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The Future of CFO’s Business Partnering

BP² – the next generation of Business Partner

The role of business partner has become almost ubiquitous in organizations today. According to respondents of this survey, 88% of senior finance professionals already consider themselves to be business partners. This key finding suggests that the silo mentality is breaking down and, at last, departments and functions are joining forces to teach and learn from each other to deliver better performance. But the scope of the role, how it is defined, and how senior finance executives characterize their own business partnering are all open to interpretation. And many of the ideas are still hamstrung by traditional finance behaviors and aspirations, so that the next generation of business partners as agents of change and innovation languish at the bottom of the priority list.

The scope of business partnering

According to the survey, most CFOs see business partnering as a blend of traditional finance and commercial support, while innovation and change are more likely to be seen as outside the scope of business partnering. 57% of senior finance executives strongly agree that a business partner should challenge budgets, plans and forecasts. Being involved in strategy and development followed closely behind with 56% strongly agreeing that it forms part of the scope of business partnering, while influencing commercial decisions was a close third.

The pattern that emerges from the survey is that traditional and commercial elements are given more weight within the scope of business partnering than being a catalyst for change and innovation. This more radical change agenda is only shared by around 36% of respondents, indicating that finance professionals still largely see their role in traditional or commercial terms. They have yet to recognize the finance function’s role in the next generation of business partnering, which can be

  • the catalyst for innovation in business models,
  • for process improvements
  • and for organizational change.

Traditional and commercial business partners aren’t necessarily less important than change agents, but the latter has the potential to add the most value in the longer term, and should at least be in the purview of progressive CFOs who want to drive change and encourage growth.

Unfortunately, this is not an easy thing to change. Finding time for any business partnering can be a struggle, but CFOs spend disproportionately less time on activities that bring about change than on traditional business partnering roles. Without investing time and effort into it, CFOs will struggle to fulfill their role as the next generation of business partner.

Overall 45% of CFOs struggle to make time for any business partnering, so it won’t come as a surprise that, ultimately, only 57% of CFOs believe their finance team efforts as business partners are well regarded by the operational functions.

The four personas of business partnering

Ask a room full of CFOs what business partnering means and you’ll get a room full of answers, each one influenced by their personal journey through the changing business landscape. By its very variability, this important business process is being enacted in many ways. FSN, the survey authors, did not seek to define business partnering. Instead, the survey asked respondents to define business partnering in their own words, and the 366 detailed answers were all different. But underlying the diversity were patterns of emphasis that defined four ‘personas’ or styles of business partnering, each exerting its own influence on the growth of the business over time.

A detailed analysis of the definitions and the frequency of occurrence of key phrases and expressions allowed us to plot these personas, their relative weight, together with their likely impact on growth over time.

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The size of the bubbles denotes the frequency (number) of times an attribute of business partnering was referenced in the definitions and these were plotted in terms of their likely contribution to growth in the short to long term.

The greatest number of comments by far coalesced around the bottom left-hand quadrant denoting a finance-centric focus on short to medium term outcomes, i.e., the traditional finance business partner. But there was an encouraging drift upwards and rightwards towards the quadrant denoting what we call the next generation of business partner, “BP²” (BP Squared), a super-charged business partner using his or her wide experience, purview and remit to help bring about change in the organization, for example, new business models, new processes and innovative methods of organizational deployment.

Relatively few of the 383 business partners offering definitions of a business partner, concerned themselves with top line growth i.e. with involvement in commercial sales negotiations or the sales pipeline – a critical part of influencing growth.

Finally, surprisingly few finance business partners immersed themselves in strategy development or saw their role as helping to ensure strategic alignment. It suggests that the ongoing transition of the CFO’s role from financial steward to strategic advisor is not as advanced as some would suggest.

Financial Performance Drivers

Most CFOs and senior finance executives define the role of the business partner in traditional financial terms. They are there to explain and illuminate the financial operations, be a trusted, safe pair of hands that manages business risk, and provide s ome operational support. The focus for these CFOs is on communicating a clear understanding of the financial imperative in order to steer the performance of the business prudently.

This ideal reflects the status quo and perpetuates the traditional view of finance, and the role of the CFO. It’s one where the finance function remains a static force, opening up only so far as to allow the rest of the business to see how it functions and make them more accountable to it. While it is obviously necessary for other functions to understand and support a financial strategy, the drawback of this approach is the shortcomings for the business as a whole. Finance-centric business partnering provides some short-term outcomes but does little to promote more than pedestrian growth. It’s better than nothing, but it’s far from the best.

Top-Line Drivers

In the upper quadrant, top line drivers focus on driving growth and sales with a collaborative approach to commercial decision-making. This style of business partnering can have a positive effect on earnings, as improvements in commercial operations and the management of the sales pipeline are translated into revenue.

But while top line drivers are linked to higher growth than financial-focused business partners, the outcome tends to be only short term. The key issue for CFOs is that very few of them even allude to commercial partnerships when defining the scope of business partnering. They ignore the potential for the finance function to help improve the commercial outcomes, like sales or the collection of debt or even a change in business models.

Strategic Aligners

Those CFOs who focus on strategic alignment in their business partnering approach tend to see longer term results. They use analysis and strategy to drive decisionmaking, bringing business goals into focus through partnerships and collaborative working. This business benefit helps to strengthen the foundation of the business in the long term, but it isn’t the most effective in driving substantial growth. And again, there is a paucity of CFOs and senior finance executives who cited strategy development and analysis in their definition of business partnering.

Catalysts for change

The CFOs who were the most progressive and visionary in their definition of business partnering use the role as a catalyst for change. They challenge their colleagues, influence the strategic direction of the business, and generate momentum through change and innovation from the very heart of the finance function. These finance executives get involved in decision-making, and understand the need to influence, advise and challenge in order to promote change. This definition is the one that translates into sustained high growth.

The four personas are not mutually exclusive. Some CFOs view business partnering as a combination of some or all of these attributes. But the preponderance of opinion is clustered around the traditional view of finance, while very little is to do with being a catalyst for change.

How do CFOs characterize their finance function?

However CFOs choose to define the role of business partnering, each function has its own character and style. According to the survey, 17% have a finance-centric approach to business partnering, limiting the relationship to financial stewardship and performance. A further 18% have to settle for a light-touch approach where they are occasionally invited to become involved in commercial decision-making. This means 35% of senior finance executives are barely involved in any commercial decision-making at all.

More positively, the survey showed that 46% are considered to be trusted advisors, and are sought out by operational business teams for opinions before they make big commercial or financial decisions.

But at the apex of the business partnering journey are the change agents, who make up a paltry 19% of the senior finance executives surveyed. These forward thinkers are frequently catalysts for change, suggesting new business processes and areas where the company can benefit from innovation. This is the next stage in the evolution of both the role of the modern CFO and the role of the finance function at the heart of business innovation. We call CFOs in this category BP² (BP Squared) to denote the huge distance between these forward-thinking individuals and the rest of the pack.

Measuring up

Business partnering can be a subtle yet effective process, but it’s not easy to measure. 57% of organizations have no agreed way of measuring the success of business partnering, and 34% don’t think it’s possible to separate and quantify the value added through this collaboration.

Yet CFOs believe there is a strong correlation between business partnering and profitability – with 91% of respondents saying their business partnering efforts significantly add to profitability. While it’s true that some of the outcomes of business partnering are intangible, it is still important to be able to make a direct connection between it and improved performance, otherwise those efforts may be ineffective but are allowed to continue.

One solution is to use 360 degree appraisals, drawing in a wider gamut of feedback including business partners and internal customers to ascertain the effectiveness of the process. Finance business partnering can also be quantified if there are business model changes, like the move from product sales to services, which require a generous underpinning of financial input to be carried out effectively.

Business partnering offers companies a way to inexpensively

  • pool all their best resources to generate ideas,
  • spark innovation
  • and positively add value to the business.

First CFOs need to recognize the importance of business partnering, widen their idea of how it can add value, and then actually set aside the enough time to become agents of change and growth.

