'Underwriting must adapt in the face of increasing life insurance demand'

While the general market impression of the effect of Covid-19 is that new life insurance business demand has dropped in most product areas, protection products appear to be a significant exception.

Such a glimmer of good news is of course welcome, but it does come with some new challenges for underwriting and pricing that could determine how safe it is to write more protection business in the short term and how resilient underwriting remains in a medium- to longer-term, post-Covid world.

For example, how do you get a potentially increased volume of quotes out quickly, accurately and efficiently through your distribution networks to meet demand and competition in the current environment, particularly if your process involves a lot of messy, manual steps? How do you manage a medical underwriting approach where perhaps medical attendance reports are difficult to obtain? Or how do you ensure your underwriting is flexible and agile enough to reflect emerging Covid-19 infection and claims trends?

Such questions are prompting more insurers to investigate the sophisticated analytics, underwriting and pricing - perhaps incorporating elements of machine learning and artificial intelligence (AI) - that have increasingly become a competitive necessity in many property and casualty markets around the world. Some life and health insurers are also pursuing the use of analytics and automation to better understand trends in experience and customer behaviour that can support, for example, better cross-selling.

The diagram below shows how such benefits are achieved in an agile underwriting process.

Figure 1. The main stages of a fully automated and controlled underwriting journey

In the core areas of pricing and underwriting, key attractions include enhanced pricing flexibility and agility, more detailed and responsive management information, better market responsiveness, operational efficiencies and cost savings, and reduced risk of costly pricing errors. Prices that could previously take up to six months to update, can now be revised within hours, complete with full review and governance.

Policyholder information

Within such a fully automated and controlled underwriting process, information can be pulled in from a wide range of sources, so quote information can potentially be enriched with data from a variety of other sources such as Fitbit outputs, postcode information, distributor information and, where permitted, personal information from other data sources. Automatic data queries will also highlight any data anomalies, such as an unknown address or an unusual sum assured request.

Risk rates

With the customer data gathered and prepared, attention moves to building the underlying view of the risk of that customer. This could happen in several ways, including calling the existing rate structure, but could also potentially use generalised linear models that incorporate claims experience, models that incorporate medical judgement, reinsurer rates, machine learning and AI-generated information. Significantly, underwriting rules can be changed in a matter of hours if necessary, say to accommodate specific constraints or insights associated with Covid-19, including new questions that might inform an applicant's susceptibility to the virus.

As an example of the benefits that can come from these approaches, some companies with which we've worked that have introduced GLMs have found the increased segmentation capabilities provide risk differentiation of around +/- 50% (identifying that high mortality groups show double the mortality of low mortality groups).

Premium calculation

Even with a simple expenses-plus type approach, a loading for risk based on a more in-depth assessment of strong data is likely to have advantages. Similarly, rate structures based on supply/demand or attaining a certain competitive position in the market can be applied with less risk of adverse selection using customer demand behaviour data.

Perhaps the key thing though is the speed, flexibility, efficiencies and ease of governance the system provides. It can support updating prices daily, including producing the up-to-date analysis and management information required to make frequent price changes. It also allows insurers to change rating structures easily, and to ease the transition from a fixed rate table to more advanced formula or algorithm driven pricing.

Market distribution

All of the technical wizardry in the world is worthless if you can't get your rates to market in a timely manner. Using industry standard API technology, the system can be called by both internal and external systems, providing channel-agnostic digital distribution. It also maintains complete transparency and flexibility over variable changes to pricing for advisors, affinity partners such as banks, and price comparison sites. Specific benefits for different distribution options could include making real-time information available to call centre staff and agents about factors such as likely customer value and upsell potential or combining company and agent data to produce channel-specific analysis.

Feedback loops

The system allows information on new business, underwriting decisions, lapses and claims to be fed in to create bespoke management reporting templates quickly and easily. These can be tailored to specific business metrics such as agent performance and market segmentation and used to inform pricing and business decisions. In the case of Covid-19, such reporting could provide early warning signals of claims trends related to, say, socio-economic grouping, occupation or geography, that might influence the underwriting and pricing approach. 

Insurers need protection too

This level of sophistication remains the exception rather than the rule in life insurance, but that doesn't mean that some companies can't get left behind, especially given the relevance of new operational factors introduced by Covid-19.

The reported surge in interest for protection products relative to other life and health insurance product lines as a result of Covid-19 brings both opportunities and risks. It could indeed be very positive for insurers that have systems that give an in-depth view of the risks and are able to underwrite and price at pace and with the agility that will give them an advantage. 

For others, the big risk is that ponderous and inflexible systems will result being left unwittingly with higher or incorrectly priced protection risks that stand a bigger chance of coming back to bite them some time down the road.

Matthew Edwards is director for insurance consulting and technology and Alastair Black is director for insurance consulting and technology, at Willis Towers Watson