and business stakeholders in the decision-making process – including data owners, data stewards and others – will always be key to robust governance at data-driven organizations.

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There’s no single blueprint for beginning a data analytics project – never mind ensuring a successful one.

However, the following questions help individuals and organizations frame their data analytics projects in instructive ways. Put differently, think of these questions as more of a guide than a comprehensive how-to list.

1. Is this your organization’s first attempt at a data analytics project?

When it comes to data analytics projects, culture matters. Consider Netflix, Google and Amazon. All things being equal, organizations like these have successfully completed data analytics projects. Even better, they have built analytics into their cultures and become data-driven businesses.

As a result, they will do better than neophytes. Fortunately, first-timers are not destined for failure. They should just temper their expectations.

2. What business problem do you think you’re trying to solve?

This might seem obvious, but plenty of folks fail to ask it before jumping in. Note here how I qualified the first question with “do you think.” Sometimes the root cause of a problem isn’t what we believe it to be; in other words, it’s often not what we at first think.

In any case, you don’t need to solve the entire problem all at once by trying to boil the ocean. In fact, you shouldn’t take this approach. Project methodologies (like agile) allow organizations to take an iterative approach and embrace the power of small batches.

3. What types and sources of data are available to you?

Most if not all organizations store vast amounts of enterprise data. Looking at internal databases and data sources makes sense. Don’t make the mistake of believing, though, that the discussion ends there.

External data sources in the form of open data sets (such as data.gov) continue to proliferate. There are easy methods for retrieving data from the web and getting it back in a usable format – scraping, for example. This tactic can work well in academic environments, but scraping could be a sign of data immaturity for businesses. It’s always best to get your hands on the original data source when possible.

Caveat: Just because the organization stores it doesn’t mean you’ll be able to easily access it. Pernicious internal politics stifle many an analytics endeavor.

4. What types and sources of data are you allowed to use?

With all the hubbub over privacy and security these days, foolish is the soul who fails to ask this question. As some retail executives have learned in recent years, a company can abide by the law completely and still make people feel decidedly icky about the privacy of their purchases. Or, consider a health care organization – it may not technically violate the Health Insurance Portability and Accountability Act of 1996 (HIPAA), yet it could still raise privacy concerns.

Another example is the GDPR. Adhering to this regulation means that organizations won’t necessarily be able to use personal data they previously could use – at least not in the same way.

5. What is the quality of your organization’s data?

Common mistakes here include assuming your data is complete, accurate and unique (read: nonduplicate). During my consulting career, I could count on one hand the number of times a client handed me a “perfect” data set. While it’s important to cleanse your data, you don’t need pristine data just to get started. As Voltaire said, “Perfect is the enemy of good.”

6. What tools are available to extract, clean, analyze and present the data?

This isn’t the 1990s, so please don’t tell me that your analytic efforts are limited to spreadsheets. Sure, Microsoft Excel works with structured data – if the data set isn’t all that big. Make no mistake, though: Everyone’s favorite spreadsheet program suffers from plenty of limitations, in areas like:

  • Handling semistructured and unstructured data.
  • Tracking changes/version control.
  • Dealing with size restrictions.
  • Ensuring governance.
  • Providing security.

For now, suffice it to say that if you’re trying to analyze large, complex data sets, there are many tools well worth exploring. The same holds true for visualization. Never before have we seen such an array of powerful, affordable and user-friendly tools designed to present data in interesting ways.

Caveat 1: While software vendors often ape each other’s features, don’t assume that each application can do everything that the others can.

Caveat 2: With open source software, remember that “free” software could be compared to a “free” puppy. To be direct: Even with open source software, expect to spend some time and effort on training and education.

7. Do your employees possess the right skills to work on the data analytics project?

The database administrator may well be a whiz at SQL. That doesn’t mean, though, that she can easily analyze gigabytes of unstructured data. Many of my students need to learn new programs over the course of the semester, and the same holds true for employees. In fact, organizations often find that they need to:

  • Provide training for existing employees.
  • Hire new employees.
  • Contract consultants.
  • Post the project on sites such as Kaggle.
  • All of the above.

