Marcela Granados

Insurers today are caught between rising claims complexity, evolving risks, and policyholders who expect more— faster. The carriers pulling ahead aren't just building better models. They're winning on data: who owns it, who can access it, and how quickly they can act on it. In this session, you'll see how leading insurers use Databricks to break down data silos, operationalize AI at scale, and put natural language insights directly in the hands of underwriters, claims teams, and distributors— turning data strategy into smarter risk selection, faster settlements, and profitable growth that compounds.

The insurance industry is at the crossroads of digital transformation, facing challenges from market competition and customer expectations. While conventional ML applications have historically provided capabilities in this domain, the emergence of Agentic AI frameworks presents a revolutionary opportunity to build truly autonomous insurance applications. We will address issues related to data governance and quality while discussing how to monitor/evaluate fine-tune models. We'll demonstrate the application of the agentic framework in the insurance context and how these autonomous agents can work collaboratively to handle complex insurance workflows — from submission intake and risk evaluation to expedited quote generation. This session demonstrates how to architect intelligent insurance solutions using Databricks Mosaic AI agentic core components including Unity Catalog, Playground, model evaluation/guardrails, privacy filters, AI functions and AI/BI Genie.

Protecting insurers against emerging threats is critical. This session reveals how leading companies use Databricks’ Data Intelligence Platform to transform risk management, enhance fraud detection, and ensure compliance. Learn how advanced analytics, AI, and machine learning process vast data in real time to identify risks and mitigate threats. Industry leaders will share strategies for building resilient operations that protect against financial losses and reputational harm. Key takeaways: - AI-powered fraud prevention using anomaly detection and predictive analytics - Real-time risk assessment models integrating IoT, behavioral, and external data - Strategies for robust compliance and governance with operational efficiency Discover how data intelligence is revolutionizing insurance risk management and safeguarding the industry’s future.