The COVID-19 pandemic, climate change, cyberattacks, and other evolving socioeconomic issues continue to garner significant attention from property and casualty (P&C) insurance carriers. Each risk alone poses a unique challenge and an additional layer of complexity to a carrier’s risk profile. When faced with treating and/or exploiting new or evolving risks, solutions are often discussed in isolation, as if cause and effect were self-contained within a silo. However, recent events have repeatedly shown that these risks are not isolated to just one side of a balance sheet, or for one fiscal year.
Moving forward, risks of this nature will undoubtedly figure heavily into most P&C carriers’ enterprise risk management (ERM) and operational discussions. Now, more than ever, it is critical to consider both the interconnectedness and the long-term implications of complex risks faced today. How can carriers build a more resilient approach to managing this evolving risk environment?
Risk, meet analysis: A dynamic approach
A commonly used risk assessment tool for P&C insurers is stress testing; a deterministic set of assumptions based on “what-if” scenarios. While this approach can be simpler and easier to communicate, it provides carriers a narrower view of risk. The focus is typically limited to specific risks without consideration of correlation with other risks within the organization. Results are based on a limited number of scenarios and are evaluated over a fixed, usually short, time horizon. Though it serves a purpose in assessing individual risks, stress testing typically fails to address the increased uncertainty and variability that accompany most carriers’ overall risk profiles.
To effectively manage risk, a company needs to be informed about the ways in which a risk can spread across both sides of its balance sheet. A more robust risk management approach assigns a probabilistic distribution of outcomes of certain key risks and attempts to capture the interplay of these key risks with others. What is the impact on a carrier’s portfolio valuation if interest rates sharply spike? How does this new interest rate environment affect the carrier’s liabilities? What is the impact on surplus this year? Next year? Are capital levels still appropriate to support last year’s increase in retained property coverage? Conversely, what is the downstream effect of a booming economy on a carrier’s products? Liabilities? What surplus might be freed for investments or new products?
A stochastic economic capital model (ECM) is used to determine a level (or reasonable range of levels) of surplus needed to support an insurer’s overall appetite for risk. It attempts to mirror the changing environments in which carriers operate by incorporating the multitude of elements that affect an organization’s key sources of risk. Each stochastically generated scenario provides insights into the most relevant, quantitative risks that might impact a carrier. Combined, the many thousands of generated scenarios are used to form a distribution of possible surplus levels over a selected time horizon.
Of course, inherent in this distribution of potential surplus outcomes are tools already at management’s disposal (e.g., reserve and pricing estimates, asset returns, natural catastrophe model results, etc.). The added benefit of a stochastic ECM, however, is the combination of each tool under one cover, thereby eliminating the “silo” approach to evaluating risks. Doing so broadens the analysis in order to better quantify the correlations and interdependencies between risks on the carrier’s capital position.
An example would be to consider the many impacts of an increasing inflationary environment. What affect might this environment have on market value of fixed income securities as interest rates adjust, and how would the underlying economic conditions influence the ultimate settlement value of unpaid liabilities? A stochastic ECM would utilize an economic scenario generator to project a distribution of interest rate environments over a selected time horizon. Layered on top of these generated scenarios would not only be the simulated asset portfolio performance under the economic conditions, but a stochastically generated distribution of reserve development and payments in real dollars, and loss ratio results for current exposure in force. With this, management has a multifaceted tool allowing evaluation of both sides of its balance sheet under a multitude of economic environments—insight that can inform decisions regarding risk mitigation and asset-liability management strategies.
Further, risks evolve over time. While capital adequacy models oriented toward a one-year time horizon may satisfy, for example, compliance objectives, the dynamic nature of a stochastic ECM presents a unique opportunity to evaluate risks over multiple-year horizons. Was that nuclear liability verdict an outlier or indicative of an unforeseen trend? Being able to understand not only an organization’s ability to withstand a shock event, but the likelihood of adequate recovery (or expected time to do so), is a force multiplier in any risk management framework. With insight into whether the organization might encounter more headwinds, management can become more proactive in devising alternative ways to hedge or avoid future perils going forward. For example, as carriers position themselves to tackle the challenges related to long-term climate change, this type of model can be particularly useful tool for gauging impacts new strategies would have on capital levels.
Using a stochastic ECM demonstrates a thoroughness and rigor in risk assessment that can increase confidence beyond the management circle. Discussions among stakeholders, rating agencies, and regulators can become more substantive and informative. Speculation and vague notions about one-off risk scenarios are replaced by insight from analyses that estimate a distribution of all probabilities of loss. This discourse can further a better understanding of a carrier’s risk appetite; sharpen decisions related to capital investment, dividend distributions, and capital allocations; and promote more durable, competitive strategies.
Moving from a deterministic approach toward a dynamic risk framework nature shifts the management paradigm to a risk-adjusted platform based on risk transparency. Doing so allows executives to unravel interconnected risks, understand their long-term impacts, and build risk-resilient strategies across capital, underwriting, and investment. This move does not come overnight—it requires robust discussions of strategies and risk appetite, significant risk modeling efforts, and education of constituents, especially boards of directors. However, the initial investments will pay off many times over if a model evolves management’s business tactics and risk tolerances.
Recognizing the inevitability of risks continuing to spread quickly and forcefully across an increasingly interconnected globe, management must closely consider the importance of utilizing this risk analysis framework going forward.