MetricsenseCall AnalyticsBook a pilot
Evidence Intelligence for Australian life-insurance leaders

The call that becomes an ASIC problem is sitting in the 95% your QA team never hears.

Metricsense reads 100% of your advisers' calls inside your own AWS, PII stripped, and flags the handful that carry real compliance risk, the same day, each pinned to the exact moment in the call. Ask it a compliance question below.

Live demo, try it yourselfInsurance callsSample data
Pick a compliance question, or write your own, then press Run:

One short meeting. Fixed-fee pilot, your data, deleted on request. Prefer email? hello@metricsense.ai

Runs in your AWS (ap-southeast-2)PII stripped before any model sees itWe report nothing to a regulator
2–5% 100%

16 genuine escalation risks, inside 5,438 calls. None of them a call a sample would ever have reached.

One analysis window at an Australian life-insurance broker (name withheld by design): every call scored on both sides, inside their own AWS account.

What gets caught

Two duties make or break an insurance call.

Staying inside general advice, and getting the product facts right. Metricsense flags the likely failures across 100% of calls, the same day.

Licensing boundary

General advice vs personal advice

Anything that weighs a caller's needs or steers them to a product can amount to personal advice, which may expose you to Corporations Act breaches, AFCA disputes and licence risk.

General advice ✓"Stepped premiums start lower and rise with age; level premiums start higher and stay flatter. Here's the PDS so you can compare."
Personal advice ✗"I'd go with this one if I were you, that's the best one for your situation."

Catches the subtle forms too, and checks the mandatory General Advice Warning was given.

Technical correctness

Premium structures explained correctly

In one analysis, more than half of premium-structure explanations were only partly accurate. Metricsense scores technical correctness on every call.

Technically correct ✓"An age-stepped premium is recalculated each year as you get older. A level premium is averaged to stay flatter: higher now, more stable later."
Incorrect / misleading ✗"Level premiums never change." (They still move with CPI and indexation.)

An inaccurate explanation that influences a decision can read as deficient advice.

How the pilot works

Proven on your calls before you commit.

Fixed fee. Nothing to integrate. Your data, deleted on request.

1

Send a sample you already hold

Around 50 calls, audio or transcripts, from any system: AWS Connect, Genesys, Twilio, your dialer, or a one-off CSV. Nothing to rip out first.

2

We configure your insights and run them

Your compliance checks, written in your wording, run across 100% of the sample inside your own AWS. No tagging, no model training.

3

You check it against your own QA

A risk readout with every flag quote-linked. You review precision and recall against your human QA before you commit a dollar to the platform.

Why you can trust it

A compliance tool you can defend, to your QA team and to the regulator.

If you're putting an AI between your advisers and ASIC, "trust us" isn't good enough.

Where does our call data go?

It runs inside your own AWS account (ap-southeast-2). Health and underwriting data never leave your environment; PII is stripped before any transcript reaches the model. Signed DPA before a single call is processed.

Does monitoring 100% create new obligations?

A flag is a candidate issue with evidence, not a finding of breach. Flags live inside your existing breach and complaints processes. We report nothing to a regulator on our own.

Will my advisers see this as surveillance?

No. Scores are a coaching tool, role-based, never a leaderboard. Every flag reaches your QA team with the evidence attached, and a human confirms or dismisses it. The model never disciplines an agent.

Is the judgment defensible?

Every flag pins to the exact transcript moment against a documented, versioned insight definition. When ASIC or AFCA asks how you monitored, you show methodology and evidence, not a black box.

How long is anything kept?

Transcripts, audio, flags and scores follow your retention schedule and purge on your timeline. Pilot data is deleted on request once the pilot ends.

Could our calls ever reach a competitor?

Never. We do not publish client names, calls or results, and no client's data goes near another's. Nothing you send trains a model shared with anyone else.

Not your call to make alone? Forward the trust & security page to your Head of Compliance.

What a peer found

A 2–5% sample would have missed every call that put their licence at risk.

Case study · Australian life-insurance broker (name withheld by design)
5,438
calls read, both sides
16
genuine escalation risks surfaced
54%
of premium explanations only partly accurate, one root cause
0
new QA analysts added

Fifteen insurance-specific checks, scored against their own QA. The same two omissions repeating across the floor: one scripting fix, not 98 separate problems.

Our discretion We do not name our clients, including this one. Your calls, and your results, would be just as private.

Stop sampling. Start with the call that could sink you.

Book a pilot and we run Metricsense on a sample you already hold, around 50 calls, and send back a risk readout scored against your own QA.

Prefer email? hello@metricsense.ai

Metricsense by Avesta Labs · AI analytics for every conversation your business has.