The impact of COVID-19 on actuarial assumptions

A 3D framework for the insurance industry

In the absence of complete, readily available data, how can insurers quantify the impact of COVID-19 in their actuarial assumptions? Start the journey with a three-dimensional framework that can help develop a hypothesis based on awareness and sound analyses.

Confronting uncertainty

Many insurance companies are navigating the impact of COVID-19 on their business and the uncertainty of the future across a spectrum of operations and coverages. In spite of this uncertainty, actuaries still need to set assumptions that drive pricing and measure financial impacts.

How do actuaries approach the assumption-setting process for morbidity, mortality, and mortality improvement in 2021 and 2022 resulting from COVID-19? When does one start accepting that readily available data is limited and perfect data does not exist, regardless of effort? Starting the assumption-setting process by developing a hypothesis based on awareness supported by data and sound analyses is a step in the right direction.

Actuarial assumptions and COVID-19

Awareness of COVID-19 impacts

Variations exist in the level of risk that COVID-19 presents to the insurance industry. As we apply professional actuarial judgment about the impact of the pandemic on actuarial assumptions, we consider the levels of risk that inform our judgment.

  • Primary: The primary risk from COVID-19 infection is death
  • Secondary: The secondary risk from COVID-19 infection is hospitalization and survival, or asymptomatic or symptomatic infection that does not result in hospitalization
  • Tertiary: The tertiary risks from COVID-19 infection are societal, economic, and emotional impacts that will continue to emerge along with the long-term impacts of the secondary risks

Establishing a “universe of sorts” for a hypothesis creates a framework to explore and build a rationale that can be shared across key stakeholders in a manner that does not demand ownership or that becomes too theoretical.

Establishing a hypothesis

Due to so much uncertainty across the time horizon of the impact that the virus can have, we establish a hypothesis based on available indications. Given the three-levels-of-risk framework noted above, and the experiences observed over the past 16 months, a hypothesis that explores a short, medium, and long-term set of impacts on an individual’s mortality/morbidity as a result of COVID-19 can be developed. This framework can be adapted to various insurance products inclusive of property/casualty and liability insurance.

Assessing the data

The availability of documented and recorded data related to COVID-19 mortality and morbidity impact is far from perfect. Companies will be faced with accepting the quality of the data, learning from it, and making adjustments, as necessary.

Companies should start by taking an inventory on what data is available and then evaluate the data, using a critical mindset to apply actuarial judgment. It will be important to establish a framework that clearly documents judgment versus fact that is used in the evaluation of the evidence.

To gain insight, consideration could be given to past pandemics, such as the Spanish flu, bird flu, or swine flu. Impacts from these previous pandemics could provide valuable information for assessing the data from the COVID-19 pandemic.

Performing analysis

Similar to performing traditional mortality experience studies, companies could consider segmenting the population by risk category, such as age. The population may not be equally impacted, therefore segmenting the analysis to consider age grouping may be a practical approach.

We segment the population into low risk (younger ages), medium risk (middle ages), and high risk (older ages) categories. Thus far, we have seen that the younger and middle ages may be less impacted by the primary risk from COVID-19. However, secondary and tertiary impacts may be more prevalent. For the older ages, the primary risk may be the most predominant; however, in the long term, this may result in reduced mortality yet still an increase in morbidity.

For mortality improvement, a study may not be necessary. Companies could consider reducing mortality improvement by age group and for a certain length of time. Judgment in this area will be critically evaluated and should be subjected to rigorous documentation.

A hypothesis matrix for morbidity might consider how long-term-care benefit costs might decrease due to mortality in the short term but spike in the long term. As with mortality, morbidity assumption assessments, made within a risk- and duration-driven framework, help the actuary to ensure consistency of thought and reasonableness of recommendations.


Assumption setting in a challenging environment

Although much time has passed since the pandemic started, there are still a lot of unknowns around the impacts resulting from COVID-19 and the data that is presented to us for consumption. In setting actuarial assumptions, judgment should always be used. We must take the knowledge that we have gained with the data in front of us and continue to perform sound analyses to arrive at the best conclusion. Then, we must communicate our evolving conclusions clearly and succinctly.

Get in touch

Thomas Q. Chamberlain, ASA, MAAA
Managing director | Actuarial and Insurance Solutions
Deloitte Consulting LLP
+1 312 486 3828

Matthew Clark, FSA, CFA CERA, MAAA
Principal | Actuarial and Insurance Solutions
Deloitte Consulting LLP
+1 312 486 0185

Maria Itteilag
Senior manager | Actuarial and Insurance Solutions
Deloitte Consulting LLP
+1 860 725 3228

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