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.

Intern: 
Fan XIA
Faculty Supervisor: 
Ken Seng Tan
Project Year: 
2018
Province: 
Ontario
Program: