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2018 AUTO LOAN DEFAULT STATISTICS: KEEPING THE REAL HORSEPOWER IN YOUR PORTFOLIO

The defi Team auto loan origination software, defi INSIGHT, News

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Hybrid cars don’t use any gas going downhill, so their drivers often coast as long as possible, increasing their overall mileage. It’s called hypermiling, and it’s a decent metaphor for the S&P/Experian Auto Default Index. The index declined from its 2010 high of 2.74 to the April 2018 value of .99. Viewed on a chart, the drop would look familiar to the hypermiling crowd. The past 4 years have been relatively stable with the auto default index fluctuating between 1.15 and 0.82. An improving economy, attractive buyer incentives, and low-interest rates for prime borrowers have helped sustain the trend.

 

auto loan default statistics

S&P/Experian Auto Default Index, April 2018

 

The Fitch Auto Loan 60+ Delinquency Index for prime borrowers reflects the recent stability of the S&P/Experian Auto Default Index, but the Fitch Auto Loan 60+ Delinquency Index for subprime borrowers has been trending upward since April 2011.  

 

auto loan default statistics

Source: FitchRatings Auto Indices

 

Several factors account for the sustained increase in subprime delinquency rates during the past 7 years. These factors include:

 

  • Ease of obtaining subprime loans even though applicants had poor credit
  • Preference for 72-month loans over 60-month loans to maintain low payments
  • High-interest rates characteristic of subprime loans
  • Overall lender optimism associated with a recovering economy

 

Of course, the media spotlight favors pessimistic news over good news. However, your interpretation of subprime delinquency data trends and their impact on auto loan default statistics depends on several factors. Your current credit policies, combined with the ability to assess current market conditions, continually analyze portfolio performance, and modify credit policies to adjust to market dynamics can help you stay profitable. You need not become a lender who is driving up auto loan default statistics.

Auto Loan Default Statistics: Smooth Road or Uphill Climb?

Over the years most banks have maintained conservative auto lending policies. For banks, the default highway won’t have any sudden bumps. The road ahead and the rearview mirror look the same: They’re both smooth because banks kept a consistent, conservative strategy, favoring prime and better borrowers.

 

Lenders who opted for higher risk in the pursuit of profit should evaluate portfolio performance to see if that risk strategy is delivering the desired results. With the current economic uptick, lenders who focus on the subprime market may be able to loosen credit policies and still maintain an acceptable level of risk.  

 

You want to minimize defaults. You can achieve this in two ways using data and analytics. First, through careful borrower qualifications, using a wider range of applicant data to accurately assess creditworthiness. Second, through identification of borrowers whose profiles and behaviors indicate potential default. These two techniques can help you minimize the impact of auto loan defaults and stay profitable.

 

Alternative Credit Data: Confidence and Opportunity

The digital economy facilitates the collection of consumer data such as employment records, income level, bankruptcies, payments, real estate ownership, and driving records. Several services now acquire, aggregate, and provide this information for lenders as alternative credit data. That helps minimize defaults by providing greater confidence in evaluating applicant credit risk. When combined with traditional credit scores during the evaluation process, alternative credit data provides a more detailed and accurate assessment of applicant creditworthiness, particularly for applicants with subprime scores.

 

 In a market with decreasing auto sales and fewer loan opportunities, alternative credit data can also be used to qualify applicants with little or non-existent credit history, but who are nonetheless creditworthy. Without the use of alternative credit data, lenders are passing up opportunities to grant loans to creditworthy applicants who would otherwise be ignored, based on their lack of a standard credit data profile.

Analytics Identify Potential Defaults

Your loan applications and portfolio have a wealth of information that can be used to continually assess and minimize default exposure. The right analytic tools are key to unlocking this insight.  Analytics can help reduce defaults in two ways: a better applicant qualification process and proactive identification of potential defaults.

 

A certain percentage of your loan portfolio will default. That is an unfortunate fact. Every lender has established an acceptable default rate. However, careful and continued analysis of your portfolio can uncover common or similar attributes or behaviors of borrowers which closely correlate with the likelihood of default.  

 

Once identified, these correlations can then be applied to modify credit policies. During the underwriting process, decision rules could be used to automatically filter out applicants who present an unacceptable degree of risk. Alternatively, decision rules could be used to identify borderline qualifications which are then passed to an experienced underwriter who would evaluate creditworthiness, override policy, and structure a loan to minimize default risk.

 

Analysis and correlations can also be used to loosen credit policies in response to competitive market changes. If default analysis shows stability (or even improvement) over the past year for segments of their portfolio, lenders may want to modify credit policies, granting credit to applicants who previously would have been declined, with the goal of growing the portfolio while maintaining an acceptable risk level.  

 

Analytics can also play a role in predicting potential defaults. Payment delinquency is the first step toward default, but there are usually underlying factors or events that precede the first delinquent payment. Loss of employment, changes of address, or sudden change in income that are monitored by alternative credit data services can provide early warning of potential defaults.  

 

Upon the first late payment, lenders can access alternative credit data to determine if any significant change in a borrower’s status has occurred, e.g., loss of employment, several other late payments, or unexpected change of address. If that’s true, then the lender, complying with local lending regulations, could contact the borrower to head off any problems that might lead to default.

 

To be efficient in proactive identification of potential defaults, lenders need to take advantage of automation. Automation and the decision rules that drive processes let you execute tasks that would be impossible to accomplish manually. Automation lets you monitor late payments, query alternative data sources to determine possible reasons for the delay, notify a servicing agent of the situation, or contact the borrower via phone, email, paper, or text. Without automation, proactive identification of potential defaults would become a burden that detracts from overall lending efficiency.  

 

Deftly Defend Against Defaults

The impact of auto loan default statistics depends upon your ability to analyze portfolio performance and minimize default exposure through better use of data and analytics. Alternative credit data combined with traditional credit scoring provides a more accurate assessment of creditworthiness. It can also be used to identify creditworthy applicants who have little to no credit history, and alert you to changes in borrower status that may eventually lead to defaults.

 

Regular and consistent portfolio analysis, comparing year-over-year performance, can give you insight into the borrower characteristics that correlate with delinquencies and defaults. You can then apply this insight to adjust credit policies with the goal of reducing defaults. Like those hypermiling techniques that help you increase fuel efficiency, data and analytics help you minimize the financial drag that defaults can have on your portfolio. Savvy use of data and analytics can flatten any default bumps and level out any uphill climb you may encounter on the road to profitability.

 

defi SOLUTIONS provides a flexible, completely configurable, loan origination system (LOS) that is quick to implement and provides actionable insights based on actual performance to help lenders compete effectively in today’s market. The defi SOLUTIONS team welcomes the opportunity to discuss your lending needs. Contact our experts online, or schedule a demo to see how we’ve incorporated the latest data and analytics technologies into our LOS to help you reduce risk and positively impact portfolio performance.

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