Corporate climate disclosures based on the TCFD recommendations are considered an important prerequisite to managing climate-related financial risks. At the same time, current disclosures are imprecise, inaccurate, and greenwashing-prone. Yet, existing research on this matter suffers from small...

We use BERT, an AI-based algorithm for language understanding, to decipher regulatory climate-risk disclosures and measure their impact on the credit default swap (CDS) market. Risk disclosures can either increase or decrease credit spreads, depending on whether disclosure reveals new risks or...

Corporate climate disclosures are considered an essential prerequisite to managing climate-related financial risks. At the same time, current disclosures are imprecise, inaccurate, and greenwashing-prone. We introduce a deep learning approach to enable comprehensive climate disclosure analyses...

Large language models (LLMs) have significantly transformed the landscape of artificial intelligence by demonstrating their ability to generate human-like text across diverse topics. However, despite their impressive capabilities, LLMs lack recent information and often employ imprecise language,...

Disclosure of climate-related financial risks greatly helps investors assess companies' preparedness for climate change. Voluntary disclosures such as those based on the recommendations of the Task Force for Climate-related Financial Disclosures (TCFD) are being hailed as an effective measure...

The severity of extreme weather events is increasing due to climate change, giving rise to physical climate risk. However, physical climate risk is not only driven by the severity of individual hazards, but also by the interdependence of those hazards. This paper establishes bounds for the...