Lifan Wu

Premium anomaly detection in Life Insurance

While pricing and underwriting are core to the insurance industry, it is also critical for insurance companies to keep healthy portfolios in their books for operational risk control and profitability. In this session, we will talk about and compare several statistical and machine learning methodologies that help automatically identify abnormal premium received from clients on a large scale. Such ideas can also be generalized to a broader context, for example, claims.

Lifan Wu is a Data Scientist at Swiss Re, working on building machine learning models and providing data-driven solutions to facilitate underwriting and portfolio management across business lines. Before joining Swiss Re, Lifan completed her Ph.D. study in operations research from Cornell University with her research focusing on extreme value theories. She also finished her M.Eng. in financial engineering at Cornell as well as her B.S. in actuarial science and mathematics at Purdue University.

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