| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w29840 |
| 来源ID | Working Paper 29840 |
| Invisible Primes: Fintech Lending with Alternative Data | |
| Marco Di Maggio; Dimuthu Ratnadiwakara; Don Carmichael | |
| 发表日期 | 2022-03-14 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 摘要 | We exploit anonymized administrative data provided by a major fintech platform to investigate whether using alternative data to assess borrowers' creditworthiness results in broader credit access. Comparing actual outcomes of the fintech platform’s model to counterfactual outcomes based on a “traditional model” used for regulatory reporting purposes, we find that the latter would result in a 70% higher probability of being rejected and higher interest rates for those approved. The borrowers most positively affected are the “invisible primes”--borrowers with low credit scores and short credit histories, but also a low propensity to default. We show that funding loans to these borrowers leads to better economic outcomes for the borrowers and higher returns for the fintech platform. |
| 主题 | Financial Economics ; Financial Institutions |
| URL | https://www.nber.org/papers/w29840 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/587512 |
| 推荐引用方式 GB/T 7714 | Marco Di Maggio,Dimuthu Ratnadiwakara,Don Carmichael. Invisible Primes: Fintech Lending with Alternative Data. 2022. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w29840.pdf（1409KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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