Welcome to the
The Ten C's
The approach being espoused will for at least the short term be referenced as the Ten C’s of Parametric Disaster Response, the respective C’s noted below with a brief description.
Systemic risk management is beyond any one constituency to collect data for, analyze, underwrite, price, determine indexes, sell product, administer, coordinate, pay, etc., and its effects cross over many jurisdictions. As such any solution needs to embrace the strengths of constituencies, and recognize the weaknesses therein. In addition, application of sources of funding, administration, legalities must be leveraged.
This is the basis of any program- what is covered, how is it determined, are all constituencies attended, are there layers of cover, or different types of cover? Application of historic data analysis, artificial intelligence, and complex data aggregation is just a start for this C.
The approach would not be indemnity-based but reflect an agreed parameter or parameters and afford benefits to a contributing constituency, and/or constituency that has significant effects in an economy.
What will trigger a parametric response constitutes this factor. What disaster will prompt the cover, and what index/trigger will drive the enactment of a payment? Cyber? Climate change? Pandemic? The measure must be uniform, easily verified and a direct function of an economic loss.
The breadth of the current pandemic suggests enormous capacity is needed in the market, even in a parametric response. How will adequate capacity levels be projected to ensure the program is viable to all involved regions when a covered disaster occurs? Capacity also suggests sufficient involvement of capital to satisfy demand and accommodate pricing models.
An exemplar $500 Bn fund would be difficult to fund immediately, but could be funded over eight years, $5 Bn contribution per month at 4% interest. Having a balance of backing/contribution would produce many capital investment options, hedging options and participation options for capital markets. There are examples of regional disaster bonds/funds in the market now; this program would expand the breadth of and financial extent of cover. With rei and government backing the initiative can even prompt formation of more localized response cover.
There is precedent for large organizations in self-insurance- captive organizations. Adaptation and expansion of the captive insurance concept in terms of systemic risk is a recommended key factor. There is experience that can be applied, and a regional or global fund can serve as backstop for organizations who choose to have captive arrangements as their primary response. Political-based captives may be an option.
Traditional insurance reserving and capitalization is inadequate for systemic risk planning. COVID-19 has proven a needed recovery would exhaust existing capital held by insurers for all lines. Engaging capital markets, cat bonds, ILS, etc. would be required and potentially beneficial for investors and those who would apply the finds for response. Designating funds as tax-free vehicles would build attraction for investors. Government backing would be present not as primary, but as backstopping availability.
Probably the most important factor- the need for active collaboration from multiple constituencies, multiple countries, multiple regions, governments, funding sources, insurance organizations, etc. Encouraging participation and benefits for agents/brokers and syndicates would ensure more robust participation and understanding of benefits of parametric plans.
Another key- funding, involvement, admin, data analysis, investment, projections must be vigorous over time. Involvement must be compelled either overtly or indirectly to counter political tendencies to forget issues. Ongoing effort from all collaborators is vital to ensuring that when an index is triggered there will be funding and response efforts sufficient to the need. An example- backing bonds that remain uncallable for an extended period, or regulation/laws that mandate policyholder contributions to the initiative.
As has been seen post-COVID the burden of bureaucracy and legislation is proving to be an impediment to releasing resources to businesses and individuals.
There must be assurance that when a trigger moment is reached there will be accurate and prompt distribution of parametric payments, with a focus on business for an insurance product (individuals’ response would be seemingly an insurmountable insurance task.) Implementation of distributed ledger technology would be a meaningful addition to a systemic risk coverage response- trigger, payment data, payment.
How to encourage business contributions? Employment of tax credit or favorable tax handling of premiums and contributions to associated insurance policies or funds. Reduction of moral hazard views of the funding is important.
Mandating funding (such as is applied for TRIA funding) levels the funding playing field.
Dr. Marcus Schmalbach
Dr. Marcus Schmalbach is Founder and CEO of RYSKEX GmbH. He has a long-standing experience in risk and captive management in various industries. Before the founding of RYSKEX he was Head of German MBA program. He is still working as a visiting professor on Innovation and Risk Management matters and also academic head of BlockART Institute with a research focus on GIG companies, Parametric Risk Trading, Blockchain Technology and the impact of AI on the captive value chain.
Joerg is an experienced insurance executive and advisor to the insurance industry. Over the past decade, he worked in leadership positions with P&C insurance carriers, Chubb and CNA Insurance, most recently as VP of Strategic Engagements. Joerg has a track record of successfully leading corporate initiatives, building partnerships and bridging the gap between business and technology. In 2019, he launched his own advisory practice with the goal to accelerate the transformation of the insurance industry. Joerg holds an MBA from London Business School and a Master’s in Electrical Engineering from Karlsruhe Institute of Technology.