Doctoral Dissertation Research: Financial Technologies, New Financial Markets, and Socio-Economic Life

信用局和评分机构发挥了积极的作用，在令人印象深刻的增长，消费信贷在美国的世纪之交。像Equifax（美国历史最悠久的信用局）或FICO（最广泛使用的消费者信用评分提供商）这样的公司已经成功地汇编了大量的消费者历史，并将其转换为标准化和客观的三位数数字，用于预测一个人的信誉。这些公司在美国境外发展，并扩展到拉丁美洲，在那里他们实施了类似的方法。然而，在一个几乎有一半人口无法利用正规银行网络的区域，它们在获取和完善消费者信息方面没有那么有效。此外，本地或区域金融技术（fintech）公司更好地捕捉了这一半，这些公司在人工智能（AI）的帮助下，通过使用和复杂的其他信息来源，成功地向没有强大信用记录的借款人提供贷款和评估。该项目的目标是了解信用评分和其他金融技术在拉丁美洲南锥体地区（包括阿根廷，智利和乌拉圭）最近但持续的信贷和债务扩张中的作用。这是通过实证跟踪和比较Equifax与当地和区域金融科技公司的工作来探索的。通过追踪南美洲金融技术的发展，这项研究使人们能够理解STEM学科在产生新形式的信贷和债务方面的作用，因为全球债务率正在上升，信贷对获得教育，医疗保健，住房和生存仍然至关重要。本项目通过对当地专家和业内人士的深入访谈、对金融科技会议和研讨会的参与观察以及对公司、行业和公共政策的档案研究，收集定性数据，回答两个主要研究问题：人工智能和相关技术如何扩大金融服务并重塑拉丁美洲的社会经济生活？B）当地金融科技公司采用了什么技术来吸引被排斥的人群，产生远远超过Equifax等信息巨头所能聚集的知识体系？这些问题的探讨，着眼于技术，创新和专业知识的组合，使拉丁美洲消费信贷市场的形成。这种方法产生了关于如何通过技术创新产生价值和知识以及如何使用通过机器学习生成的算法来预测经济行为的宝贵见解，特别是在社会经济不确定性的背景下。该项目建立在一个假设的基础上，该假设指出，南美正规金融基础设施的覆盖面较浅，限制了Equifax的扩张能力，而区域金融科技公司则能够利用这一基础设施不足的优势，通过将新形式的数据转化为商业上有用的知识，开发评估信誉的技术。该奖项反映了NSF的法定使命，并被认为值得支持通过使用基金会的知识价值和更广泛的影响审查标准进行评估。

Credit bureaus and scoring agencies have played an active part in the impressive growth of consumer credit in the United States at the turn of the twenty-first century. Companies like Equifax (America’s oldest credit bureau) or FICO (providers of the most widely used consumer credit score) have managed to compile a massive volume of consumer histories and translate them into a standardized and objective three-digit number meant to predict the creditworthiness of a person. These companies grew beyond the US borders and expanded to Latin America, where they implemented similar methods. However, they were not as effective in seizing and refining consumer information in a region where almost half of the population lacks access to formal banking networks. This half, furthermore, has been better captured by local or regional financial technology (fintech) firms, that, assisted by artificial intelligence (AI), have managed to successfully lend to and assess borrowers without robust credit histories via the use and sophistication of other sources of information. The goal of this project is to understand the role of credit scoring and other financial technologies in the recent but sustained expansion of credit and indebtedness in the Southern Cone region of Latin America, which includes Argentina, Chile, and Uruguay. This is explored by empirically tracking and comparing the work of Equifax with that of local and regional fintech firms. By tracing the development of financial technologies in South America, this research makes intelligible the role of STEM disciplines in generating new forms of credit and indebtedness in a context where indebtedness rates are on the rise worldwide and credit remains crucial to access education, healthcare, housing, and subsistence. This project contributes to understanding the potential of financial technology to continually reshape socio-economic life.Drawing on qualitative data collected through in-depth interviews with local experts and industry insiders; participant observation in fintech conferences and seminars; and archival research on company, industry, and public polices, this project responds to two main research questions: a) How are AI and related technologies expanding financial services and reshaping socio-economic life in Latin America? b) What techniques have local fintech firms employed to capture excluded populations, generating knowledge regimes that far surpass what information giants like Equifax can assemble? These questions are explored by looking at the combination of technologies, innovation, and expertise that bring Latin American consumer credit markets into being. Such an approach yields valuable insights on how value and knowledge are produced through technical innovation and on how algorithms generated through machine learning are used to predict economic behaviors, especially in contexts of socio-economic uncertainty. This project builds on a hypothesis that states that the shallow reach of formal financial infrastructures in South America placed limits on Equifax’s capacity to expand, whereas regional fintech firms were able to take advantage of this infrastructural deficit by developing techniques for assessing creditworthiness by translating novel forms of data into commercially useful knowledge.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.