Tobi Schneider, Sector Engagement Lead for Financial Services & FinTech, Edinburgh Futures Institute: Creating a new kind of assurance & insurance framework for AI-related risks (391)

In this episode, Robin Merttens is joined by Tobi Schneider, Sector Engagement Lead for Financial Services & FinTech at the Edinburgh Futures Institute, to unpack one of the most ambitious research initiatives currently shaping the future of AI risk in insurance. Backed by UKRI and developed in collaboration with AXA Group and three leading universities, the project aims to build a foundational blueprint for how insurers can understand, audit and underwrite emerging AI risks. 

Tobi shares why the shift from traditional to generative and agentic AI has outpaced current risk frameworks, leaving insurers exposed to risks that are poorly defined, difficult to monitor and impossible to price using historic loss data. He explains how his team is exploring dynamic underwriting models, parametric solutions and novel assurance techniques like LLM-based judges and automated red teaming, all with the goal of enabling safer, more accountable AI adoption. 

Ahead of the Agentic AI Half Day event, hosted in collaboration with AI Risk, Tobi Schneider and Lukasz Szpruch wrote an article The New Frontier: Managing and insuring generative and agentic AI risks, further exploring this topic.  

In this conversation, Tobi shares: 

• Why AI systems that function “correctly” can still produce harmful or costly outcomes 
• How traditional insurance models fail in the face of opacity, model drift and dynamic learning 
• What makes AI risk so difficult to price and how parametric triggers can help bridge the gap 
• Why better assurance leads to better insurance, and how incentives can drive safer AI deployment 
• How continuous monitoring tools are being developed to audit AI models in real time 
• What today’s early AI insurance offerings (from the likes of Munich Re and Relm) are actually covering 
• The role of non-profit research in supporting commercial innovation without commercial bias 
• What insurers can do now to prepare for an AI-driven future even without historical data 

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