INDUSTRY · INSURANCE

AI in insurance: AI prepares, the case handler decides.

Pre-assessed claims, sorted requests, documented duty to advise: we build uses that respect the AI Act, the ACPR’s expectations and your policyholders’ confidentiality.

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  • AI Act, ACPR, DDA built in from the design stage
  • Policyholder data stays within your perimeter
AI IN INSURANCE
For
Claims, underwriting, compliance
Who decides
The case handler
Updated
October 15, 2026

THEY TRUST US

  • Celio
  • Plein Sens
  • Shiseido
  • Green-Got
  • Promologis
  • Bridgestone

IN BRIEF

Where is AI useful for an insurer?

Wherever files arrive in volume and documents are checked one by one: claims reporting and assessment, incoming requests from policyholders and brokers, online underwriting, case handler preparation, regulatory watch.

The AI Act classifies pricing and risk selection in life and health insurance for natural persons as high-risk; file preparation, sorting and summaries, when a human decides, fall under a different regime. The ACPR, France’s insurance supervisor, also expects the duty to advise to be documented, including in online journeys.

We design every use so that AI prepares and the case handler decides, with a record of every action and data that stays within your perimeter.

FIVE USE CASES

Pre-assessed claims · Sorted requests · Online underwriting · Documented duty to advise · Regulatory watch.

  • Executive management
  • Claims
  • Underwriting
  • Compliance
  • IT

Updated October 15, 2026.

WHAT YOUR TEAMS FACE

Case handlers spend their time on documents.

What claims and underwriting leaders tell us.

  • CLAIMS

    “Every file starts with chasing missing documents.”

  • REQUESTS

    “Emails, forms, brokers: everything lands in the same inbox.”

  • ADVICE

    “Proving the duty to advise takes almost as long as giving the advice.”

WHO IT’S FOR

  • Insurers
  • Mutual insurers
  • Brokers
  • Claims
  • Compliance

USE CASES

AI prepares, the case handler decides.

Uses built with your teams, connected to your management tools, with a record of every action.

  • Pre-assessed claims

    AI checks the documents and drafts the summary of the file. The case handler decides on the settlement.

  • Sorted incoming requests

    Each request is qualified and sent to the right person, with a reply prepared.

  • Online underwriting

    A journey that checks documents as they arrive, with advisors alerted at the right time.

  • Documented duty to advise

    The needs assessment is structured and archived with the policy, ready for an inspection.

  • Prepared case handlers

    Policy coverage and procedures summarized before each exchange with the policyholder.

  • Regulatory watch, summarized

    The relevant texts, summarized with their source and sent to the teams concerned.

AI-READY

Your AI agents read and act in the tool, through MCP.

MCP is an open standard: a universal plug, under your control, between your software and AI. Your IT department approves every access.

  • SAMPLE REQUESTS TO YOUR AGENTS
  • “Which documents are missing from this claim file?”
  • “Summarize this policy’s coverage before my call.”
  • “Which broker requests are awaiting a reply?”

BEFORE / AFTER

What changes for your policyholders.

TODAYWITH AI, APPROVED BY YOUR TEAMS
ClaimDocuments requested several times over.Completeness checked when reported, summary ready.
RequestRead when it surfaces.Qualified on arrival, reply prepared, reviewed.
AdviceScattered notes.Structured needs assessment, archived with the policy.

Every gain is measured in your company, from your starting point.

OUR METHOD

Four steps, with your compliance team.

The four steps of our method, in a loop. Each can be done on its own; together, they organize AI across the whole company.

  1. Inspire your leadership team

    A keynote built on cases from your business. Your leadership decides where AI will be useful, and where it will not.

  2. Map your operations

    We spot the bottlenecks, rank use cases by gain and difficulty, and name the tools to keep.

  3. Bring your teams on board

    In a hands-on session, everyone arrives with a real problem and leaves with the AI agent that solves it. An AI policy sets the shared rules.

  4. Build with the AI Factory

    Our engineers build AI-ready business tools with you. You keep the keys.

You take back the keys.

The code and data stay with you, documented. We keep improving the tool with you, or you take it over. This is step 4 of our method: Build with the AI Factory.

YOUR QUESTIONS

What insurers ask us.

What are the main use cases for AI in insurance?

Claims assessment, sorting incoming requests, online underwriting, case handler preparation, the documented duty to advise and regulatory watch.

Can AI handle a claim from start to finish?

We do not recommend it. AI checks the documents and prepares the summary; the case handler decides on the settlement and replies to the policyholder.

Which AI uses are high-risk for an insurer under the AI Act?

Notably risk assessment and pricing in life and health insurance for natural persons (Annex III). File preparation and summaries, when a human decides, are not among them.

How do you reconcile online underwriting with the duty to advise?

By structuring the needs assessment within the journey and archiving the proof with the policy, as the ACPR expects, including for distance selling.

Can a mutual insurer use AI on health data?

With stronger safeguards: a legal basis, minimization, suitable hosting and strict access rights, to be validated with your DPO.

Do we need to replace our policy administration tool?

No. We connect AI to your current tools. If an in-house tool is holding you back, we can rebuild it AI-ready.

Does AI decide in place of your teams?

No. AI prepares: it sorts, checks, summarizes and writes a first draft. A named person reviews and decides. Every AI action is logged.

SOURCES

The texts and studies cited on this page.

Every figure on the site is sourced. See all our sources.

LET’S TALK ABOUT YOUR PROJECT

Let’s talk about your policyholders and your teams.

Thirty minutes to understand your priorities, and tell you where we would start.

Your contact

The AI Origin team that runs the projects

You talk directly with the people who will run your project, from scoping to go-live.

No specific project yet? Start with a hands-on session: everyone brings a real problem and leaves with the AI agent that solves it. See step 3, Bring your teams on board

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