Setting actuarial assumptions has always been a complex challenge for actuaries. The 2008 financial crisis brought significant volatility in the global equity markets, creating difficulties for companies relying on mean reversion assumptions for their investment-linked products and long-term guaranteed contracts. As a result, actuaries faced increased scrutiny regarding their selection of lookback periods and whether they should have included volatile experience data in the assumption setting process.
More than a decade later, actuaries now face the challenge of setting assumptions under new accounting standards such as US GAAP Long Duration Targeted Improvements (LDTI) and International Financial Reporting Standards (IFRS) 17, all while navigating the lingering impacts of the COVID-19 pandemic. Under current circumstances, assumptions that have historically been stable, such as mortality, now require more vigilance given the increased visibility and consequences under the new accounting and disclosure standards. More than before, how assumptions are developed, supported and perceived are just as important as the actual assumption.
With market analysts, rating agencies and regulators putting the industry under a magnifying lens, it is our opinion that actuaries can no longer rely on the use of conservatism in setting assumptions. Continued use of consistently over/underestimated assumptions will likely raise questions of bias from stakeholders, possibly undermining a company’s credibility and thereby affecting its favorable credit rating and confidence among investors.
In response to this situation, the industry has adopted a range of approaches to analyze and set the ultimate mortality assumptions in a post-COVID environment. Three main approaches have emerged; the first two are the most common, while the third is seldom used: (1) exclusion of COVID mortality data, (2) partial inclusion of COVID mortality data with adjustments, and (3) inclusion of COVID mortality data without adjustments.
Many companies chose to exclude COVID-tainted data entirely, viewing the event as an anomaly and unlikely to recur. Another significant portion of companies elected to include partial COVID data with adjustments, to moderate the pandemic’s impact while also taking short-term and long-term disruption into consideration. A smaller group included COVID data without any adjustments, treating the data as part of the evolving mortality landscape.
For companies that opted to exclude COVID data entirely, this allows them to preserve the continuity of historical pre-pandemic trends thereby basing forecasts on “normal” conditions. While this helps avoid distortion from the short-term volatility introduced by COVID, it does not recognize the changes in mortality that may persist during and beyond the initial crisis, given that US health officials now consider COVID-19 to be an endemic disease (Stein, 2024).
On the other hand, partial inclusion of COVID mortality data with targeted adjustments allows actuaries to acknowledge disruption and emerging trends. This approach offers a balanced view, but at the risk of introducing subjective adjustments that could raise more questions on the appropriateness of the adjustments and use, compared to other options.
Including all COVID mortality data provides greater transparency, accurately reflecting observed experience in the assumption setting process. While this approach portrays the current reality, it also raises questions of applying excessive weight to an unusual, infrequent and extraordinary event, increasing volatility and mispresenting long-term risk.
All three of these approaches offer valuable insights on mortality risk and are valid, provided they are supported by rigorous evaluation, precise documentation, and clear rationale over relevant and credible data. There is no set standard or preferred approach; rather, the key is not which method is chosen, but the level of transparency and credibility supporting the ultimate assumption.
Given the variety of reasonable approaches, it’s imperative that companies analyze experience data and the mortality assumptions developed through different perspectives and, perhaps, in tandem. While a single assumption is ultimately selected, reviewing the data with and without the COVID pandemic impacts, much like sensitivity testing, can yield valuable insights. In the same vein, equal importance must be allotted to reconciling any negative evidence introduced by the alternative approaches which were not chosen. For example, if a company decides to exclude COVID data, this decision should be justified by demonstrating COVID is an endemic event, unlikely to distort future expectations and quantifying the potential impact. Adopting a multi-lens approach can assist in uncovering biases, understanding the impact of including/excluding experience data while supporting informed and credible decision-making.
At its very core, the effectiveness of assumption setting ties back to actuarial judgment. The focus should not be on which method is most popular, but on how professional judgment shapes the ultimate results. Under the current regulatory environment, continued misalignment of assumptions will likely raise red flags. Assumptions and the resulting model outcomes they support need to be explainable, appropriate, and periodically reassessed. When developing actuarial assumptions, the decision to include or exclude COVID data or any other adjustments should consider the associated impact on results and broader appropriateness.
Beyond the immediate mortality impacts, COVID-19 introduced residual effects that actuaries should consider. These include delayed medical screenings, increased late-stage diagnoses, and other indirect consequences. Given the long-term nature of the mortality assumption, actuaries should consider being cautious about overreacting to early trends and prematurely discounting future shifts.
Navigating forward, there are several guiding principles that companies could leverage in this complex environment. Assumption reviews could be conducted under multiple lenses to fully understand the impact of decisions. Furthermore, companies might consider avoiding aligning to a single industry standard, justified logic and context are essential to informing decisions. Backtesting should be helpful when performed to retrospectively analyze the fit of assumptions, thereby safeguarding ongoing appropriateness.
Conversely, companies should consider avoiding excessive, granular analysis, as it can obscure broader trends. Also, eliminating actuarial judgment in favor of purely mechanical approaches, ignoring company-specific data, or overlooking the underlying causes of volatility can all potentially undermine the credibility of assumptions.
Ultimately, it’s an actuary’s role to help navigate uncertainty while applying sound judgment and maintaining clear communication. By embracing a multi-lens approach, documenting decisions transparently and maintaining consistency and credibility, actuaries can assist their companies in meeting the demands of an increasingly complex and scrutinized regulatory and reporting environment.
This article is provided for informational and educational purposes only. Neither the Society of Actuaries nor the respective authors’ employers make any endorsement, representation or guarantee with regard to any content, and disclaim any liability in connection with the use or misuse of any information provided herein. This article should not be construed as professional or financial advice. Statements of fact and opinions expressed herein are those of the individual authors and are not necessarily those of the Society of Actuaries or the respective authors’ employers.
Matt Clark, FSA, MAAA, is a principal for Deloitte Consulting LLP. Matthew can be contacted at matthewclark@deloitte.com.
Thomas Chamberlain, ASA, MAAA, is a managing director for Deloitte Consulting LLP. Thomas can be contacted at tchamberlain@deloitte.com.
Kwesi Acquah, FSA, MAAA, is a senior manager for Deloitte Consulting LLP. Kwesi can be contacted at kacquah@deloitte.com.
Justin Peterson, FSA, is a specialist leader for Deloitte Consulting LLP. Justin can be contacted at jpeterson@deloitte.com.
Harjas Sahni is a manager for Deloitte Consulting LLP. Harjas can be contacted at hsahni@deloitte.com.
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References
Stein, R. (2024, Aug. 9). Is COVID endemic yet? Yep, says the CDC. Here’s what that means. NPR.