Experian’s Data Network Aims to Help Us Automotive Lenders Fight Fraud

The Hunter Automotive Fraud Alliance empowers participants to share fraud intelligence for real-time fraud detection

With rising vehicle prices and the automotive industry relying more heavily on digital retailing, lenders are experiencing an uptick in fraudulent loan applications. As a result, Experian  introduced the Hunter Automotive Fraud Alliance, a collaborative data network designed to help automotive lenders in the United States share real-time fraud intelligence to minimize fraud risk, while maintaining a positive customer experience.

The Hunter Automotive Fraud Alliance builds on the company’s recent announcement of a fintech-focused version of Experian’s Hunter in the U.S., as well as the data network’s 30-year track record of success across the globe. Hunter is used by more than 360 organizations in 17 countries across a variety of vertical markets. In the automotive industry, Hunter is used by organizations in five countries, saving $684 million in potential fraud losses annually.

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“As fraudsters become increasingly sophisticated, it’s imperative for automotive lenders to work with trusted partners and leverage the latest technology to stay ahead of bad actors,” said John Gray, president of Experian Automotive in North America. “We have long been committed to helping businesses anticipate future fraud risks and verify consumers’ identities. The Hunter Automotive Fraud Alliance harnesses the power of advanced data and analytics and empowers automotive lenders to share fraud intelligence to identify suspicious activity, mitigate fraud losses and protect their customers.”

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How it works

Automotive lenders participating in the Hunter Automotive Fraud Alliance contribute historical data, including previously suspected and known fraud applications, to provide member organizations visibility into potential fraud risk. New loan applications are cross-referenced with multiple internal and external data sources, as well as the shared fraud database, to identify data anomalies and other signs of suspicious activity. Hunter calculates a fraud score to indicate the level of risk associated with each application, empowering lenders to make more informed lending decisions.

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The network includes integrated workflow tools that facilitate lenders’ deeper examination of suspected fraud. Additionally, a unique capability is the machine learning automated portfolio review of previous transactions which are continuously rescored for fraud indicators.

On average, clients see a 35% uplift in fraud detection when participating in a Hunter network. It also greatly reduces “false positives,” which improves the customer experience by providing a more streamlined application process.

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