Data unlocks business partnering

Data is the most valuable organizational currency in today’s competitive business environment. Most companies are still in the process of working out the best method to collect, collate and use the tsunami of data available to them in order to generate insight. Some organizations are just at the start of their data journey, others are more advanced, and our research confirms that their data profile will make a significant difference to how well their business partnering works.

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The survey asked how well respondents’ data supported the role of business partnering, and the responses showed that 18% were data overloaded. This meant business partners have too many conflicting data sources and poor data governance, leaving them with little actual usable data to support the partnering process.

26% were data constrained, meaning they cannot get hold of the data they need to drive insight and decision making.

And a further 34% were technology constrained, muddling through without the tech savvy resources or tools to fully exploit the data they already have. These senior finance executives may know the data is there, sitting in an ERP or CRM system, but can’t exploit it because they lack the right technology tools.

The final 22% have achieved data mastery, where they actively manage their data as a corporate asset, and have the tools and resources to exploit it in order to give their company a competitive edge.

This means 78% overall are hampered by data constraints and are failing to use data effectively to get the best out of their business partnering. While the good intentions are there, it is a weak partnership because there is little of substance to work with.

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The diagram above is the Business Partnering Maturity Model as it relates to data. It illustrates that there is a huge gap in performance between how effective data masters and data laggards are at business partnering.

The percentage of business partners falling into each category of data management (‘data overloaded’, ‘data constrained,’ etc) has been plotted together with how well these finance functions feel that business partnering is regarded by the operational units as well as their perceived influence on change.

The analysis reveals that “Data masters” are in a league of their own. They are significantly more likely to be well regarded by the operations and are more likely to act as change agents in their business partnering role.

We know from FSN’s 2018 Innovation in Financial Reporting survey that data masters, who similarly made up around one fifth of senior finance executives surveyed, are also more innovative. That research showed they were more likely to have worked on innovative projects in the last three years, and were less likely to be troubled by obstacles to reporting and innovation.

Data masters also have a more sophisticated approach to business partnering. They’re more likely to be change agents, are more often seen as a trusted advisor and they’re more involved in decision making. Interestingly, two-thirds of data masters have a formal or agreed way to measure the success of business partnering, compared to less than 41% of data constrained CFOs, and 36% of technology constrained and data overloaded finance executives. They’re also more inclined to perform 360 degree appraisals with their internal customers to assess the success of their business partnering. This means they can monitor and measure their success, which allows them to adapt and improve their processes.

The remainder, i.e. those that have not mastered their data, are clustered around a similar position on the Business Partnering Maturity Model, i.e., there is little to separate them around how well they are regarded by operational business units or whether they are in a position to influence change.

The key message from this survey is that data masters are the stars of the modern finance function, and it is a sentiment echoed through many of FSN’s surveys over the last few years.

The Innovation in Financial Reporting survey also found that data masters outperformed their less able competitors in three key performance measures that are indicative of financial health and efficiency: 

  • they close their books faster,
  • reforecast quicker and generate more accurate forecasts,
  • and crucially they have the time to add value to the organization.

People, processes and technology

So, if data is the key to driving business partnerships, where do the people, processes and technology come in? Business partnering doesn’t necessarily come naturally to everyone. Where there is no experience of it in previous positions, or if the culture is normally quite insular, sometimes CFOs and senior finance executives need focused guidance. But according to the survey, 77% of organizations expect employees to pick up business partnering on the job. And only just over half offer specialized training courses to support them.

Each company and department or function will be different, but businesses need to support their partnerships, either with formal structures or at the very least with guidance from experienced executives to maximize the outcome. Meanwhile processes can be a hindrance to business partnering in organizations where there is a lack of standardization and automation. The survey found that 71% of respondents agreed or strongly agreed that a lack of automation hinders the process of business partnering.

This was followed closely by a lack of standardization, and a lack of unification, or integration in corporate systems. Surprisingly the constraints of too many or too complex spreadsheets only hindered 61% of CFOs, the lowest of all obstacles but still a substantial stumbling block to effective partnerships. The hindrances reflect the need for better technology to manage the data that will unlock real inter-departmental insight, and 83% of CFOs said that better software to support data analytics is their most pressing need when supporting effective business partnerships.

Meanwhile 81% are looking to future technology to assist in data visualization to make improvements to their business partnering.

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This echoes the findings of FSN’s The Future of Planning, Budgeting and Forecasting survey which identified users of cutting edge visualization tools as the most effective forecasters. Being able to visually demonstrate financial data and ideas in an engaging and accessible way is particularly important in business partnering, when the counterparty doesn’t work in finance and may have only rudimentary knowledge of complex financial concepts.

Data is a clear differentiator. Business partners who can access, analyze and explain organizational data are more likely to

  • generate real insight,
  • engage their business partners
  • and become a positive agent of change and growth.

Click here to access Workiva’s and FSN’s Survey²

Cyber Risk Management – From Security to Resilience

Rapidly evolving threats and infiltration techniques have rendered traditional cyber defense strategies insufficient and ineffective. The emerging threat vectors and speed of change amplified by the digital transformation cannot be addressed by traditional means. Globally, laws are also changing to keep pace as cybercrime evolves, knowing no
boundaries. Therefore, organizations must be nimble and agile to keep pace with policy changes, especially when expanding across different jurisdictions.

This report highlights three strategic imperatives to strengthen cyber resilience:

  • Understand (know your threats): Identify organization and industry-specific cyber threats and regulations calls for robust strategies that include cross-disciplinary considerations.
  • Measure (know yourself): Quantify the potential financial impact of cyber exposures to compare against the level of risk appetite acceptable to the board. This will determine the amount of investment necessary to mitigate and transfer any residual risk.
  • Manage (know what you can do): Proactively manage cyber risks by having clear action plans based on your capabilities and capacities to protect against cyber criminals.

It is inefficient and impractical to expect organizations to be ahead of every threat, but organizations should at least be on par with the evolution of cyber threats while ensuring compliance with changing laws and regulations. While cyber attacks are inevitable, proper preparation is the essential element that sets resilient organizations apart from the rest in managing risk, minimizing damage, and recovering quickly from any incidents.

Cyber Risk: A Top Concern

Technology continues to play a profound role in shaping the global risk landscape for individuals, businesses, and governments. Risk experts around the world continue to rank massive data fraud and theft and cyber attacks as their greatest and most likely risks over the next decade, a pattern that is consistent with previous years. Most risk experts also expect cyber attacks to have a much greater impact through business disruption and the targeted theft of money, data and intellectual property. Our increased dependence on pervasive, integrated digital technologies also increases anxiety around cyber security.

Rapid Innovation

The pace of business innovation has been driven by technology and connectivity megatrends such as mobile, the Internet of Things (IoT), big data and cloud solutions. The adoption and use of mobile devices have surpassed that of desktops since the last quarter of 2016, with mobile traffic accounting for 52 percent of total internet traffic in 2018. While business benefits include greater convenience and productivity, the use of mobile devices for both work and personal reasons has blurred the lines between sensitive corporate and confidential personal data, which are increasingly exposed to weaker application security features, mobile malware and other vulnerabilities.

Pervasive, Sophisticated Technologies

A recent study by FireEye Mandiant revealed that cyber attackers have followed cloud-reliant organizations, such as software-as-a-service and cloud computing, into the cloud. Mandiant researchers observed an increased volume of attacks against organizations with access to vast amounts of personal and confidential data, such as cloud providers, telecommunications, and retail and hospitality. More than 730 investigations were performed by Mandiant experts globally in 2018, a higher volume than any year before and an increase of more than 30 percent over 2017.

Devious, Organized Threat Actors

The modern cyber risk landscape is rapidly evolving and populated by threat actors with a myriad of motivations and attack sophistication levels. The methodologies can vary from highly-targeted and deliberate, to mass-scale with self-distributing malware. Different threat actors also have different motivations and ambitions that can be uniquely destructive.

