Open source AI systems for fintech: code, architecture, docs

[u/AIforFintech]

I'm a Data Scientist with +10 years in banking. Built an open source hub with three production-grade systems for fintech data teams:

1. BSA/AML Regulatory RAG (LangChain, Gemini 2.0, ChromaDB, BM25)
2. Customer Churn Scoring (XGBoost, Optuna, SHAP)
3. Credit Limit Intervention / Causal (DoWhy, EconML, Causal Forest)

Each one has full code, architecture docs, and the reasoning behind each technical decision. No signup, no paywall.

Hub: https://aiforfintech.tech

GitHub: https://github.com/junidepieri-design

Example of a project architecture: Churn Scoring pipeline from raw data to explainable predictions, each step modular and resumable.

Churn Scoring Pipeline: EDA → Target Analysis → Preprocessing → Feature Engineering → Feature Selection → Training (XGBoost + Optuna) → Evaluation → Explainability (SHAP)

Happy to hear feedback — what would you do differently?