Why Econometrics Matters for Anti-Money-Laundering: A Practical Roadmap

Money-laundering is an economic problem dressed as a criminal problem: it distorts markets, corrodes institutions, and hides wealth that should be visible to regulators. Detecting it is not a matter of intuition alone — it needs careful measurement, robust models, and an eye for real-world tradeoffs.

In this blog, I’ll show how standard econometric tools — from panel regressions to network analysis and anomaly detection — can be used to identify suspicious patterns, evaluate policy changes, and provide clear, defensible recommendations. Every post will come with code and data (or synthetic analogues) so you can reproduce the results and adapt them to your case.

This first series will start small: a reproducible demo that builds a simple anomaly detector from aggregated transaction data, then tests whether that detector flags historic events or policy changes. Let’s begin. **https://github.com/Mjeedkh/Econometrics-in-practice-**