The demand for vehicles has been strong post-recession, and lender portfolios have grown, helping to serve the demand for consumers in financing vehicles. The total outstanding auto loan volume has grown to nearly $1.2 billion. After the recession, lenders began to offer more subprime and deep subprime loans as delinquency rates remained low, supported by strength in the used vehicle valuations.
After sustained strength in used vehicles, we are now starting to see signs of weakness developing, resulting in higher depreciation rates. In the last 12 months (Oct ’18 through Oct ’19), two-to-six-year old vehicles experienced a depreciation rate of 13.9%, more than two percentage points higher than the same period a year ago. As vehicles depreciate faster, the collateral risk increases. Non-prime lenders are particularly exposed to higher risk in this environment. Taking steps to managing increasing risk is important.
Understand which vehicles are depreciating faster
Understanding projected depreciation rates using residual values is key to analyzing the risk of higher loan terms. Accurate collateral valuations and residual projections, combined with advanced analytics, can help lenders determine how to balance their portfolios. Collateral data can help bring the right decision into focus. Data can help determine the loan-to-value ratio during origination, historical depreciation patterns and the projected residual forecast based on the desired time frame for the loan term. Knowing which vehicles are depreciating faster and, thus, exposed to more risk can help a lender fine tune loan term strategy. The risk is lower to go extended term on a vehicle that is depreciating at a lower rate. Understanding the latest trends and projections can provide an edge over the competition.
Know when a loan reaches positive equity
The loan terms have continued to go up. In an environment where used vehicle values are stable, the risk may be manageable. However, when underlying collateral values drop faster, the risk is magnified. Consider the following examples:
• A 60-month loan with 120 LTV, 10% APR, and 15% collateral depreciation takes 28 months to reach positive equity.
• An 84-month loan with 120 LTV, 10% APR, and 15% collateral depreciation takes 54 months to reach positive equity.
• An 84-month loan with 120 LTV, 10% APR, and 20% collateral depreciation takes 64 months to reach positive equity.
In the above example, it takes 10 more months for a long-term loan to reach positive equity when collateral depreciation increases from 15 to 20 percent.
Many lenders seek the opportunity to increase their market share via increasing loan terms to keep the monthly payment low. Loan terms need to be optimized at an account level to help improve profitability while limiting additional risk.
Precise data is critical to detect powerbooking
The content and trims on vehicles have become more complex. The valuations of vehicles can have a wide range depending on those variables. For example, a 2018 Ford F150 XL is currently valued at $28,500 versus a 2018 Ford F150 King Ranch is valued at $43,000. Adding certain optional equipment to the vehicle could further increase the value on the King Ranch to $47,000. That’s a difference of $18,500 in collateral, but 10-digit VIN decoders will not be able to decode the correct trim in this example.
If a lender does not verify the collateral, the risk could be huge on some transactions with more loan extended on a collateral that is worth much less. With advanced analytics solutions available, a full 17-digit VIN can now provide a precise valuation for a vehicle.
Furthermore, the Vehicle History Report information can have a substantial impact on vehicle value. In some cases, a frame-damaged vehicle could be $10,000 to $20,000 lower in value. Using a precise value that automatically adjusts for all the positive and negative events in a vehicle’s history has become critical.
In changing conditions, it is even more important to manage risk in the portfolio to remain competitive and maximize profit potential. Having access to precise data enables lenders to perform analytics at an account level as well as understanding portfolio segments where they should take on more or less risk.