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.

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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.

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  • 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.

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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

 

EIOPA reviews the use of Big Data Analytics in motor and health insurance

Data processing has historically been at the very core of the business of insurance undertakings, which is rooted strongly in data-led statistical analysis. Data has always been collected and processed to

  • inform underwriting decisions,
  • price policies,
  • settle claims
  • and prevent fraud.

There has long been a pursuit of more granular data-sets and predictive models, such that the relevance of Big Data Analytics (BDA) for the sector is no surprise.

In view of this, and as a follow-up of the Joint Committee of the European Supervisory Authorities (ESAs) cross-sectorial report on the use of Big Data by financial institutions,1 the European Insurance and Occupational Pensions Authority (EIOPA) decided to launch a thematic review on the use of BDA specifically by insurance firms. The aim is to gather further empirical evidence on the benefits and risks arising from BDA. To keep the exercise proportionate, the focus was limited to motor and health insurance lines of business. The thematic review was officially launched during the summer of 2018.

A total of 222 insurance undertakings and intermediaries from 28 jurisdictions have participated in the thematic review. The input collected from insurance undertakings represents approximately 60% of the total gross written premiums (GWP) of the motor and health insurance lines of business in the respective national markets, and it includes input from both incumbents and start-ups. In addition, EIOPA has collected input from its Members and Observers, i.e. national competent authorities (NCAs) from the European Economic Area, and from two consumers associations.

The thematic review has revealed a strong trend towards increasingly data-driven business models throughout the insurance value chain in motor and health insurance:

  • Traditional data sources such as demographic data or exposure data are increasingly combined (not replaced) with new sources like online media data or telematics data, providing greater granularity and frequency of information about consumer’s characteristics, behaviour and lifestyles. This enables the development of increasingly tailored products and services and more accurate risk assessments.

EIOPA BDA 1

  • The use of data outsourced from third-party data vendors and their corresponding algorithms used to calculate credit scores, driving scores, claims scores, etc. is relatively extended and this information can be used in technical models.

EIOPA BDA 2

  • BDA enables the development of new rating factors, leading to smaller risk pools and a larger number of them. Most rating factors have a causal link while others are perceived as being a proxy for other risk factors or wealth / price elasticity of demand.
  • BDA tools such as such as artificial intelligence (AI) or machine learning (ML) are already actively used by 31% of firms, and another 24% are at a proof of concept stage. Models based on these tools are often cor-relational and not causative, and they are primarily used on pricing and underwriting and claims management.

EIOPA BDA 3

  • Cloud computing services, which reportedly represent a key enabler of agility and data analytics, are already used by 33% of insurance firms, with a further 32% saying they will be moving to the cloud over the next 3 years. Data security and consumer protection are key concerns of this outsourcing activity.
  • Up take of usage-based insurance products will gradually continue in the following years, influenced by developments such as increasingly connected cars, health wearable devices or the introduction of 5G mobile technology. Roboadvisors and specially chatbots are also gaining momentum within consumer product and service journeys.

EIOPA BDA 4

EIOPA BDA 5

  • There is no evidence as yet that an increasing granularity of risk assessments is causing exclusion issues for high-risk consumers, although firms expect the impact of BDA to increase in the years to come.

In view of the evidence gathered from the different stake-holders, EIOPA considers that there are many opportunities arising from BDA, both for the insurance industry as well as for consumers. However, and although insurance firms generally already have in place or are developing sound data governance arrangements, there are also risks arising from BDA that need to be further addressed in practice. Some of these risks are not new, but their significance is amplified in the context of BDA. This is particularly the case regarding ethical issues with the fairness of the use of BDA, as well as regarding the

  • accuracy,
  • transparency,
  • auditability,
  • and explainability

of certain BDA tools such as AI and ML.

Going forward, in 2019 EIOPA’s InsurTech Task Force will conduct further work in these two key areas in collaboration with the industry, academia, consumer associations and other relevant stakeholders. The work being developed by the Joint Committee of the ESAs on AI as well as in other international fora will also be taken into account. EIOPA will also explore third-party data vendor issues, including transparency in the use of rating factors in the context of the EU-US insurance dialogue. Furthermore, EIOPA will develop guidelines on the use of cloud computing by insurance firms and will start a new workstream assessing new business models and ecosystems arising from InsurTech. EIOPA will also continue its on-going work in the area of cyber insurance and cyber security risks.

