Key Findings
FinTech Serves Underserved Areas
FinTech lenders disproportionately provided PPP loans in ZIP codes with fewer bank branches, lower incomes, and larger minority populations
Limited Substitution Effect
Only 27% of decreased traditional bank lending was replaced by FinTech lending, suggesting FinTech expanded rather than redistributed credit access
Higher COVID Response
FinTech lenders were approximately 10x more responsive to areas with severe COVID-19 economic impacts compared to traditional banks
FinTech Lending by Demographics
- Areas with fewer bank branches received 17% of loans from FinTech vs 13% in high-branch areas
- Lower income ZIP codes had 17% FinTech share vs 13% in higher income areas
- Areas with lower white population percentage had 17% FinTech share vs 13% in majority white areas
Traditional vs FinTech COVID-19 Response
- FinTech lenders showed a 4.72 coefficient response to COVID case rates
- Traditional banks showed only a 0.48 coefficient response
- FinTech was approximately 10x more responsive to areas with higher COVID impact
Substitution Between Bank and FinTech Lending
- For every 15 fewer traditional bank PPP loans, FinTech increased by only 4 loans
- Only 27% substitution rate between traditional and FinTech lending
- Suggests FinTech largely expanded rather than redistributed credit access
Contribution and Implications
- First systematic study comparing traditional banks and FinTech lenders in government-backed lending programs
- Demonstrates FinTech's potential to increase financial inclusion in underserved areas
- Supports expanding FinTech participation in government loan programs beyond crisis periods
- Highlights need to balance increased access with appropriate oversight of online lending
Data Sources
- Demographics chart based on Table 3 showing relationship between bank branches, income, demographics and FinTech lending
- COVID response visualization based on Table 2 coefficients comparing traditional and FinTech lending response to COVID-19
- Substitution chart constructed from Table 10 showing effects of predicted bank lending on actual lending volumes