Insurance AI Guides

A hands-on comparison of three AI platforms that extract data from ACORD forms, with real accuracy numbers, pricing differences, and honest assessments of where each tool fails.

A buyer's framework for choosing between API-first document parsing tools and enterprise IDP platforms for insurance document processing, with pricing ranges and decision criteria.

A practical guide to AI tools that parse insurance loss runs, covering what works, what doesn't, and how to evaluate extraction accuracy on your own loss run formats.

A practical guide to using AI tools for extracting data from Statements of Values (SOVs), covering the specific challenges of SOV parsing and which tools handle them best.

A commercial lines underwriter's comparison of three AI submission intake platforms, covering scoring accuracy, integration depth, and how each handles out-of-appetite submissions.

A practical guide for insurance compliance officers on identifying and managing AI underwriting bias risks under ECOA, fair lending, and state insurance regulations.

An insurance underwriter's analysis of AI accuracy claims — what the data shows, where it breaks down, and what it means for practitioners.

A detailed comparison of Applied Epic and Vertafore AMS360 focused on their AI and automation features, covering recent acquisitions, pricing, and practical workflow differences.

A practical guide to AI tools that independent insurance agencies can actually afford and use today, from CRM and rating to document processing and client communication.

A head-to-head comparison of InsuredMine and Vertafore AgencyZoom (now integrated into Vertafore) for independent insurance agency CRM, with pricing, feature, and workflow differences.

Real pricing data on AI tools for independent insurance agencies — what each tier costs, what you get, hidden fees, and an ROI framework that actually works.

A comparison of three AI platforms for auto claims damage estimation, covering photo-based assessment accuracy, repair shop network effects, and how each fits into different carrier workflows.

A detailed comparison of FRISS and Shift Technology for insurance fraud detection, covering scoring approaches, network analysis, deployment models, and practical differences for carriers.

A claims professional's side-by-side breakdown of AI and manual claims processing — real cycle times, accuracy rates, and where each approach earns its keep.

A claims professional's comparison of Shift Technology, Friss, and SAS fraud detection — real numbers, honest trade-offs, and who each tool actually fits.

An insurance professional's breakdown of AI claims processing tools — speed, accuracy, and cost — with real numbers and honest trade-offs.

A property underwriter's comparison of three leading AI property intelligence platforms, covering imagery currency, attribute coverage, peril models, and practical integration considerations.

A side-by-side comparison of Claude and ChatGPT for drafting insurance underwriting memos, with real output examples and honest notes on where each model fails.

Ten tested AI prompts for drafting insurance claims denial appeal letters, with prompt text, example scenarios, and important warnings about when NOT to use AI for appeals.

A prompt library for summarizing insurance policies with AI, covering personal lines, commercial lines, and specialty policies with tested prompts and output quality notes.

A practical prompt library for insurance adjusters writing field reports, damage estimates, and coverage summaries with AI. Includes 8 prompts with example outputs and honest notes on where AI helps and where it breaks down.

A practical prompt library for summarizing insurance policies with ChatGPT. Includes 8 ready-to-use prompts for auto, home, life, and health policies with real output examples.

A plain-language guide to Colorado's SB 24-205 and the NAIC Model Bulletin on AI for insurance professionals who need to understand what their carriers and AI vendors must now comply with.