Motivations and methodologies of threat actors can also overlap with one another. In many cases, similar tools and techniques are used by different groups since those may be the only tools available. In some cases, state-sponsored actors may even work with hacktivists to carry out an attack. Some threat groups demonstrate increased determination by maintaining persistence in victims’ networks. Some APT attackers plan out their modus operandi and patiently pursue their goals over a long period of time—months or years—before they launch their attack. They rapidly adapt to a victim organization’s attempts to remove them from the network and frequently target the same victim again if access is lost.

After an organization has been successfully attacked, there is a higher probability of re-compromise. According to FireEye, globally two in three (64 percent) compromised organizations were successfully attacked again within a year. It is more significant in APAC where almost eight in 10 (78 percent) of compromised organizations are likely to face at least one additional significant attack over the next year.

Organizations that have been attacked should strengthen their cyber security defenses and close any identified gaps to mitigate risks; unfortunately, this doesn’t always happen.

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Data Sharing Economies

Data sharing is inevitable as we accelerate into the digital economy. Our growing interconnectedness is combined with a massive increase in velocity, volume, and variety of data shared across boundaries and jurisdictions. The accelerated digitalization of countries and industries amplifies the systemic effects from cyber attacks and increases the severity of successful cyber attacks.

With the advent of digital and transformative technologies that change the nature of business, policymakers are challenged to maintain the robustness of cyber laws and legislations. The anonymity of the Internet further ensures little or no risk of repercussion for cyber criminals.

According to FireEye CEO Kevin Mandia, ”We are on a slippery slope in terms of frequency and seriousness of cyber attacks” and it is likely to get worse unless serious consequences can be put in place for criminal behavior.

Although cyber regulations have lagged behind evolving cyber threats, the past years have seen a substantial increase in new cyber laws and other regulatory schemes, and this is expected to continue. Most regulatory schemes aim to protect data and privacy and fulfil notification obligations by breached organizations, but disclosures and notifications are critical first steps to reveal the volume, frequency and complexity of breaches before data protection and privacy can be further improved.

Complications That Impact Cyber Resilience

In an increasingly complex business and cyber landscape, organizations encounter greater challenges when trying to balance their business resilience and cyber security priorities.

Between 2016 and 2018, the rate of growth for internet users was 10 times faster than the global population. Correspondingly, the surface area for attack has expanded exponentially. The exposure is estimated to impact up to six billion internet users by 2022, approximately three-quarters of the projected world population. Increased connectivity coupled with the expanded adoption of mobile devices makes building cyber security defenses much more challenging since every employee or web-connected device now represents a potential vulnerability.

Underlying Trends Impose Additional Layers of Fiduciary Responsibilities

Rapid digitalization amplifies the systemic effect of cyber threats, which leads to more cyber regulations and policies. In addition to safeguarding the interests of individuals and businesses, governments and policymakers also aim provide a conducive and well-regulated environment to develop transformative technologies to spearhead their respective digital economies.

Unsurprisingly, their business models are impacted by new cyber laws and regulations. As these laws are introduced, revised and enacted, companies can find themselves in a continually reactive state when attempting to comply with changing policies. Organizations with operations across national boundaries face additional compliance costs as they attempt to navigate diverse regulations in different jurisdictions. While GDPR has led to the convergence of cyber security and data protection laws in the EU, cyber regulations in other parts of the world remain largely localized and diverse.

Re-Thinking a Cyber Resilient Culture

To reduce our growing vulnerability to humanenabled cyber threats, workplace culture needs to change. The outlook, attitudes, values, moral goals and legacy systems shared within an organization have a direct impact on how cyber threats are perceived and managed. While cyber security involves many different technical and information solutions, necessary defenses and resilience cannot be fully achieved without the right mindset.

To establish a cyber resilient culture, everyone in the organization—from executive leadership and management to data analysts and salespeople—have an equal and important role to play in defense.

Through social engineering, threat actors increasingly exploit individuals as the weakest link of the cyber security chain. Therefore, cyber security and resilience must begin with the individual. Although Finance or HR departments may be primary targets for potential access to sensitive information, other executives and employees may also be targeted to gain network access.

How To Line Up Your Defense

Given the reality of the cyber threat landscape, you need to determine the tools you need to mitigate and respond to inevitable cyber attacks. Unfortunately, while both the aggressiveness and sophistication of cyber attacks have accelerated, defensive capabilities have been relatively slow to evolve and respond.

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Darren Thayre, Partner in the Digital, Technology and Analytics Practice for Asia Pacific at Oliver Wyman, mentioned that typical cyber security discussions are often absent when organizations initially strategize on cloud implementation, a process normally driven by developers or infrastructure demands.

Many victim organizations and those working diligently on defensive improvements still lack the fundamental security controls and capabilities to either prevent breaches or to minimize the damages and consequences of an inevitable compromise.

Based on trend observations, Kelly Butler, Head of Cyber Practice, Pacific, Marsh, stated that while security remains important in the 2019 cyber landscape, it is becoming more about resilience.

Organizations must maintain a posture of continuous cyber resilience to prepare for and adapt to the changing threat landscape and recover from the disruptive attacks. Otherwise, they risk facing significant gaps in both basic security controls and—more critically—visibility and detection of targeted attacks. The saying goes, “what gets measured, gets managed,” but you can only measure what you understand.

Understand Cyber Risks from a Business Perspective

Cyber risk is now at the forefront of most corporate risk agendas. Organizations are increasingly looking to understand and assess the nature and extent of their potential cyber-related losses—a necessary first step to mitigate those losses.

A cyber defense strategy delivers substantial benefits for both the senior management and the organization, especially when the strategy and associated action plans are mandated from the top and prioritized with the necessary investments and budgets. A proactive cyber defense strategy demonstrates to regulators that the organization takes cyber risk management seriously and has clear priorities in place.

A cyber security strategy is how you direct and focus the creation of an actionable roadmap and build a comprehensive cyber security program. This process allows you to clearly link gaps identified in the program assessment to your organization’s cyber security investments. However, developing a fit-for-purpose strategy and obtaining buy-in for the cyber security program from senior management can be difficult.

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After you understand cyber risks from a business perspective, you need to identify how much cyber risk is acceptable (to be absorbed) across your entire organization. This baseline helps make decisions related to cyber risk and implement controls.

For example, you can use a structured methodology to determine your organization’s cyber risk appetite. Ideally, you should break down and prioritize your cyber risk appetite, and the metrics you need to inform and measure the risk appetite. Later, you can develop recommendations regarding governance and operating model requirements, which in turn will determine and influence corporate decisions with respect to cyber security investments.

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After you assess the amount of acceptable cyber risk, work to quantify your potential cyber risk exposure. Measure its financial impact to inform the business case for cyber security investments as well as cyber insurance that can mitigate or transfer risk.

Quantification determines nature and extent of risk impacts for different threats and scenarios. However, boards and senior executives often struggle to clearly and comprehensively gain a current understanding of their organization’s cyber risk profile.

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The increase in awareness, cyber data breaches and adoption of cloud-based services are a few of the factors that drive the growth of the cyber insurance market, while high costs inhibit growth. High premiums can be effectively overcome by systematically and clearly understanding organization-specific cyber risks to lower risk exposure and enhance risk profile. For example, the use of data analytics to quantify risk exposure and underwrite cyber risks has proved to drive more efficient and effective risk profiling and provide more accurate policy coverage.

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With an internally aligned cyber risk strategy and adequately measured risk exposure around expected losses due to cyber attacks, organizations can better insure and secure stronger financials to respond and recover from an incident. An incident response plan requires the support of proper security technologies and expertise. At a minimum, a response plan requires full view of IT assets, strong detection capabilities, clear roles and responsibilities and fast reaction times. The plan must also be regularly practiced through drills to ensure that personnel know their roles and to track and record various metrics that measure their performance. Frequent testing can help identify areas for improvement and provide opportunities to continually refine processes and protocols.

Click here to access MMC-FireEye’s Report

EIOPA : Sound Regulation in an Evolving Landscape

Regulation is only effective for as long as it remains relevant. While EIOPA is evolving into a supervisory-focused organisation, it pays close attention to how regulation is applied and how effective it remains, with a view to reinforcing cross-sectoral consistency and improving fairness and transparency and with a focus on better and smart regulation.

