PATRIZIA Scores €45B Portfolio on 0–100 Scale Using Machine Learning

For proptech founders and investors, the real estate industry’s data problem is the opportunity of the decade. The SREF made clear that the race to normalise building‑level ESG data is accelerating, with major landlords already deploying machine learning to score entire portfolios. Startups that can solve data fragmentation, automate energy retrofitting analytics, or measure climate risk at parcel level are poised to capture demand from the world’s largest real estate allocators — who are now actively pricing in a ‘brown discount’ for assets that lack this intelligence.

The Sustainable Real Estate Forum convened senior industry leaders on June 23–24, 2026, during London Climate Action Week, marking a pivotal moment in the real estate investment ecosystem's shift from aspirational ESG commitments to data‑driven, investment‑grade decision‑making. In a keynote address that set the tone for the event, RICS Senior Vice President Susanne Eickermann‑Riepe argued that sustainability must be evaluated through the lens of materiality, not morality. Drawing on RICS research and the IMF’s April 2026 World Economic Outlook, she demonstrated that sustainable practices now simultaneously enhance cash flows, improve growth assumptions, and reduce discount rates — a triple‑bottom‑line benefit that is reshaping asset pricing. Moreover, she highlighted that geopolitical turmoil, with a record 65 state‑based armed conflicts recorded in 2025, is accelerating the repricing of non‑resilient properties, a trend that creates a growing “brown discount” in secondary markets.

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In a keynote address that set the tone for the event, RICS Senior Vice President Susanne Eickermann‑Riepe argued that sustainability must be evaluated through the lens of materiality, not morality.

The subsequent panel discussion, moderated by Cecile Babcock, brought together fund managers and data experts from M&G Real Estate, The Crown Estate, PATRIZIA, and Recogizer to dissect how leading institutions are operationalizing ESG and performance data. A central theme was the transformation of fragmented building‑level information into consistent portfolio‑level insights. Regulatory requirements, such as evolving EU and UK disclosure mandates, are evolving from compliance burdens into strategic assets that enable more precise risk assessment and capital allocation. The emergence of the “brown discount” was identified as a concrete market signal that investors are now differentiating resilient assets from those with high transition risk. This, in turn, is driving growing investment in building retrofits and data infrastructure.

Artificial intelligence and machine learning emerged as dual‑edged forces in this transformation. Eickermann‑Riepe predicted that AI would polarise the valuation profession, automating routine tasks while elevating roles that demand expert judgment and interpretation. Meanwhile, Dr. Marcelo Cajias of PATRIZIA described how his firm has applied machine learning across its €45 billion global portfolio to create a location‑scoring model on a 0–100 scale. That scoring system now directly informs investment committee evaluations, helping to quantify climate risk, connectivity, and social infrastructure at hyper‑local levels. This demonstrates a path for large‑scale investors to move beyond static sustainability ratings toward dynamic, input‑driven valuation.