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Dealer Ops

Managing Risk In A High Risk Environment

Sub prime auto finance has evolved substantially since its emergence in the late eighties and early nineties. Over the last 15 years, the sub prime landscape has been littered with the business failures and exits of numerous financial institutions that were eager to participate in the attractive yields associated with the industry. While most were aware of the higher risks, history has clearly indicated that few were actually prepared to deal with these risks. Obviously, business failure in and of itself is not good for any industry. However, it’s safe to say that the lessons learned during this evolutionary cycle have created a more stable and disciplined sub prime environment.

Consequently, the financial institutions that survived are spending a great deal of time focused on understanding, identifying and tracking risk. While there are several types of risk that must be managed, there are two that relate more specifically to the relationship between dealers and the financial institutions who purchase their contracts; credit risk and fraud risk.

Credit Risk

Although the sub prime auto finance industry is relatively young, the number of companies that have either failed or exited is staggering. Most of these business failures or exits can be traced to an inability to properly manage credit risk. At the most basic level, credit risk is the risk that an account will result in repossession (probability of default) as well as the risk associated with how severe the individual loss will be (loss per unit). While factors such as growth, yield and operating expenses are all contributors to profitability for finance companies, losses associated with credit risk, by far, have the largest impact on absolute and relative profitability.

While judgmental lending is critical in the sub prime credit underwriting process, history has proven that judgment alone can not measure sub prime credit risk with the precision necessary to ensure the long term viability of a financial institution. Based on this reality, the use of empirically derived and statistically valid scoring models has proliferated rapidly in the sub prime auto space.

Contrary to popular belief, scoring is not always just about reducing credit risk for a financial institution. Scoring also positions companies to purchase more business. While it’s true that at some score threshold credit risk becomes excessive and approval rates drop dramatically, it’s equally true that on applicants who score above this threshold approval rates may increase substantially.

Over time financial institutions back test their performance against these scores to validate the credit risk associated with different score levels. By doing this, they position themselves for increased approval rates and greater confidence in the underwriting process in general.

While credit scoring is a critical tool in assessing credit risk, underwriter judgment is equally important. Because credit scores typically measure a limited number of primarily bureau-based attributes on an applicant, judgment is necessary in assessing the credit risk associated with elements not being measured by the scorecard. Confirming an applicant’s capacity to repay the proposed debt as well as loan-to-value on the proposed collateral are important elements that require the expertise of the underwriter.

Additionally, credit underwriters investigate Social Security Number authenticity, check out bureau-based fraud alerts, verify income and make sure the deal is within established guidelines and policies. Due to the fact that a credit score is only as good as the input that goes into the score, one of the most critical elements of judgment has to do with ensuring that the deal makes sense in general. One of the more common examples of this would be for the underwriter to ensure the applicant was not a “straw purchaser” (individual signing contract while unknown third party drives vehicle and services debt).

Fraud Risk

At its most fundamental level, fraud is defined as deception or an act committed with the intent to deceive. There are several types of fraud. The following are examples of a few of the more common types of fraud dealers and financial institutions should be aware of:

Application Fraud

o Falsification of employment

o Falsification of income

o Falsification of residential status

Collateral Fraud

o Falsification of vehicle equipment or trim level

Borrower Identity Fraud

o Straw buyer misrepresentation

o Identity theft

o Social Security Number misrepresentation

While some of these types of fraud are often perpetrated by the consumer seeking financing, it’s important for dealers to understand that they are ultimately responsible for ensuring that the application information on the prospective applicant as well as the equipment trim level on the proposed collateral is disclosed accurately to the financial institution purchasing the contract. Dealer operating agreements typically address this issue specifically under the “Representations and Warranties” section.

Financial institutions are spending more and more time trying to isolate and track these and other types of fraud. The primary reason for the increased focus has to do with the fact that fraud is on the rise. Last year alone approximately 10 million people were victims of identity theft. As a result of this increase, it’s becoming a larger contributor to losses across the industry. One staggering industry statistic suggests that nearly 40 percent of all financial institution losses are the result of some type of loan fraud. Based on these trends, underwriters are working more diligently than ever to identify fraud.

Overall, assessing credit risk and fraud risk is an extremely important endeavor for both dealers and the companies purchasing their contracts. Ultimately, both will benefit from improvements in the process. Lower credit and fraud losses could very well contribute to more favorable pricing in the form of either lower interest rates and/or discounts. Additionally, the industry in general will benefit from the more stable environment.

Vol 2, Issue 10