Jeff Chandler

July 26, 2018

Pole Position- It’s not just an 80’s game.

In early 2006, I received the chance of a lifetime. I was given the opportunity to participate in a 3-day racing course hosted by Panoz Racing School (now Skip Barber) at Sebring International Raceway. It was a seventeen-turn road course measuring 3.74 miles in length with long straights, several high-speed corners, and very technical slower corners. I was able to do about 50 laps, which for an adrenaline junkie like myself, was amazing. Even with all of that excitement, my most vivid memory from the experience was not an enjoyable one. On the final day, I was to be in the pole position coming out of the pit which was quite an honor considering that there were 15 other students in the class. All eyes were on me as the anticipation built, my elation quickly turned to nervousness and when I shifted the car into first gear…I stalled out.

This continued several more times while my fellow students sat idling behind me, waiting to get out onto the track and race. Eventually I sat there while I watched them all pass me. I opened the day as the leader and ended up taking a back seat. Things can change very quickly when you stall out. This not only pertains to the racetrack but also in auto lending.

The credit models that got you this far may not perform as expected.

The Seasonally Adjusted Annualized Rate (SAAR) shows vehicle sales continuing to hover around the 17 million mark. This means many opportunities for financing of these vehicles. As an established auto lender in key markets, you have come to rely on preferred data sets and models to assess consumer credit risk for vehicle loans. Those models perform well, you’re growing a healthy book of business and you’re revving up to expand into new regions. Nevertheless, it may not be as easy as you thought: the view is hazy, and your visibility of credit risk is obscured. There may be significant segments of the local population—i.e., Millennials, immigrants—that are off your radar, because like millions of other consumers, they have no credit history. Being the newcomer in a region, especially when it comes to indirect lending, means you don’t have strong established relationships with dealers—potentially subjecting you to adverse selection. You find yourself in unknown territory, with limited data coverage, unexpected regional variances and a model that does not map to clear decisions.

One lender went down that road. Here’s what happened.

After several years of focusing primarily on a single state—aided by a custom data model built for that market—this lender decided to capitalize on new opportunities in other regions. However, as they began to branch out, they immediately saw noticeable differences in the way their model performed in these new territories: their “bad rate” was 1.5 times higher than their “home” state, and in some scoring bands, it was 1.7 times higher.

The reason for the differential? The lender’s custom model heavily weighted one relevant attribute specific to the original market. However, that attribute happened to be less relevant in the new regions.

Cover More Ground in Auto Lending eBook | LexisNexis Risk SolutionsRead more in our latest eBook, Cover More Ground in Auto Lending, to see what happened when they updated their data models to address local variances.

What does this mean to you?

You know you have to update your data models. But it’s not just about adding more data. You need the right kind of data. The truth is, by specifying data models to significant attributes in distinct geographic areas, you will significantly enhance the predictiveness of the data. LexisNexis® Risk Solutions RiskView™ can help you address these regional challenges. RiskView™ uses a variety of different types of information—details not typically found on a credit report—to provide more comprehensive insight into how a consumer might manage new contracts or financial products. Check out this white paper for more information on how to effectively model with blended trade line and alternative data: Modeling Blended Alternative and Traditional Data.

Take a page from our manual.

LexisNexis® Risk Solutions has perfected credit risk analysis for the consumer lending industry. Our capabilities are unmatched, allowing you to uncover predictive information for lending decisions on 95% of U.S. consumers and more than 80% of credit bureau unscorables.

RiskView™ puts you in pole position—enabling you to respond quickly and competitively; approve more applications; and establish your business as “the” lending partner that can fuel dealership growth. Finish the race strong and gain traction in any market.

I always like to get feedback from my peers and colleagues around trends they are seeing in the industry or thoughts about what I am writing. Please post a comment or you can email me at