Dynamic Pricing is a market-aware pricing engine for motor insurance, covering MTPL (Motor Third Party Liability) and CASCO (motor own damage). It is delivered as a hosted API: on every new-business quote your system calls our endpoint, and the response is a coefficient that maps your base tariff onto an optimal price by combining your own risk model with live CEE competitor signals. A parallel batch process handles renewals — the same market signal applied to the retention problem instead of the acquisition one.

It is the most-asked-about product in our portfolio because it covers both ends of the pricing problem (new business and renewals) and ties them to the wider motor market on every quote.

What it does for your book

The point of Dynamic Pricing is not the technology underneath. It is the outcome. By bringing the wider motor market into every quote, we shift the loss ratio versus volume curve your team is operating on.

You can take the gain in two directions, depending on what your firm needs at the time:

Lower the loss ratio at the volume you already have. Same book size, better economics on the book.
Grow volume at the loss ratio you already accept. Same risk appetite, larger book.

The same engine drives both, calibrated each cycle to whichever balance you set for the period.

Try it on your data

A proof-of-concept engagement is available for prospects that want to see the engine running on their portfolio before committing to a full rollout. We take a slice of your historical quote and conversion data, run it through the engine, and show you what the engine would have priced and what the resulting loss ratio and volume would have looked like. The PoC is the fastest way to know whether this works on your book.

Results from a real engagement

A CEE motor insurer adopted Dynamic Pricing alongside Client Zone in a recent engagement. Year 1 outcome, confirmed real, not a projection:

~5 p.p. loss ratio improvement at constant volume.
+30% volume growth in priority segments.
+33% profit growth on the motor book.
3 months from signed SoW to first live quote.

Achievable magnitudes depend on local market conditions, chiefly how available the insurer is to policyholders relative to its competitors. What the numbers above show is that the engine moves real KPIs in real engagements, on timelines the board notices.

How it works

The optimizer combines all risk, ratebook and market knowladge to set the tariff that hits your target loss ratio versus volume balance. The optimization itself does not run live per quote. We calibrate it periodically, deploy a static tariff that holds for roughly a month, and refresh on the next cycle. The API call is fast because it reads from that pre-computed tariff. The heavy work has already happened.

Delivery

Hosted API endpoint on AWS. No infrastructure for your team to host or maintain. Latency p99 under 100 ms for the per-quote call. Faster commitments are available if you need them.
Periodic re-pricing of the tariff. Optimization runs on a cadence that fits your release cycle, typically monthly. The refreshed tariff sits behind the API until the next refresh. Competitor-aware on every cycle.
Loss ratio versus volume optimization. Calibrated to the balance you actually want. Protect the loss ratio, push for volume in good segments, walk away from bad ones. Not the default a black box produces.
Sees the market in real time. Client Zone brings the competitor monitoring that feeds the pricing model into one place where your team can read it and act on it.

Renewals and retention

Renewals are a different pricing problem from new business. Retention curves matter, the cost of losing the wrong policy matters, and the right price for a renewal is not a clean function of the right price for the same risk at new business. We do not bundle renewals into the new-business engine. A parallel retention mechanism handles them.

What the retention mechanism does:

Outputs a proposed renewal premium per contract. Each contract gets its own recommended price, not one shared coefficient.

Delivery is a batch process aligned with your renewal cycle. You get a file of proposed prices ready to feed into the communications you send your renewing policyholders.

What we need from you

The integration prerequisites are deliberately minimal.

No data warehouse, no ML platform, no in-house pricing team is required. We have onboarded clients with each of these missing.

Implementation timeline

A typical Dynamic Pricing engagement goes live within about three months from signed SoW. Month one is data: collect logs and conversions, validate, agree the integration message format. Months two and three are model build, sandbox testing, and the live integration.

Cost of switching off

This is built into the engagement by design.

Disconnection is immediate. The API is a plugin. You stop calling it and the dependency is over.
You keep what you paid for. The coefficients, the calibrated models, the diagnostic outputs are handed over to you. No proprietary lock-in on the things your team needs to keep operating.
Cancellation terms by agreement. Specifics are negotiated in the SoW with both sides at the table. We do not aim for a long tail of platform fees.

A pricing partner you can replace cheaply is the only kind of pricing partner worth having.

Want to see it

Write to info@com-pass.cz . A proof-of-concept on your data is the fastest way to know whether this works for you.