Market Intelligence for Modeling & Ratemaking
AI is turning market intelligence from "interesting context" that is painful to extract into a lightning-fast, model-ready input for P&C pricing and ratemaking. This webinar shows how modern filings and rate extraction can be operationalized to benchmark a book of business against competitors, quantify market position dynamics, and feed those signals directly into modeling workflows.
We'll cover conventional approaches that were historically impractical at scale - and newer applications that only become possible when AI can parse and structure vast, messy market data. The result goes beyond discovery: it strengthens objection handling, sharpens the story behind your indications, and accelerates the path to filing-ready decisions.
Learning Objectives:
- Evaluate how AI-extracted competitive intelligence from regulatory filings can be structured and integrated into P&C pricing and ratemaking workflows.
- Identify practical methods for benchmarking a book of business against competitors using large-scale, AI-parsed market data.
- Articulate how market positioning signals can strengthen rate indications, support filing narratives, and accelerate pricing decisions.
Register
Our team will contact you with the event details.
Market Intelligence for Modeling & Ratemaking
AI is turning market intelligence from "interesting context" that is painful to extract into a lightning-fast, model-ready input for P&C pricing and ratemaking. This webinar shows how modern filings and rate extraction can be operationalized to benchmark a book of business against competitors, quantify market position dynamics, and feed those signals directly into modeling workflows.
We'll cover conventional approaches that were historically impractical at scale - and newer applications that only become possible when AI can parse and structure vast, messy market data. The result goes beyond discovery: it strengthens objection handling, sharpens the story behind your indications, and accelerates the path to filing-ready decisions.
Learning Objectives:
- Evaluate how AI-extracted competitive intelligence from regulatory filings can be structured and integrated into P&C pricing and ratemaking workflows.
- Identify practical methods for benchmarking a book of business against competitors using large-scale, AI-parsed market data.
- Articulate how market positioning signals can strengthen rate indications, support filing narratives, and accelerate pricing decisions.
Learn more about the speakers
Sergey Filimonov
A regular speaker at CAS conferences, Sergey translates AI into actuarial practice for carriers nationwide. His essays on AI have been reshared well beyond insurance—by Google's executives, the founder of Llama-Index, and other industry leaders—highlighting his standing as a cross-sector authority on AI. Before Akur8, he scaled production ML models across Honda’s U.S. operations.
Max Martinelli
Max Martinelli is a Managing Director in the Insurance and Actuarial Advisory Services practice of EY, where he focuses on P&C pricing, actuarial data science, applied AI and external rating. He has over a decade of experience in actuarial and data science roles, primarily in predictive modeling for personal and commercial lines, and a background in machine learning and computational mathematics. A dedicated collaborator with the Casualty Actuarial Society, he co-designed and led the CAS AI Fast Track bootcamp and co-hosts Almost Nowhere, the CAS Institute podcast exploring AI and data science in insurance.
