AI CMBS Analysis
The Problem
“CMBS valuation and surveillance are stuck in spreadsheets—risk signals arrive too late”
Organizations face these key challenges:
Analysts spend hours pulling comps, market data, and rent/NOI inputs from multiple systems before any real analysis starts
Valuations vary by analyst and methodology, making pricing and IC decisions hard to defend and audit
Surveillance is periodic and reactive—deterioration shows up after reports are filed, not when markets shift
High-potential deals get missed because teams can’t screen enough assets/markets with limited headcount
Impact When Solved
Real-World Use Cases
AI Property Valuation & Automated Appraisal
This is like an always-on digital appraiser that looks at thousands of past property sales, current listings, and local market signals to estimate what a home or building is worth—instantly and consistently—rather than waiting days for a human-written appraisal report.
Deep Learning-Based Real Estate Price Estimation
This is like an ultra-experienced real estate agent who has seen millions of property deals and can instantly guess a fair price for any home or building by looking at its features and location. Instead of human gut-feel, it uses deep learning to learn complex patterns from past sales data.