Developing an ML Decision Support System for Digital Finance in Emerging Markets
Ganesh Iyer, Professor
Business, Haas School
Closed. This professor is continuing with Fall 2023 apprentices on this project; no new apprentices needed for Spring 2024.
The rails for the ongoing digital payments revolution in emerging markets are dependent on Point of Sale (POS) acceptance terminals at small merchants in developing countries. Those merchants play a crucial role in providing access to financial services to underserved regions. However, Indian payment firms face high merchant churn rates and an even greater merchant dormancy challenge. To tackle the challenge, we develop a machine learning (ML)-driven decision support system to augment merchants' decision-making.
Role: Research apprentices will be involved in all stages of the project potentially: 1) Literature review of financial inclusion model, payment platform in developing countries; 2) data collecting, cleaning and analyzing massive data source (e.g., financial transaction data, satellite image data); 3) building up ML models; 4) presenting results.
Qualifications: Ideal applicants have intrinsic interest in digital payment, fin-tech, financial inclusion in emerging market, have background in computer science or related and are familiar with Python or R coding to implement ML models.
Day-to-day supervisor for this project: Yixiang Xu, Ph.D. candidate
Hours: to be negotiated
Social Sciences