NOW’S THE BEST TIME TO GIVE YOUR PORTFOLIO AN MRI!

B Y KENNETH B. SHILSON , CPA

FOUNDER / PRESIDENT – SUBPRIMEANALYTICS

 

BHPH dealers began this year with considerable optimism. Customer demand for affordable used vehicles was high, interest rates were low, employment was strong and reduced subprime competition were all the reasons for this optimism! Unfortunately, along came the COVID-19 Pandemic in March which spoiled the promising start to the new year.

 

With that history in the rear-view mirror, what should operators do to emerge successfully from the Pandemic disaster? The best answer: “look under the hood of your portfolio now” so you don’t repeat your bad debt losses tomorrow.

 

Availability of the capital needed to regain market share will likely constrain future growth for several months. Therefore, operators must generate more internal cash flow and “make more from less”. This means giving your portfolio a thorough MRI to identify what is working best and what isn’t working at all! Simply, operators must learn from their past losses instead of repeating them. Future success will be determined by “keeping them sold” and customers paying. Cash and cash flow will provide “the gas” which fuels your operations.

 

In these circumstances, operators are encouraged to perform a “deep dive” review of their subprime portfolio (in essence, a financial MRI) which should include the following analysis:

 

1. Static pool and loss/liquidation (the inverse of CRR) calculations which compute performance statistics tied to the periods of origination. This allows operators to determine whether losses are increasing or decreasing and to identify important trends. In addition, it is also important to compare the pace of losses between different periods of each year. If you are not familiar with these metrics, visit the videos on the home page of my website at www.subanalytics.com for a brief tutorial.

 

2. Loss rate analysis should also include gross loss (before recoveries), net loss (after recoveries) and default rate calculations which correlate to their dates of origination. In this type of analysis, the entire portfolio is segregated by origination (usually monthly) intervals so that loss trends can be identified and compared. When your loss metrics are compared with your regional and national peers from our $24 billion database, it puts your own performance in perspective.

 

3. Recovery rates must be calculated to ascertain whether yields on repos and other recovery techniques are working successfully. Improving recovery rates will help mitigate net losses even when default rates remain the same or increase. Operators must maximize their recovery proceeds in the current environment. This starts by identifying what your average recovery rates are currently.

 

1.     A comparison should be made of bad debt losses with deals that performed to identify underwriting differences and areas where future underwriting, collateral or business model changes are needed. This comparison should focus on all your business model elements such as the vehicle cost, sales price, markup, down payment, payment amount, loan term and all the other components of each deal.

There are only three (3) key elements to every buy here, pay here deal: 1.) the customer, 2.) the vehicle, and 3.) the deal structure. However, all three elements are vitally important to repayment success or failure. In order to maximize profits and cash flow, operators must avoid trial and error mistakes. Such mistakes cost millions of dollars in losses! Alternatively, use portfolio analysis to validate the most successful underwriting strategy before additional bad debt losses are incurred.

 

Some operators believe that credit scoring systems are the key to successful underwriting. However, credit scoring only assures consistency and not that the current credit decisions will be successful. Only when credit scores are directly correlated to portfolio loss statistics can the results be accurately validated. Individual portfolios perform differently and custom credit scoring models are needed to produce predictable results based upon your own market data and business model. This requires a detailed analysis of your existing portfolio performance to identify the important customer attributes to include in the scorecard.

 

Computerized analysis prepared from a data extract provided by your software provider is the most efficient and cost-effective way to perform all the above referenced analysis. The use of data mining technology enables the analysis to be done without requiring any input or data entry by your personnel. The cost is minimal and the resultant reduction in losses and increased customer repayments directly improves cash flow and profitability!

 

In summary, compiling bad debt losses should be the start of portfolio analysis, not the end! Without a “deeper dive” to identify the causes, underwriting mistakes will likely be repeated and the future will be no better than the past. Those who do not identify and learn from their past mistakes are destined to repeat them.