Which risks you accept and on what terms, covering both the selection models and the rules that turn a submission into a decision.
We build and review the models that decide which risks you accept and on what terms, whether that is a protection application, a motor or property risk or a treaty submission, and evidence their accuracy, stability and fairness.
We design and test the rules, scores and referral triggers that turn a submission into a decision, covering risk selection, pricing, exclusions, evidence requirements and reinsurance cession.
The useful partner is the one whose output steers the portfolio rather than describing it. At Gini we build frequency and severity models at the granularity your underwriting decisions are made at, decompose loss cost into the components you can act on, and produce the combined ratio analytics that show which segments are earning and which are being subsidised.
Yes, and a review is often the better first step. Gini refits from your own experience data and explains every difference from your figures, including the judgements behind them. The frequent finding is a model still calibrated to a mix the book has since moved away from, which shows up as consistent bias in one segment rather than as poor overall fit.
Yes, with the uncertainty stated rather than hidden. At Gini we pool across comparable exposures, use market and external data to anchor the estimate, and quantify how much of the answer rests on the data and how much on judgement. A confident model fitted to too few claims is the version that fails review.
They should run off the same experience analysis. When the frequency and severity assumptions behind the price differ from those behind the reserve, the difference is a decision somebody should have made deliberately. Gini builds one set of assumptions, states where each use case departs from it, and documents why.