A key make-or-break factor for any business or industry during the COVID-19 pandemic has been the ability to shift business online and provide “contactless” service. This holds particular pain for an industry built on home paramedical exams and handshakes across dining room tables, but the solution has actually been here the whole time, and it all comes down to some innovative and powerful uses of credit-based and non-credit-based data.
This Q&A features TransUnion’s Jeff Reynolds, whose background and expertise center on insurance product development and strategy, and Mike Moran, a 45-year industry veteran — from life insurance to securities — who led their company’s shift into the life insurance space.
They tell the story of how TransUnion and digital data solutions are vitalizing the life insurance industry, including a behind-the-scenes look at how they custom-fit their solutions to position carrier success and customer satisfaction throughout the product life cycle.
Q: What is the importance of credit-based risk scores to today’s life insurance industry?
Reynolds: Credit-based insurance scores measure the behavioral responsibility of individuals. People who manage their finances well tend to also manage other important aspects of their lives responsibly, such as avoiding smoking or excessive drinking, and instead maintain a healthy lifestyle. Insurance scores have been very stable as a risk indicator, and have shown stability even during the global pandemic.
Moran: Since it’s calibrated on long-term behavioral aspects, even though the death rate is up, the pandemic has not affected our TrueRisk® Life credit-based insurance scores one basis point. Credit-based risk scores, specifically from our product TrueRisk Life (TRL), helped both the carrier and consumer during the pandemic, when no one wanted to let a paramedical professional into their house and doctors were unavailable to create the reports. By enabling accelerated underwriting, TRL helped our existing customers do significantly more business during COVID-19 than they did previously.
Reynolds: Moving forward, this speed to market will continue to be crucial. Consumers more and more are gravitating toward online distribution channels. Using insurance scores ensures insurance carriers are able to accurately predict risk, and it provides products to customers at a price that accurately reflects the cost of insurance, allowing products to be delivered much quicker, which is what people want in the digital age.
Q: How are insurance risk scores calculated?
Moran: The gold standard has always been the Social Security Death Master file (pre-2012), which was our source document when we built TrueRisk Life. Of the approximately 800 credit attributes of a consumer, we identified 25 categories that were predictive of mortality, which can be put into four buckets.
The first provides a consumer’s credit profile, like the length of credit history and number of credit lines. A second bucket is shopping codes, which include applications for loans and credit cards. The third is the consumer’s utilization of credit, such as average balances, debt to credit limit. The fourth bucket is the derogatory codes, such as bankruptcies, collection delinquencies. This is not a credit score.
The TrueRisk Life score is calibrated to mortality. We use long-term attributes. Somebody can’t just make changes in their financial credit management to move the TRL score.
Q: How else do data solutions benefit insurance carriers?
Moran: TransUnion is best in class with its matching capabilities. We have credit data on some 350 million credit-active consumers. To be able to identify the right John Smith is spectacular. Furthermore, we use non-credit data as well to provide a diversified solution suite from cradle to grave, through the whole life cycle.
Reynolds: We can help carriers target the most profitable customers. We can help them properly segment risk and underwriting, make sure that they can verify the identities, especially digitally, and also allow them to monitor policies to keep the information current and accurate, and fulfill their fiduciary responsibilities as a life carrier, by notifying them if there has been a mortality event that they need to investigate and get the life insurance proceeds to the hands of the beneficiary as soon as possible.
We just developed a solution for the group life market that allows those carriers to aggregate the individual risk level of employees up to the employer level so they can get a relative risk profile of that employer. It’s a brand-new pricing solution. It’s much more granular than just looking at something like an SIC code.
Q: How are TRL scores leveraged for targeting capabilities on the marketing side?
Moran: The old paradigm was that many insurance salespeople would typically quote a preferred risk rate level, and then once it went into underwriting, maybe something was picked up and it ended up being issued “other than applied for” at a standard higher rate level — not a great customer experience. What’s happening is that risk-based quoting is moving to the left into the marketing space, helping carriers reinforce brand reputation and customer sentiment by delivering a more seamless experience.
Carriers can target specific customers based on an insurance score that would qualify for their traditional and digital marketing programs, or they can utilize aggregated data to target a broader group of consumers. Every quarter, we score 350 million consumers with TRL scores. We then bucket those TRL scores into ZIP codes with minimum aggregation rules strictly enforced. Now, there’s no personalization. That aggregated data can be used in marketing.
The consumer who hesitates to give any of their personal data, on a landing page for example, seems OK providing a ZIP code. This is how TRL has been reengineered to be a marketing solution that helps with the user experience, defining the journey, quoting the right rate, and not surprising them at the end of the process.
Q: Just how many customers can ultimately get accelerated underwriting?
Moran: Out of a pool of applicants, maybe 70% of them get very attractive TrueRisk Life scores, and these can be fast-tracked. There is definitely a consumer benefit when you triage like this. For those other 30% who have marginal TRL scores, they would be subject to more underwriting.
We were told by one regulator that the reason they like TrueRisk Life is because it was consistently applied. There was no judgment. There’s nothing wrong with the traditional underwriting model other than it’s time-consuming and expensive. Good underwriters are worth their weight in gold. Traditional underwriting is truly an art form. You should save only your tough cases for a traditional underwriter to review.
Q: How are a life cycle’s worth of solutions tailored to different carriers?
Reynolds: Typically, if we’re building a marketing model, we’ll get what we call a seed file from a customer, which includes as much data as they can provide from a known group they’ve advertised to. It may include response data, conversion data, the names of the people who converted, conversion channel, whether the consumer had a loss or any other data points that support the key performance indicator the carrier’s trying to optimize.
We take that seed file and apply advanced modeling to it and then correlate the different datasets that we have here at TransUnion, TrueRisk Life being one of them, and turn that into a predictive model that can score any consumer in the United States. Then, based on that seed file, we can identify which data elements in our data library are the most correlative to that particular customer who was a high converter, high lifetime value. There are many ways we can build and customize these models and marketing campaigns to deploy across different marketing channels.
If the carrier is looking at a solution for their underwriting program, we can do a validation of the solutions on their historical book to evaluate the lift and protective value of the solution. TransUnion has a team of industry experts who understand your business. We work in partnership with you, and you can test the solutions before committing.
Moran: Yes, we can build marketing models for testing, at no cost. Ultimately, we try to be a trusted advisor and not a data vendor, understanding what our customers need in order to grow and sustain a profitable business. This collaboration informs our product strategy. We’re not in business unless we’re helping you grow yours.