Consumer and business finance companies and microcredit organizations have had limited success in serving the needs of economically-active low-income families and micro-enterprises in Southern countries. Recent advances in computing and telecommunications technology are dramatically transforming this landscape by changing the way the financial industry operates. A key mechanism underlying this transformation concerns the use of Big Data in assessing, evaluating and refining the creditworthiness of potential borrowers. Important technological and strategic driving forces are behind the implementation of Big Data techniques for such purposes. The objective of this paper is to examine this issue from the perspective of Southern economies. The approach of this study can be described as theory building based on multiple case studies. The study analyses seven cases of financial technology companies operating in the Global South.
The paper investigates how various inherent characteristics of Big Data volume, velocity, variety, variability and complexity are related to the assessment of the creditworthiness of low-income families and micro-enterprises. The paper looks at various categories of personal financial and non-financial information being used as proxy measures for a potential borrower’s identity, ability to repay and willingness to repay. The analysis of the paper indicates that the main reason why low-income families and micro-enterprises in emerging economies lack access to financial services is not because they lack creditworthiness but merely because banks and financial institutions lack data, information and capabilities to access the creditworthiness of this financially disadvantaged group.