What it is.
For a given ENID scenario, the new modelling creates an annual liability loss distribution curve for a given jurisdiction e.g. UK. It then apportions the mean loss across industry codes. Where relevant, the time development of that loss is also estimated from latency periods and from likely dates of knowledge. The time-is-money value of reserving for the loss can then be estimated and the potential opportunity cost of delayed reserving can be calculated.
Given that emerging risks arise from science studies it should be no surprise that the same studies can be analysed to give estimates of attributable frequency of loss. Other work is then used to assess how many of these attributable losses could make a reasonable liability claim. For example, if half the attributable cases could prove a breach of duty then the attributable frequency is at most, half the attributable loss frequency. The model takes account of the probability of duty being owed, the probability of duty being broken, diagnostic accuracy and the probabilities of generic and specific causation being found in that jurisdiction.
Severity profiles are based on age profiles, loss of earnings, general damages and medical intervention costs.
Combining frequency and severity and the uncertainties in each, leads to the loss distribution curve.
Users can enter their own preferred values to test the “what if” questions. For example,
- the cost of deciding not to defend on proof of breach can be compared with the cost of making such a defence.
- what if the precision of the estimated probability of proof of breach was decreased?
- what would be the mean loss in 5 years time?
User-defined systematic sensitivity analyses are enabled.
As with all models the key is to enter the right data. Ours is a “best data” approach based on the highest quality studies. This ensures self-consistency of the variables used in the model and avoids the problem of trying to combine the results of different studies each of which may have doubtful interpretations.
Why is it needed?
Solvency regulations require that insurers make best estimate loss calculations based on mean loss. One component of this is ENIDs. For ENIDs the approach they are looking for is that estimates are made for each proposed cause of loss and that probabilistic methods are used to make a best estimate of the net effect by year of projection. Liability insurers may have a dozen or so ENIDs that they believe are likely to occur within the next 10 years.
The new service therefore informs business planning, ERM and regulatory compliance.
How to get hold of this modelling service.
Models are provided to Radar subscribers at no additional cost. From January 2018, new subscribers to Radar will pay a joining fee to cover the commercial value of all models circulated to date. So long as the subscription is maintained, all subsequent models are provided at no additional cost.
Subscribers also have access to a reduced fee rate for confidential bespoke modelling work.
Non-subscribers may contract privately for such models.