Working Paper: NBER ID: w29364
Authors: Sabrina T. Howell; Theresa Kuchler; David Snitkof; Johannes Stroebel; Jun Wong
Abstract: Process automation reduces racial disparities in credit access through enabling smaller loans, broadening banks’ geographic reach, and removing human biases from decision-making. We document these findings in the context of the Paycheck Protection Program (PPP), a setting where private lenders faced no credit risk but decided which firms to serve. Black-owned firms primarily obtained PPP loans from automated fintech lenders, especially in areas with high racial animus. After traditional banks automated their loan processing procedures, their PPP lending to Black-owned firms increased. Our findings cannot be fully explained by racial differences in loan application behaviors, pre-existing banking relationships, firm performance, or fraud rates.
Keywords: credit access; racial disparities; process automation; fintech lenders; Paycheck Protection Program
JEL Codes: G21; G23; G28; G41; J15
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| process automation (L23) | increase in the share of PPP loans extended to black-owned businesses (H81) |
| automation allows lenders to make smaller loans (G21) | increase in access for black-owned businesses (N87) |
| automation broadens geographic reach (L81) | increase in access for black-owned businesses (N87) |
| automation removes human biases from decision-making (D91) | increase in access for black-owned businesses (N87) |
| lenders with automated systems (G21) | more likely to extend loans to minority-owned firms (J15) |
| traditional banks automating their processes (G21) | increased lending to black-owned firms (G21) |
| fintech lenders (G21) | disproportionate share of loans to black-owned businesses (G21) |