AI is solving research-level maths problems, yet most banks and insurers still use it to answer basic questions about their data, and struggle to show what their agentic analytics projects return. Drawing on case studies in insurance and financial services, this session reframes ROI around the one thing that pays: better decisions.
Learn to apply a decision-driven framework for analytics, that judge analytics by the decisions it improves rather than by the data that happens to be available, to crate AI that can be trusted.
Hear examples from banking and insurance showing how the framework applies across sales and distribution, risk management and fraud.
Create agents that can be trusted through a shared model of the business, including definitions, relationships and permissions, so answers are consistent, traceable and safe to act on.
Find out how peers use agents today to monitor performance, explain changes and recommend next steps.
Check out the incredible speaker line-up to see who will be joining Marcos.
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