A. Behind the scenes, carriers use data and predictive analytics instead of full underwriting to assess risk and make an offer. They query databases that hold things like driving and prescription medication records, as well as previous insurance applications, all while the consumer’s online and waiting.
Databases Used
- Public Records Search (LexisNexis): Many carriers use LexisNexis Risk Classifier, which compiles data from sources like federal/state/county records, insurance records, law enforcement, and healthcare providers. The report will include mortgages, liens, bankruptcies, criminal records, professional licenses, and more.
- Medical Information Bureau (MIB): This group of 400+ insurers stores information from previous applications for health, life, disability, long-term care, and critical illness insurance. Insurers check this to make sure your client’s information and answers match up with what they’ve reported in the past.
- Motor Vehicle Records (MVR): As with fully underwritten policies, your client’s driving history helps evaluate risk. This database will show any DUIs, DWIs, moving violations, etc.
- Milliman Rx Risk Score: Your client’s answers to health questions will be compared to this database of prescription history. This proprietary algorithm predicts relative mortality based on prescription drug info.
- Build chart: Some carriers will also use a build chart in addition to the above databases. This would result in a knockout if your client exceeds the allowed combinations of height and weight set by that carrier.
- Lab results: Up to 40% of carriers use these results, with the client’s permission. An additional 30% are planning to add this to the array of data they use to assess risk, according to the 2018 Insurance Barometer Study.
If there’s a discrepancy between these records and your answers on the application, the carrier may not issue the policy then and there. Instead, the application is usually referred for further underwriting.