Speaking
Keynotes and panels across insurance, reinsurance and financial services since 2024. Practical, drawn from live deployments, and clear for mixed audiences.
Practical deployment of machine learning and generative AI in credit, bond and political risk.
Beyond chatbots: autonomous workflows in financial services, and where they break.
Building data infrastructure and models that underwriters, and regulators, actually trust.
Where automation ends and judgement begins, and how to measure what AI is worth.
Everyone is investing in AI. Far fewer can answer the question the CFO is asking: what did we actually get for it? A practical framework for measuring AI return in insurance, from hard cost savings and automation to decision quality and speed to quote.
As AI moves into pricing, claims and underwriting decisions, governance stops being a compliance checkbox and becomes a competitive edge. Firms building explainable, auditable systems today are the ones regulators will trust with more autonomy tomorrow.
Generative AI is not an efficiency tool for insurance, it is a structural shift. From submission triage to treaty analysis, the underwriting workflow of 2030 will look fundamentally different. The question is how fast, and how safely.
Credit insurance is both a financial risk product and a leading indicator of economic stress. How early-warning models can help primary credit insurers underwrite through the cycle rather than react to it.
Past the theory and into the specifics: document intelligence, agentic workflows, real-time bordereaux analysis and portfolio monitoring at scale, each drawn from live deployments rather than pilots.
AI is not replacing actuarial judgement, it is accelerating it: faster pricing cycles, dynamic risk segmentation, and models that learn from live portfolio data rather than historical averages alone.
For organisers
Banu Munnangi is SVP, Credit Reinsurance AI at Marsh Re in London, where he leads data and AI for the Credit, Bond and Political Risk specialty.
Before Marsh Re he was Lead Data Scientist for Credit & Surety at Swiss Re, where he worked with Prof. Dimitris Bertsimas of MIT on bond default prediction and deployed generative AI in underwriting. Earlier, at Wipro, his forecasting work was presented at the World Economic Forum in Davos and his COVID-19 drug repurposing research earned a NASSCOM AI GameChanger Award.
He speaks on AI in reinsurance, agentic systems, AI governance and the future of underwriting, and is often asked for his perspective on enterprise AI, data platforms, and credit and surety.
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