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Lender Automation and Racial Disparities in Credit Access
Journal of Finance ( IF 7.915 ) Pub Date : 2023-12-11 , DOI: 10.1111/jofi.13303
SABRINA T. HOWELL , THERESA KUCHLER , DAVID SNITKOF , JOHANNES STROEBEL , JUN WONG

Process automation reduces racial disparities in credit access by 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), where private lenders faced no credit risk but decided which firms to serve. Black-owned firms obtained PPP loans primarily 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, preexisting banking relationships, firm performance, or fraud rates.

中文翻译:

贷款人自动化和信贷获取方面的种族差异

流程自动化通过提供小额贷款、扩大银行的地理覆盖范围以及消除决策中的人为偏见来减少信贷获取方面的种族差异。我们在薪资保护计划(PPP)的背景下记录了这些发现,在该计划中,私人贷款机构不面临信用风险,但可以决定为哪些公司提供服务。黑人拥有的公司主要从自动化金融科技贷款机构获得 PPP 贷款,特别是在种族敌意较高的地区。传统银行将贷款处理程序自动化后,向黑人企业提供的 PPP 贷款有所增加。我们的研究结果不能用贷款申请行为、现有银行关系、公司业绩或欺诈率方面的种族差异来完全解释。
更新日期:2023-12-11
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