Don’t assume that your employees can pick up new applications and frameworks 15 minutes at a time every other week. They can’t.

8. What will be done with the results of your analysis?

A company routinely spent millions of dollars recruiting MBAs at Ivy League schools only to see them leave within two years. Rutgers MBAs, for their part, stayed much longer and performed much better.

Despite my findings, the company continued to press on. It refused to stop going to Harvard, Cornell, etc. because of vanity. In his own words, the head of recruiting just “liked” going to these schools, data be damned.

Food for thought: What will an individual, group, department or organization do with keen new insights from your data analytics projects? Will the result be real action? Or will a report just sit in someone’s inbox?

9. What types of resistance can you expect?

You might think that people always and willingly embrace the results of data-oriented analysis. And you’d be spectacularly wrong.

Case in point: Major League Baseball (MLB) umpires get close ball and strike calls wrong more often than you’d think. Why wouldn’t they want to improve their performance when presented with objective data? It turns out that many don’t. In some cases, human nature makes people want to reject data and analytics that contrast with their world views. Years ago, before the subscription model became wildly popular, some Blockbuster executives didn’t want to believe that more convenient ways to watch movies existed.

Caveat: Ignore the power of internal resistance at your own peril.

10. What are the costs of inaction?

Sure, this is a high-level query and the answers depend on myriad factors.

For instance, a pharma company with years of patent protection will respond differently than a startup with a novel idea and competitors nipping at its heels. Interesting subquestions here include:

  • Do the data analytics projects merely confirm what we already know?
  • Do the numbers show anything conclusive?
  • Could we be capturing false positives and false negatives?

Think about these questions before undertaking data analytics projects Don’t take the queries above as gospel. By and large, though, experience proves that asking these questions frames the problem well and sets the organization up for success – or at least minimizes the chance of a disaster.

SAS2

Most organizations understand the importance of data governance in concept. But they may not realize all the multifaceted, positive impacts of applying good governance practices to data across the organization. For example, ensuring that your sales and marketing analytics relies on measurably trustworthy customer data can lead to increased revenue and shorter sales cycles. And having a solid governance program to ensure your enterprise data meets regulatory requirements could help you avoid penalties.

Companies that start data governance programs are motivated by a variety of factors, internal and external. Regardless of the reasons, two common themes underlie most data governance activities: the desire for high-quality customer information, and the need to adhere to requirements for protecting and securing that data.

What’s the best way to ensure you have accurate customer data that meets stringent requirements for privacy and security?

For obvious reasons, companies exert significant effort using tools and third-party data sets to enforce the consistency and accuracy of customer data. But there will always be situations in which the managed data set cannot be adequately synchronized and made consistent with “real-world” data. Even strictly defined and enforced internal data policies can’t prevent inaccuracies from creeping into the environment.

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Why you should move beyond a conventional approach to data governance?

When it comes to customer data, the most accurate sources for validation are the customers themselves! In essence, every customer owns his or her information, and is the most reliable authority for ensuring its quality, consistency and currency. So why not develop policies and methods that empower the actual owners to be accountable for their data?

Doing this means extending the concept of data governance to the customers and defining data policies that engage them to take an active role in overseeing their own data quality. The starting point for this process fits within the data governance framework – define the policies for customer data validation.

A good template for formulating those policies can be adapted from existing regulations regarding data protection. This approach will assure customers that your organization is serious about protecting their data’s security and integrity, and it will encourage them to actively participate in that effort.