INSURANCE

  • SOLVENCY II REVIEW

Since the successful implementation of Solvency II Directive in 2016, EIOPA played an important role in monitoring its consistent implementation and during 2018 was able to provide valuable input into preparations for its review.

EIOPA provided advice to the European Commission on the review of the Solvency Capital Requirement based on an in-depth analysis of 29 different elements of the Standard Formula. The advice focused on increasing proportionality, removing unjustified constraints to financing the economy and removing technical inconsistencies.

EIOPA proposed further simplifications and reduced the burden to insurers by:

  • Further simplifying calculations for a number of sub-modules of the Solvency Capital Requirement (SCR) such as natural, man-made and health catastrophes, in particular fire risk and mass accident;
  • Simplifying the use of external credit ratings in the calculation of the SCR (an issue especially relevant for small insurers);
  • Reducing the burden of the treatment of lookthrough to underlying investments;
  • Developing simplifications in the assessment of lapse and counterparty default risks;
  • Recommending the use of undertaking specific parameters for reinsurance stop-loss treaties.

Furthermore, one of the major technical inconsistencies found related to the calculation of interest rate risk, which did not capture very low or even negative interest rates. EIOPA recommended to adjust the methodology using a method already adopted by internal model users and, given the material impact on capital requirements, suggested to implement it gradually over three years.

EIOPA also carried out an analysis of the loss-absorbing capacity of deferred taxes practices. In face of the evidence of wide diversity, especially concerning the projection of future profits, EIOPA proposed a set of key principles that will ensure greater convergence and level playing field, while maintaining a certain degree of flexibility.

Finally, EIOPA analysed the treatment and the evidence available on unrated debt and unlisted equity and proposed criteria for a more granular treatment, namely with the use of financial ratios.

In some areas, the analysis of recent developments did not provide for sufficient reasons to change. This is, for example, the case of mortality and longevity risks and the cost of capital in the calculation of the risk margin. The evolution of financial markets does not justify a change in the cost of capital: the decrease in interest rates has not lead to a decrease in the cost of raising equity.

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  • REPORTING ON THE IMPLEMENTATION OF SOLVENCY II

In 2018, EIOPA published a number of reports related to different aspects of Solvency II.

  • Report on group supervision and capital management

In response to a European Commission’s request for information, EIOPA submitted its Report on Group Supervision and Capital Management of (Re)Insurance Undertakings and specific topics related to Freedom to Provide Services (FoS) and Freedom of Establishment (FoE) under the Solvency II Directive. The report concluded that overall the Solvency II Group supervision regime was operating satisfactorily. The tools developed by EIOPA to further strengthen group supervision and supervision of cross-border issues contributed to further convergence of practices of NCAs’ supervisory practices.

The report also highlighted a number of gaps in the regulatory framework, including issues related to the application of Solvency II requirements for determining scope of insurance groups subject to Solvency II group supervision, the application of certain of these provisions governing the calculation of group solvency in particular where several methods are used, the definition and supervision of intra-group transactions, or the application of governance requirements at group level.

Further, EIOPA’s report emphasised that effective supervision of insurance groups will benefit from a harmonised approach on a number of areas, for example, early intervention, recovery and resolution and the assessment of group own funds.

  • Second annual report on the use of capital addons under Solvency II

In December 2018, EIOPA published its second annual report on the use of capital add-ons by NCAs according to Article 52 of Solvency II. The objective was to contribute to a higher degree of supervisory convergence in the use of capital add-ons between supervisory authorities and to highlight any concerns regarding the capital add-ons framework. In general, the capital add-on appears to be a good and positive measure to adjust the Solvency Capital Requirement to the risks of the undertaking, when the application of other measures, for example the development of an internal model, is not adequate.

  • Third annual report on the use of limitations and exemptions from reporting under Solvency II

This report, published in December 2018, addresses the proportionality principle on the reporting requirements, from which the limitations and exemptions on reporting – as foreseen in Article 35 of the Solvency II Directive – are just one of the existing proportionality tools. Reporting requirements also reflect a natural embedded proportionality and in addition, risk-based thresholds were included in the reporting Implementing Technical Standard (ITS).

  • Third annual report on the use and impact of long-term guarantee measures and measures on equity risk

This is a regular report published in accordance with Article 77f(1) of the Solvency II Directive. This year’s report also included an analysis on risk management aspects in view of the specific requirements for LTG measures set out in Article 44 and 45 of the Directive as well as an analysis of detailed features and types of guarantees of products with long-term guarantees.

This report shows that – as in previous years – most of the measures, in particular the volatility adjustment and the transitional measures on technical provisions are widely used. The average Solvency Capital Requirement (SCR) ratio of undertakings using the voluntary measures is 231 % and would drop to 172 % if the measures were not applied. This confirms the importance of the measures for the financial position of (re)insurance undertakings.

  • INVESTIGATING ILLIQUID LIABILITIES

The treatment of long-term insurance business remains a hotly debated issue. In particular, it has been discussed whether the risks of long-term insurance business and the associated investments backing those long-term insurance business are adequately reflected. The illiquidity characteristics of liabilities may contribute to the ability of insurers to mitigate short-term volatility by holding assets throughout the duration of the commitments, even in times of market stress.

To explore any new evidence on the features of liabilities, especially concerning their illiquidity characteristics, a dedicated EIOPA Project Group on illiquid liabilities was set up with the following main goals:

  1. To identify criteria of liquidity characteristics for the liabilities and measures for insurers’ ability to invest over the long term;
  2. To explore the link between the characteristics of liabilities and the management of insurers’ assets;
  3. To analyse whether the current treatment in the regulatory regime appropriately addresses the risks associated with the long-term nature of the insurance business.

Following a request for information from the European Commission on asset and liability management, EIOPA launched a request for feedback on illiquid liabilities in autumn and held a roundtable with interested stakeholders in December to discuss the submitted responses on illiquidity measurements and asset liability management practices.

  • ANALYSIS OF THE INTERNATIONAL FINANCIAL REPORTING STANDARDS (IFRS) 17 INSURANCE CONTRACTS

Following the publication of International Financial Reporting Standards (IFRS) 17 Insurance Contracts by the International Accounting Standards Board (IASB), EIOPA assessed its potential effects on financial stability and the European public good, on product design, supply and demand of insurance contracts, and the practical implementation in light of the applicable inputs and processes for Solvency II.

EIOPA concluded that the introduction of IFRS 17 can be described as positive paradigm shift compared to its predecessor IFRS 4 Insurance Contracts, bringing increased transparency, comparability and additional insights on insures’ business models. EIOPA, however, noted a few reservations regarding concepts that may affect comparability and relevance of IFRS 17 financial statements.

PENSIONS

EIOPA promotes greater transparency in the European pensions sector. In support of this aim, EIOPA is working to enhance the information available to consumers and supporting pension providers by making clear the expectations, justifications and decisions linked with the information they provide, in particular to prospective members, members and beneficiaries as laid out in Articles 38 – 44 of the EU Directive on the activities and supervision of institutions for occupational retirement provision (IORP II).

  • REPORT ON THE PENSION BENEFIT STATEMENT: GUIDANCE AND PRINCIPLESBASED PRACTICES IMPLEMENTING IORP II

The report presents the outcomes of NCA exchanges of views and assessments of current practices for the implementation of the IORP II Pensions Benefit Statement (PBS) requirement. Based on this investigation, several principles have been identified that will facilitate clear understanding and comparability of statements.

Two proposals are now in further development: a basic PBS and an advanced PBS (containing more detailed information) to meet the PBS goals. These proposals will, as far as possible, take account of the behavioral approach principle be subject to further consumer testing.

  • DECISION ON THE CROSS-BORDER COLLABORATION OF NCAS WITH RESPECT TO IORP II DIRECTIVE

This Decision, published in November 2018, replaces the former Budapest Protocol which had to be revised as a result of the new IORP II Directive. The Decision introduces new rules to improve the way occupational pension funds are governed, to enhance information transparency to pension savers and to clarify the procedures for carrying out cross-border transfers and activities.

