Big Data Privacy in Emerging Market Fintech and Financial Services: A Research Agenda

TL;DR

This paper proposes a research agenda to address data privacy challenges in emerging market fintech, emphasizing understanding local privacy perceptions, technical solutions, and policy approaches to protect consumers' data.

Contribution

It outlines five priority research areas to advance understanding and solutions for data privacy issues in emerging market financial services.

Findings

Identifies key sources of privacy risk in emerging markets.

Highlights potential technical solutions like differential privacy.

Emphasizes importance of policies and practices for data protection.

Abstract

The data revolution in low- and middle-income countries is quickly transforming how companies approach emerging markets. As mobile phones and mobile money proliferate, they generate new streams of data that enable innovation in consumer finance, credit, and insurance. Already, this new generation of products are being used by hundreds of millions of consumers, often to use financial services for the first time. However, the collection, analysis, and use of these data, particularly from economically disadvantaged populations, raises serious privacy concerns. This white paper describes a research agenda to advance our understanding of the problem and solution space of data privacy in emerging market fintech and financial services. We highlight five priority areas for research: conducting comprehensive landscape analyses; understanding local definitions of ``data privacy''; documenting key sources of risk, and potential technical solutions (such as differential privacy and homomorphic encryption); improving non-technical approaches to data privacy (such as policies and practices); and understanding the tradeoffs involved in deploying privacy-enhancing solutions. Taken together, we hope this research agenda will focus attention on the multi-faceted nature of privacy in emerging markets, and catalyze efforts to develop responsible and consumer-oriented approaches to data-intensive applications.