Beyond prediction: causal inference and experiments in credit

Originally published at han-co.com · Part of the "Basics" strand of my Credit & Finance Data Science series. (The original has hand-drawn diagrams; the text below is identical.) So far this series has mostly been about getting "who is risky" right. Building good features, scoring with trees, checking whether those scores are well calibrated. But in practice the harder question, the one with real money riding on it, is a little different. If we raise a limit, will defaults go up? If we chase…