Parametric Insurance for Disasters

One of the professional hazards in my line of work is that I’m at times invited to speak on topics that are complex and in which I have limited expertise. Last week, I had to speak on Parametric Insurance for Disaster Risk Management. For the uninitiated, in normal insurance, payouts are made through filing a claim, an assessment by the insurance company followed by a payout. In parametric insurance, the payouts are automatically initiated whenever a ‘trigger’ gets hit. For instance, an earthquake of a particular magnitude, a cyclone of a specific category etc. The advantage is that these products can circumvent the claim and assessment process.

A short summary of the inputs I shared:

One of the foundational principles of insurance is that losses are supposed to happen randomly and should be non-catastrophic. This is what makes insurance for disasters complex.

A general survey of the existing literature on Parametric insurance pointed me to products aimed at individual homeowners that offered protection from specific disasters. And as expected, these were all sold in the West. In India, where insurance penetration is abysmally low, parametric products aimed at the household is still a distant reality.

But what has garnered substantive attention in this space has been the parametric cover against extreme rainfall that Nagaland has purchased for itself from SBI General with Munich-Re as the reinsurer – an important milestone in the process of mainstreaming insurance as a risk mitigation tool.

However, to understand the potential of parametric insurance, one has to first grapple with the elephant in the room – the Disaster Risk Financing allocated to the states by the XV Finance Commission (XVFC). For the ongoing XVFC period, INR 220,000 crores have been allocated for Disaster Management with the States’ share being INR 160,000 crores. This allocation has been further funneled into four buckets –Response (40%), Disaster Mitigation (20%), Capacity Building (10%) and Recovery and Reconstruction (30%). The Response and Recovery windows are guided by National Guidelines that determine the compensation and Relief that can be provided. For example, INR 4 lakhs for death, INR 1.5 lakhs for loss of houses, etc. Despite this source of financing, the reality is that if you’re hit by a disaster, the relief component will barely cover your total losses. This is the reason why disasters keep wiping out development gains time and again.

Nagaland has an allocation of approximately INR 50 Crores each year for Disaster Management under the XVFC. So, say, if a payout happens under the parametric product, will the additional inflow top up the SDRF. If yes, will it be channeled to the Response Window to augment the compensation provided to the affected communities or will it be used for Mitigation? An analysis of the utilization of the pre-existing allocation to the state may also help in providing clarity in designing similar products for other states.

The other issue around the promotion of parametric insurance is the role of the private sector. Disaster Risk Financing has primarily been seen as the responsibility of the State. Involving the Markets in it can be politically tricky. Personally, being a libertarian, I believe that the State must have no business doing what the Private Sector can do efficiently. And in case of market failure, the State must be swift to intervene.

As a thought experiment, imagine a situation where insurance companies design parametric products based on the underlying risk profile of the buyer (in this case a state, city, district or village government). The price discovery through a fair competitive process would then act as a barometer of the state’s risk profile. This in turn would act as a signal and attract/repel future investments into the state, and encourage a stronger focus on risk mitigation interventions which in turn would get reflected in lowered premiums. Thus one can argue that in efficient markets, disaster risk insurance premiums can become climate adaptation tools. However, in India, in the current state of play, this is utopian thinking. Despite this, the ongoing dialogue with the private sector and small beginning as in the case of Nagaland are indicators of the government’s seriousness in mainstreaming insurance.

The other challenge in this domain is the Information asymmetry around the understanding of risk between the State and Private Sector. In insurance markets, risk models reign supreme. The aphorism, “All models are wrong, but some are useful” attributed to the British statistician George Box is pertinent here. State Disaster Management Authorities (SDMAs) must have detailed risk assessments at a sufficiently detailed scale, publicly available, and offered as the basis for insurance companies to work with in designing products. Presently, this is a distant reality in most states. The ability of the states to rely on the expertise of the private sector is also hampered by limited capacities within the SDMAs to draw up detailed Terms of Reference and by the complexities of carrying out technically sophisticated procurements.

States like Himachal Pradesh and Assam have commenced work in putting together their historic damage and loss data into a database. The Disaster Management Act of India is also being amended to include a provision for a national database on disaster statistics. Again, it’s important to note that the concept of a database belongs to the previous century. In a world that is moving from ‘automation to autonomous’ ways of functioning, policymakers have to be in sync with the revolutionary changes afoot in the AI/Machine Learning space. Remote sensing technologies are sufficiently advanced and need to be considered as tools to complement these processes.

The National Institute of Disaster Management’s Working Group Report on Disaster Risk Financing, Insurance and Risk Transfer’ had some interesting datapoints on the Indian states’ historic losses due to disasters compared with the allocations made under the SDRF. As a next step, an analysis of the nature of these losses in terms of sectors affected, primary hazards involved, nature of losses and a forensic review of the quality of utilization of the XVFC allocations under the windows of Mitigation and Prevention may be a way forward to better understand and argue the case for parametric insurance products.

And finally, Governments themselves are the ‘Insurers of Last Resort’. Developing parametric products for them should not be the sole focus of the industry. The more complex task of designing products aimed at households that protect assets and livelihoods should be explored. With time, transparency and a healthy market should lead to affordable products that Panchayats or Urban Local Bodies could then subscribe to. Affordability is key here. After all, as the adage goes, “Price is a signal wrapped up in an incentive.”

Further Reading:

• The Promise of Parametric Insurance by Safi Ahsan Rizvi, Advisor National Disaster Management Authority India
• Jonathan Gonzalez from Raincoat speaking on Parametric Insurance: Here and Here (In fact, Spotify has numerous podcasts on the topic with insights from the movers and shakers of this field)
• Carolyn Kousky’s writings on Insurance and Disaster Management

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