07 / PROJECTS
Comparing approaches to fraud detection
Coursework revisited as a fraud-detection service, with decisions weighted by the cost of approving, declining or reviewing a transaction.
Comparing decisions by their cost.
The project grew from coursework into a closer look at evaluation and decision costs. I reviewed the earlier methodology and documented test-set threshold selection and inconsistent cross-validation scaling by file and line in IMPROVEMENTS.md. The original code remains available alongside those notes.
Later work added a FastAPI service and cost-aware decisions. Comparing the approaches showed that reinforcement learning did not consistently outperform a simpler threshold on individual transactions. It showed a stronger result in an offline sequential-fraud scenario, where earlier transactions affect the decision.
The comparison separates individual transaction decisions from sequential ones, making the conditions behind each result explicit.
Scope and context
Evaluation uses offline data; the comparisons do not establish performance on live transactions. The repository preserves the earlier coursework and its documented methodology issues. Automated tests and CI are not included, and an end-to-end deployment is not documented.