The sweeping letter was a warning to the industry.
It spilled over six single-spaced pages and 2,000 words, putting life insurers on notice for the emerging use of unconventional data in their automated underwriting.
Data such as criminal and civil judgments. Credit information. Retail purchase history. Internet and mobile device usage. Geographic location tracking. Even social media and facial analytics, sources rarely used now but expected to be widely adopted in coming years.
After an 18-month investigation into insurers’ underwriting practices, the New York State Department of Financial Services leveled a stern warning: Apply external data only if you can justify its actuarial validity and independently verify it does not discriminate or contain prohibited criteria.
But also tucked into that guidance was approval for using third-party data that has “the potential to result in more accurate underwriting,” the January letter read.
And with that, the influential regulator became the first to establish specific guidelines just as the exploration and application of nontraditional data in algorithms soars.
“The gist of that letter was insurance companies couldn’t outsource whether [the data] was discriminatory to the vendor. It was on them, so they better know what they’re doing,” said Tom Scales, head of life and health insurance at Celent.
The race to perfect fully underwritten, accelerated products using algorithms, predictive modeling and analytics as a substitute for paramedical exams and fluid tests has driven life insurers to increasingly embrace new forms of data.
Leveraging it enables carriers to provide a shorter, cheaper and more customer-friendly approval process amid rising consumer expectations in an Amazon world.
But that emerging data carries a host of privacy and regulatory concerns. It also presents accuracy and reliability issues that need to be addressed.
However, accelerated underwriting and external data remain “the No. 1 topic” in the industry, Scales said. “How can we change the way we underwrite? How can we do instant underwriting?”
Using alternative data from new sources such as social media and other digital footprints is “the next big thing” in life underwriting, said Mike Vogt, executive director of data, analytics and machine learning for technology consulting firm SPR.
“We are at the beginning of the curve with how insurers are applying unconventional data,” he said. “The biggest change and the biggest risk will be the information that we gather from social media and [artificial intelligence] will actually lead to more accurate risk predictions—at the expense of privacy.”
About 25 U.S. insurers offer accelerated underwriting using nontraditional data streams, and several more are testing platforms.
The objective is to skip the invasive medical tests whenever possible without losing precise risk assessment and fraud detection.
“It’s a game-changer. Unless there’s a regulatory challenge, we’re 24 months from everybody doing it at a fully-underwritten price, at least up to a certain age, because your competitor is going to do it,” Scales said. “That’s the heart of all this. It’s not simplified issue.
“This is the same price as a regularly underwritten product. It’s just underwritten differently. It’s part of an ecosystem change.”
Insurers are using data analytics tools such as LexisNexis Risk Solutions, TransUnion TrueRisk Life Score and MassMutual’s LifeScore360 to cull data and supply a mortality score from a wealth of sources.
Think of those scores as the mortality version of credit scores in the mortgage loan process. They have developed over the past five years, and in the case of LexisNexis, include information from more than 20,000 databases.
Meanwhile, a new frontier of alternative data is emerging from social media, facial analytics, retail purchases, public filings and epigenetics—the study of how environment and lifestyle choices such as diet, exercise and substance use influence mortality at the molecular level—to further understand and price risks. One day, genetics could join them.
The products people buy, the services they use and even the magazines they read can be highly predictive of policyholder longevity, analysts say. And so can the things they say and the photos they post on social media.
Only a “small handful of carriers” are using such information, said Samantha Chow, senior life insurance and annuity analyst at research and advisory firm Aite Group. But many insurers are exploring them.
“You’re talking about everything from scoring data to social data to data from selfies and DNA,” she said. “Over the next couple of years, you’ll see people utilizing more advanced scoring methodology using this type of data.
“How soon depends. How scary is it? It’s not about changing how they underwrite. It’s about being more accurate in their underwriting, pricing and improving the overall experience.
