Correlate the FUND scores with the performance of franchise loans


The pandemic has not only affected small businesses; it turned small business credit markets upside down. It happened so quickly and hit so hard that the government stepped in with federally guaranteed PPP funding, altering the normal credit cycle and making it harder to predict what lenders were likely to do at the start of the crisis. reprise.

The biggest challenge for any lender is uncertainty, and the pandemic has created a heavy dose of it. Among the questions they faced was how a particular franchise system they were lending to was affected and how quickly it would recover. Lending is about making bets over the next 5-10 years of the life of a loan, so it’s really about picking the winners and avoiding the losers after an economic shock. Recognizing that the story hasn’t fully played out yet, let’s see what the updated FUND scores tell us about what could happen to us.

The FUND Score has become the industry standard for credit forecasting franchise system credit. The model analyzes historical factors influencing the ability of franchisees in a system to meet their credit obligations. To ensure that FUND scores continue to predict accurately, FRANdata has continued to test and review the FUND model. Despite the challenges of 2020, the FUND score continued to be strongly correlated with loan success (> 0.6), reinforcing the predictive power of the FUND model.

The performance of franchise loans is influenced by the interplay of customer preferences, the management capacity of the borrower and the performance of the franchisor / franchisee system. Lenders are skilled at assessing the risk implications of customer trends and borrower management. With the FUND Score, lenders can differentiate loan performance expectations based on the comparative credit risk of other franchise systems. FUND categories and FUND scores show the credit risk position of each franchise system relative to all other franchise systems and help inform a lender’s loan performance expectations. FRANdata continued to back-test the scoring model with unit and brand-level loan performance, which remains strongly correlated with loan performance.

To understand this predictability, we compared the year-by-year mark-level performance through the fourth quarter of fiscal 2020 of seasoned SBA loans (loans initiated in fiscal years 2011 to 2017) to the expected loan success rate. by the current scores of the FUND brand. This provided a franchise over a no-franchise foundation, recognizing that all SBA guaranteed loans are, by definition, a high-risk business borrower population.

Over the period under review, including all of 2020, the SBA loan failure rate for franchise loans disbursed in fiscal years 2011, 2012, and 2013 matches the SBA’s non-franchise loan portfolio. . SBA-backed franchise loans created between fiscal 2014 and 2017 overall slightly underperformed the non-franchise portfolio (but not to statistically significant levels).

At the end of the fourth quarter of fiscal 2020, failure rates for SBA loans paid to franchises between fiscal 2014 and 2017 are slightly higher than those for non-franchise SBA loans during the same period, from 13 to 70 basis points. SBA-backed annual loan books, franchised and non-franchised, experience a slightly higher percentage of loan failures than the books from 2011 to 2013 in the same maturity year, no doubt reflecting the less established position in which were the new businesses when the pandemic hit.

This information gave FRANdata a benchmark against which to recalibrate loan performance expectations for lenders based on updated data as the impact of the pandemic begins to manifest.

Before Covid, a FUND score above 800 had a success rate above 95%; however, this success rate fell below 95% during the pandemic. Likewise, all of the FUND’s ranges have been adjusted downward on the basis of the benchmarking analysis. As the positive impact of the PPP program becomes smaller over time, we would expect the upper ends of the bands to tighten again, while the lower FUND scores could continue to decline, reflecting the difficulties that brands that have entered the downturn in weaker positions will have to deal with a greater relative number of underperforming units.

What does it all mean?

First, it means that at this point in the economic recovery, franchise and non-franchise loans have worked roughly the same (and have been influenced by PPP funding as well). Although, based on past business cycles, we believe the performance will eventually show that the franchise business model will perform better. However, it also means that lenders perceive that the management teams of franchise brands with higher FUND scores have been able to adapt more quickly and will be able to focus more on the future, while the teams Managing brands with lower FUND scores will likely be challenged. for a while with internal problems. Differentiated performance will stimulate the interest of lenders.

Chen Wang is a Senior Market Research Analyst and David Swift is Vice President of Data Analytics and Research Development at FRANdata. Darrell Johnson is CEO of FRANdata, an independent research firm providing information and analysis for the franchise industry since 1989. He can be reached at 703-740-4700 or [email protected]


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