数字次贷:追踪信用追踪者

J. Deville
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引用次数: 6

摘要

本章介绍了一种我称之为“数字次贷”的现象。数字次贷代表了贷款机构寻求预测能力的前沿,涉及越来越多的科技初创企业,它们正在进入不同国家的次贷、发薪日贷款市场,并以高利率向通常信用记录较差或没有信用记录的借款人放贷。在这种消费信贷贷款的变体中,通过算法分析的形式处理各种形式的数据,试图更好地预测个人的还款行为。这些数据通常看起来非常普通,与手头的信贷产品几乎没有关系。本章试图描绘出各种形式的数据所代表的可能性的地形,这些数据可以提供给贷款人,一部分是作为未来研究的基础,一部分是为了突出当前和未来货币本体论的关键发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital subprime: tracking the credit trackers
This chapter introduces a phenomenon I call ‘digital subprime’. Digital subprime represents a frontier in lenders’ quest for predictive power, involving a growing group of technology startups who are entering subprime, payday lending markets in various countries and are lending at high rates of interest to borrowers who often have either poor or not credit histories. In this variant of consumer credit lending, diverse forms of data are processed through forms of algorithmic analysis in the attempt to better predict the repayment behaviour of individuals. This data often appears extremely mundane and to have very little to do with the credit product in hand. The chapter seeks to map the terrain of possibility represented by the diverse forms of data that are rendered accessible to lenders, partly as a basis for future research, and partly to highlight key developments in the present and future ontologies of money.
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