利用开放api通过基于电信数据的信用评分推动金融包容性

A. Olowe, J. K. Olorundare, Temitope Phillips
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引用次数: 1

摘要

金融排斥仍然是发展中经济体面临的一个重大挑战。研究表明,获得信贷便利是金融包容性的一个强有力的预测指标。信用报告和评分仍然是传统和替代贷款机构的有效工具,然而,获得可靠的信用数据和评分机制是发展中经济体替代贷款机构面临的最大障碍之一。虽然一些贷款机构已经开发出了利用社交媒体分析和智能手机数据来创建评分系统的系统,但穷人和弱势群体仍然被排除在这种评分系统之外。在使用电信数据进行信用评分方面取得了重大进展,使其成为信用局数据的一个有希望的替代方案。然而,现成的数据仍然是一个问题。随着开放api的开发和使用的增加,电信数据可以随时用于信用评分,同时解决隐私和其他问题。本文是一篇概念性论文,提出了一个使用电信数据中的开放api进行信用评分的模型,最终将增加获得信贷的机会,并最终实现非洲的金融包容性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Open APIs To Drive Financial Inclusion Via Credit Scoring Built on Telecoms Data
Financial exclusion remains a significant challenge in developing economies. It has been shown that access to credit facilities is a strong predictor of financial inclusion. Credit reporting and scoring remain effective tools for both traditional and alternative lenders, however, access to credible credit data and scoring mechanisms is one of the biggest roadblocks that alternative lenders in developing economies face. While some lenders have developed systems that leverage social media analytics and data harvested from smartphones in order to create a scoring system, the poor and vulnerable are still excluded from such scoring systems. There have been significant advances in the use of telecoms data for credit scoring, making it a promising alternative to credit bureau data. However, readily available data is still an issue. With the increase in the development and use of open APIs, telecoms data could be made readily available for credit scoring, while addressing privacy and other issues. This paper is a conceptual paper that proposes a model for the use of Open APIs from telco data for credit scoring that will ultimately increase access to credit, and ultimately financial inclusion in Africa.
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