Click here to access EIOPA’s detailed Big Data Report

Overcome Digital Transformation Distress

Digital has become one of the most over-loaded words in the English language, meaning very different things in different contexts. Insurers have been digital since the first policy was recorded on magnetic drum or tape in the 1960s. Oddly enough, insurers now lag considerably behind other industries in their digital maturity and stage of adoption.

Why insurers lag in digital strategy

So many factors go into understanding why insurers trail in developing and implementing a modern digital strategy. At this point, most insurers have developed a digital footprint and deliver varying levels of engagement with their customers and partners, including some direct access to policy information and service. The transactional nature of some Personal and Commercial (P&C) lines make this process more straightforward. However, for Life, Accident and Health (LA&H) carriers, especially those providing Group Employee Benefits, it’s a more complex problem with additional parties involved and customization of product and service at the plan level, requiring more detailed policy information and flexibility requirements in service options. Combined with the legacy technology platforms most carriers still employ, this makes direct self-service options more difficult to implement requiring more manual intervention which ultimately erodes customer satisfaction. Ironically, the prevalent underlying key stumbling block to implementing a next generation digital strategy is insurers’ digital legacy.

Digital Transformation Distress

According to McKinsey, Insurtechs are focusing more on P&C than LA&H but there is significant activity in distribution and new business-related activities, which falls squarely in the digital arena. In a recent multi-country study by Couchbase across multiple industries including insurance,

  • 64% of respondents say if they can’t keep up with digital innovation they will go out of business or be absorbed;
  • 95% say digital transformation seems an insurmountable task and
  • 83% felt they would face being fired if such a project failed.

Despite the challenges, LA&H insurers are putting more comprehensive digital strategies into place and technology vendors servicing this market must think beyond providing basic digital engagement capabilities to supporting a more complete vision of digitally-enabled business.

Digital Enagement and Flexibility

Leading SaaS core insurance system providers believe insurance business leaders need a platform that can provide a level of digital engagement and service equal to their customers’ expectations for all service providers. To enable this, there must be an underlying OpenCore system that can ensure accurate, open and flexible product development, deployment and service to serve a rapidly changing market.

  • Digital Engagement is a critical element of a complete strategy and the most visible. In the Group and Employee Benefits market, there are multiple stakeholders in the value chain with differing roles and digital engagement should be role-based, whether it is transactional or purely informational.
  • Flexibility is required within the business model. The chain of carrier(s), brokers, benefit administration companies (ben admin), enrollment vendors, employers, and employees must provide rapid and accurate straight through processing and be flexible enough to change out any given player in the chain, based on the deal.

Legacy systems are proving inadequate

The traditional approach to support these two key needs of the value chain is

  • either to provide an end-to-end portal solution driven from the core system architecture
  • or a standardized data feed interface between the core system and the next link in the value chain.

The problem with these two approaches is that they are inadequate. Why?

The first approach of end-to-end portal solution is not feasible given current and future insurance market directions around multi-carrier plans and value-added services from benefit admin providers. The standardized data feed interface can work but invariably leads to a great deal of custom IT interface work, even when employing industry standards like the emerging LIMRA-backed Workplace Benefits standard. This proves especially difficult when there are broad systems of engagement in play from companies like Salesforce.com that are used in call centers and broad community portals.

