Combating the $75 Billion Nondisclosure Challenge: How Behavioral Analytics Enhances Life Insurance Underwriting and Fraud Detection
Life insurance fraud detection needs to improve. As is, fraud, misrepresentation, non-disclosure, and anti-selection pose a significant financial burden for life insurance carriers, contributing to industry losses of around $75 billion annually, according to a recent study by RGA and MIB. As the life insurance industry shifts toward accelerated underwriting (AUW) models to meet consumer demand for a streamlined process, the risks associated with fraud and nondisclosure have increased.
According to the study, 96% of carriers offering accelerated underwriting limit face amounts, issue ages, or the number of policies issued to manage fraud risk. ForMotiv’s Nondisclosure Solution provides a strategic advantage by identifying patterns of nondisclosure and anti-selection early in the application process. Carriers increasingly integrate behavioral analysis into their protective value requirements in the AUW triage process. These actionable insights form the first line of defense in the life insurance fraud detection battle.
Addressing Key Life Insurance Fraud Concerns with Behavioral Data
The RGA study highlights medical misrepresentation as the top fraud concern for carriers, particularly around tobacco use. Misrepresentations on lifestyle-related disclosures, such as alcohol and drug use or build, also pose significant challenges. For example, 22% of cases are removed from AUW due to discrepancies between disclosed and verified information.
Leveraging real-time behavioral data science, ForMotiv provides a nuanced understanding of applicant intent and disclosure accuracy. By embedding ForMotiv’s Nondisclosure Solution in their AUW triage processes, carriers can evaluate cases more effectively, identifying signs of possible misrepresentation before issuing policies. This data-driven, real-time solution not only directs cases to the appropriate evidence paths but also supports broader AUW adoption with less restrictive limitations. This empowers carriers to expand face amount limits and policy options within AUW models by improving fraud detection confidence.
Expanding Life Insurance Fraud Detection through Advanced Algorithms and Analytics
As highlighted in the RGA study, the insurance industry has seen a significant rise in the use of algorithms and analytics to detect fraud, increasing from just 10% in 2016 to 32% in 2024. This surge underscores insurers’ growing reliance on data-driven tools like Risk Classifiers, credit scoring, and activity tracking to identify patterns of misrepresentation and fraud in underwriting applications. ForMotiv adds a new layer of protection by utilizing real-time behavioral data to identify potentially risky behavior on important underwriting questions like tobacco, alcohol, height/weight, avocation, family medical history, and more.
Monitoring behavioral red flags in real-time is critical for carriers aiming to combat medical and lifestyle misrepresentations in AUW that wouldn’t otherwise be discovered using traditional 3rd party data checks. By integrating ForMotiv’s solutions, insurers can proactively prevent applicants from submitting incorrect information, thus reinforcing the underwriting process as the first line of defense.
Harnessing the Future of AI and Behavioral Data in Life Insurance Fraud Prevention
According to the survey, 74% of insurers express strong interest in expanding the use of data analytics, with a substantial percentage actively exploring AI. Given the regulatory constraints of life insurance underwriting, we think the benefits of AI in underwriting are a ways off. In the meantime, advanced behavioral analytics like ForMotiv’s Nondisclosure Solution empower carriers to detect “red flag” behaviors, enhancing traditional fraud risk assessments and real-time triage capabilities.
As we mentioned, by incorporating ForMotiv’s real-time analytics, insurers can improve their triage process, redirecting questionable applications before they reach underwriting completion. Such preemptive measures add a robust protective layer, allowing carriers to increase policy limits and expand AUW offerings with confidence.
Conclusion
Behavioral analytics is crucial for life insurers navigating the challenges of accelerated underwriting. ForMotiv’s solutions provide carriers with a scalable, efficient approach to enhancing nondisclosure and fraud prevention, empowering insurers to increase face amounts and the percentage of policies placed through AUW.