The Decision also describes different situations and possibilities for NCAs to exchange information about cross-border activities in relation to the ‘fit and proper’ assessment and the outsourcing of key functions, both new provisions of the IORP II Directive in addition to the cross-border transfer.

PRESERVING FINANCIAL STABILITY

As part of EIOPA’s mandate to safeguard financial stability, EIOPA works to identify trends, potential risks and vulnerabilities that could have a negative effect on the pension and insurance sectors across Europe.

  • 2018 INSURANCE STRESS TEST

EIOPA published the results of its stress test of the European insurance sector in December 2018. This exercise assessed the participating insurers’ resilience to the three severe but plausible scenarios: a yield curve up shock combined with lapse and provisions deficiency shocks; a yield curve down shock combined with longevity stress; and a series of natural catastrophes.

EIOPA2

In total, 42 European (re)insurance groups participated representing a market coverage of around 75 % based on total consolidate assets. EIOPA published for the first time the post-stress estimation of the capital position (Solvency Capital Requirement ratio) of major EU (re)insurance groups.

Overall, the stress test confirmed the significant sensitivity to market shocks combined with specific shocks relevant for the European insurance sector. On aggregate, the sector is adequately capitalised to absorb the prescribed shocks. Participating groups demonstrated a high resilience to the series of natural catastrophes tested, showing the importance of the risk transfer mechanisms, namely reinsurance, in place.

An additional objective of this exercise, stemming from recommendations from the European Court of Auditors, was to increase transparency in order to reinforce market discipline by requesting the voluntary disclosure of a list of individual stress test indicators by the participating groups. Since EIOPA does not have the power to impose the disclosure of individual results, participating groups were asked for their voluntary consent to the publication of a list of individual stress test indicators. Only four of the 42 participating groups provided such consent.

  • RISK DASHBOARD

EIOPA publishes a risk dashboard on a quarterly basis and a financial stability report twice a year. In the December 2018 report, EIOPA concluded:

  1. the persistent low yield environment remains challenging for insurers and pension funds;
  2. the risk of a sudden reassessment of risk premia has become more pronounced over recent months amid rising political and policy uncertainty;
  3. interconnectedness with banks and domestic sovereigns remains high for European insurers, making them susceptible to potential spillovers;
  4. some European insurers are significantly exposed in their investment portfolios to climate-related risks and real estate.
  • FINANCIAL STABILITY REPORT

EIOPA published two reports on the financial stability of the insurance and occupational pensions sector in 2018.

In general the persistent low yield environment remains challenging for both the insurance and pension fund sector, which continues to put pressure on profitability and solvency. However, towards the end of the year, as noted in the December report, the risk of a sudden reassessment of risk premia became more pronounced. This is largely due to rising political uncertainty and trade tensions, concerns over debt sustainability and the gradual normalisation of monetary policy. In the short run a sudden increase in yields driven by rising risk premia could significantly affect the financial and solvency position of insurers and pension funds as the investment portfolios could suffer large losses only partly offset by lower liabilities. In this regard, the high degree of interconnectedness with banks and domestic sovereigns of insurers could lead to potential spillovers in case a sudden reassessment of risk premia materialise.

While overall the insurance sector remains adequately capitalised, profitability is under increased pressure in the current low yield environment. The Solvency Capital Requirement ratio for the median company is 225 % for life and 206 % for non-life insurance sector, although significant disparities remain across undertakings and countries.

In the European occupational pension fund sector, total assets increased for the euro area and cover ratios slightly improved. However, the current macroeconomic environment and ongoing low interest rates continue to pose significant challenges to the sector, with the weighted return on assets considerably down in 2017.

  • ENHANCED INFORMATION AND STATISTICS

EIOPA continuously works to improve the availability and quality of available information and statistics on insurance and pensions.

  • Solvency II information

For the insurance sector, EIOPA publishes high-quality insurance statistics at both solo and group level. The statistics are based on Solvency II information from regulatory reporting and their regular publication demonstrates EIOPA’s commitment to transparency. Over the past year, through the increased availability of Solvency II data EIOPA has been able to increase the coverage of its statistics. In June 2018, for the first time, the Authority published further insight into the assets of solo (re)insurance undertakings at country level.

  • Decision on EIOPA’s regular information requests towards NCAs regarding provision of occupational pensions information

In April 2018, the Authority published its decision regarding the submission of occupational pension information. The decision defined a single framework for the reporting of occupational pension information that facilitates reporting processes. As a result, EIOPA will receive the information required to carry out appropriate monitoring and assessment of market developments, as well as in-depth economic analyses of the occupational pension market. The requirements were developed in close cooperation with the European Central Bank in order to minimise the burden on the industry and will apply as of 2019.

  • Pensions information taxonomy

In November 2018, EIOPA published the eXtensible Business Reporting Language (XBRL) Taxonomy applicable for reporting of information on IORPs. It provides NCAs with the technical means for the submission to EIOPA of harmonised information of all pension funds in the European Economic Area. Developed in close collaboration with the European Central Bank (ECB), it allows for integrated technical templates and means to report via a single submission both the information required by EIOPA and the ECB.

CRISIS PREVENTION

In addition to regular financial stability tools, EIOPA undertooka number of additional activities in 2018 related to crisis prevention.

  • Development of a macroprudential framework for insurance

With the aim of contributing to the overall debate on systemic risk and macroprudential policy, over the last year, EIOPA has published a series of reports that extend the debate to the insurance sector and, more specifically, the characteristics of that sector. These reports cover the following:

  1. Systemic risk and macroprudential policy in insurance;
  2. Solvency II tools with macroprudential impact; and
  3. Other potential macroprudential tools and measures to enhance the current framework.

As a next step, EIOPA will consult on concrete proposals to include macroprudential elements in the upcoming review of Solvency II.

  • Analysis of the causes and early identification of failures and near misses in insurance

In July 2018, EIOPA published ‘Failures and near misses in insurance: Overview of the causes and early identification’ as the first in a series aimed at enhancing supervisory knowledge of the prevention and management of insurance failures. The report’s findings are based on information contained in EIOPA’s database of failures and near misses, covering the period from 1999 to 2016, including sample data of 180 affected insurance undertakings in 31 European countries.

The report focuses on an examination of the causes of failure in insurance, as well as the assessment of the reported early identification signals. It also examines the underlying concepts ‘failure’ and ‘near miss’ as well as providing further information on EIOPA’s database, established in 2014.

Click here to access EIOPA’s 2018 Annual Report

Can Data and Technology Support the Insurance Industry to Regain Lost Relevance?

Since the start of the Third Industrial Revolution in the 1980s, the world has changed in many different ways:

  • rapid introduction and adoption of technological innovation (global internet; social networks; mobile technologies; evolving payment solutions; data availability);
  • new economic realities (volatile and shorter economic cycles; interconnected financial climate; under utilisation of assets);
  • structural shifts in society’s values (desire for community; generational altruism; active citizenship);
  • and demographic readjustment (increasing population; urbanization; longer life expectancy; millennials in the work force).

While these changes have been happening, the Insurance industry has seemingly preferred to operate in a closed environment oblivious to much of the impact these changes could bring:

  • Resistance to change,
  • Failure to meet changing customer demands
  • Decrease in the importance of attritional risks

has led the Insurance industry to reduce its relevance.

However

  • the availability of data,
  • the introduction of new capital providers,
  • the impact of new business models emerging from the sharing economy
  • and the challenge of InsurTechs

are affecting the industry complacency. Collectively, these factors are creating the perfect storm for the incumbents allowing them to re-evaluate their preference for maintaining the status quo. There is an ever increasing expectation from the industry to be more innovative and deliver a vastly improved customer experience.

As data and emerging technology are accelerating the need for change, they are also opening doors. The industry is at cross roads where it can either choose to regain relevance by adapting to the new world order or it can continue to decline. Should it choose the latter, it could expose the US$ 5 trillion market to approaches from large technology firms and manufacturers who have the access to customers, transformational capabilities and more than enough capital to fill the void left by the traditional players.

