Established in 1913, Jewelers Mutual Insurance Company, SI (JM) insures jewelry businesses and personal jewelry owners throughout the United States and Canada. As a mutual insurer focused on the best interests of its policyholder members, JM has an obligation to ensure it carefully evaluates the accuracy of all information that it receives concerning new business applications and claims. Deliberate submission of false information is unusual, but it does happen and is something JM needs to be vigilant against. To help prevent losses owing to the submission of false or deceptive information, JM is pursuing the idea of building lightweight, interpretable machine learning models to identify potentially deceptive information. Project participants will leverage cutting-edge research from the field of interpretable machine learning in their work.
Project Leads: Emily Wenger, Chris Hardin, Emet Gordon and Abhishek Patel, ECE
