Accessible data platform for dynamic experience study of lifestyle underwriting

We seek to replace or enhance the traditional underwriting approach (namely identification of insureds via a pre-defined fixed set of risk criteria) with one based on a set of dynamic protocols that are responsive to human behavioral factors for continual health improvement. We seek to provide a live and interactive in-market research dataset that can be used to explore the benefit of and improve data-driven approaches (namely artificial intelligence or AI) for immediate use in life & health insurance product development and actuarial risk assessment.

Faculty Supervisor:

Ken Seng Tan

Student:

Fan XIA

Partner:

Besurance Corporation

Discipline:

Computer science

Sector:

Finance, insurance and business

University:

University of Waterloo

Program:

Accelerate

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