An Engagement Model that Works

Leading insurance technology vendors are proving that OpenCore is the best approach applying a role-based scenario to defining digital engagement requirements for the core system. This tactic provides a layered architecture to suit those roles and the engagement path needed for the particular customer. The way that might evolve could include a large carrier that uses a system of engagement for their customer service reps (CSR) and works with a broker, enrollment vendor and larger employer in the following scenarios:

  • The insurance specialist who installs and manages the details of a case works directly with the core system interface, designed for experts.
  • The CSR who works for the carrier and answers basic questions about the case for the employer or employee and who interacts with the system of engagement, which is tied to the core system in real-time via an app written by the core system vendor specifically for that platform.
  • The broker who does case and member inquiries and updates through a broker portal provided by the carrier with role-based access into the core system.
  • The enrollment vendor uses industry standard real time APIs and batch file transfers to exchange data directly with the carrier’s core system. The larger employer exchanges transactions through API or data feed to the HCM system and has direct access to the carrier’s core system through a role-based portal designed for the exchange process.
  • The employee has access to the employers Human Capital Management (HCM) employee portal and the option to go directly to the carrier for deeper interactions such as claims or absences, or portability issues. The interaction with the carrier is via portal, mobile, voice or SMS depending on the employee’s preference or circumstance.

Insurance technology companies that provide a layered digital engagement architecture, with core systems capabilities supporting role-based APIs sets that support both digital engagement applications and are available for customers and partner DIY projects, enables the insurer to achieve the most flexible, stable and modern digital experience.

OpenCore

Click here to access Fineos’ White Paper

The Customer Journey of a Lifetime: Step-by-Step Modernisation to Maximise Retention

Customer experience is the insurer’s latest hot topic. Improving it at existing touchpoints and finding new opportunities to deliver it beyond purchase, renewal and claims dominate discussions. McKinsey found in the B2B sector that improved customer experience lowered churn by 15%, increased win rate from 20% to 40% and lowered costs to serve by up to 50%.

But understanding how to deliver great insurance customer experience, whether on mobile, in a contact centre or at a repair shop means far more than finessing an individual point of interaction. How the customer experiences each interaction and how it colours past and future interactions is critical to building a successful customer experience.

In other words, if you don’t give your customer the best journey, they’ll never arrive at the desired destination.

In this paper we look at the latest research supporting customer journey analysis and speak to three insurance executives who are putting this strategy at the heart of their customer experience and engagement policy. Progress towards the optimal customer journey is examined in the following stages:

  1. Proof points for customer journey analysis
  2. Embedding effective customer tracking
  3. Solid data collection practice
  4. Assessing and enhancing the availability of information
  5. Upskilling the organisation to manage the journey
  6. Discovering and mitigating pain points in the customer journey
  7. An atmosphere of continuous improvement

Proof points for customer journey analysis

Customer journey analysis and optimisation is so important because of the multiple channels and external influences involved in the buying process. So much can happen between intent and purchase. No-one is exempt. Google and Ipsos found that 90% of people move between devices in a sequential fashion to accomplish a goal. In online shopping, 61% of internet users and 80% of online millennials start shopping on one device but finish on another.” This is a pretty simplistic view. If we turn to research by user experience research house, GfK, the customer journey looks even more convoluted:

CX Survey

From this infographic, we note that most insurance customers use branded search but also go across around eight touchpoints including social media and email. Only 14% don’t do any research and for those who do, most will research online covering around five different websites. Further research on the insurer journey from GfK found that hardly any purchasers bothered with word of mouth (5%) but price comparison sites (PCS) wield a strong influence (26%).

This diagram only relates to the insurance purchase journey. There are many more influences on customer retention such as claims journey, customer engagement campaigns (increasingly popular under the influence of internet of things (IoT) technology).

Embedding effective customer tracking

The business case for journey analysis established, insurers need to make sure they are tracking all the essential touchpoints.

ERGO Group AG’s Head of Customer and Sales Service Health, Dr. Carsten Rahlf explains his process: “If a phone number is saved in the database we can see the customer’s profile upon calling, their historic interaction points, so we know where he is in the process. If he went to the doctor, paid him and wants to be reimbursed, also we can see when and how he submitted his bills. He may have sent them by post or used the app. He and we can see through the online portal that his request has been accepted and the customer and the agent can then track it to see if it has been executed.”

