How Costly are Cultural Biases? Evidence from FinTech
How Costly are Cultural Biases? Evidence from FinTech
复制标题
文化偏见的代价有多大？
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Alberto G. Rossi
中科院分区：
文献类型：
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作者：
Francesco D’Acunto;Pulak Ghosh;R. Jain;Alberto G. Rossi
我们利用领先的金融科技点对点贷款平台与自动机器人建议贷款工具相结合，以测试和量化文化偏见在大赌注风险选择中的影响，其中统计歧视的范围很小。比较出借人做出的选择与机器人咨询工具代表他们做出的选择，我们发现群体内歧视与群体外歧视以及刻板印象歧视都是普遍存在的，而且在经济上是相当可观的。在消费效用方面，歧视使贷款人处境更糟——与受歧视群体的借款人相比，受歧视的贷款人向受优待群体的借款人发放贷款时，违约率要高出32%，贷款回报率要低11%左右。所有这些结果对于居住在文化偏见突出程度较高的地区的贷款人来说都更为明显。
We exploit a leading FinTech peer-to-peer lending platform paired with an automated robo-advising lending tool to test for and quantify the effects of cultural biases in large-stake risky choices for which the scope for statistical discrimination is minimal. Comparing the choices lenders make with those made by the robo-advising tool on their behalf, we find that both in-group vs. out-group discrimination and stereotypical discrimination are pervasive and economically sizable. Discrimination makes lenders worse off in terms of consumption utility—discriminating lenders face 32% higher default rates and about 11% lower returns on the loans they issue to borrowers belonging to favored demographics, relative to borrowers in the discriminated groups. All the results are stronger for lenders who reside in regions where the salience of cultural biases is higher.
DOI：
10.1073/pnas.1818816116
发表时间：
2019-06-11
影响因子：
11.1
作者：
Payne, B. Keith;Vuletich, Heidi A.;Brown-Iannuzzi, Jazmin L.
通讯作者：
Brown-Iannuzzi, Jazmin L.