The technical price, the price you go to market with, and what the policyholder does after the business is written.
We develop and validate the models behind the technical price: frequency and severity for general lines, mortality, morbidity and persistency for life, health and protection, and the loading for expenses, capital and profit that sits on top.
We calculate the profit a policy generates across its whole lifetime, renewal and lapse included, and work back from it to the price the product has to carry.
We model observed policyholder behaviour beyond contractual terms: lapse, surrender, paid-up rates and the take-up of options and guarantees.
Optimisation is easy to run and hard to defend, so what matters is where the constraints are applied. At Gini we build the technical price, the demand and elasticity models around it, and customer lifetime value and lapse models, with the fair-pricing constraints the FCA expects built into the optimisation rather than checked afterwards.
Gini treats the constraint as part of the objective. Prohibited factors and the outcomes the rules protect are set before the optimisation runs, so the model cannot recommend a price you would not defend, and the resulting price differences are testable by customer group. An optimisation reviewed for fairness after the fact will occasionally have to be reversed, which is the expensive way to learn this.
Yes. At Gini we recalculate the technical price from your own experience data, compare it to what you charge, and decompose the gap into risk, expense, elasticity and judgement. That decomposition is usually the point of the exercise, because it shows which part of the margin comes from risk selection and which comes from inertia.
Yes, and they belong in the same build as the price. Lapse behaviour under a price change is what turns a technical price into an expected margin, and lifetime value is what makes a first-year loss defensible or not. Gini fits both to your own retention experience rather than to a market assumption.