Insurance industry is slow to evolve

The Insurance industry has historically lacked an appetite to evolve and has shown reluctance in adopting industry-wide changes. A number of key elements, have created high barriers to entry. New entrants have found it difficult to challenge the status quo and lack appetite to win market share from incumbents with significantly large balance sheets. Such high barriers have kept the impact of disruption to minimal, allowing the industry to stay complacent even when most other industries have undergone significant structural shifts. In many ways ‘Darwin’ has not been at work.

  • A complex value chain

The Insurance industry started with a simple value chain involving four roles – the insured, a broker who advices the insured, an underwriter who prices the risk and an investor who provides the capital to secure the risk. Over centuries, the chain has expanded to include multiple other roles essential in helping the spreading of large risks across a broad investor community, as shown below.

Aon1

These new parties have benefitted the chain by providing expertise, access to customers, secure handling of transactions, arbitration in case of disputes and spreading of risk coverage across multiple partners. However, this has also resulted in added complexities and inefficiencies as each risk now undergoes multiple handovers.

While a longer value chain offers opportunities to new entrants to attack at multiple points, the added complexities and the importance of scale reduces opportunities to cause real disruption.

  • Stringent regulations

Insurance is one of the highest regulated industries in the world. And since the global financial crisis of last decade, when governments across the globe bailed out several financial service providers including insurers, the focus on capital adequacy and customer safety has increased manifold.

While a proactive regulatory regime ensures a healthy operating standard with potential measures in place to avoid another financial meltdown, multiple surveys have highlighted the implications of increased regulatory burden, leading to increased costs and limited product innovation.

  • Scale and volatility of losses

The true value of any insurance product is realised when the customer receives payments for incurred losses. This means that insurers must maintain enough reserves at any time to meet these claims.

Over the years volatility in high severity losses have made it difficult for insurers to accurately predict the required capital levels.

In addition, regulators now require insurers to be adequately capitalised with enough buffer to sustain extreme losses for even the lowest probability of occurrence (for example 1-in-100 years event or 1-in-200 years event). This puts additional pressure on the insurers to maintain bulky balance sheets.

On the other hand, a large capital base gives established insurers advantage of scale and limits growth opportunities for smaller industry players/new entrants.

  • Need for proprietary and historical data

Accurate pricing of the risk is key to survival in the industry. The insurers (specifically underwriters supported by actuaries) rely excessively on experience and statistical analysis to determine the premiums that they would be willing to take to cover the risk.

Access to correct and historical data is of chief importance and has been a key differentiating factor amongst insurers. Since the dawn of Third Industrial Revolution in the 1980s, insurers have been involved in a race to acquire, store and develop proprietary databases that allow them to price risks better than the competitors.

The collection of these extensive databases by incumbent insurers have given them immense benefits over new entrants that do not typically have similar datasets. Additionally, the incumbents have continued to add on to these databases through an unchallenged continuation of underwriting– which has further widened the gap for new entrants.

Struggling to meet customer needs

Despite years of existence, the Insurance industry has failed to keep up with the demand for risk coverage. For example the economic value of losses from all natural disasters has consistently been more than the insured value of losses by an average multiple of 3x-4x.

The gap is not limited to natural disasters. As highlighted by Aon’s Global Risk Management Survey 2019, multiple top risks sighted by customers are either uninsurable or partially insurable leading to significant supply gap.

Aon2

Six of the top 10 risks, including Damage to reputation/brand and Cyber, require better data and analytical insights to achieve fully effective risk transfer. However, current capabilities are primarily applied to drive better pricing and claims certainty across existing risk pools, and have not yet reached their full potential for emerging risks.

This inability to meet customer need has been driven by both an expensive model (for most risks only 60% of premiums paid are actually returned to the insured) and a lack of innovation. Historically, the need for long data trends meant insurance products always trailed emerging risks.

Status Quo is being challenged

While the industry has been losing relevance, it is now facing new challenges which are creating pressure for change. While these challenges are impacting the incumbents they also provide the potential for insurance to regain its key role in supporting innovation. Creating opportunity for lower costs and new innovations.

The insurance customer landscape has changed considerably: traditional property and casualty losses are no longer the only main risks that corporations are focused on mitigating. The importance of intellectual property and brand/reputation in value creation is leading to a realignment in the customer risk profile.

Value in the corporate world is no longer driven by physical/ tangible assets. As technology has advanced, it has led to the growth of intangibles assets in the form of intellectual property. The graph below shows that 84% of market capitalization in 2018 was driven by intangible assets. While the five largest corporations in 1975 were manufacturing companies (IBM; Exxon Mobil; P&G; GE; 3M), that has completely changed in 2018 as the first five positions were occupied by Tech companies (Apple; Alphabet; Microsoft; Amazon; Facebook). Yet, organizations are only able to secure coverage to insure a relatively small portion of their intangible assets (15%) compared to insurance coverage for legacy tangible assets (59%).

Aon3

This shift represents both a challenge and an opportunity for the Insurance industry. The ability to provide coverage for intangible assets would enable insurance to regain relevance and support innovation and investment. Until it can, its importance is likely to remain muted.

InsurTech

The Insurance industry has had traditionally manual processes, and has been a paper driven industry with huge inefficiencies. While customers´ needs are evolving at an unprecedented quick pace, the incumbents´ large legacy systems and naturally conservative approach, make them slow to reach the market with new products and an improved customer experience.

InsurTechs are companies that use technology to make the traditional insurance value chain more efficient. They are beginning to reshape the Insurance industry by targeting particular value pools or services in the sector, rather than seek to provide end-to-end solutions.

InsurTechs have seen more than US$ 11 billion of funding since 2015, and the volume in 2018 is expected to reach US$ 3,8 billion (FT PARTNERS). While Insurtechs were originally viewed as a disruptive force competing with traditional insurers to gain market share, there is a growing collaboration and partnership with the incumbent players. Most of them are launched to help solve legacy insurer problems across the organization, from general inefficiency in operations to enhancing underwriting, distribution, and claims functions, especially in consumer facing insurance. More recently they are also moving into the commercial segment focusing on loss prevention and efficiency. (CATLIN, T. et al. 2017). Incumbent insurers have managed to leverage InsurTechs to speed up innovation (DELOITTE, 2018: 11). From a funding perspective most of the US$ 2.6 billion that went into the InsurTechs in the first nine months of 2018 came from incumbent Insurers. (MOODY`S, 2018: 6).

The accelerated use of technology and digital capabilities again represents both a challenge for the industry but also an opportunity to innovate and develop more efficient products and services.

Data and technology with potential to transform

Traditionally, the Insurance industry has used proprietary historic data to match the demand from risk owners with the supply from capital providers. Focusing on relative simplistic regression analysis as the main approach.

While robust, this approach is reliant on a long data history and limits insurers ability to move into new areas. Increasingly the transformative power of data and technology is changing this relationship, as shown in the graph below. While underwriting data used to be in the hands of the incumbents only, emerging technologies, new analytical techniques and huge increases in sensors are enabling usage of new forms of data that are much more freely accessible. In addition, these technologies are supporting instant delivery of in-depth analytics that can potentially lead to significant efficiency gains and new types of products.

Aon4

  • Artificial Intelligence

Artificial Intelligence – Robotic Process Automation (RPA) and Cognitive Intelligence (CI) – is know as any system that can perceive the world around it, analyse and understand the information it receives, take actions based on that understanding and improve its own performance by learning from what happended.

Artificial Intelligence not only gives the opportunity to reduce costs (process automation; reduction of cycle times; free up of thousands of people hours) but improves accuracy that results in better data quality. For insurers this offers significant potential to both enable new ways of interpreting data and understanding risks. As well as reducing the costs of many critical processes such as claims assessment.

This dual impact of better understanding and lower costs is highly valuable. Insurers’ spend on cognitive/artificial intelligence technologies is expected to rise 48% globally on an annual basis over five years, reaching US$ 1.4 billion by 2021. (DELOITTE, 2017: 15).