Examples of customer data engagement policies

  • Data protection defines the levels of protection the organization will use to protect the customer’s data, as well as what responsibilities the organization will assume in the event of a breach. The protection will be enforced in relation to the customer’s selected preferences (which presumes that customers have reviewed and approved their profiles).
  • Data access control and security define the protocols used to control access to customer data and the criteria for authenticating users and authorizing them for particular uses.
  • Data use describes the ways the organization will use customer data.
  • Customer opt-in describes the customers’ options for setting up the ways the organization can use their data.
  • Customer data review asserts that customers have the right to review their data profiles and to verify the integrity, consistency and currency of their data. The policy also specifies the time frame in which customers are expected to do this.
  • Customer data update describes how customers can alert the organization to changes in their data profiles. It allows customers to ensure their data’s validity, integrity, consistency and currency.
  • Right-to-use defines the organization’s right to use the data as described in the data use policy (and based on the customer’s selected profile options). This policy may also set a time frame associated with the right-to-use based on the elapsed time since the customer’s last date of profile verification.

The goal of such policies is to establish an agreement between the customer and the organization that basically says the organization will protect the customer’s data and only use it in ways the customer has authorized – in return for the customer ensuring the data’s accuracy and specifying preferences for its use. This model empowers customers to take ownership of their data profile and assume responsibility for its quality.

Clearly articulating each party’s responsibilities for data stewardship benefits both the organization and the customer by ensuring that customer data is high-quality and properly maintained. Better yet, recognize that the value goes beyond improved revenues or better compliance.

Empowering customers to take control and ownership of their data just might be enough to motivate self-validation.

Click her to access SAS’ detailed analysis

Optimize for both Social and Business Value – Building Resilient Businesses, Industries, and Societies

Why Is Corporate Capitalism at a Tipping Point?

Stakeholders are beginning to pressure companies and investors to go beyond financial returns and take a more holistic view of their impact on society. This should not surprise us. After all, we have lived through two decades of hyper-transformation, during which rapidly evolving digital technologies, globalization, and massive investment flows have stressed and reshaped every aspect of business and society.

As in previous transformations, the winners created new dimensions of competition and built innovative business models that increased returns for shareholders. Many others found their businesses at risk of being disrupted, with familiar formulas no longer working. To meet the unwavering demands of Wall Street, many companies relentlessly optimized operating models, streamlined and concentrated supply chains, and specialized their assets and teams — leaving them less resilient and less adaptable to shifting markets and trade flows. The resulting waves of corporate restructuring, consolidation, and repositioning have fractured companies’ cultures and undermined their social contracts.

Furthermore, this hyper-transformation cascaded beyond individual companies and created socio-economic dynamics that left many people and communities economically disadvantaged and politically polarized. Combined with the increasing shared anxiety that the earth’s climate is changing faster than the planet can adapt, a global zeitgeist of risk and insecurity has emerged. We will enter the 2020s with more citizens, investors, and leaders convinced that the way business, capital, and government work must change — and change quickly.

We now must rethink the sustainability of the whole system in the face of extreme externalities — or risk losing social and political permission for further progress. The 2030 UN Sustainable Development Goals (SDGs) identify the moral and existential threats that we must meet head-on. While some question the SDGs’ breadth and timeline, most agree that, if achieved, they would create a more just, inclusive, and sustainable world.

Goal 17 calls for new engagement by companies and capital in partnership for collective action across the public, social, and private sectors. Five years into the SDG agenda, there is ample evidence that governments, investors, and companies are beginning to exercise their capacity to create much-needed change.

Change Is Underway but Is Hardly Sufficient

Many institutional investors are racing to integrate ESG (environmental, social, and governance) assessments into their decision making, and they are expecting companies to report on how they deliver on those metrics. New efforts promote radical disclosure, like the Bloomberg/Carney TCFD (Task Force on Climate-Related Financial Disclosures), which encourages signatories to report on the climate risks of their financial holdings.

