AI use cases for sustainable finance
This section lists a selection of some AI use cases in sustainable finance currently live. It is a subset of the array of use cases that we will share in our upcoming publication "Developing Sustainable Finance with Artificial Intelligence" (scheduled Q4 2025).
The page will be regularly enriched with new cases.
Sentiment Analysis on corporate sustainability reports
Corporate sustainability reporting is a critical tool for evaluating climate and environmental performance. Yet, in practice, its value is undermined by complexity, inconsistency and the absence of verifiable standards. To overcome these challenges, the Department of Finance at the University of Zurich has developed two AI-driven tools: ASKCLIMATE and ASKNATURE. These tools are designed to provide free access to high-quality sustainability analysis and bring greater structure and traceability to corporate sustainability disclosures. They can be used by the public or by professionals, e.g. investment managers.
AI-powered investment due diligence
Portfolio Managers and Investment Analysts are under pressure to quickly assess the sustainability performance of a potential portfolio company ahead of an investment decision or an upcoming investment committee meeting, for example. The challenge is not just the volume of data but its complexity, and the need to translate it into actionable insights under time pressure. ClarityAI has developed AI-powered tools to help investment management teams in this process, with a focus on providing efficiency gains in data aggregation, curation, and preliminary assessment.
AI-based Analysis for Real Estate Portfolio Decarbonisation
For institutional investors, assessing the sustainability of real estate portfolios remains a significant challenge. A key objective of the initiative by Conser and ZHAW is therefore to examine whether the CO₂ reduction commitments and net-zero targets of real estate funds are realistic given the current condition of their building stock, and whether the required renovations are both achievable and aligned with reported measures.
AI-Driven Network Analysis to assess Carbon Markets integrity
Carbon markets are systems that enable the trading of carbon emission allowances or credits, assigning a monetary value to greenhouse gas emissions in order to drive climate action. However, the credibility of these entities is increasingly undermined by the presence of "hot air" credits, which have the potential to distort price signals, mislead investors and ultimately risk slowing global climate progress. To address this, ZHAW is developing an AI-based network analysis tool designed to uncover inefficiencies, detect patterns of risk, and enhance market accountability, with the aim of aligning financial flows with meaningful climate action.
- To be released early September. Stay tuned!
Pilot use case to extract insights from stewarship reports
In the past few years, Stewardship has become one of the main sustainable investment approaches applied by financial services companies in Switzerland. A significant portion of Asset Managers (more than 40%) and a great majority of Asset Owners (83%) do not perform stewardship by themselves, but rely on a third-party provider. This means that a large number of Asset Managers and Asset Owners rely on third party reporting to assess the effectiveness of these activities. If they have several providers, they need to screen several such reports in different formats - the workload increases accordingly, which, especially for some Asset Owners with limited resources, can become an issue.
Any suggestion, comment or question? Reach out to Romain Leroy-Castillo, Director & Artificial Intelligence lead at SSF
