Though it has become the industry standard for solar financing, using FICO scores for calculating the risk of solar loans/leases remains imperfect. FICO scores calculate credit risk, but includes too much extraneous data that are unlikely to accurately determine the ability of the customer to pay electricity bills on time (ie. FICO includes data such as the length of credit history and the number of credit lines, while ignoring data such as monthly utility payments).
The limitations of using FICO scores are evident in the data. The three largest US solar companies, Sunrun, Vivint, and SolarCity, have average customer FICO Scores of 732, 747, and 761, respectively. Mosaic, the largest solar loan company, has an average customer FICO score of 747. And yet, despite these high FICO cutoffs, solar companies face annual default rates of 0.5-0.8% for their 20 year contracts, which amount to about a 10-20% lifetime default rate. However, credit scores continue to limit the number of households that solar companies will serve, even for households with no history of missing electricity payments.
Additionally, the use of FICO scores has increased customer acquisition costs. Because every solar company competes for the same fraction of customers who qualifies for solar loans, every company must outspend their competitors on marketing to increase sales. As a result, the cost of user acquisition has increased by 27% in the last 3 years, even while the cost of solar has decreased by 60%, and soft costs now account for 68% of solar installation costs. Using FICO scores to determine loan reliability is a missed opportunity for the solar industry, given that the National Renewable Energy Lab reports that 60% of the US solar potential exists on low-to-medium-income households.
Solar investors need a methodology (1) to better calculate the risk of high credit customers, and (2) to better reach lower-credit and non-credited customers. This would create enormous value for the solar industry, by decreasing the amount of money lost from defaulted loans/leases, and by decreasing the ever increasing customer acquisition cost.