Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Learn to build a comprehensive mortgage loan analysis application that combines traditional Combined Loan-to-Value (CLTV) calculations with AI-driven risk assessment and borrower scoring in this 40-minute tutorial. Develop a CLTV Simulator that integrates LTV/CLTV calculation, front-end and back-end DTI assessment, and a "Comprehensive Borrower Score" weighing risk across multiple factors including collateral, repayment capacity, credit history, stability, and down payment. Create an application designed for financial professionals such as loan officers, underwriters, and risk analysts, as well as IT audiences seeking reproducible, auditable, and scalable assisted underwriting solutions. Build four complementary features: a traditional CLTV simulator for evaluating leverage and equity, AI Analysis for automated underwriting review with actionable recommendations, AI Chat for conversational queries with dynamic tool invocation including PMI Analysis and Debt Consolidation, and Advanced Tools for specific deterministic calculations. Implement loan structure and down payment scenario comparisons, PMI/MIP estimation and removal modeling, debt consolidation impact analysis, and home affordability calculations under different DTI bands (28/36/43/50%). Construct the user interface using Streamlit with interactive Plotly visualizations, perform calculations with pandas and numpy, integrate external data via yfinance, and develop the intelligent agent using LangChain and LangGraph with OpenAI or Google Vertex AI language models. Master modular architecture design that exposes tools for programmatic Python use or web interface access, with secure API key handling and environment variable configuration management, while prioritizing performance through AI analysis caching, deterministic transformations, and explainable outputs for auditing and reproducibility.
