Oliver Werneyer asks whether actuaries can master the power of new technologies
Imagine you wake up one morning and hear: "It is the year 2054AD, and crime has been eliminated in Washington DC thanks to an elite law enforcement squad called 'Precrime'. They predict a felony before it happens, and John Anderton heads the team in arresting criminals before they can commit the crime..." Relax, take a deep breath. It was only the movie, Minority Report, on your television. One aspect of the movie is how data is used in such an advanced way. We might not find ourselves in a world with predictive policing units, but it makes you think. Will we ever be in a position to predict crime?
It is an actuary's job to predict various events. The world has changed a lot, and never faster than in the past five years. We have seen the rise of social media, crowd-funding, wearable gadgets, telematics and the concept of 'the quantified self'. The latter is the one actuaries should be most excited about, but also the most cautious. Its rise has come about through the partnership between technology and services that enable users to track aspects of their activity and health, and centrally store this data.
Apple has just announced the HealthKit component to its operating system and Samsung is launching a similar service called 'Sami'. Both of them cater for and prepare platforms for major expansion in this area.
We have seen telematics in the motor insurance market for a while now, but life insurance companies are nowhere near this level of sophistication yet. Most of the companies who actually have some type of telematics offering have done so off the back of the medical insurance business they write, and combined it into a form of loyalty programme. One of the most successful and well-known examples of this is the Vitality loyalty programme. It is proof that activity data integration into insurance products is not only doable but also beneficial to the business and its policyholders.
Wearable devices alter behaviour
The life insurance market is ripe for innovation, and wearable devices are a good example of an emerging technology that can spark a wave of developments in the market for life insurers to explore.
Many published studies into human behaviour have shown that purely by monitoring or recording something about a person affects their behaviour. Whether the effect on behaviour is good or bad very much depends on the reason for monitoring, the incentives and what the insights are ultimately used for. So far, life actuaries have only had an indirect effect on policyholder behaviour, either through the initial underwriting protocol or through some form of loyalty programme.
In future, life actuaries who embrace more innovative solutions can fully integrate such policyholder behavioural information not only into product design but also into underwriting philosophies, and can develop completely new product concepts.
We could be looking at products where we underwrite a risk on a continuous basis, not only once upfront. What about products for people with chronic diseases with built-in protocol-adherence checks through devices? The technology can help previously uninsurable risks gain access to insurance at very reasonable terms.
Devices generate a lot of data
Actuaries do love data. This is our life blood. It fuels our thoughts, our models, and it helps form expert opinions on longer-term risks. Actuaries are regarded as masters of data and extract insights from data. The problem is that, for the past 50-100 years, not much has changed with regards to the data life actuaries get to see - age, gender, smoker status, BMI, occupation, medical history, for example.
With the revolution on the individual health monitoring front, we are seeing so much more information being recorded in new ways. This is exciting as it means actuaries are entering a period of opportunity and reinvention.
Wearable technology is able to provide data in milliseconds. FitBit, a wireless-enabled activity tracker device, can identify age, gender, height (to estimate step length) and weight (most users record their weight). It also has application programming interfaces (APIs) that allow third parties to extract any data from the device once the customer enters their account credentials, similar to opening an account on a website using your Facebook login. This makes it very easy to submit the data, and also removes many legal obstacles around how the data was acquired, as the user has given express permission to use it.
This means access to much more detail through these gadgets, compared with traditional underwriting. It includes sleep analysis (possible links to psychological and health concerns), weight-tracking, body measurements, activity information, dietary profile and more. It can help improve the quality of information and reduce non-disclosure and fraud. It allows for more accurate measurements, and a continual check on data can be performed for a set period. This new data can be used to design new products and make better underwriting decisions.
Consider someone applying for a policy with a BMI of 29.8. This makes them overweight and borderline obese. What terms would you offer them? Standard rates, load their premium or decline them cover?
You have to make that decision based on the BMI measure at that point in time but the decision you make will last the entirety of the policy.
Now imagine you could get their BMI values for the past six months. You could figure out whether this person has been losing weight (give standard rates), has maintained their weight (load premium) or has been gaining weight (decline cover), and use that to make a better underwriting decision. On top of this, you could get access to their activity data to separate those who are fit but have high BMI from those who are not and have a high BMI.
This could have a massive effect on the accuracy of the underwriting decision and enhance the time it takes to arrive at this more accurate decision. The confidence you now have in your risk pool could also be significantly increased, meaning more accurate (and less intense) stress-testing can be performed to get a more reliable view on the portfolio risk. Experience buffers could be reduced on the portfolio, or a subset of lives, which could mean better premiums for your policyholders or higher margins for the business.
Anti-selection in the portfolio could be reduced, because we would consider data collected over a period of several months rather than relying on responses on a single underwriting form. There are so many positive second-order effects that can lead to a better understanding of the risk pool and thus also better pricing of that risk.
The possibilities for innovation are huge for those brave enough and entrepreneurial enough to explore the opportunities. Unfortunately, to solve the challenges that actuaries face will require equal amounts of both attributes, but it is certainly possible.
There is also appetite in the market for new products (behaviourally assessed, individually monitored), underwriting philosophies (perpetual underwriting, probational underwriting) or risk assessment and management tools.
We also need actuaries to develop new ways of thinking, to look at new data sources and to look at data differently. But, most importantly, we need actuaries who need to be challenged by change and inspired by other industries that have embraced these new data sources and technologies. Here's to the future of the life industry and the role that actuaries can play in that future.
Data doesn't get you all the way
There is sometimes the tendency for those working in predictive analytics to believe that, given the right data, perfect predictions can be made. Unfortunately, this is not the case. Models make mistakes and customers don't always behave the way they are expected to. There will always be the customer with a low propensity to lapse who cancels their policy.
Analytics can help improve the process, by removing redundant health questions for healthy customers, for example. However, strong sales methods and messages are still needed. Reliable results can only be expected when good analytics come together with strong sales or retention processes.
The growing body of evidence emerging from the field of behavioural economics is a helpful reminder that we are not as fully rational as we think we are - and as we claim to be. This should encourage taking a 'test and learn' approach to everything we do. Only then will the true drivers of customer behaviour be determined.
Lots of people talk about it - but few actually do it
It's easy to lose count of the number of industry events where the presenter has spoken about Google and Amazon and what they are doing with their data, but the life insurance industry is still very slow to react in actually making use of the data it has access to. Experience so far has proven that much can be achieved through matching life insurance data with other descriptive data in order to predict health, purchase or lapse. Some insurers have led the way on this, and hopefully many more will follow.