Case Study: Global Reinsurance Company achieves improved underwriting efficiency and increased revenue with Cognizant

Data Helps Define the World of Risk Insurance

A global reinsurance company engaged Cognizant Digital Business to improve underwriting across its portfolio, particularly for automobile programs. The challenge was to move beyond broad actuarial segmentation—age, gender, income—and develop timely, individual-level insight to more accurately price transferred risk and improve underwriting decisions.

Cognizant created a data science center of excellence and piloted a solution combining big-data analytics, geospatial and demographic data, the reinsurer’s internal data, and deep learning (R, Python, Keras/Theano) to produce individual driver risk scores integrated into underwriting models. In a six-month R&D phase the approach reduced underwriting time, improved efficiency, increased case acceptance and revenue, and delivered a more accurate, scalable model for managing risk across more than one million policies.