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How Data and Innovation Are Solving Auto Recall Challenges

In October last year, we hosted our first-ever DRN Virtual Showcase, which brought together experts from across the auto recall industry to discuss how effective and creative use of data and communication can improve auto recall completion rates. Our panelists included:  Angel Preston – Formerly Director, Safety, Alliance for Automotive Innovation Dr. Stephen Ridella – Director, Office of Defects Investigation, National Highway Traffic Safety Administration (NHTSA) Neil Steinkamp – Managing Director, Complex Situations Consultant, STOUT Oscar Nunez – Executive Director of Product & Commercial Markets, DRN Background Since 2000, auto manufacturers have issued 679 million vehicle and equipment recalls.* Typically,

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Blog

Everything is bigger in Texas, even Risk Scoring

One of our most innovative clients is a large, Dallas-Fort Worth, Texas-based subprime lender that began using DRNsights in 2019 as part of their collections and repossession processes. They achieved a significant uptick in overall recovery rates because the DRNsights vehicle location data was being taken into consideration at the

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Lender Roundtable Offers Insights on Lenders’ Use of LPR Data

In October, DRN hosted a golf tournament for lenders at Whistling Straits in Kohler, Wisconsin. The event brought auto lenders together to network, share best practices and learn more about DRN. This year’s event included a roundtable where lenders discussed challenges they’re currently facing as the economy – and our

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How Repwest Succeeds Using LPR Data for U-Haul

As North America’s premier commercial license plate recognition (LPR) data provider, we offer the richest data set and analytics available. For insurers, our extensive database of 18 billion license plate scans – which include addresses and date/timestamp – can play a major role in fraud cases from vehicle location to

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The Evolution of Risk Scoring

The Sooner, the Better: How Risk Scoring Became a Powerful Pre-Repo Tool DRN data has long been used in collections and repossessions to find more vehicles faster. We believed this data could be just as powerful for lenders as they scored loans and considered when to assign a vehicle for

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