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Accelerating Insurtech - From Pipedream to Reality

Nicholas van der Nest, Head of Product Innovation, Life & Health, Asia-Pacific, Munich Re

Nicholas van der Nest, Head of Product Innovation, Life & Health, Asia-Pacific, Munich Re

We have seen a significant increase in the number of startups developing solutions specifically for the life insurance industry. Solutions generally focus on one of three main elements: improving the on-boarding journey for new clients; transforming the underwriting journey and driving ongoing engagement to offer personalized insurance offerings to clients.

To date, however, the implementation of new technology far underperforms the level of activity in the Insurtech industry. Most current implementations focus on either improving existing processes marginally or offering alternative value-add service solutions to existing customers, often through developing new digital health ecosystems.

Given the amount of Insurtech activity, it’s only a matter of time before there is a large-scale embedding of new technologies in the sector, and once implemented, rapid adoption is likely to follow. The question is how long it will take, and who will be first to make the required shifts in business practices?

To answer this question, it’s important to critically evaluate the life insurance industry and clear the hurdles standing in the way of such transformation.

The reality is that until now, the life insurance industry has followed largely linear processes when issuing a new policy. A typical process takes three to six weeks and involves a sales agent; regulatory KYC processes; completion of lengthy application forms; medical, financial and a vocational underwriting; and eventually payment of a premium and issuance of a policy document. Underwriting processes were designed to ensure appropriate risk management using rigid processes relevant at the time of design, many years ago. Adopting a digitized, customer-centric journey often faces significant challenges and costs alongside incompatible older technology, hardcoded back-end systems, and tried and tested distribution processes.

Once a policy is issued, an insurer’s focus tends to turn to infrequent communication with policyholders around their benefits and costs of cover, and nearly non-existent engagement levels around the clients’ needs, wants and likes.

The development of digital health ecosystems aims to address this shortcoming by using data and lifestyle signals combined with artificial intelligence and machine learning to customize communication methods and promote appropriate platform services related to these insights.

Given the amount of insurtech activity, it’s only a matter of time before there is a large-scale embedding of new technologies in the sector, and once implemented, rapid adoption is likely to follow

Long-term customer engagement levels are largely untested though, and true product customization is still some way off.

To truly embrace technology in developing new processes acceptable to today’s customers, insurers need to actively overcome three key features of our industry.

Firstly, insurers and Insurtech companies alike need to be realistic around business cases for deploying new technology solutions. Most insurers are well-established and have built up significant blocks of in-force, long-term business. Using conservative valuation bases (relative to best estimate claims costs) implies an almost guaranteed stream of future profits as these in-force books mature. Insurtech solutions, on the other hand, have generally been untested, with future profitability unknown and difficult to quantify relative to the required upfront (resource and cash) investments.

Secondly, insurers need to critically evaluate their understanding of the data available and how they use it. Standard paper-based application forms and underwriting exams collect at least 150 data fields and could be a source of very rich data useful for creating deep insights into customers with the help of predictive analytics teams. Thus far, focus for using data has been mainly to ensure insurers follow risk management guidelines at underwriting and determine whether a client should get standard or substandard rates. After that, data is generally discarded. Developing truly customized product solutions based on data-led customer insights requires a complete change in the way we view our data as an asset. It may also require significant investment in the digitization of historical data.

Augmenting existing data with additional sources from third-party data platforms provides significant scope for creating a more holistic view of customers, in terms of both understanding the true risk they pose and designing appropriate engagement processes. However, few companies are embracing external data, mostly due to concerns around data protection legislation, costs, and compatibility with existing underwriting processes and systems.

Finally, the insurance industry should recognize that distribution methods have largely remained unchanged over the last few decades. Although some companies are offering online sales, this sector has not grown as quickly as expected, and most still rely on a face-to-face sales channel. For new products to be successful, they need to appeal to the sales force, be easy to explain and contain as little potential customization as possible. The result is a static product development approach with features skewed towards advisers’ reality rather than individually customized, customer-insights driven solutions.

Delivering solutions appropriate to today’s customer requires a complete re-think of existing product development practices. New solutions are likely to require an ability to fully customize benefits, underwriting processes, sales journeys, and post-sale engagement. New product sets require expansion beyond the single, one-size fits all approach of today to a holistic range of potential solutions, offered to and customized for customers based on what we know about them and what they need.

Interesting technologies like OCR, data aggregation and analytics, dynamic underwriting engines, and AI-based engagement platforms are becoming more mature and will no doubt play some part in this journey. However, the transformation challenge will likely become a mindset change challenge rather than an Insurtech adoption challenge.