Wesleyan’s Group Head of Marketing Robin Gibson is in the middle of bringing CRM data into a Microsoft Dynamics system to improve their single view of the customer – vital to make any sense of customer tracking data. Executives looking to follow his lead should be aware it is a long-term project: “We spent the last three years on integration, migrating all the data into new CRM systems. The first part is to allow financial consultants and the customer to jointly have a single view of finances. »

« The next part is to allow customers to self-serve on their devices. Next, we need to put marketing plugins into the system to simulate interactions and use the database to find new customers.” He adds that a manageable, clean source of customer information is vital to comply with May 2018’s GDPR legislation which requires explicit data consent ongoing. It’s clear that tracking the customer journey means not just focusing on points of customer interaction such as cookies on a website or calls to a call centre but also looking internally to see what processes are helping or hindering that customer journey.

This will never be an exact science. Explaining where tracking begins and ends in MyCustomer, SEO expert Martin Calvert admits a degree of arbitrariness is expected “The start and end points of a customer journey are always going to be debatable. Does the journey ultimately start when they see one of your brand’s adverts years ago…does it end after they’ve bought their last product from you in their 80s?”

The learning is to track what you can and hunt out two specific areas:

  • one, where gaps in the customer journey appear
  • and two, where customers appear to experience pain points that are unaccountable – so far.

To get reliable pictures of this, insurers need to access as much data as possible.

Customer Journey

Click here to access InsuranceNexus’ White Paper

By investing heavily in start-ups and technology, (re)insurance companies appear to have assumed a semblance of control over the InsurTech revolution

Who Benefits from Modularization?

With technology moving forward at an unprecedented pace, incumbents are increasingly electing to outsource functions to highly specialized new entrants, renting evolving modules of technology that can be tailored to suit their individual needs. Though this approach may be more cost effective, it further fuels the question of whether incumbents will allow value in the industry to shift towards new entrants. In time, market participants will come to understand which module in the chain generates the most value. It is plausible that automation in distribution will shift value towards efficiency of internal processes that support cutting-edge modeling and underwriting engines.

InsT0

The State of InsurTech

InsurTech funding volume increased 36% year-over-year in 2017, demonstrating that technology driven innovation remains a core focus area for (re)insurance companies and investors heading into 2018. However, perhaps contrary to many of the opinions championed in editorial and press coverage of the InsurTech sector, further analysis of the growing number of start-ups successfully attracting capital from (re)insurers and financial investors reveals that the majority of InsurTech ventures are not focused on exiling incumbents by disrupting the pressured insurance value chain. According to research from McKinsey & Company,

  • 61% of InsurTech companies aim to enable the value chain,
  • 30% are attempting to disintermediate incumbents from customers
  • 9% are targeting full scale value chain disruption.

Has the hype surrounding InsurTech fostered unjustified fear from overly defensive incumbents?

We have taken this analysis a step further by tracking funding volume from strategic (re)insurers versus financial investors for InsurTechs focused on enabling the value chain relative to their counterparts attempting to disintermediate customers from incumbents or disrupt the value chain altogether and found that 65% of strategic (re)insurer InsurTech investments have been concentrated in companies enabling the value chain, with only 35% of incumbent investments going to start-ups with more disruptive business models. What does it mean? While recognizing the subjective nature of surmising an early stage company’s ultimate industry application at maturity from its initial focus, we attribute this phenomenon to the tendency of incumbents to, consciously or subconsciously, encourage development of less perceptibly threatening innovation while avoiding more radical, potentially intimidating technologies and applications.

Recognizing that this behavior may allow incumbents to preserve a palatable status quo, it should be considered in the context in which individual investments are evaluated – on the basis of expected benefits relative to potential risk. We have listed several benefits that InsurTechs offer to incumbents :

InsT1

Segmenting the InsurTech Universe

As InsurTech start-ups continue to emerge across the various components of the insurance value chain and business lines, incumbents and investors are evaluating opportunities to deploy these applications in the insurance industry today and in the future. To simplify the process of identifying useful and potentially transformational technologies and applications, we have endeavored to segment the increasingly broad universe of InsurTech companies by their core function into four categories:

  1. Product & Distribution
  2. Business Process Enhancement
  3. Data & Analytics
  4. Claims Management

This exercise is complicated by the tendency of companies to operate across multiple functions, so significant professional judgment was used in determining the assignment for each company. A summary of the criteria used to determine placement is listed below. On the following pages, we have included market maps to provide a high level perspective of the number of players in each category, as well as a competitive assessment of each subsector and our expectations for each market going forward. Selected companies in each category, ranked by the amount of funding they have raised to date, are listed, followed by more detailed overviews and Q&A with selected representative companies from each subsector.

