Auto loan delinquencies extending beyond subprime consumers

February 2, 2017 by Kelly Kent

auto trade data

There has been a lot of discussion around the auto loan market regarding delinquency rates in the past year. It is a topic Experian is asked about frequently from clients in regard to what particular economic market behaviors mean for the overall consumer lending. To understand this issue more clearly, I ran a deeper dive on the data from our Q3 Experian-Oliver Wyman Market Intelligence report. There are some interesting, and perhaps concerning, trends in the data for automotive loans and leases.

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Auto loan delinquency rates are at their highest mark since 2008

The findings indicate that the performance of the most recent loans opened from Q4 2015 are now performing as poorly as the loans from the credit crisis back in 2008. In fact, you have to go back to 2008, and in some cases, 2007, to see loan default rates as poorly as the Q4 2015 auto loans originated in the last year.

Below we have the auto loan vintage performance for loans originated in Q4 of the last 8 years — going back to 2008. The lines on the chart each represent 60 days late or more (60+) delinquency rates over specific time period grades. For these charts, I analyzed the first three, six, and nine months from the loan origination date. As you can see, the rates of delinquency have steadily increased in recent years, with the increase in the Q4 2015 loans opened equaling or even surpassing 2008 levels.

The above chart reflects all credit grades, so one might think that this change is a result of the change in the credit origination mix. By digging a little deeper into the data, we can control for the VantageScore at the loan opening, or origination date, and review performance by looking at two different score segments separately.

Is there concern for Superprime and Prime consumers auto loans?

In the chart immediately below, the same analysis as above has been conducted, but only for trades originated by Superprime and Prime consumers at the time of origination. You can see that although the trend is not as pronounced as when all grades are considered, even these tiers of consumers are showing significant increases in their 60+ days past due (DPD) rates in recent vintages.

Separately, looking at the Subprime and Deep Subprime segments, you can really see the dramatic changes that have occurred in the performance of recent auto vintages. Holding score segments constant, the data indicates a rate of credit deterioration in the Subprime and Deep Subprime segments that we have not observed since at least 2008 — back to when we started tracking this data. What’s concerning here is not only the absolute values of the vintage delinquencies but also the trend, which is moving upward for all three time periods.

Where does the risk fall?

Now that we see the evidence of the deterioration of credit performance across the credit spectrum, one might ask – who is bearing the risk in these recent vintages? Taking a closer look at the chart below, you can see the significant increase in the volumes of loans across lender type, but particularly interesting to me is the increase in 2016 for the Captive Auto lenders and Credit Unions, who are hitting highs in their lending volumes in recent quarters. If the above trend holds and the trajectory continues, this suggests exposure issues for those lenders with higher volumes in recent months.

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Just to be thorough, let’s continue and look at the relative amounts of loans going to the different score segments by each of the lender types. Comparing the lender type and the score segments (below) reveals that finance lenders have a greater than average exposure to the Subprime and Deep Subprime segments.

To summarize, although auto lending has recently been viewed as a segment where loan performance is good, relative to historical levels, I believe, the above data signals a striking change in that perspective. Recent loan performance has weakened to a point where comparing the 2008 vintage with 2015 vintage, one might not be able to distinguish between the two.

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