  • Internet of Things

The Internet of Things refers to the digitization of objects around us. It works by embedding advanced hardware (e.g. sensors, cameras and meters) into everyday objects and even people themselves, linking those objects further to online networks. (MOODY`S, 2018: 11).

For example, connected devices in the homes such as water leakage detectors, smoke alarms, C02 readers and sophisticated home security systems will support prevention and reduction in losses from water damage, fire and burglary, respectively.

The Internet of Things has the potential to significantly change the way that risks are underwritten. The ability to have access to data in ‘real time’ will provide greater precision in the pricing of risk and also help insurers to respond better to the evolving customer needs. Consider the example of home insurance; customers will be forced to resconsider the decision to buy home insurance as packaged currently when their house is already monitored 24/7 for break-ins and the sensors are constantly monitoring the appliances to prevent fires. The insurers could utilise the same data to develop customised insurance policies depending on usage and scope of sensors.

The Internet of Things applies equally to wearable devices with embedded sensors for tracking vital statistics to improve the health, safety and productivity of individuals at work. It is predicted that the connected health market will be worth US$ 61 billion by 2026.

The Internet of Things offers the Insurance industry an opportunity to reinvent itself and to move from simply insuring against risk to helping customers protect the properties / health. This integration of insurance with products through live sensor data can revolutionise how insurance is embedded into our every day lives.

  • Blockchain

All disruptive technologies have a “tipping point” – the exact moment when it moves from early adopters to widespread acceptance. Just as it was for Google in the late 1990s and smartphones in the 2000s, could we be approaching the tipping point for the next big disruptive technology – blockchain?

Essentially, blockchain is a shared digital ledger technology that allows a continuously growing number of transactions to be recorded and verified electronically over a network of computers. It holds an immutable record of data, stored locally by each party to remove the barrier of trust. Through smart contacts, blockchain can enable automation of tasks for more efficient processing. It made its debut in 2009 as the system used to track dealing in the first cryptocurrency, Bitcoin, and, since then, organisations around the world have spotted blockchain’s potential to transform operations.

Most industries are currently experimenting with blockchain to identify and prove successful use cases to embrace the technology in business as usual. IDC, a leading market intelligence firm, expects the spend on blockchain to increase from US$ 1.8 billion in 2018 to US$ 11.7 billion in 2022 at a growth rate of 60%.

With all the aforementioned benefits, blockchain also has potential to impact the Insurance industry. It can help Insurers reduce operational and administrative costs through automated verification of policyholders, auditable registration of claims and data from third parties, underwriting of small contracts and automation of claims procedures. Equally, it can help reduce the fraud which would contribute to reduce total cost.

In an industry where ‘trust’ is critical, the ability to have guaranteed contracts, with claims certainty will help the take-up of insurance in new areas. BCG estimates that blockchain could drastically improve the end-to-end processing of a motor insurance policy and any claims arising thereof as shown in the graph below.

Aon5

Conclusion

The relevance of insurance, which has declined over the last few decades, after peaking in the early 1980s, is set to increase again:

  • Big shifts in insurance needs, both in the commercial and consumer segments,
  • New sources of cheap capital,
  • Prevelance of cheap and accessible data and the technology to automate and analyse

will transform the Insurance industry.

Not only is this important for insurers, it is also important for all of us. Insurance is the grease behind investment and innovation. The long term decline in the Insurance´s industry ability to reduce risk could be a significant impediment on future growth.

However we believe that the reversal of this trend will mean that insurance can once again grow in its importance of protecting our key investments and activities.

Click here to access Aon’s White Paper

 

Marketing’s Role in Employee & Customer Experience Journeys

Is your Marketing department aligned with customer experience and employee experience? The necessity and logic of doing this was highlighted in a recent presentation by Hootsuite’s Vice President of Customer, Kirsty Traill. She pointed out that Marketing Communications is unfortunately the typical focus of customer journey maps and customer-centric marketing.

Her observations are in accordance with the first half of this six-part series which also pointed out that MarCom-focus for customer-centric marketing is extremely short-sighted in what’s needed by your company. It short-changes marketing’s impact.

Hootsuite takes a holistic view of “brand experience” by applying customer-centric research and thinking to each phase of the end-to-end customer experience and employee experience journey maps — for use by all groups within Marketing and beyond. Brand integrity relies upon both employees’ and customers’ perceptions. It also relies on the company’s fulfillment of their needs. Marketing plays a significant role in understanding, communicating and assuring these needs.

“We recognize the importance of employee engagement in driving the customer experience,” said Kirsty. “Marketing touches every part of the employee journey and is a key part of driving a truly customer-centric culture, starting with recruiting and whether the public’s image of our employer brand is likely to attract high-caliber talent.”

The journey team at Hootsuite includes Marketing, Sales and Customer Success representatives. This allows them to look through different lenses. Their work has developed an overarching messaging hierarchy informed by customer journey mapping, and grounded in customer needs. “It’s an overall guide of how customers talk about the category,” explained Kirsty. “It describes how customers and employees think about each phase of their journeys, and how they talk about their needs. It provides vocabulary for consistent messaging to each of four core customer personas and to employees.”

Marketing decisions are guided by a table of customer insights available for each journey stage, showing which voice-of-customer insights inform each stage and who owns it. Julie Garrah, Customer Experience Manager on Kirsty’s team at Hootsuite, explained: “We emphasize closing-the-loop in communicating what action we’re taking. This drives improvement in scores. We send customers a closing-the-loop email on a six-month cadence, sharing what we’re doing.”

The image below describes the interpretation. Green phrasing is the suggestion to foster outside-in thinking.

Research for Marketing Across the Customer Experience Journey

Hootsuite has defined four core personas and developed a customer journey map for each persona. (identify natural customer segments by looking for patterns across qualitative data) Hootsuite builds a deep understanding of each segment’s journey stages by answering these questions:

  • Need Something: How does a customer become aware of the need for what your category represents, how would they describe the need in their own words, what is it that triggers the activation of that customer need?
  • What are My Choices: Which other companies are in your customers’ consideration set, where are they finding information to make a decision in the category, what is their evaluation criteria?
  • Decide & Buy: What information are they looking for to make their decision, what is it that locks them in to your product versus your competition’s, do they talk to anyone, what does your purchase process look like, how long does it take, how easy was it for customers relative to their expectations?
  • Receive Order: What do they need to get started, where do they find information during this stage?
  • Install / Use: How do customers use your product/service, how do they define the value, how do you deliver upon that value, how do you reinforce that they’ve made the right decision?
  • Questions / Moments of Truth (1) : Which touch-points triggered repeat purchase, upgrade or expansion; where did you fail to deliver on their expectations; what caused customers to cancel, suspend, return, leave, what were the triggers; what information do they need and in what format?
  • Integrations (2): Which touch-points turn fans into loyal fans and advocates, what is the customers’ context for usage of your product, what are their interactions with your people, what is their connection with your brand?
  1. Questions / Moments of Truth: Researching the “moments of truth” stage can be a difficult process to go through, but Kirsty explained: “This information is rich and can be used in very productive ways for improving customer experience as well as your marketing mix and marketing touch-points.”
  2. Integrations: Integrations might be the most significant part of the journey as it answers “what is the customer trying to get done . . . with or by whom, under what circumstances, in combination with what processes or hardware/software?” This context can be a game-changer for up-leveling your marketing, product development, and operations.

