Sometimes, it can feel that insurance payouts are elusive creatures. Small risks are too inconsequential to merit a payout, and are dispensed with by excesses. Huge risks, on the other hand, are either excluded or subject to arbitrary payment limits. So getting a payout becomes a question of hitting the sweet spot between a claim event that is too small and a claim event that is too big. There are many sound commercial reasons for insurance companies excluding both small and very large claims, but it can create a feeling that the sector runs a ‘heads you lose, tails I win’ approach.
Is there a clearer way to present the logic behind insurers’ approach to exclusions that is related to consumer needs? Perhaps one approach might be to link payments to benchmarks; rather than to absolute monetary amounts. For example, if there is a huge event, such as a national lockdown for a pandemic, it is not unreasonable to assume that the government that introduces a lockdown is also going to put in place financial measures to mitigate the impact for firms and individuals.
To maintain cover for everyday risks while excluding cover for huge, systemic risks that the government should be catering for, policies could promise to make payments relative to a certain benchmark. So, for example, if we are living under a regime of social distancing, the policy would not pay out if a business’s income fell in line with the benchmark for the rest of the sector that is also subject to social distancing. But if that business suffered flooding, the insurance would cover the loss of revenue that exceeded the benchmark.
Of course, this approach has its own challenges – which benchmark do you choose? How do you know you are applying the right benchmark to a particular business? How do you explain the extra complexity that comes with this novel approach? However, despite these challenges, this design could help to reduce confusion about what a policy is all about – whether it is an expensive policy for all risks, or a more affordable one for medium-sized ones.
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