How predictive analytics is closing the life insurance gap
If you asked the ‘man on the street’ about their attitude towards life insurance, it would most likely be one of “disdain and fear.”
That’s according to Brett Wilson, VP of Risk and Actuary at life insurance startup Ethos.
Created in 2016, the San Francisco-based insurtech has secured U$100 million in funding in its mission to deconstruct and rebuild the insurance market, and shatter negative perceptions around the incumbent industry.
Drafted into the team earlier this year, Wilson’s no stranger to how things have been done so far in the global finance sector. Former roles, including heading up finance for Old Mutual Latin America, span a career that’s taken him around the world to geographies that would generally be regarded as developing economies, and it’s in these places— where wealth gaps are more pronounced— where his passion for democratizing life insurance has sprung.
“[…] having seen the impact of families not having life insurance— and how devastating that can be— is what’s made me so passionate about my career- pursuing access to life insurance for families that need it,” Wilson told TechHQ.
But the impact of not having life insurance is not limited by borders. Nearly 70 percent of families in the US who don’t have life insurance could be bankrupt in three months if they lost their primary breadwinner— and more than a third of adults remain uninsured.
An incumbent industry
The reason for the hesitance to invest comes, firstly, down to what has traditionally been a daunting and extensive application process. In the States, the process can last weeks, months even, while often compulsory medical tests and physical examinations are enough to put off half of applicants off.
Perhaps more worryingly, the life insurance industry, like other areas of insurance, has long been built on a model whereby agents are incentivized to sell the largest premiums possible (generally life-long cover or investment-based policies) in order to maximize their commissions. Needless to say, this is not always in the best financial interests of the individual based on their particular needs or circumstances, and it means that the vast majority of policies are abandoned prematurely, with the value of investments suffering as a result.
There is a “misalignment of incentives”, Wilson explained, and ultimately, it all amounts to a significant coverage gap made up largely of those who are disillusioned about the motivations of insurance companies; those who don’t think they can afford a policy; and those who are put off by the application process from the get-go.
Traditional insurance firms are aware of these negative perceptions, but models are so ingrained, and partner relationships so embedded, that established players can be hesitant to “upset the apple-cart.” But where established industries drag their feet, rest assured there are innovators on the sidelines ready to disrupt.
The life insurance industry is built on data, and “that’s going to continue to be the case going forward,” said Wilson. “But traditionally, the industry review aggregate data, rather than data that they take from individual clients, and in many cases, this is incomplete or siloed,” he continued.
“Traditionally insurers would look at population statistics— population of the country or the insurance population— which is still nowhere near a holistic view of what specific risk the client represents.”
As a result of this more generalized view, insurers will typically err toward conservatism and caution in their risks, which drives up the cost of premiums on the side of the individual. Ethos has recognized the opportunity to provide quick, convenient and tailored life insurance policies based on data provided directly by the individual combined and stratified with data available from third-parties.
In a process that Wilson said could be completed in the time it takes for you to queue for your Starbucks, Ethos can offer applicants a tailored quote built on the data they input, and data such as medical or pharmaceutical records provided by third parties that the applicant has given permission to share.
“We’re looking to get a good understanding of their mortality, and the data we have access to can give us just as good a predictor of that as medical exams would,” said Wilson.
With predictive analytics, Ethos is able to offer protection recommendations that applicants will be able to afford in the long-run, not just those they could sustain in the short-term and be forced to surrender later.
“We are using machine learning to analyze what the customer’s financial situation looks like straight from the data that they have provided to us to ensure they’re not paying more than need to for coverage,” Wilson said. “We can approach them and say this policy might be more appropriate than the other one they have applied for. This is more sustainable in the long-term and more appropriately fits their needs.
“We’re able to do that not just because of the tech and machine learning that informs us, but also the fact we’re not reliant on commission agents, who would never be incentivized to operate in that manner.”
Ethos is just one of a wealth of new entrants rocking the oil tanker insurance industry which has long been too embedded in a technological and cultural rut to innovate. As observed by KPMG, transformation in the insurance sector is not just about digitizing existing business models, it is about a new way of working which helps to rebrand the industry of one of “positive energy, new opportunities, and rewarding outcomes.”
By using data cleverly, new entrants are able to build convenient experiences quickly for customers that are personalized to their needs at more affordable prices— it’s a combination that will become increasingly hard for traditional agency-based firms, stuck in old ways, to compete with.
“That’s going to increase access and democratize the life insurance market, increasing access to more people,” Wilson told us.
“I don’t think it’s going to change the overall profile of people who are applying for life insurance, but it will widen the net.
“We’re still going to see a lot of people who are in good health, and a handful of those that aren’t. Either way, I think it’s a good thing for the industry, and the startups that are entering are enabling the industry to do that much faster than the traditional firms would have found possible.”