Articles - Life pricing and the balance between profitability and trust

Life insurers have been continuing the journey towards automated pricing and underwriting, influenced by the growth of InsurTech and the desire to make more use of data. However, greater use of data raises questions about trust. Are policyholders willing to give more data? Would they do so only if it could result in lower premiums? If so, what will be the penalty for other policyholders, as average premiums must – all other things being equal – remain constant?

 By Matthew Edwards is Head of Mortality and Longevity in Willis Towers Watson’s UK Life Insurance Practice.
 The ideal for insurers would be to have access to the Electronic Health Records of policyholders, which would allow much more precise risk rating according to reliable medical information, as well as lifestyle aspects. More precise risk rating obviously does not mean generally higher premiums, although that is part of the communication challenge insurers would face. Clearly, insurers would be able to rate business according to a more precise risk assessment, hence premiums should, in aggregate, reduce owing to slightly lower margins in respect of uncertainty. The availability of such data would also facilitate market entry, increasing competitive pressure in the market, putting further downward pressure on premiums.
 Why trust matters more than ever
 However, there are huge issues in trust. Insurers are fundamentally not trusted nearly as much as they would like to be, with mis-selling scandals in particular laying bare how insurers have not acted in the public interest (although the issue there bears no direct relation to the question of data). The lack of trust may relate to concerns about higher premiums or even to outright unavailability of cover for policyholders with severe medical histories.
 A recent report published by the Chartered Insurance Institute, ‘Shaping the Future of Medical Records and Protection Insurance’, considered the issues around use of medical data and trust. The report quotes research by Ipsos MORI, conducted in 2016, that showed 59% of the public do not trust insurers, in addition to providing further interview-derived examples of trust issues.
 At the moment, the scale of public concern around data privacy in conjunction with this lack of trust makes the idea of any imminent revolution in the availability of health data seem ‘pie in the sky’.
 However, what other ways are there to rate risks better, whilst ideally also providing a smoother ride for policyholders?
 Other routes to richer data
 One of the more tangible routes to richer data is the ‘FitBit’ approach – collecting large amounts of data from policyholders’ fitness/lifestyle wearables (or equivalent apps), with the incentive of reduced premiums for those policyholders who ‘hit their targets’.
 However, although such data would be an analyst’s dream in 10 to 20 years when a sizeable amount of health-related events have been recorded (deaths, in particular, which will tend to be very low frequency in such populations and so require a long period to monitor), using the data in rating new risks ‘now’ is a major challenge.
 Quantifying ‘FitBit mortality’ can be difficult. Research has been done into the impact of steps and their relationship between morbidity and mortality, but the amount of steps done is less predictive than the intensity of the exercise. One Canadian InsurTech firm has access to a relatively small data set of over 15,000 people over 20 years and claims that some of the exercise-related figures are more relevant to mortality than even smoking.
 What other ways are there to use data to improve underwriting? Larger insurers (in particular, banking groups or composites) may already have information about the potential policyholder in a different part of the group, making the underwriting process quicker and more predictive. An extreme example of this is a new approach by a UK insurer to home insurance on the P&C side, aiming to ask no questions at all – with ‘get a quote not a quiz’ being an appropriate catchphrase that sums up this philosophy.
 If you do need to ask underwriting questions, there is growing research into the risk impact of some ‘easy to answer’ questions where the potential policyholder would find it hard to know what answer would lead to a lower premium, thus ideal for obtaining more honest responses! For instance, research done on the UK Biobank data, comprising around 500,000 lives with detailed data, has given rise to the ‘UK Biobank Longevity Explorer’ which provides many novel rating factors. An interesting example is ‘number of vehicles used in your household’, which is surprisingly predictive of mortality.
 A two-step approach to rebuilding trust
 Is it possible for an insurer to collect data and, at the same time, increase policyholders’ trust in the company? There is great potential in products such as those launched recently in the UK aimed at diabetics. With these, policyholders provide data as a way to show what progress they are making conforming with diabetes treatment guidelines; adherence to targets then affects premium levels.
 This type of policy, rather like insurance covers involving fitbits and gym attendance, can create more of a ‘relationship’ between the insurer and the insureds, whereby the perception of the insurer moves from being an abstract monolith that people pay money to, to a firm that engages with you in a positive way to improve your health (while reducing premiums or some equivalent tangible benefit).
 This philosophy of helping policyholders become more healthy is the cornerstone of the recent launch of a life insurance venture in the UK which rewards smokers who convert to lower-risk alternatives to traditional tobacco with a discount on their life insurance premiums.
 Significant developments are evident within the InsurTech space, with much of that work being aimed at helping clients improve their data and, in turn, improve their profitability. While obtaining rich medical data may never happen, there are alternatives that can allow insurers to improve their risk rating and ease the process from the policyholder’s perspective. Some of these alternatives also have the potential to help reshape the public’s perception of insurers, hopefully away from ‘money takers’ towards an image of ‘health helpers’.

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