Real estate loan origination and monitoring with a macroeconomic-coherent Monte Carlo approach

Real estate investments are complex and risky for financial institutions. Traditional ways of valuing them, such as Discounted Cash Flows (DCF), often don't account for the risk and uncertainty involved. We suggest a new approach that uses Monte Carlo simulations of different economic and financial scenarios and real estate-specific factors. 

This paper introduces a framework and software suite, called Real Estate Analytics (REA), that makes cash flow estimates for real estate investments under various economic conditions, allowing for a better assessment of the real estate projects and their risks. We will show a use-case of loan structuring and pricing for real estate-backed projects, and how our approach helps optimize risk-return trade-offs by finding optimal loan terms and interest rates. We also provide monitoring metrics from our analysis, which can track investment performance. The paper aims to show how Monte Carlo simulations based on economic scenarios can improve a sector like real estate, which can be profitable for banks and other financial institutions, but also very risky.