I will build a fraud detection system with machine learning

Money moves fast fraud needs to be caught faster.

I build production-style fraud detection systems: a rule engine plus a machine learning model screening every transaction in real time, turning each decision into labeled data for the next training round not a notebook that only works on clean sample data.

What you get:

Feature engineering on your transaction data (amount patterns, velocity, account age, network signals)

A trained ML model (LightGBM or logistic regression) scored alongside custom business rules

A REST API you can plug into your existing app

A live dashboard: flagged transactions, model metrics, score distributions

Full test coverage, CI, and Docker deployment built for real traffic, not just a demo

I work in Python and PHP, and I document what I ship: test suite, CI pipeline, and a clear list of production trade-offs (idempotency, ledger design, latency budget, where a human still needs to review).

You get a system you understand, not a black box.

Message me with your data volume and current stack before ordering, so I can scope this precisely for your case