It’s times like these with a global pandemic when we are reminded- insurance as a concept is simply not that complicated. We make it so, with regulation, complex policy language, limited access to the products, seemingly endless variety of lines, mystique about its function, a vernacular that challenges even the legal world, etc.
Why this matters is that most cultures/countries/economies are ill-suited to deal with unexpected events like the novel coronavirus, or COVID 19. It’s not the occurrence of COVID 19 as much as its direct or indirect adverse effects of the outbreak that touch each of us in different ways, and our distress when there are few mitigative measures of which we can avail ourselves to limit health or economic consequences.
Setting aside health care responses, the entire global economy is suffering an economic shock from COVID 19 since its first reported cases. Unlike natural disasters like typhoons, tornadoes or earthquakes, there are few financial backstops for individuals, businesses, industries, regions, countries or governments when a viral outbreak occurs, or in straight language, little insurance cover for the outbreak’s effects. Let’s keep in mind that insurance cover does not solve the problems of natural disaster, but insurance cover provides a peace of mind that some of the effects can be dealt with and there is continuity. We humans even gain comfort in the planning of insurance cover- yes, with paid premium there is this or those coverage benefits, interruption cover, funds to jump start getting back to normal. Not so much with COVID 19 and coverage- we are all naked to that risk, and we just don’t like that. There’s even anger that ‘someone’ didn’t help us plan for the possibility of a COVID 19, that a huge economic whack was not planned for, that a clear trail to recovery was not mapped out for our use. In fairness insurance companies could not make those plans because insurance companies knew that a pandemic occurrence would be impossible to plan for- too costly, too widespread, too concentrated of costs, plenty of indirect losses that fly in the face of typical coverage drivers, and so on. As such what could be planned was placement of exclusions from coverage pretty much any adverse outcomes of a viral outbreak. That risk management was really the only easy decision to make.
As we go forward from COVID 19 (and we will), efforts must be made to not repeat the economic experiences of this outbreak, if it’s possible. The continuing difficulty for business is that viral outbreaks have been uninsured risks, or a huge coverage gap. Can the risk be approached uniquely from the many levels of business that are affected? One might think so.
The case and parameters
Consider one example- cancellation of a business conference due to risk of exposing attendees to a health danger. The cost of the cancellation is reflected in many ways but let’s consider the organizer’s position in terms of risk management:
- The cost of planning, organizing, marketing, and outfitting the event
- The cost to the event’s brand
- Contractual costs for keynote or hired speakers
- Deposits or upfront costs to vendors
- The cost of reserving a venue
- Potential costs of rescheduling
The index or trigger
These are quantifiable in terms of expenses that would be foregone if an event is cancelled, so that part of the issue is easy. What is not as easy-
- How to decide if an event must be cancelled or if the organizer chooses to cancel
- What determines if a cause can be pre-identified as a potential outcome?
- Does the cause have to exist in the event’s location, or can it be regional/national in nature?
- And so on.
And the ‘big dog’ challenge- how to determine a probability of the underlying outbreak condition occurring such as the underwriting of risk can be calculated.
These discussion points have typically been daunting because the gap between true economic injury and overall outbreak basis risk has been difficult to bridge. The advent of AI methods that are more effective in and capable of determining commonalities in the breadth of available data provides opportunities in narrowing the gap to the point where loss parameters and indexes can be determined and priced. Indemnity models have not been practical for the types of claims in discussion, but the efficacy of parametric products increases. Not having to calculate a loss for indemnity, but instead establishing a trigger and agreed payment based on the respective trigger being reached reduces admin costs, investigation, reserving questions, among other benefits.
If the concept is referenced back to the event cancellation example, would there be a change in an underwriter extending parametric cover that includes a risk such as the COVID 19 outbreak? It might if what the policy covered was specific, addressed key economic factors for the insured, had a specific trigger that is uniform across health outbreaks, and could be empirically confirmed. Such a policy would not have to be written to reimburse direct and indirect costs for the insured, but since nothing is covered now a targeted parametric policy would be attractive, and premiums could be rolled into registration and sponsorship costs.
There could be many parameters and associated triggers/indexes for these products, and perhaps even many participants (captive parametric?) How best to keep those data fully transparent and uniformly updatable? Consider Blockchain/distributed ledger technology to be a framework for what might be a series of factors, and for what might be changing parameters over the life of the policy. In the absence of insured property the policy form can adapt to depth and breadth of coverage, and (potentially) to addition or removal of participants. DLT would be a suitable and verifiable record of the policy and its factors.
The unique nature of parametric cover and the trigger- an outbreak- the backing for the polices may also reside outside typical insurance financing (depending on amount of cover) or require reinsurance backing. The cover seems an ideal opportunity for risk sharing/financing with catastrophe bonds or other insurance linked securities (ILS), and with potentially many contracts or layers of risk the sharing of risk among multiple backers could be facilitated through ILS exchanges. Distribution of risk to shelter any one backer from a shock-style claim would be an additional attraction for the ILS network.
With agreed parameters, uniform, verifiable indexes, and clearly described participants payment can be immediate from continuously verified sources, perhaps using payment platforms and thus closing the loop from parameter to payment.
The scenario noted above is one basic approach to what can be a broader effort in closing coverage gaps, not through wrestling indemnity, but in recognizing some risks are difficult to insure, unless the risk is approached in smaller bites and dealt with on a parametric basis.
Advances in AI, expansion of capital markets in risk financing, and adjusting risk recovery expectations for insureds will be the cushion that softens the next economic blow from a similar outbreak. But don’t get caught up in this example- the concepts can carry into almost any hard to write risk, regional risk, or whatever can be identified for probability of occurrence. New thinking. New protection.