Sustainability in Valuation: Emerging AI-Driven Real Estate Approaches

In response to evolving sustainability regulations, this study addresses the need to quantify sustainability within real estate valuations. Traditional Discounted Cash Flow (DCF) models face limitations in capturing the full impact of Environmental, Social, and Governance (ESG) factors, resulting in undervaluation of sustainable assets. The proposed solution shows the evolution of the DCF model into a meta-instrument for the real estate life cycle integrating sustainability and digitalization. The future proof DCF framework introduces seven key new tech approaches driven by emerging AI and established Building Information Modeling: dynamic cash flow and discount rate adjustments, predictive sustainability analytics, scenario modeling, advanced sensitivity analysis, automated ESG data integration and transparency. These emerging approaches offer a granular, forward-looking valuation method that better reflects the financial benefits of sustainability across the real estate life cycle. The model provides a transparent tool for investors and property managers, aligning valuations with regulatory standards and supporting informed, sustainable investment decisions. By merging advanced digital technologies with traditional valuation methods, this study challenges established property valuation tools, offering an adaptive, accurate, dynamic, and data-driven approach that meets the demands of an evolving real estate development market.

Authors

Publication Details

Journal
CIB Conferences
Published
2025-06-19
DOI
https://doi.org/10.7771/3067-4883.1818
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Sustainability in Valuation: Emerging AI-Driven Real Estate Approaches

Mihaela Meslec, Matthias Haase, Isabelle Wrase
CIB Conferences
Insurance and Financial Risk Management
article

Sustainability in Valuation: Emerging AI-Driven Real Estate Approaches

Mihaela Meslec, Matthias Haase, Isabelle Wrase
article en

Abstract

In response to evolving sustainability regulations, this study addresses the need to quantify sustainability within real estate valuations. Traditional Discounted Cash Flow (DCF) models face limitations in capturing the full impact of Environmental, Social, and Governance (ESG) factors, resulting in undervaluation of sustainable assets. The proposed solution shows the evolution of the DCF model into a meta-instrument for the real estate life cycle integrating sustainability and digitalization. The future proof DCF framework introduces seven key new tech approaches driven by emerging AI and established Building Information Modeling: dynamic cash flow and discount rate adjustments, predictive sustainability analytics, scenario modeling, advanced sensitivity analysis, automated ESG data integration and transparency. These emerging approaches offer a granular, forward-looking valuation method that better reflects the financial benefits of sustainability across the real estate life cycle. The model provides a transparent tool for investors and property managers, aligning valuations with regulatory standards and supporting informed, sustainable investment decisions. By merging advanced digital technologies with traditional valuation methods, this study challenges established property valuation tools, offering an adaptive, accurate, dynamic, and data-driven approach that meets the demands of an evolving real estate development market.

CIB ConferencesVol. 1(1)
Openalex Percentile: Top 79%
Insurance and Financial Risk Management
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Sustainability in Valuation: Emerging AI-Driven Real Estate Approaches — Mihaela Meslec, Matthias Haase, et al. · CIB Conferences (2025) | TGRS Research Map | TGRS