Working Paper: NBER ID: w30160
Authors: Lei Liu; Guangli Lu; Wei Xiong
Abstract: By comparing uncollateralized business loans made by a big tech lending program with conventional bank loans, we find that big tech loans tend to be smaller and have higher interest rates and that borrowers of big tech loans tend to repay far before maturity and borrow more frequently. These patterns remain for borrowers with access to bank credit. Our findings highlight the big tech lender’s roles in serving borrowers’ short-term liquidity rather than their long-term financing needs. Through this model, big tech lending facilitates credit to borrowers underserved by banks without experiencing more-severe adverse selection or incurring greater risks than banks (even during the COVID-19 crisis).
Keywords: Big Tech; Lending; Financial Inclusion; Credit Risk
JEL Codes: G23
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| big tech loans (H81) | repayment speed (G51) |
| big tech loans (H81) | repayment risk (F34) |
| bank loans (G21) | repayment risk (F34) |
| prior loans from big tech (G21) | delinquency rate (G33) |
| big tech loans (H81) | advantageous selection (C52) |
| big tech loans (H81) | no greater risks than traditional loans (G21) |
| big tech loans (H81) | higher interest rates (E43) |