Insurance · Canada

AI for insurers and brokers: claims files, policy wordings and renewals, with adjusters in charge

We build AI that reads loss notices, wordings and claim files the way a careful examiner would, then hands the adjuster, underwriter or broker a cited summary to act on.

Talk to us about AI for insurance

Why now

Where AI fits in insurance

Insurance runs on documents written for different readers: policy wordings, endorsements, declarations pages, adjuster reports, repair estimates, medical reports and broker submissions. Current language models can read those at the volume a claims or underwriting team actually sees, and check a claim against the exact wording that was in force on the date of loss. The gain is in the reading and cross-referencing: summarizing a file, finding the endorsement that changed a sublimit, gathering every open claim tied to one storm. Coverage positions, reserves and settlements stay with licensed adjusters, examiners and underwriters.

Common challenges

Wordings that drift at every renewal. Forms, endorsements and manuscript wordings change between policy years and between carriers. Working out which version applied on the date of loss, and what a new endorsement took away, is slow line-by-line reading.
First notice of loss in every format. Emails, broker portal entries, call-centre notes, photos and PDFs land in the same queue. Someone has to read each one, find the policy, open the file and decide where it goes before an adjuster sees it.
Event aggregation after a storm or flood. After a catastrophe event, reserving and reinsurance reporting depend on knowing which open claims belong to the event, which hit a flood exclusion or sublimit, and what they add up to. That picture is spread across hundreds of files.
Commercial submissions with gaps. Submissions arrive with missing schedules, stale statements of values and loss runs in a dozen layouts, so underwriters spend their time chasing information before they can quote.

Use cases

AI automation for insurance

FNOL intake and triage

Read each loss notice, match it to the policy and term, extract date, cause and location, and route the file to the right desk with a short summary for the adjuster.

Coverage check against the wording

For a given claim, pull the declarations, endorsements and exclusions in force on the date of loss and point the adjuster to the clauses worth reading, page by page.

Renewal and carrier wording comparison

Line up this year's wording against last year's, or one carrier's form against another's, and list every change in limits, deductibles, exclusions and conditions for the account manager.

Catastrophe event roll-up

Search open claim files for a named event, group them by exclusion or sublimit, and assemble the figures the reserving and reinsurance teams need.

Advisor and agent enablement

Give life and benefits advisors plain-language plan explainers, needs-analysis drafts and talk tracks built from your product documents, so client conversations start from accurate material.

Subrogation leads

Read adjuster notes, fire and police reports and contractor statements to flag files where another party may be responsible, so the recovery team sees them early.

Example workflow

Water-damage claim, from loss notice to adjuster review

01
A loss notice arrives by email with photos and a broker note. The intake agent reads it and finds the matching policy and term.
02
It extracts the date of loss, address, reported cause and damage, and opens a draft file in the claims system.
03
It retrieves the wording in force on that date and flags the flood exclusion, any sewer-backup or overland-water endorsement and the applicable sublimit, citing each page.
04
It drafts an acknowledgement to the insured and a note for the adjuster listing the documents still needed.
05
The adjuster reviews the cited clauses, takes the coverage position and edits or sends the acknowledgement. Nothing reaches the insured without that approval.
06
Every extraction, citation and edit is logged on the file for audit and claims quality review.

Insurance claims: which open claims hit a flood exclusionAnimated, narrated story: Maya, a claims lead, connects policies and claim files to Akurion and asks which open claims hit a flood exclusion or sublimit. The answer names two claims, each cited to a policy page, using fictional sample data.

From our work

Agent and client platform for a life insurer

A two-audience platform with plan explainers, self-serve calculators, a plan recommender, a lead pipeline, need analysis and talk tracks for agents.

Data and privacy

Handling sensitive data

Claim files hold some of the most sensitive information an organization keeps: injury and medical details, banking information, photos of the inside of people's homes. In Canada, private-sector insurers and brokers handle that under PIPEDA or substantially similar provincial privacy laws, and insurers are also supervised either by OSFI, which publishes expectations for outsourcing and technology risk, or by a provincial regulator such as FSRA in Ontario. We design around that: the minimum data per task, access by line of business and role, processing in Canadian cloud regions or on your own infrastructure, open-weight models where a file should not leave your environment, and a log of what the AI read and produced. Your privacy and compliance teams decide what is acceptable.

Kitchener-Waterloo

Local support

Waterloo Region has long been one of Canada's insurance centres, home to life and property and casualty insurers, mutuals and independent brokerages. We're based in Kitchener and can run discovery sessions on site with claims, underwriting and broker teams.

AI consulting in Kitchener-Waterloo AI for small businesses

AI for insurance: frequently asked questions

How well does AI handle handwritten claim forms and adjuster notes?

Typed notes, emails, PDFs and photos of forms are read well by current models. Legible handwriting usually works too, but the system records a confidence level for each field and sends anything uncertain to a person instead of guessing. Before going live we test extraction on a sample of your own closed files, so you see the accuracy on your documents rather than on a demo set.

Who signs off on coverage when AI reviews a claim?

The adjuster or examiner. The system gathers the wording, endorsements and claim documents, highlights clauses that may apply and cites each page, but it does not accept, deny or value a claim. Licensed staff take those positions, and the audit log shows both what the AI surfaced and what the person decided, which is useful for quality reviews and complaints.

Can AI compare policy wordings from several carriers for a broker?

Yes. Brokers often market one risk to several carriers, each with its own forms and endorsements. The comparison lines up limits, deductibles, exclusions and conditions side by side and points to the page behind each difference, so the broker can explain the options clearly. The broker still checks the comparison before it goes into a client recommendation.

Can AI help find subrogation opportunities?

It can help find candidates. By reading adjuster notes, fire and police reports and contractor statements, the system flags files that mention another party's involvement, such as a failed appliance, a contractor error or a third-party vehicle, and explains why. The recovery team decides which files to pursue. Finding them early matters because evidence and limitation periods do not wait.

Other industries

Banking & Financial Services Legal Accounting Healthcare Manufacturing Real Estate

Tell us about the process you want to automate.

A 30-minute call is enough to tell whether AI is a fit, what a first project would look like and what it would take to run it in production.

Start a conversation dassjaylabs@gmail.com