About

UCL’s partnership with RealAssetX focuses on Automating the Debt Underwriting Process.

The project’s aim is to develop an enhanced measure of U.S. multifamily residential and commercial properties' performance based on net operating income (NOI). The current rule-based model used for loan re-rating lacks accuracy, dynamism and exposure to property and market characteristics. The current model is set to:

NOI Prediction Automation: Automates and improve the prediction of net operating income (NOI) by modelling individual income and expense line items, replacing the traditional manual underwriting process

Integration of External Data: Enhances prediction accuracy by incorporating market indicators, macroeconomic variables, and property-specific characteristics alongside internal financial variables.

Property Risk Profiling: Generates property-specific risk insights by evaluating income volatility, expense reliability, and sensitivity to external factors.

Scalability Across Property Types: Though initially developed for U.S. multifamily properties, the model is designed to extend to other asset classes.

Improved Underwriting Consistency: Reduces subjectivity and human error in the underwriting process by standardising the evaluation criteria and applying data-driven logic across portfolios.

Forecasting Power: Despite current limitations like sparse data or fluctuating inputs, the model provides a foundational forecasting engine that can be refined as more data in integrated.