Insurance Billing operations North America

Nine agents do the gathering. The biller still signs.

A Fortune Global 500 insurance brokerage with $9.7B in annual revenue recovered 96 analyst hours every working day, without migrating a single system.

80%Reduction in manual data entry per billing activity
$2.5MAnnualized value of the analyst time released
~10×Return on the engagement, annualized
01 · Client

Global scale. A billing operation still running on people.

One of the world’s largest insurance brokerages. Its North America billing team processes a continuous stream of B2C billing activities every working day.

AI had been discussed internally for years. It had never actually run the operation.

RegionNorth America
FunctionBilling operations
Team~40 analysts
Volume in scope~1,000 / day
Annual revenue~$9.7B
Time in productionLive · 8 weeks
02 · The problem

Where the 300 hours a day were going.

Every billing activity took a biller about 18 minutes of pure manual work. At a thousand activities a day, the loss showed up in four places.

01

No single source of truth

A core AMS for the policy, a repository for documents, separate tools for classification, routing and banking verification.

02

Nineteen fields, typed by hand

Policy numbers, premiums, dates, commissions, payable entities – re-keyed out of PDFs and emails on every activity.

03

Critical details fell through

Routing rules and banking references lived outside the main flow. A missed instruction became rework or a compliance question later.

04

No audit trail

Little visibility into where an activity stood or who changed what. The answer lived in a biller’s memory.

03 · Native limits

What they tried first, and where it stopped.

The first attempt was the one most enterprises make: put an assistant in front of the biller and let it summarise the document on screen.

Copilots and chat assistants were never going to move the number. To take 18 minutes off an activity, four things had to happen together, on every activity, every day.

01

Pull from every system, not one

Reach across all five the way a biller does, and bring the answer back to one place.

02

Read documents built for people

Nineteen fields out of PDFs, binders and attachments never designed to be parsed.

03

Validate before a human looks

Routing, banking and premium checks run first, so people only see what needs a decision.

04

Keep the biller in charge

Nothing reaches a customer without a named human on the record.

04 · What Lyzr built

Nine agents. One pipeline. One screen for the biller.

Nine agents in four stages. The biller sees one confidence-scored screen at the end.

Activity Parser
Reads notes, extracts policy IDs and document links.
Document Retrieval Agent
Locates and downloads billing documents from SharePoint.
OCR Agent
Converts PDFs and emails to machine-readable text.
Key Value Extraction
Pulls all 19 billing fields with confidence scores.
Validation Agent
Cross-checks extracted data against Cross-System policy records.
Industry Mapper
Classifies policy by department, profit centre, GLOB type.
Routing Validation
Checks for special invoice routing instructions.
Payment Validation
Confirms premium payable entity and banking reference.
Dashboard Summary
Produces outcomes and recommended actions for the biller.
05 · Architecture

Slotted alongside the stack already in place.

No migration. No replatforming. The agents run against the systems already in place.

B2C Billing Automation agentic data flow - from a raw Cross-System activity through intake, extraction, validation and enrichment, decision and action, with a human-in-the-loop review and a self-learning feedback loop.
06 · Controls

What happens when the agent is not sure.

When the pipeline is unsure, it is unsure loudly – in front of a person who can fix it.

Confidence
Every field scored. Below threshold gets flagged, never passed through.
Disagreement
Both values shown side by side. The activity stops.
Exceptions
Routed to the biller queue as work, not as errors.
RFI
Raised on screen. The activity holds until the answer returns.
Audit trail
Agent, source, correction and approver logged – closing problem 04.
07 · Re-imagined workflow

The biller used to gather. Now the biller just signs.

Before: a biller opens five systems, hunts for nineteen fields across PDFs and email, and hopes nothing was missed. After: nine agents do that work in the background, the biller opens one screen, reviews a confidence score, and signs.

With LyzrAgents gather, read and check. The biller decides.
Agent runtime 5m 57s, unattended. Biller reviews outcomes only.
SOURCE Policy Management System GATHER AND READ Activity Parser Document Retrieval OCR Key Value Extraction VALIDATE Cross-System Validation Industry Mapper Routing Validation Payment Validation 1 SCREEN Dashboard SUCCESS WARNING EXCEPTION HUMAN GATE Biller approves nothing posts without it 2 human checkpoints: biller can correct inputs and edit any of the 19 fields
Before Lyzr1 biller, 5 systems, everything by hand.
~18 minutes per activity. Around 25 activities per analyst per day.
Unstructured PDFs and emails Biller 19 FIELDS TYPED BY HAND Policy ManagementSystem Document Repository Industry Mapper Routing Validation Payment Validation ~18 MIN PER ACTIVITY
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08 · Results

What changed, by the numbers.

Per activity, before and after.

MeasureBeforeAfter
Handling time per activity18 min~4 min
Manual data entry19 fields, by handReview only
Systems touched per activity5, manually1 screen
Analyst roleEntryReview & approval
Analyst hours per working day96 on manual handlingRecovered
$2.5MRecovered per year
$9,600Recovered per working day
~10×Return, annualized
09 · What’s next

The same pipeline, pointed at the next queue.

Billing was the first workflow. Gather, read, validate, then hand the decision to a named human. That pattern generalizes across the operation.

8 weeks from idea to agents in production

Got a use case in mind?

Platform, engineers and governance all in. We’ll map your workflow against the same four tests this one had to pass.