Risk can be mispriced
An incorrect expected loss can make an attractive price produce poor claims results later.
Price optimisation
Compete where the expected profit allows.
Combine the expected cost of risk with demand, retention, and customer lifetime value. Then choose prices within limits on close rate, loss ratio, price movement, capacity, and applicable regulation.
The pricing problem
A good risk estimate does not choose the commercial price.
The team still needs to understand how customers respond, define the value it wants to improve, and protect the portfolio limits it cannot cross.
Demand varies
Conversion and retention can respond differently by customer segment and price position.
One target is not enough
Growth, margin, customer value, capacity, and regulation place different limits on the final strategy.
Three separate decisions
Risk is the foundation. It is not the final price.
A competitive price requires a clear separation between expected claims, customer behaviour, and the commercial objective.
Risk
Estimate the expected claims cost for the risk.
Demand
Estimate how conversion and retention change with price.
Value
Define future margin and the customer lifetime value horizon.
Decision
Choose the price that best meets the objective and constraints.
Product workflow
Choose the portfolio outcome, not just the highest score.
Every point is an achievable pricing strategy under the same portfolio, risk model, demand model, and constraints. Select one to compare its portfolio impact with current rates.
Efficient frontier
Select a scenario
Frontier scenarios
See the metric across different scenarios
| Metric | Current | |||||
|---|---|---|---|---|---|---|
| Conversion rate | 69.11% | 69.00% | 70.00% | 71.00% | 72.00% | 73.00% |
| Written margin | £11.95m | £14.11m | £14.39m | £14.63m | £14.81m | £14.99m |
| Written premium | £23.89m | £26.11m | £26.52m | £26.90m | £27.20m | £27.49m |
| Average premium | £418 | £457 | £464 | £471 | £476 | £481 |
| Average margin | £209 | £247 | £252 | £256 | £259 | £262 |
| Expected loss ratio | 50.00% | 45.96% | 45.76% | 45.62% | 45.55% | 45.48% |
| Average rate change | 0.00% | 4.49% | 5.38% | 6.31% | 7.45% | 9.23% |
| Policies | 57,134 | 57,134 | 57,134 | 57,134 | 57,134 | 57,134 |
Swipe to compare scenarios.
Define value
Make the objective explicit.
Choose the measure the strategy should improve. Customer lifetime value uses the insurer's definition of expected future premium, claims, expenses, retention, and the chosen time horizon.
The assumptions behind renewal, retention, claims, costs, and discounting remain visible so the team can understand what the optimiser is being asked to do.
- Risk inputThe approved expected claims estimate and its model version.
- Demand inputConversion, retention, and price sensitivity by supported segment.
- Strategy outputA separate version of the proposed prices, objective, limits, and expected portfolio result.
Portfolio constraints
Protect the boundaries the business cannot cross.
Set minimum and maximum conditions at portfolio or segment level. The optimiser searches for better prices inside those boundaries rather than treating growth or profit as an unconstrained target.
- Close rateSet a minimum expected conversion level.
- Loss ratioSet a maximum expected portfolio or segment loss ratio.
- MovementLimit the size of customer or segment level price changes.
- CapacityProtect volume or exposure limits where required.
- RegulationApply the insurer's relevant fairness and regulatory requirements.
Strategy comparison
Compare growth, margin, and balanced outcomes.
Generate candidate strategies from the same approved risk and demand inputs. The efficient frontier keeps every achievable trade-off visible, while the linked scenario grid makes the portfolio effect of each choice directly comparable.
- One frontierSee the trade-off between conversion and expected written margin.
- Linked evidenceSelect a point and inspect its premium, loss ratio, rate movement, and volume.
- Shared baselineCompare every scenario with current rates on the same portfolio.
Validation and testing
Test the selected strategy before customers see it.
Run the strategy across the full portfolio, compare it with the current rate set, inspect key segments, and record the approval. A controlled A/B test can use clear traffic allocation, stopping rules, guardrails, and outcome attribution.
Optimisation should end with a testable pricing strategy.
The result remains linked to its risk model, demand model, assumptions, constraints, approval, and portfolio simulation.