The Climate Risk Signals Explorer is an analytical tool designed to track how climate-related physical and transition risks are discussed in corporate communications. It leverages AI-powered analysis of earnings calls and financial reports to provide insights into emerging climate trends and management responses. For finance professionals, it serves as a resource for monitoring corporate sentiment and the evolving landscape of climate risk management across sectors.

Organisation behind the tool

The tool is developed and maintained by Climate Proof, a media and research platform focused on climate adaptation and finance. It utilises AI-driven methodology to process large volumes of corporate earnings call data.

What the tool does

The Climate Risk Signals Explorer provides several key functions:

• Analyses corporate earnings calls using AI to identify specific climate risk “signals”.
• Categorises findings into physical risks, transition risks, and adaptation opportunities.
• Allows users to track management sentiment and the frequency of climate-related topics over time.
• Scales corporate analysis to identify sector-wide trends in climate resilience and financial vulnerability.

Target audience

The primary audience includes finance professionals, ESG analysts, institutional investors, and researchers interested in how climate change impacts corporate strategy and financial performance.

Relevance to finance professionals

Finance professionals can apply the tool in the following areas:

• Risk assessment – identifying specific physical threats and disaster impacts mentioned by corporate leadership in public disclosures.
• ESG analysis – providing qualitative data on environmental metrics and management preparedness for reporting requirements.
• Investment context – monitoring long-term environmental trends and how different industries are adjusting their business models to climate-related economic shifts.
• Market insights – understanding how infrastructure, energy, and commodity-dependent sectors are reacting to climate-driven volatility.