InsT2

Click here to access WTW’s detailed birefing

Technology Driven Value Generation in Insurance

The evolution of financial technology (FinTech) is reshaping the broader financial services industry. Technology is now disrupting the traditionally more conservative insurance industry, as the rise of InsurTech revolutionises how we think about insurance distribution.

Moreover, insurance companies are improving their operating models, upgrading their propositions, and developing innovative new products to reshape the insurance industry as a whole.

Five key technologies are driving the change today:

  1. Cloud computing
  2. The Internet of Things (including telematics)
  3. Big data
  4. Artificial intelligence
  5. Blockchain

This report examines these technologies’ potential to create value in the insurance industry. It also examines how technology providers could create new income streams and take advantage of economies of scale by offering their technological backbones to participants in the insurance industry and beyond.

Cloud computing refers to storing, managing, and processing data via a network of remote servers, instead of locally on a server or personal computer. Key enablers of cloud computing include the availability of high-capacity networks and service-oriented architecture. The three core characteristics of a cloud service are:

  • Virtualisation: The service is based on hardware that has been virtualised
  • Scalability: The service can scale on demand, with additional capacity brought online within minutes
  • Demand-driven: The client pays for the services as and when they are needed

cloud

Telematics is the most common form of the broader Internet of Things (IoT). The IoT refers to the combination of physical devices, vehicles, buildings and other items embedded with electronics, software, sensors, actuators, and network connectivity that enable these physical objects to collect and exchange data.

The IoT has evolved from the convergence of

  • wireless technologies,
  • micro-electromechanical systems,
  • and the Internet.

This convergence has helped remove the walls between operational technology and information technology, allowing unstructured, machine-generated data to be analysed for insights that will drive improvements.

IoT

Big data refers to data sets that are so large or complex that traditional data processing application software is insufficient to deal with them. A definition refers to the “five V” key challenges for big data in insurance:

  • Volume: As sensors cost less, the amount of information gathered will soon be measured
    in exabytes
  • Velocity: The speed at which data is collected, analysed, and presented to users
  • Variety: Data can take many forms, such as structured, unstructured, text or multimedia. It can come from internal and external systems and sources, including a variety
    of devices
  • Value: Information provided by data about aspects of the insurance business, such as customers and risks
  • Veracity: Insurance companies ensure the accuracy of their plethora of data

Modern analytical methods are required to process these sets of information. The term “big data has evolved to describe the quantity of information analysed to create better outcomes, business improvements, and opportunities that leverage all available data. As a result, big data is not limited to the challenges thrown up by the five Vs. Today there are two key aspects to big data:

  1. Data: This is more-widely available than ever because of the use of apps, social media, and the Internet of Things
  2. Analytics: Advanced analytic tools mean there are fewer restrictions to working with big data

BigData

The understanding of Artificial Intelligence AI has evolved over time. In the beginning, AI was perceived as machines mimicking the cognitive functions that humans associate with other human minds, such as learning and problem solving. Today, we rather refer to the ability of machines to mimic human activity in a broad range of circumstances. In a nutshell, artificial intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider smart or human.

Therefore, AI combines the reasoning already provided by big data capabilities such as machine learning with two additional capabilities:

  1. Imitation of human cognitive functions beyond simple reasoning, such as natural language processing and emotion sensing
  2. Orchestration of these cognitive components with data and reasoning

A third layer is pre-packaging generic orchestration capabilities for specific applications. The most prominent such application today are bots. At a minimum, bots orchestrate natural language processing, linguistic technology, and machine learning to create systems which mimic interactions with human beings in certain domains. This is done in such a way that the customer does not realise that the counterpart is not human.

