Linking AI Initiatives to Real-World Outcomes

Use Case

UNDERWRITING ANALYTICS: PREDICTIVE PRICING

 
Client

Large healthcare insurance provider based in Pennsylvania.

Problem

Improve the pricing and customer service for their group insurance members by predicting medical costs. Accurate claim records can positively impact reserve requirements/loss ratio. This leads to premiums that are more reflective of client/member actual experience, than a conservative estimate.

Methodology
  • Combination of Deep Learning based professional service and modularized AI components used according to organization’s cognitive maturity
  • Business transformation with smarter cognitive outcomes
  • Adding industry, business and customer insights to the value chain
  • Seamlessly integrate data across functions
Solution
  • Interacted with actuarial, underwriting and products team during the discovery phase to understand the nature of costs and their current pricing methodology
  • Developed a predictive model which is now helping in predicting costs for a cohort based on various input data parameters
  • Developed a pricing methodology incorporating the cost prediction model into the carrier’s current underwriting process
Benefits:
  • 82% accurate cost prediction and improved pricing accuracy at a personalized level
  • Proactive identification of high risk claimants improved customer satisfaction by focusing efforts into preventive care management
 

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