CXEX

Research & Actions for Marketing Across the Employee Experience Journey

Hootsuite applies customer experience insights to all stages of the employee experience journey:

  • Need a Job Opportunity / What are My Choices: Does your Careers web page paint the image of a customer-centric company, how employees are portraying you on LinkedIn and GlassDoor, is your employer brand aligned with your corporate brand and customer-focus?
  • Decide & Sign / Start Job: Educate every new employee on buyer personas and user personas in every team and department, show videos from customers explaining what they use and like, provide pocket guide with customer needs and value proposition, explain company standards to new hires so they understand how important customer-focus is and how their specific role affects customer experience.
  • Daily Work: Empower everyone in the company to address customer issues since it’s impossible for your Customer Success team to manage every touch-point customers have with your company, role-based training, create a central repository of customer information and unified customer profile across the journey, design your tech stack to integrate the fewest systems necessary to house customer data for a comprehensive story of individual customers.
  • Higher Purpose: Make “customer love” visible through stories shared with employees, display your Customer Support vision, encourage employees to participate in shadowing, ride-alongs, and capturing customer quotes.
  • Championing: Encourage brand spirit through corporate apparel and swag, empower employees to “share love” through social media, arrange for people from development to shadow Customer Support and Sales Enablement to sit in on sales calls, invite Product Marketing and Vertical Marketing teams to attend customer events to see how customers are interacting and engaging with content.

Hootsuite studies a flow of qualitative data from marketing touch-points about what customers want and need. By gaining a deeper understanding of how customers are thinking and feeling about information at each stage in their journey, the company has also gained appreciation for how the touch-points interact with one another.

These insights re-orient employees’ outlooks. They break down traditional silo mentality. The goal is to become a more customer-centric organization by driving behavior in doing what’s best for the customer as the way to drive business growth.

Click here to access CustomerThink-10-Big-Ideas-Customer-Experience-Success Paper

Data Search and Discovery in Insurance – An Overview of AI Capabilities

Historically, the insurance industry has collected vast amounts of data relevant to their customers, claims, and so on. This can be unstructured data in the form of PDFs, text documents, images, and videos, or structured data that has been organized for big data analytics.

As with other industries, the existence of such a trove of data in the insurance industry led many of the larger firms to adopt big data analytics and techniques to find patterns in the data that might reveal insights that drive business value.

Any such big data applications may require several steps of data management, including collection, cleansing, consolidation, and storage. Insurance firms that have worked with some form of big data analytics in the past might have access to structured data which can be ingested by AI algorithms with little additional effort on the part of data scientists.

The insurance industry might be ripe for AI applications due to the availability of vast amounts of historical data records and the existence of large global companies with the resources to implement complex AI projects. The data being collected by these companies comes from several channels and in different formats, and AI search and discovery projects in the space require several initial steps to organize and manage data.

Radim Rehurek, who earned his PhD in Computer Science from the Masaryk University Brno and founded RARE Technologies, points out:

« A majority of the data that insurance firms collect is likely unstructured to some degree. This poses several challenges to insurance companies in terms of collecting and structuring data, which is key to the successful implementation of AI systems. »

Giacomo Domeniconi, a post-doctoral researcher at IBM Watson TJ Research Center and Adjunct Professor for the course “High-Performance Machine Learning” at New York University, mentions structuring the data as the largest challenge for businesses:

“Businesses need to structure their information and create labeled datasets, which can be used to train the AI system. Yet creating this labeled dataset might be very challenging apply AI and in most cases would involve manually labeling a part of the data using the expertise of a specialist in the domain.”

Businesses face many challenges in terms of collecting and structuring their data, which is key to the successful implementation of AI systems. An AI application is only as good as the data it consumes.

Natural language processing (NLP) and machine learning models often need to be trained on large volumes of data. Data scientists tweak these models to improve their accuracy.

This is a process that might last several months from start to finish, even in cases where the model is being taught relatively rudimentary tasks, such as identifying semantic trends in an insurance company’s internal documentation.

Most AI systems necessarily require the data to be input into an AI system in a structured format. Businesses would need to collect, clean, and organize their data to meet these requirements.

Although creating NLP and machine learning models to solve real-world business problems is by itself a challenging task, this process cannot be started without a plan for organizing and structuring enough data for these models to operate at reasonable accuracy levels.

Large insurance firms might need to think about how their data at different physical locations across the world might be affected by local data regulations or differences in data storage legacy systems at each location. Even with all the data being made accessible, businesses would find that data might still need to be scrubbed to remove any incorrect, incomplete, improperly formatted, duplicate, or outlying data. Businesses would also find that in some cases regulations might mandate the signing of data sharing agreements between the involved parties or data might need to be moved to locations where it can be analyzed. Since the data is highly voluminous, moving the data accurately can prove to be a challenge by itself.

InsIA

Click here to access Iron Mountain – Emerj’s White Paper

 

Financial Risk Management – Global Practice Analysis Report

Survey participants indicated they are involved in the daily practice of financial risk management as financial risk managers, in supervisory roles, as consultants, academics and trainers, auditors and regulators. They self-identified as highly educated — 71 percent hold a Master’s degree or higher. While 61 percent of respondents had more than five year’s experience in the financial services industry, less than half — 41 percent — had more than five year’s experience in financial risk management. This indicates that experienced financial services professionals enter the field of risk management from other areas of responsibility at financial institutions.

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More than 40 percent of respondents worked at banks, with consulting and asset management firms employing 17 and 16 percent, respectively. Approximately one-third of respondents hold the title of risk manager, one-quarter are analysts and 11 percent are consultants. Approximately 61 percent are employed at firms with more than 1,000 employees.

The GARP Global Practice Analysis survey addressed 49 specific tasks across six process-based domains. Respondents were asked to assign an importance rating from 1 (not important) to 4 (extremely important) to each task. Significantly, all 49 tasks were found to be important on the 4-point Importance Scale, meeting the industry best-practices threshold of 2.5 out of 4. Forty-seven of the 49 tasks received a mean importance rating of at least 3.0, indicating that these tasks are considered of moderate to high importance to the work of financial risk managers.

The top five tasks identified by respondents as most important, earning a mean importance rating of at least 3.3 among all survey respondents, are to:

  1. Identify signs of potential risk based on exposure, trends, monitoring systems regulatory and environmental change, organizational culture and behavior.
  2. Analyze and assess underlying risk drivers and risk interconnections.
  3. Communicate with relevant business stakeholders.
  4. Monitor risk exposure in comparison to limits and tolerances.
  5. Evaluate materiality of risk and impact on business.

The five tasks identified as least important, with a mean importance rating of or below 3.0 among all respondents, are:

  1. Create and inventory of models.
  2. Generate, validate, and communicate standardized risk reports for external purposes.
  3. Develop transparent model documentation for independent replication/validation.
  4. Set capital allocations and risk budgets in accordance with risk management framework.
  5. Recommend policy revisions as necessary.

Respondents were asked to identify at what level of experience each task should be part of the financial risk manager’s profile, according to a five-level Experience Scale:

  • Not necessary
  • Less than 2 years
  • 2 to 5 years
  • 6 to 10 years
  • More than 10 years

One-half of respondents indicated that financial risk managers should be able to perform all 49 tasks within the first five years of practice.

More than 77 percent of respondents said financial risk managers should be able to perform these specific tasks within their first five years of practice in financial risk management:

  • Monitor risk exposure in comparison to limits and tolerances
  • Define and determine type of risk (e.g., credit, market, operational) by classifying risk factors using a consistent risk taxonomy
  • Gather quantitative data to perform model evaluation
  • Select monitoring methods and set frequency (e.g., intra-daily, daily, weekly, monthly)
  • Gather qualitative information to perform model evaluation
  • Generate, validate, and communicate standardized risk reports for internal purposes (e.g., staff, executive management, board of directors)
  • Identify risk owners
  • Investigate why limits are exceeded by performing root-cause analysis
  • Analyze and assess underlying risk drivers and risk interconnections
  • Escalate breach when limits or alert levels are exceeded according to risk management plan/policies/strategies
  • Generate, validate, and communicate ad hoc reports to meet specific requirements
  • Escalate unusual behavior or potential risks according to risk management plan/ policies/strategies

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Financial risk managers are vital to any integrated financial system of managing and communicating risk. The GPA study is a contemporary and comprehensive description of the work of risk managers across work settings, geographic regions, job roles and experience levels.

The process of a practice analysis is important for programs that desire to continually evolve and reflect the critical knowledge and tasks in the industry. It is important for practitioners who desire to evolve and be successful in their career.

Click here to access GARP’s detailed survey report