FinSight: Open-Source AI for Smarter Financial Analysis

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸

Submission for Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle.

FinSight is a financial anomaly detection and reporting tool designed for freelancers, accountants, and small businesses.

FinSight also provides financial dashboards, profit and loss analysis, balance sheet validation, variance analysis, and PDF reports.

The goal is to make financial analysis more accessible without expensive proprietary AI services.

FinSight uses a synthetic dataset of 1,000 transactions to demonstrate its workflow.

The dashboard visualizes financial metrics and detected anomalies, while PDF reports make the results easier to review.

Built with Python, Pandas, scikit-learn, Streamlit, Plotly, SQLite, SQLAlchemy, and ReportLab.

I built FinSight using a modular Python architecture.

The pipeline combines deterministic financial checks, Z-score analysis, and Isolation Forest, an unsupervised machine learning algorithm from scikit-learn.

Streamlit powers the interactive dashboard, Plotly handles visualizations, SQLite supports local storage, and ReportLab generates PDF reports.

Open-source machine learning makes FinSight more affordable and customizable.

For a small business, an affordable tool that keeps financial data under its control can be more practical than an expensive cloud-based solution.

My next steps are to improve anomaly explanations, support more transaction formats, customize detection rules, and test FinSight with freelancers and small business owners.

The goal is to turn an open-source machine learning project into a practical tool that solves a real financial problem.

Add this section after someone has tested FinSight and provided feedback.

Add the applicable partner categories before submitting.