Accelerated Underwriting Process for a Fortune 500 Life Insurance Company

Business Objective

Our Client, one of the largest life insurance companies in the US, wanted to develop a straight through processing (STP) framework for the accelerated underwriting (UW) of life insurance policies. The framework was to use a predictive model-based approach leveraging only fluid-less, examination-less, and non-APS (Attending Physician Statement) evidence data

Challenges

Interpreting diverse evidence sources like application data, Motor Vehicle Records (MVR), Medical Information Bureau (MIB), prescription data, diagnosis data, etc. and understanding how and where they can be used
Balancing data-driven insights with domain experience-driven decisions from underwriters
Ensuring the models are interpretable with clear reasoning for the final decision, given UW risk class assignment is a regulated decision for adverse cases

Solution Methodology

Developed a 2-step predictive model framework to process incoming applications using fluid-less, non-APS evidence data:
- Decline triage model: Classifies all applications into 3 groups – high mortality risk (automated decline), low mortality risk (automated approval and risk class assignment), and medium mortality risk (sent for manual UW assessment using additional evidence data)
- Risk class model: Classifies all the low mortality risk applications into the right risk classes
Leveraged advanced boosting techniques for both decline triage model and risk class model
Overlaid the models with a knock-out rules framework to capture rare mortality events
Created an Adverse Reasoning Framework to provide top contributing reasons for decline and adverse risk class decisions

Business Impact

The new AI-driven accelerated underwriting workflow estimated to save ~39% of evidence costs with ~40% STP and
less than 4% decline leakage into the STP approved cases
- Decline triage model showed 86% accuracy for all non-APS ordered policies
- Risk class models showed 30% reduced mortality load compared to previous model

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Accelerated Underwriting Process for a Fortune 500 Life Insurance Company

Business Objective

Challenges

Solution Methodology

Business Impact

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