A new urban insurance underwriting methodology that uses what its creators say are sophisticated data mining technology and new sources of information beyond traditional credit scores may help insurers better analyze risk in urban areas, according to the Urban Insurance Partners Institute, a nonprofit organization dedicated to helping insurers succeed in urban markets.
The new platform will be presented at the fifth national UIPI Urban Insurance Advantage workshop Sept. 13 by Pattern Recognition Systems, a national database consulting and modeling firm, and RW Ventures, an urban marketing consulting company.
“Urban markets present unique challenges for even the best underwriting models,” according to Robert Weissbourd, president of RW Ventures. “The use of credit has proven to be a highly effective underwriting tool. Alternative data can help refine market segments which more frequently
have thin or no credit files.”
Advanced data mining technology, combined with nontraditional sources of data, can be an effective approach in addressing instances where standard underwriting tools are also challenged by the fact that the urban population is more diverse than traditional suburban markets, according to Canh Tran, president of Pattern Recognition Systems.
The new platform applies a more sophisticated segmentation analysis to millions of records in a way that allows PRS to recognize patterns, categorize, and profile a wider array of risk, thereby increasing underwriting accuracy, according to Tran.
PRS said it also enhances the data analysis by including credit information from a wide array of sources, including nontraditional sources, that help fill in credit information gaps. Tran believes the technology-based platform will offer insurers a safer way to enter additional markets and write more personal lines and small commercial business.
UIPI is working with PRS and RW Ventures to conduct a proof of concept test on the new method. Once funding is obtained, UIPI supporters would be eligible to participate in the test, thereby learning firsthand how the new methodology works against their current system.
Gwendolyn Jones, UIPI chairman, and director of emerging market development at American Family Insurance, said UIPI therefore looks forward to learning more about this new approach.
Others are also looking to learn about the tool.
“The (proof of concept) proposal is exciting because it has the potential to improve the process of ‘competitive risk classification’ in ways that will benefit both insurers and residents of underserved urban markets,” notes Robert Detlefsen, public policy director for the National Association of Mutual Insurance Companies (NAMIC).
“Farmers is always looking for any new tool or resource that can help it better serve the urban market,” added Illinois Farmers Insurance Company President Bill Matlock. “If this new approach helps companies better evaluate risk, it will further improve competition in urban markets.”
To market its products effectively, an insurer must utilize a risk classification system that will allow the company to offer insurance to as many potential customers as possible, emphasizes NAMIC’s Detlefsen. “Increased market penetration provides economies of scale, and competitive risk classification therefore serves to increase the availability of insurance, even for high-risk individuals. Insurers can also benefit, because an insurer that discovers and adopts a superior underwriting method will outperform other insurers,” he said.
Pattern Recognition Systems, which specializes in forecasting and segmentation models, has developed systems for finance, credit card, and insurance companies that reduce fraud, manage risk, and predict consumer behavior that have become industry standards.
The Urban Insurance Partners Institute is the only insurance industry organization dedicated solely to urban affairs.
For more information on UIPI programs or the Urban Insurance Advantage workshop see www.uipi.org.
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