Alternative ways to Structure Parametric Solutions

Basis Risk

Simply put, basis risk refers to the possibility that losses incurred by the policyholder exceed the pre-agreed payout upon the policy’s index diverging from the non-trigger interval. Basis risk works both ways, it is the difference between the actual economic loss and the payouts made by the parametric structure.
This is a risk that is not present to the same extent in traditional, loss/liability-based insurance policies, but can be an issue with parametric insurance policies. However, a combination of robust loss correlation modelling, high-quality data analytics and bespoke policy design in the index and trigger can go a long way to minimising basis risk in parametric policies

Double-Trigger Contracts

Double-trigger contracts rely on two, uncorrelated triggers determining contingent payment. We specify uncorrelated because, if the two triggers are highly correlated, it would in most cases be possible to construct a single-trigger parametric contract serving the same function. The pricing of such contracts can be more complex, but the underlying theory and use case are similar to those for single-trigger policies. So-called “cat-in-a-box” policies, where payout is determined by a sufficient intensity of event (1 st trigger) occurring within a certain geography (2 nd trigger) are an example of a double-trigger policy, and represent one of the most popular policy types currently available in the market.

Data

The bedrock of any well-structured parametric risk-transfer solution is high-quality, available data to monitor and assess the policy’s trigger. Any risk to which one can apply an index is, in theory, a risk which can be mitigated by appropriate parametric coverage. However, the index that is developed must be supported by quality data of sufficient reporting frequency. This then also helps to supports the ability of the calculation agent, an independent third party on parametric contract, to support the settlement of claims, calculation of the index, choice of data etc. Where traditional insurance policies may be based upon individual, complex loss distributions whose intricacies require specialist expertise to fully appreciate, parametric policies can be based upon publically-available indices backed with a significant reservoir of past data for analysis. This has the potential to reduce information asymmetries.

The data must also take into account the impact of trends such as climate change in the design of the structure. Simulations and models are based on detrended data. This means that in structuring to solutions there needs to be robust modelling capabilities in the process that often requires strong actuarial and econometric skills along with technical knowledge of the risks involved.

Modelling Risk Correlation

Necessarily, the trigger associated with a parametric insurance policy should be highly correlated with financial loss. Policyholders will benefit most from the payout at points where cashflows and liquidity become stressed. However, the process of determining the correlation between an adverse climate-related peril and financial loss may not be straightforward. Catastrophes are tail events, and by their very nature past experience is limited. Like any model, a climate model, no matter how rigorous, relies on some degree of judgement and the underlying assumptions may be open to challenge.

Moral Hazard and Structuring

Providers of climate-focussed risk-transfer solutions need to carefully consider the moral hazard associated with parametric solutions. Properly structured parametric policies should provide adequate protection while minimising moral hazard. Ideally, novel insurance solutions will instead incentivise the improvement of climate resilience for an organisation and give policyholders breathing room to enact any necessary climate adaptations. With the link broken between loss and sum assured, parametric solutions are less likely to induce riskier behaviours. Even where a potential loss is almost certain to be less than the parametric cover, the payout is pre- agreed, so policyholders are still incentivised to minimise loss as any payout not used to cover damages will still be realised and can be redeployed elsewhere.

 
Previous
Previous

How Banks can use Parametric Solutions to protect their Credit Risk Exposures from Nat Cat Events

Next
Next

How Parametric Insurance Solutions can Increase resilience for the Agricultural Sector