Case study / Project archive
FinCortex
A finance-analytics prototype exploring spend data, anomaly inspection, and forecasting.
Historical team prototype; individual contribution is not independently established. AI-assisted portfolio development.
The idea
The problem
Make sample finance data inspectable through transaction, anomaly, forecasting, and question-answering endpoints while keeping demo inputs visible.
The implementation
What I built
The source assembles a finance-analytics API around sample data, anomaly inspection, forecasting, and chat. The README names Gaurav and Mohit; exact personal implementation scope is not independently established.
- Python
- FastAPI
- scikit-learn
Features
- List generated sample transactions and inspect Isolation Forest anomaly flags.
- Request a cash-flow forecast through a model/statistical-fallback interface.
- Expose a finance-question chat endpoint with resettable conversation state.
Architecture
- FastAPI routes connect transaction ingestion, a scikit-learn anomaly detector, a cash-flow forecaster, and a separate copilot module.
- The inspected API initializes mock transactions and a generated cash-flow series; the forecaster falls back to exponential smoothing without a trained neural model.
Validation and measured results
- Source reviewed on 15 October 2026. The application and its external integrations were not executed in this review.
- Mock transaction generation, startup initialization, feature extraction, and forecasting fallback were inspected. No live Zaggle connection or predictive-quality result was reproduced.
Limits and unfinished work
- Demo anomaly flags and forecasts do not establish fraud detection, financial savings, or compliance automation.
- Older source can contain superseded descriptions. Numerical impact, adoption, awards, and deployment claims are not carried into this entry.
Evidence and sources
- Reviewed source and implementation
Public README and selected implementation files; source inspection only, without a reproduced runtime or benchmark. Inspected files: src/api/main.py, src/ai_engine/forecaster.py, src/ingestion/zaggle_connector.py.