Post by Fulcrum Digital Inc

2024 was the third costliest year for insured losses from natural catastrophes since Munich Re began tracking in 1980. $140 billion. Global insured losses have now exceeded the 10-year inflation-adjusted average for several consecutive years, and the gap between what is insured and what is lost keeps widening. That trajectory is what prompted us to dig deeper. Talking to BFSI executives. Reading the regulator filings. Pulling the loss data. Here's what we found, and why we wrote our latest whitepaper. Spanish banks had €20 billion in loan exposure sitting inside the Valencia flood zone when the October 2024 floods hit. 9% of ATMs went out of service. 37 branches closed. Canadian P&C insurers posted underwriting losses on personal property two years running. The IBC put Canada's 2024 insured losses at CAD $8.5 billion, 12 times the 2001–2010 annual average. These institutions had risk models. Most had climate scenario frameworks. What they didn't have was a data infrastructure that could get predictive signals into decisions fast enough to matter. The protection gap hit $181 billion in 2024. That's not just an insurance problem. That's a data architecture problem. So we asked the operational question: what does it take to move from climate exposure visibility to a decision that changes something? Not in theory. In production. At the speed climate events now demand. The answer maps back to the same gaps we see across Financial Services AI programmes, batch pipelines where real-time signals are needed, model outputs that don't reach the decisioning system, governance structures built for quarterly review cycles applied to risks that move weekly. Our latest whitepaper covers what the data shows, what the regulatory pressure looks like (OSFI B-15, ECB climate stress tests, NGFS scenarios), and what the infrastructure requirements are for institutions trying to move from exposure management to predictive response. What we found is here to read: https://lnkd.in/eaKCUweP #ClimateTech #EnterpriseAI #AIOps #DataArchitecture #ESGData