New standards initiatives are creating a foundation for nonfinancial performance accounting, and the prospect of widespread “integrated reporting” seems realistic. Companies are investing in “purpose” and defining their contributions to society against material ESG factors and SDG goals. Corporate sustainability and CSR (Corporate Social Responsibility) functions, historically on the sidelines, are now being integrated into line business activity, with progressive companies expanding the scope of competition to include differentiation on environmental and societal dimensions. And through industry consortia, many companies are taking collective action on issues that both threaten their right to operate and open up new opportunities for their industries.

Such examples are important early signals that the context for business is changing. However, for all the progress on commitments, agreements, metrics, and policies, there has been little aggregate progress against top-level goals, like

  • reducing CO2 emissions,
  • cutting plastics waste,
  • or narrowing social and economic inequality within nations.

Without demonstrable impact and collective progress, social and political pressure will only build, further threatening the legitimacy of corporate capitalism.

A New Societal Context for Business

Companies will face escalating social activism by investors, stakeholders, social mission organizations, and policymakers on issues of

  • climate risk,
  • economic inequality,
  • and societal well-being.

Governments and local communities will set a higher bar for a company’s right to operate, and in a connected world a company’s local performance will quickly affect its global reputation and trigger social and regulatory consequences. Stakeholders will expect radical transparency on ESG performance.

This will shift investors’ perceptions of a company’s risk and opportunity, skewing capital toward those that deliver both financial returns and positive societal impact. To satisfy a growing demographic of socially minded consumers and businesses, companies will need to demonstrate “good products doing good” and anchor their brands and identity around a credible purpose.

Talent will gravitate toward companies that give employees a line-of-sight to making the world better while also providing a fulfilling career. To win, companies will need to define competition more broadly, adding new dimensions of value through

  • environmental sustainability,
  • holistic well-being,
  • economic inclusion,
  • and ethical content.

This will require radical business model innovation

  • to enable circular economies for precious resources;
  • to provide assets that are shared rather than owned;
  • to broaden access and inclusion;
  • and to multiply positive societal impact.

At this critical moment for corporate capitalism, business is more trusted than government, according to the Edelman Trust Barometer. Farsighted corporate leaders will see the opportunity for their industries to

  • mitigate environmental and societal threats,
  • catalyze collective action to discover new solutions,
  • shape wider ecosystems,
  • and expand trust with stakeholders.

Such actions will be indispensable to strengthen social permission for corporate capitalism before it is further undermined.

CEOs Need an Agenda for Value and the Common Good

We frame the journey to new corporate value and the common good around six imperatives.

It begins with reimagining corporate strategy, then

  • involves transforming the business model,
  • reframing performance and scorekeeping,
  • leading a purpose-filled organization,
  • practicing corporate statesmanship,
  • and elevating governance.

BCG 1

While challenging to execute, we argue that this agenda will be essential to create a great company, a great stock, a great impact, and a great legacy.

Reimagine Corporate Strategy

We believe few companies have strategies for this new era of business. The following exhibit illustrates the ambition of such a strategy, which establishes competitive advantage at the intersection of

  • shareholder value,
  • corporate longevity,
  • and societal impact.

The “quality” of the strategy is thus judged by how it delivers both total shareholder returns and total societal impact.

BCG 2

Consequently, it widens the scope of competition to encompass creating rich differentiation and relative advantage in multiple areas of societal value. It embeds “social value” into new business constructs, shared value chains, and reconstructed ecosystems.

It also opens, broadens, and deepens markets to enable access and inclusion. And it expands the scope of business by calling for coalitions for collective action that address existential risks to environmental and societal ecosystems.

This new type of strategy flips leadership’s perspective from “company-out” to “societal needs-in,” by asking how a specific SDG target could be met by extending the company’s capabilities, assets, products, services, and ecosystem—and those of its industry. The following exhibit lists ten questions that strategists should incorporate into their strategy processes to ensure that they embrace the opportunity to create both shareholder returns and societal impact.

