Hundreds of millions of people in low-income economies do not have a credit or bank
account because they have insufficient credit history for a credit score to be ascribed to …

Purpose Over the last few decades, microfinance industry is argued to have played a
constructive role in alleviating poverty level and providing the underprivileged with access to …

Recently, the high penetration of mobile devices and internet access offers a new source of
fine-grained user behavior data (aka “alternative data”) to improve the financial credit risk …

The importance of pursuing financial inclusion to accelerate economic growth and enhance
financial sustainability has been well noted. However, studies have provided few actionable …

Abstract Cong, Li, and Zhang introduce recent research in economics and business-related
fields utilizing data from unconventional sources or of unstructured nature. Highlighting …

Machine learning models have been used extensively for credit scoring, but the
architectures employed suffer from a significant loss in accuracy out-of-sample and out-of …

Data-driven customer segmentation is one of the most commonly used techniques followed
by FinTech companies for its marketing, focus strategies, and customer acquisition …

Microfinance based institutions have emerged as a potential solution to the financial
exclusion problem in developing economies around the world. A key challenge facing such …

We investigated the value of credit borrowers' social media posts, such as microblog posts,
in the prediction of their credit risk. We used a mixed methodology to enhance credit …

Given the sheer size of the consumer credit market and the huge number of consumer credit
users, credit risk modeling, or predicting delinquent (or default) probabilities of borrowers to …