Life Insurance Underwriting

Insurance Operations Underwriting Decrease Costs Increase Revenue Reduce Risk
Improve life insurance underwriting with AI to increase revenues, reduce costs, and grow your business.
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Problem: The Life Insurance Underwriting Process is Difficult 

Life insurance provides a crucial safety net for society–a lifeline that gives families and individuals peace of mind and financial stability in case of tragic circumstances. However, the life insurance underwriting process flow for folks with a serious disease is typically arduous for both applicants and insurance companies alike. 

The good news is that, with the help of AI, it doesn’t need to be that way any longer. 

Life insurance companies typically do not underwrite customers who have suffered and survived serious diseases like cancer. Doing so would require a long and expensive medical assessment process. Unless a reinsurance company covers the risk, direct insurance companies do not underwrite life insurance for individuals who have suffered a serious disease and are in a status of “impaired life.” 

A reinsurance company wants to predict which customers have positive health prospects and are insurable.

Solution: Life Underwriting with the Help of AI 

With the help of AI modeling, a life reinsurer can use medical history and conditions specific to each individual to accurately predict the risk of underwriting a serious disease survivor. The insurer can identify which customers have good health prospects and directly underwrite them without a further medical assessment, leading to more customers and reduced medical costs.

Across the board, life insurers are discovering that when they combine their data with an AI solution, they can reap enormous benefits, such as increasing revenues, reducing costs, and growing their businesses.

Why DataRobot: A Leader in Machine Learning Underwriting

For life insurance providers, AI offers the chance to increase revenue, improve efficiency, and reduce risk. Among the many benefits of AI is the ability to improve mortality, lapse, and other model assumptions, and optimize decision-making to help build and sustain profitable customer relationships. 

Hand coding models cannot possibly meet the demand or realize the incredible opportunities that AI can provide. Even though insurtech companies are innovating by leaps and bounds, established insurers have more expertise and data, which is critical for the success of AI in insurance applications. They can harness this data to become AI-driven, propelling their business forward. 

Specifically, AI can help life insurers: 

  1. Identify and retain the right customers and keep them happy and engaged.
  2. Offer the most appealing products to each customer profile.
  3. Improve mortality and other actuarial assumptions, even undiagnosed risks.
  4. Accelerate the underwriting process.
  5. Improve distribution effectiveness.

DataRobot can inspect hundreds of medical, demographic, and/or other third-party variables in a few clicks, automatically deriving simple and powerful rules to segment potentially high-risk patients, and identifying those who need further medical assessment. 

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Insurance companies are using machine learning and AI to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from underwriting to marketing in order to make data-driven decisions to lead to increased profitability.