BCG 3

However, these new strategies cannot simply be grafted onto existing business models. Business models themselves will need to be transformed. Sustainable business model innovation (S-BMI) takes a much wider perspective than traditional business model innovation by considering

  • a broader set of stakeholders;
  • the system dynamics of the socio-environmental context;
  • longer time horizons for sustaining adaptable advantage;
  • the limits of business model scale, viability, and resilience;
  • the cradle-to-grave production and consumption cycle;
  • and the points of leverage for profitable and sustainable transformation.

Transform Business Models

We can already observe seven topologies for sustainable business model innovation, sometimes in combination, all with the potential to increase both financial returns and societal benefits.

  • Own the origins. Compete on capturing and differentiating the “social value” of inputs to production processes, products, or services. For example,
    • pursue cleaner energy,
    • sustainable practices,
    • preserved biodiversity,
    • recycled content,
    • inclusive and empowering work practices,
    • minimized waste,
    • digitized traceability,
    • fair trade, and so on.

Performance here will require differentially advancing the societal performance of the supplier base and its stewardship of resources, communities, and trade flows. Achieving this may require backward integration to ensure fast and complete upstream transformation and then holding and using these new capabilities for competitive advantage and differentiation.

  • Own the whole cycle. Compete by creating societal impact through the whole product usage cycle, from creation through end of life. This competitive typology puts a wide aperture on the business and requires systems analysis to uncover business models that offer the richest competitive and financial options. For example,
    • designing for circularity, recyclability, and waste to value;
    • creating offerings that enable sharing rather than owning to ensure high utilization of resources and end-of-life value;
    • constructing infrastructure to facilitate circularity and repurposing;
    • integrating into other value chains to capture societal value;
    • educating and enabling consumers to choose whole-cycle propositions on the basis of value to people and planet.

To achieve these ends, expect to reposition operations, reinvent supply chains and distribution networks, pursue new backward or forward integration, acquire business adjacencies, or undertake unconventional strategic partnering.

  • Expand “social value.” Compete by expanding the value of products or services on six dimensions:
    • economic gains,
    • environmental sustainability,
    • customer well-being,
    • ethical content,
    • societal enablement,
    • and access and inclusion.

Then advocate new standards, increase transparency and traceability, tune marketing and segmentation, engage customers on the product’s wider value and their involvement in bigger change, and seek premium pricing. In business-to-business offerings, help customers integrate the full social value of your products, services, and business model into their own differentiation and ESG ambitions.

  • Expand the chains. Compete by extending the company’s value chain, layering onto other industries’ value chains to extend the reach of your products and services and the societal impact for both parties, while changing the economics and risks of doing so. For example,
    • use the reach of a consumer products distribution system to extend payments and financial services to small merchants;
    • layer one company’s health services onto another company’s physical supply chain to benefit its workers and their families while expanding markets for health services;
    • or use the byproducts of one company’s operations as feedstock in other companies’ value chains.
  • Energize the brand. Compete by digitally encoding, promoting, and monetizing the full accumulated social value that is embedded in products and services, along the whole value chain— from origins to customer, from cradle to grave. Use such data to rethink differentiation, the brand experience, customer engagement, pricing for value, ESG reporting, investor engagement, and even potential new businesses. For example,
    • strengthen the brand with promotions that showcase the business’s performance on the open, clean, green, renewable, and inclusive attributes of its operations;
    • and increase customer engagement and loyalty by using data on the product’s environmental and societal footprint to empower customers in choosing how their lifestyle affects the planet and its people.
  • Relocalize and regionalize. Compete by contracting and reconnecting global value chains to bring societal benefits closer to home markets in ways stakeholders value. For example,
    • build local and regional brands that better express local tastes and values;
    • source from smaller local producers to minimize logistics emissions and strengthen local economies;
    • reimagine production networks against total environmental and societal costs;
    • capture local waste streams as feedstocks for other activities;
    • or reconstitute jobs for microwork to use local talent.
  • Build across sectors. Compete by creating models that include the public and social sectors to improve the company’s business and societal proposition, particularly in emerging and rapidly developing economies. For example,
    • work alongside governmental bilateral aid institutions and NGO development organizations to improve the agricultural capacity of small farmers so they become reliable sources of agricultural inputs to the agro-processing value chain;
    • partner with global environmental organizations and governments to promote the reuse of ocean plastics as feedstocks to production systems;
    • partner with governments to strengthen social safety nets and prevent corruption through digitization and electronic payments;
    • or partner across sectors to restructure recycling systems to enable higher penetration of waste-to-value business models.