Blockchain is a distributed ledger technology used to store static records and dynamic transaction data distributed across a network of synchronised, replicated databases. It establishes trust between parties without the use of a central intermediary, removing frictional costs and inefficiency.

From a technical perspective, blockchain is a distributed database that maintains a continuously growing list of ordered records called blocks. Each block contains a timestamp and a link to a previous block. Blockchains have been designed to make it inherently difficult to modify their data: Once recorded, the data in a block cannot be altered retroactively. In addition to recording transactions, blockchains can also contain a coded set of instructions that will self-execute under a pre-specified set of conditions. These automated workflows, known as smart contracts, create trust between a set of parties, as they rely on pre-agreed data sources and and require not third-party to execute them.

Blockchain technology in its purest form has four key characteristics:

  1. Decentralisation: No single individual participant can control the ledger. The ledger
    lives on all computers in the network
  2. Transparency: Information can be viewed by all participants on the network, not just
    those involved in the transaction
  3. Immutability: Modifying a past record would require simultaneously modifying every
    other block in the chain, making the ledger virtually incorruptible
  4. Singularity: The blockchain provides a single version of a state of affairs, which is
    updated simultaneously across the network

Blockchain

Oliver Wyman, ZhongAn Insurance and ZhongAn Technology – a wholly owned subsidiary of ZhongAn insurance and China’s first online-only insurer – are jointly publishing this report to analyse the insurance technology market and answer the following questions:

  • Which technologies are shaping the future of the insurance industry? (Chapter 2)
  • What are the applications of these technologies in the insurance industry? (Chapter 3)
  • What is the potential value these applications could generate? (Chapter 3)
  • How can an insurer with strong technology capabilities monetise its technologies?
    (Chapter 4)
  • Who is benefiting from the value generated by these applications? (Chapter 5)

 

Click here to access Oliver Wyman’s detailed report

Insurance Data Integrated Platform

The insurance industry today is poised for a paradigm shift in the way that technology is deployed to provide products and services to customers. This has primarily been driven by changing business needs and the innovations brought about by myriad insuretech firms, leading to an inevitable shift towards adopting the new digital innovations.

Analysts have forecast significant investments geared towards the digitalization of the industry and expect such investments to continue pouring in for several years. It is also expected that an increasing number of new insurance companies will be driven by technology companies to bring better products, services, and customer service in the insurance industry.

A forward-looking plan of action, sufficient operational flexibility, an effective implementation strategy, and a willingness to adopt digital disruptions in every aspect of their organization – those insurers that have all of the above can position themselves to leverage the impending digital disruptions to propel their organization to the very forefront of the industry.

DEALING WITH THE DIGITALIZATION OF THE INSURANCE INDUSTRY

These adopters of digital technology will have a clear upper hand against their competition. Suitably equipped to cut costs and design more attractive offerings, the digital insurance carriers are sure to acquire a whole new set of customers, thus increasing market share. Those who fail to quickly adopt the new technologies, on the other hand, will struggle to maintain their competitive positions in the midst of a customer-centric, price-sensitive market.

Data has always been at the center of the insurance industry, and despite the changes that are to come, data will continue to be the focal point of the industry. In fact, it’s set to play a bigger role to play than ever before.

The continued criticality of data in the insurance landscape is ensured by carriers’ need for information-driven strategies in the digitalized business scenario. They’ll have to leverage data as an asset, enabling automated decision-making in critical business processes, in order to thrive. This, in turn, is why a digital business technology platform – one that incorporates information management and analytical capabilities – will become a necessity in the future.

Without a system in place to support the analytics and reporting needs of the business, decision-makers may be left with no choice but to rely on conventional time-consuming manual processes those are more qualitative rather than quantitative in nature. This is bound to cause serious repercussions for the organization, ultimately resulting in missed opportunities and loss of competitiveness.

According to a Gartner study, the two following technology platforms are essential for any digital business:

  1. Data and analytics platform – This platform should consist of data management programs and analytics applications to enable data-driven decision making
  2. Ecosystems platform – This platform’s role should be to support the creation of and connection to external ecosystems, marketplaces, and communities

MFX

 

Click here to access MFX’s detailed White Paper