Bias Correction Methodology in Microfinance Lending

This research article examines bias in loan applications for microentrepreneurs, particularly within microfinance institutions. It highlights how biases can affect credit assessment processes, influencing lending decisions and financial inclusion. The study focuses on sensitive attributes such as gender, economic sector, and education level, analyzing how these factors contribute to disparities in lending outcomes. By utilizing data from a prominent microfinance institution, the research investigates the impact of various social and economic contexts on lending patterns. A novel methodology is introduced to quantify bias at the individual assessor level, analyzing past credit assessments to measure bias across different sensitive attributes. This framework aims to provide a data-driven approach to assess and mitigate biases in microfinance lending, ultimately contributing to the development of fairer credit evaluation models. The findings are intended to support salesforce management by guiding training efforts to reduce biases and promote equitable access to credit for marginalized groups.