Extend this into industry coalitions for collective action that reshape broader rights to operate and generate new opportunities.

All seven types of S-BMI create new sources of differentiation, operating advantage, network dynamics, and societal value — enabling more durable and resilient businesses that benefit shareholders and society. But to assess and improve the performance of these business models and communicate their value, we need to expand today’s scorecards.

Click her to access BCG’s full article

 

From Risk to Strategy : Embracing the Technology Shift

The role of the risk manager has always been to understand and manage threats to a given business. In theory, this involves a very broad mandate to capture all possible risks, both current and future. In practice, however, some risk managers are assigned to narrower, siloed roles, with tasks that can seem somewhat disconnected from key business objectives.

Amidst a changing risk landscape and increasing availability of technological tools that enable risk managers to do more, there is both a need and an opportunity to move toward that broader risk manager role. This need for change – not only in the risk manager’s role, but also in the broader approach to organizational risk management and technological change – is driven by five factors.

Marsh Ex 1

The rapid pace of change has many C-suite members questioning what will happen to their business models. Research shows that 73 percent of executives predict significant industry disruption in the next three years (up from 26 percent in 2018). In this challenging environment, risk managers have a great opportunity to demonstrate their relevance.

USING NEW TOOLS TO MANAGE RISKS

Emerging technologies present compelling opportunities for the field of risk management. As discussed in our 2017 report, the three levers of data, analytics, and processes allow risk professionals a framework to consider technology initiatives and their potential gains. Emerging tools can support risk managers in delivering a more dynamic, in-depth view of risks in addition to potential cost-savings.

However, this year’s survey shows that across Asia-Pacific, risk managers still feel they are severely lacking knowledge of emerging technologies across the business. Confidence scores were low in all but one category, risk management information systems (RMIS). These scores were only marginally higher for respondents in highly regulated industries (financial services and energy utilities), underscoring the need for further training across all industries.

Marsh Ex 3

When it comes to technology, risk managers should aim for “digital fluency, a level of familiarity that allows them to

  • first determine how technologies can help address different risk areas,
  • and then understand the implications of doing so.

They need not understand the inner workings of various technologies, as their niche should remain aligned with their core expertise: applying risk technical skills, principles, and practices.

CULTIVATING A “DIGITAL-FIRST” MIND-SET

Successful technology adoption does not only present a technical skills challenge. If risk function digitalization is to be effective, risk managers must champion a cultural shift to a “digital-first” mindset across the organization, where all stakeholders develop a habit of thinking about how technology can be used for organizational benefit.

For example, the risk manager of the future will be looking to glean greater insights using increasingly advanced analytics capabilities. To do this, they will need to actively encourage their organization

  • to collect more data,
  • to use their data more effectively,
  • and to conduct more accurate and comprehensive analyses.

Underlying the risk manager’s digitalfirst mind-set will be three supporting mentalities:

1. The first of these is the perception of technology as an opportunity rather than a threat. Some understandable anxiety exists on this topic, since technology vendors often portray technology as a means of eliminating human input and labor. This framing neglects the gains in effectiveness and efficiency that allow risk managers to improve their judgment and decision making, and spend their time on more value-adding activities. In addition, the success of digital risk transformations will depend on the risk professionals who understand the tasks being digitalized; these professionals will need to be brought into the design and implementation process right from the start. After all, as the Japanese saying goes, “it is workers who give wisdom to the machines.” Fortunately, 87 percent of PARIMA surveyed members indicated that automating parts of the risk manager’s job to allow greater efficiency represents an opportunity for the risk function. Furthermore, 63 percent of respondents indicated that this was not merely a small opportunity, but a significant one (Exhibit 6). This positive outlook makes an even stronger statement than findings from an earlier global study in which 72 percent of employees said they see technology as a benefit to their work

