Insurtech Is Reinventing Alternative Risk Transfer for Insurers and Investors
Originally published in Financial IT
At the intersection of insurance and capital markets, the alternative risk transfer market enables insurers and reinsurers to pass on their risks to third parties, in innovative ways, using the financial markets.
Insurers traditionally transfer risk to reinsurance companies, who earn the premiums associated with the risks. However, the reinsurance sector lacks the capacity to provide solvency relief and liability hedging for immense market needs, which leaves trillions in unfunded liabilities.
Beyond reinsurance, the current market for alternative risk transfer to the capital markets is dominated by catastrophe risks. But catastrophe losses from floods, fires and storms have been escalating in recent years due to climate change.
This paves the way for significant growth in the alternative risk transfer market for Life and Property and Casualty (P&C) risks. Unlike catastrophe risks, Life and P&C risks are mostly high frequency and low severity and provide predictable investment returns. Advanced data-driven methods can be used to model these risks and structure them in standardised financial vehicles, by leveraging technology for objective, accurate prediction.
To turbocharge the transfer of insurance risk to the capital markets, it’s crucial to develop and apply transformative data-driven technologies for risk management. AI-based technology can enable the structuring, pricing and placement of deals to transfer this risk more quickly, transparently and at a much greater scale. It can accurately predict the future development of liabilities, improve the accuracy of expected loss projections and help mitigate risk. The enhanced accuracy and transparency enables ratings agencies to participate by applying their ratings methodologies – a crucial step to democratise and broaden access for capital markets investors.
The AI technology is fed large data sets from stochastic sources, such as historical data from the underlying portfolio, and non-stochastic sources, including inflation data or extreme events, over which the risk models train. The AI risk modelling technologies then run simulations on these data sets to select the model with the best predictive power for forecasting best estimate, standard deviation and stress scenarios used to structure the deals.
These technologies help unlock the market for new participants and drive innovation in how products are structured. For example, Vesttoo has used AI technologies to create the first risk transfer vehicle which pools reinsurance deals and allows investors to use existing assets as collateral, rather than requiring the direct allocation of cash. The Insurance-Linked Program (ILP) lets investors pledge high-quality assets, such as corporate bonds, as collateral for reinsurance deals, earning additional spread from existing assets while minimising risk due to the technologies used to structure the programme.
Ultimately, these advanced technologies can help realise an exciting vision which fuses the insurance and capital markets, facilitates access to a wide range of insurance risks for capital markets investors and provides liquidity and much needed capacity in the reinsurance ecosystem.
Yaniv Bertele, CEO at Vesttoo