Applicability of Large Corporate Credit Models to Small Business Risk Assessment
This addresses the problem of unmet financing needs for small businesses in the US, but the abstract suggests it is an incremental approach by applying existing methods to a new domain.
The paper tackled the problem of assessing credit risk for small businesses, which lack publicly available data and analyst coverage, by exploring the applicability of deep learning-based large corporate credit models to small business credit rating, but no concrete results or numbers are provided.
There is a massive underserved market for small business lending in the US with the Federal Reserve estimating over \$650B in unmet annual financing needs. Assessing the credit risk of a small business is key to making good decisions whether to lend and at what terms. Large corporations have a well-established credit assessment ecosystem, but small businesses suffer from limited publicly available data and few (if any) credit analysts who cover them closely. We explore the applicability of (DL-based) large corporate credit risk models to small business credit rating.