2. The second supporting mentality will be a habit of looking for ways in which technology can be used for benefit across the organization, not just within the risk function but also in business processes and client solutions. Concretely, the risk manager can embody this culture by adopting a data-driven approach, whereby they consider:

  • How existing organizational data sources can be better leveraged for risk management
  • How new data sources – both internal and external – can be explored
  • How data accuracy and completeness can be improved

“Risk managers can also benefit from considering outside-the-box use cases, as well as keeping up with the technologies used by competitors,” adds Keith Xia, Chief Risk Officer of OneHealth Healthcare in China.

This is an illustrative rather than comprehensive list, as a data-driven approach – and more broadly, a digital mind-set – is fundamentally about a new way of thinking. If risk managers can grow accustomed to reflecting on technologies’ potential applications, they will be able to pre-emptively spot opportunities, as well as identify and resolve issues such as data gaps.

3. All of this will be complemented by a third mentality: the willingness to accept change, experiment, and learn, such as in testing new data collection and analysis methods. Propelled by cultural transformation and shifting mind-sets, risk managers will need to learn to feel comfortable with – and ultimately be in the driver’s seat for – the trial, error, and adjustment that accompanies digitalization.

MANAGING THE NEW RISKS FROM EMERGING TECHNOLOGIES

The same technological developments and tools that are enabling organizations to transform and advance are also introducing their own set of potential threats.

Our survey shows the PARIMA community is aware of this dynamic, with 96 percent of surveyed members expecting that emerging technologies will introduce some – if not substantial – new risks in the next five years.

The following exhibit gives a further breakdown of views from this 96 percent of respondents, and the perceived sufficiency of their existing frameworks. These risks are evolving in an environment where there are already questions about the relevance and sufficiency of risk identification frameworks. Risk management has become more challenging due to the added complexity from rapid shifts in technology, and individual teams are using risk taxonomies with inconsistent methodologies, which further highlight the challenges that risk managers face in managing their responses to new risk types.

Marsh Ex 9

To assess how new technology in any part of the organization might introduce new risks, consider the following checklist :

HIGH-LEVEL RISK CHECKLIST FOR EMERGING TECHNOLOGY

  1. Does the use of this technology cut across existing risk types (for example, AI risk presents a composite of technology risk, cyber risk, information security risk, and so on depending on the use case and application)? If so, has my organization designated this risk as a new, distinct category of risk with a clear definition and risk appetite?
  2. Is use of this technology aligned to my company’s strategic ambitions and risk appetite ? Are the cost and ease of implementation feasible given my company’s circumstances?
  3. Can this technology’s implications be sufficiently explained and understood within my company (e.g. what systems would rely on it)? Would our use of this technology make sense to a customer?
  4. Is there a clear view of how this technology will be supported and maintained internally, for example, with a digitally fluent workforce and designated second line owner for risks introduced by this technology (e.g. additional cyber risk)?
  5. Has my company considered the business continuity risks associated with this technology malfunctioning?
  6. Am I confident that there are minimal data quality or management risks? Do I have the high quality, large-scale data necessary for advanced analytics? Would customers perceive use of their data as reasonable, and will this data remain private, complete, and safe from cyberattacks?
  7. Am I aware of any potential knock-on effects or reputational risks – for example, through exposure to third (and fourth) parties that may not act in adherence to my values, or through invasive uses of private customer information?
  8. Does my organization understand all implications for accounting, tax, and any other financial reporting obligations?
  9. Are there any additional compliance or regulatory implications of using this technology? Do I need to engage with regulators or seek expert advice?
  10. For financial services companies: Could I explain any algorithms in use to a customer, and would they perceive them to be fair? Am I confident that this technology will not violate sanctions or support crime (for example, fraud, money laundering, terrorism finance)?

