We measured social outcome at Microfund for Women using data science
Microfund for Women (MFW) is a leading microfinance institution in Jordan with over 140,000 current clients spread over 60 branches. Since 1996 MFW provides financial services to low-income, small business owners (96% women) to empower them economically and socially. Triple Jump is an impact-focused investment manager that provides responsible investment opportunities in developing countries. Triple Jump and Microfund for Women sought the assistance of Steward Redqueen to measure the social outcome of MFW using innovative technological solutions.
Microfinance institutions increasingly measure the social performance of their portfolios to obtain insight in the socioeconomic situation of clients and the impact on their lives. Social performance measurement can be costly and complex, however using data science methods enables cost-efficient data collection and analysis.
We developed an innovative method to analyse the demographic, financial and social data of over 300,000 of MFW’s clients using various statistical techniques. With time-series analysis we determine the change (delta) in social outcome over time. Using correlation analysis we determined the drivers underlying the social outcome. And with supervised and unsupervised machine learning we clustered the MFW portfolio into segments, allowing MFW to identify sub-groups of clients with difference social and financial performance.
MFW now has access to a theory of change linking its financial and non-financial instruments to their social outcome, a list of indicators against which to measure progress, a dashboard visualizing its achievements over time and the capacity to analyse its social outcome on a day-to-day basis.