AI Debt Service Coverage Prediction
The Problem
“Your team can’t refresh DSCR fast enough—risk and pricing decisions are made on stale models”
Organizations face these key challenges:
Underwriting analysts spend days normalizing rent rolls, T-12s, and borrower docs into brittle spreadsheets
DSCR outcomes vary by analyst assumptions; audit trails and model governance are hard to maintain
Deal screening can’t keep up with pipeline volume, so promising opportunities are missed or reviewed too late
Portfolio monitoring is reactive—DSCR breaches are discovered after covenants are already tripped
Impact When Solved
Real-World Use Cases
AI for Finding High-Potential Real Estate Investments
It’s like giving every real-estate investor their own tireless analyst that quietly scans thousands of properties and markets in the background, then taps you on the shoulder when it finds deals that match your strategy and are likely underpriced or high-potential.
AI in Real Estate: Price Prediction and Lead Scoring
This is like giving every real-estate agent a super-smart assistant that can (1) estimate what any property should be worth and (2) tell you which potential buyers are most likely to actually close a deal.