Welcome to the Mortgage KPI Project! This repository is dedicated to analyzing key performance indicators (KPIs) in the mortgage industry using data analytics and visualization tools. The goal is to provide valuable insights into mortgage trends, risk assessment, and portfolio performance.

The project is deployed on Steamlit at: https://pacificwidekpi.streamlit.app/ - Give it a try (Email: datmai@pacificwide.com & PW: Datmai@2205)

The mortgage industry generates vast amounts of data that, when analyzed correctly, can offer significant insights for lenders, investors, and policymakers. This project leverages statistical analysis and machine learning techniques to evaluate mortgage KPIs, helping stakeholders make informed decisions.

• Data Cleaning and Preprocessing: Tools to clean and prepare raw mortgage data for analysis.
• KPI Calculations: Modules to compute KPIs like delinquency rates, default probabilities, and prepayment speeds.
• Visualization Dashboards: Interactive dashboards to visualize trends and patterns.
• Predictive Modeling: Machine learning models to forecast future mortgage performance.
• Automated Reporting: Generate reports summarizing key findings and insights.

• Python 3.7 or higher
• Git
• pip (Python package installer)

1. Clone the Repository

   git clone https://github.com/dmai287/mortgage_kpi_proj.git
   cd mortgage_kpi_proj
   

2. Create a Virtual Environment (Optional but Recommended)

3. python -m venv venv
   source venv/bin/activate  # On Windows, use venv\Scripts\activate
   

4. Install Required Packages

   pip install -r requirements.txt