10/07/2026
What if financial service providers could use the data they already have to make credit more precise, not just in predicting who will repay a loan, but who is most likely to benefit from one?
In this Behind the Research video, CGAP's Jessica Meckler shares what motivated the team to explore Precision Causal Modeling (PCM) with five financial institutions and what they learned.
Advances in data science and machine learning are expanding the analytical toolkit available to financial service providers. Through this work, CGAP piloted a methodology using machine learning not traditionally applied in financial inclusion to examine how existing customer data might help providers better understand differences in the impact of credit.
For providers, investors, and funders, these advances create new opportunities to move from broad credit decisions toward more precise ones, identifying more clearly when, where, and for whom credit can create value.
Watch this video below, and learn more in the full technical guide: https://cgap.pub/4hMj41N
We know a lot about the impact of financial services at the global ...