I will build an explainable ai loan approval system with shap

I build explainable AI systems that solve real decision problems, not just prediction models, but the full workflow that makes AI usable in regulated industries.

Example of my work: Bank Loan AI Co-Pilot, an explainable AI system that helps loan officers make underwriting decisions, instead of a black-box model nobody can trust.

- TensorFlow neural network predicts loan approval with a confidence score

- SHAP explainability shows exactly which factors drove the decision

- Multi-modal intake: form data, notes, and bank statement PDF parsing

- Claude-powered plain-English explanations for non-technical reviewers

- Human-in-the-loop dashboard for officer review before final decision

- Audit-ready PDF report generation

Tech stack: Next.js, FastAPI, TensorFlow, scikit-learn, SHAP, Claude API, SQLite, Docker.

What I can build for you:

- Custom ML model for your decision problem

- SHAP explainability so results are transparent

- Clean Next.js frontend + FastAPI backend

- PDF/document parsing if needed

- Database integration + Docker deployment

Message me your use case, I will tell you honestly if it is a good fit before you order.