Notre Dame researchers develop 'FraudBuster' system to reduce fraud in auto insurance market | News | Notre Dame News | University of Notre Dame Skip To Content Skip To Navigation Skip To Search University of Notre Dame Notre Dame News Experts ND in the News Subscribe About Us Home Contact Search Menu Home › News › Notre Dame researchers develop 'FraudBuster' system to reduce fraud in auto insurance market Notre Dame researchers develop 'FraudBuster' system to reduce fraud in auto insurance market Published: June 25, 2018 Author: Brandi Klingerman Nitesh Chawla In 2012, fraud cost U.S. auto insurers 7.7 billion dollars in excess payments. Although the rate of fraudulent policies for most insurers was 5 percent, that rate for nonstandard auto insurers – or insurers that underwrite drivers with multiple accidents, prior convictions and state minimum coverage – was significantly higher at 84 percent. Unfortunately, this cost is often passed down to policyholders in the form of increased insurance premiums. To better control these costs, University of Notre Dame researchers at the Interdisciplinary Center for Network Science and Applications (iCeNSA) have developed artificial intelligence algorithms and a system that identifies potential fraudulent risks. The study, which was published in Big Data, focused on creating a framework dubbed “FraudBuster,” which combats the following challenges: identifying the worst affected segments of the auto insurance market, identifying “actionable” fraud and ensuring compliance with the industry regulations.  “Our goal with this research was to create an operationally viable AI system that could identify which population segments were demonstrably more affected by auto insurance fraud by using machine learning techniques,” said Nitesh V. Chawla, Frank M. Freimann Professor of Computer Science and Engineering, director of iCeNSA and co-author of the study. “The FraudBuster system is able to not only accomplish this but also demonstrates a framework for compliance with industry regulations while accurately assessing bad risks at the underwriting stage.” To create the system, the research team utilized de-identified data from more than one million drivers and then characterized that information with 44 different descriptors. The data descriptors represented both underwriting and claims information. Through a rigorous modeling and evaluation approach, the team demonstrated that FraudBuster can identify drivers who are likely to be fraudulent risks and are associated with high loss ratios, resulting in an operationally viable and compliant system to identify the segments that are most affected by fraud. “The approach used in this study could also be adapted to predict and assess the significantly bad risks of other markets including those within the credit, lending, health care and marketing industries,” said Chawla. Collaborators on the study include Reid A. Johnson, former research assistant professor of computer science and engineering and data scientist at Concur Technologies, and Saurabh Nagrecha, former graduate student of computer science and engineering at the University of Notre Dame, lead author of the study and machine learning researcher for Capital One.  To learn more about the study, visit https://www.liebertpub.com/doi/abs/10.1089/big.2017.0083?journalCode=big.  Contact: Brandi R. Klingerman, research communications specialist, Notre Dame Research, bklinger@nd.edu, 574-631-8183; @UNDResearch Originally published by Brandi Klingerman at research.nd.edu on June 22. Posted In: Research Home Experts ND in the News Subscribe About Us Related October 05, 2022 Astrophysicists find evidence for the presence of the first stars October 04, 2022 NIH awards $4 million grant to psychologists researching suicide prevention September 29, 2022 Notre Dame, Ukrainian Catholic University launch three new research grants September 27, 2022 Notre Dame, Trinity College Dublin engineers join to advance novel treatment for cystic fibrosis September 22, 2022 Climate-prepared countries are losing ground, latest ND-GAIN index shows For the Media Contact Office of Public Affairs and Communications Notre Dame News 500 Grace Hall Notre Dame, IN 46556 USA Facebook Twitter Instagram YouTube Pinterest © 2022 University of Notre Dame Search Mobile App News Events Visit Accessibility Facebook Twitter Instagram YouTube LinkedIn