SECURING A MORE TECHNOLOGY-CONVERSANT RISK WORKFORCE

As risk managers focus on digitalizing their function, it is important that organizations support this with an equally deliberate approach to their people strategy. This is for two reasons, as Kate Bravery, Global Solutions Leader, Career at Mercer, explains: “First, each technological leap requires an equivalent revolution in talent; and second, talent typically becomes more important following disruption.”

While upskilling the current workforce is a positive step, as addressed before, organizations must also consider a more holistic talent management approach. Risk managers understand this imperative, with survey respondents indicating a strong desire to increase technology expertise in their function within the next five years.

Yet, little progress has been made in adding these skills to the risk function, with a significant gap persisting between aspirations and the reality on the ground. In both 2017 and 2019 surveys, the number of risk managers hoping to recruit technology experts has been at least 4.5 times the number of teams currently possessing those skills.

Marsh Ex 15

EMBEDDING RISK CULTURE THROUGHOUT THE ORGANIZATION

Our survey found that a lack of risk management thinking in other parts of the organization is the biggest barrier the risk function faces in working with other business units. This is a crucial and somewhat alarming finding – but new technologies may be able to help.

Marsh Ex 19

As technology allows for increasingly accurate, relevant, and holistic risk measures, organizations should find it easier to develop risk-based KPIs and incentives that can help employees throughout the business incorporate a risk-aware approach into their daily activities.

From an organizational perspective, a first step would be to describe risk limits and risk tolerance in a language that all stakeholders can relate to, such as potential losses. Organizations can then cascade these firm-wide risk concepts down to operational business units, translating risk language into tangible and relevant incentives that encourages behavior that is consistent with firm values. Research shows that employees in Asia want this linkage, citing a desire to better align their individual goals with business goals.

The question thus becomes how risk processes can be made an easy, intuitive part of employee routines. It is also important to consider KPIs for the risk team itself as a way of encouraging desirable behavior and further embedding a risk-aware culture. Already a majority of surveyed PARIMA members use some form of KPIs in their teams (81 percent), and the fact that reporting performance is the most popular service level measure supports the expectation that PARIMA members actively keep their organization informed.

Marsh Ex 21

At the same time, these survey responses also raise a number of questions. Forty percent of organizations indicate that they measure reporting performance, but far fewer are measuring accuracy (15 percent) or timeliness (16 percent) of risk analytics – which are necessary to achieve improved reporting performance. Moreover, the most-utilized KPIs in this year’s survey tended to be tangible measures around cost, from which it can be difficult to distinguish a mature risk function from a lucky one.

SUPPORTING TRANSFORMATIONAL CHANGE PROGRAMS

Even with a desire from individual risk managers to digitalize and complement organizational intentions, barriers still exist that can leave risk managers using basic tools. In 2017, cost and budgeting concerns were the single, standout barrier to risk function digitalization, chosen by 67 percent of respondents, well clear of second placed human capital concerns at 18 percent. This year’s survey responses were much closer, with a host of ongoing barriers, six of which were cited by more than 40 percent of respondents.

Marsh Ex 22

Implementing the nuts and bolts of digitalization will require a holistic transformation program to address all these barriers. That is not to say that initiatives must necessarily be massive in scale. In fact, well-designed initiatives targeting specific business problems can be a great way to demonstrate success that can then be replicated elsewhere to boost innovation.

Transformational change is inherently difficult, in particular where it spans both technological as well as people dimensions. Many large organizations have generally relied solely on IT teams for their “digital transformation” initiatives. This approach has had limited success, as such teams are usually designed to deliver very specific business functionalities, as opposed to leading change initiatives. If risk managers are to realize the benefits of such transformation, it is incumbent on them to take a more active role in influencing and leading transformation programs.

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