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Case study

The challenge

A global reinsurance company needed help developing a data-driven information management solution that could determine the best cases for underwriting and assist underwriters in assessing case files to decide which cases must be underwritten. The company asked Cognizant to help build an intelligent underwriting tool, driven by artificial intelligence (AI), to aid the underwriting process and boost efficiency while predicting and prioritizing the cases that should and should not be accepted.

Our approach

We helped the company build an intelligent underwriting tool—Life & Health Underwriting Document Analytics (LUDA)—that summarizes case files for easy review, assesses the cases and makes recommendations to the underwriters. Using optical character recognition and image processing, complex and varied stacks of documents are read and assembled as a single, consistently formatted document. We used natural language processing to aid organizing and extracting data from the source documents, and AI-based machine learning to make sense of the data and assign scores to the most promising cases.

Underwriting made more efficient and productive

The number of cases rejected is expected to drop from the company’s current rate of 40% as LUDA makes the underwriting process faster and more precise. This will enable the re-insurer to take on more customers. As the number of accepted cases goes up, the underwriting time is expected to go down significantly. This, in turn, is expected to boost revenues.


underwriting efficiency


total underwriting time


case acceptance percentage and revenue