Build a Web-Based Financial Risk Assessment Tool

Risk management is critical in finance. Whether it’s personal investments, business credit evaluation, or insurance underwriting, understanding financial risk is essential. Manual risk assessments are often subjective. A data-driven automated tool ensures consistency, objectivity, and scalability.

Build a web app that takes user financial data (income, liabilities, savings, investments, credit history) and uses ML models and scoring algorithms to assess financial health. Predict creditworthiness, investment risk, or insurance eligibility with automated reports.

Users input personal and financial information (salary, debts, savings, credit history). ML models predict risk scores for investment losses, loan default probability, or insurance risks. The platform presents a professional risk report with explanations and recommendations.

• Users fill a guided multi-step form collecting financial, demographic, and behavioral data points.
• Backend runs pre-trained ML models (classification, regression) to predict risk scores based on inputs.
• Customized feedback and action plans are generated based on user risk profiles.
• Users can download or share risk reports for loan applications, investment guidance, or insurance processes.
• Admins/financial advisors can view anonymized data insights for broader portfolio risk analysis (optional feature).

• Building a Risk Prediction Model with Python
• Understanding Financial Risk Assessment Techniques
• Using scikit-learn for Risk Model Development
• Generating PDFs in Python with ReportLab
• Designing Multi-Step Forms in React
• Best Practices for Financial App Security