Group Life COVID-19 Mortality
Survey Report
NOVEMBER | 2023

Group Life COVID-19 Mortality Survey
ReportAUTHORS

Patrick Hurley, FSA, MAAA
Mike Krohn, FSA, CERA, MAAA
Tony LaSala, FSA, MAAA
Rick Leavitt, ASA, MAAA
Cynthia S. MacDonald, FSA, MAAA, SOA
Patrick Nolan, FSA, MAAA, SOA
Steve Rulis, FSA, MAAA
Matthew Sawyer, FSA, MAAASPONSORS

Group Life Experience Committee

Caveat and Disclaimer
The opinions expressed and conclusions reached by the authors are their own and do not represent any official position or opinion of the Society ofActuaries Research Institute, Society of Actuaries, or its members. The Society of Actuaries Research Institute makes no representation or warranty to theaccuracy of the information.
Copyright © 2023 by the Society of Actuaries Research Institute. All rights reserved.

3

CONTENTS
Section 1: Purpose of the Survey ............................................................................................................................... 5
Section 2: Overview .................................................................................................................................................. 6
2.1 Background .............................................................................................................................................................. 6
2.2 Scope ........................................................................................................................................................................ 6
2.3 Survey Highlights ..................................................................................................................................................... 7
Section 3: Group Life Mortality Results—Reported Death Claims ............................................................................ 11
3.1 Reported Claim Incidence by Count—All Causes ................................................................................................. 11
3.2 Reported Claim Incidence by Count—COVID-19 Versus All Other Causes ......................................................... 12
3.3 Reported Claim Incidence by Amount—All Causes ............................................................................................. 14
3.4 Reported Claim Incidence by Amount—COVID-19 Versus All Other Causes ..................................................... 14
Section 4: Group Life Mortality Results—Estimated Incurred Death Claims ............................................................. 15
4.1 Incurred Claim Incidence by Count—All Causes .................................................................................................. 15
4.2 Incurred Claim Incidence by Count—COVID-19 Versus All Other Causes .......................................................... 16
4.3 Incurred Claim incidence by Amount—All Causes ............................................................................................... 18
4.4 Incurred Claim Incidence by Amount—COVID-19 Versus All Other Causes ....................................................... 18
4.5 Development of Face Amount Trend Assumption............................................................................................... 18
4.6 Other Drivers of Amount Versus Count Mortality Differences ........................................................................... 20
Section 5: Estimated Incurred Mortality Results by Segment .................................................................................. 22
5.1 Industry .................................................................................................................................................................. 23
5.2 Geography .............................................................................................................................................................. 24
5.3 Age and Sex ............................................................................................................................................................ 25
5.4 Company Size ......................................................................................................................................................... 28
Section 6: Detailed Cause of Death ......................................................................................................................... 29
Section 7: Exposure Trends ..................................................................................................................................... 36
7.1 Premiums ............................................................................................................................................................... 36
7.2 Lives ........................................................................................................................................................................ 37
Section 8: Company Variations ............................................................................................................................... 39
8.1 Variations in COVID-19 Mortality Results ............................................................................................................. 39
8.2 Variations in COVID-19 Claim Coding Procedures ............................................................................................... 40
8.3 Variations in Claim Reporting Patterns................................................................................................................. 40
Section 9: Comparisons to General U.S. Population Mortality Results ..................................................................... 41
9.1 Aggregate Excess Mortality Comparisons ............................................................................................................ 41
9.2 Excess Mortality Comparison by Age.................................................................................................................... 42
9.3 Excess Mortality Comparison by Geographic Region .......................................................................................... 54
Section 11: List of Participating Companies ............................................................................................................. 57
Appendix A: 2020 SOA Group Term Life COVID-19 Mortality Survey Data Request ................................................. 58
Appendix B: Geography and Industry Code Mappings ............................................................................................. 61
Appendix C: Survey Methodology and Documentation ........................................................................................... 66
C.1 Documentation ...................................................................................................................................................... 66
C.2 Results Processing and Review ............................................................................................................................. 68
C.2.1 Completion of Claims ............................................................................................................................. 68
C.2.2 Broader Classification of Segment Information ................................................................................... 68
C.2.3 Unknown Claim Diagnosis ..................................................................................................................... 68

Copyright © 2023 Society of Actuaries Research Institute4

C.2.4 COVID-19 Claims from 2019 or Earlier ................................................................................................. 69
C.2.5 Groupings by Company Size .................................................................................................................. 69
Appendix D: Completion Factor Development ........................................................................................................ 70
D.1 By Claim Count ...................................................................................................................................................... 70
D.2 By Face Amount..................................................................................................................................................... 72
D.3 By Cause of Death ................................................................................................................................................. 72
D.4 By Company Reporting Speed .............................................................................................................................. 73
Appendix E: Cause of Death Mapping ..................................................................................................................... 74
About The Society of Actuaries Research Institute .................................................................................................. 75

Copyright © 2023 Society of Actuaries Research Institute5Group Life COVID-19 Mortality Survey Report
Section 1: Purpose of the Survey
The purpose of this survey was to gather a high-level view of U.S. Group Term Life Insurance mortality results during
the COVID-19 pandemic, as compared to prior period baseline mortality results. COVID-19 is caused by the novel
coronavirus SARS-CoV-2, which was identified in 2019. As of the writing of this document, complications fromCOVID-19 have resulted in more than 1.1 million deaths in the U.S. alone, and more than 6.9 million worldwide.
This report is an update to the previous Group Life COVID-19 Mortality Survey published in June 2023, which
included pandemic data from April 2020 through December 2022. This update includes Group Life mortality resultsfrom April 2020 through June 2023 (referred to in this report as the “pandemic period”), representing 39 months ofGroup Life mortality experience during the COVID-19 pandemic.
The survey was conducted by the Group Life Experience Committee (the Committee) of the Society of Actuaries
Research Institute and has been structured as a recurring monthly data collection and compilation process from U.S.
Group Term Life insurers. The datasets for this report encompass all Group Term Life claims for the calendar years
2017–2022 and the first half of 2023 reported to participating carriers as of June 30, 2023, and include more than
2.9 million claims and more than $131 billion in earned premium. The Committee is grateful that 20 of the top 21
U.S. Group Term Life insurers focused on employer groups participated in this survey, with market sharerepresenting roughly 90% of the employer-based Group Term Life industry. Thus, the Committee believes thefindings herein are representative of the COVID-19 mortality impact on the U.S. Group Term Life industry as awhole.
Guiding principles for the survey include the following:•••

Providing timely information on total high-level Group Life mortality results versus baseline expectations
during the pandemic is the most important goal. Thus, the survey is not a seriatim mortality study. Rather,
it is a synopsis of monthly Group Life exposures, death counts and amounts.
It is critical for this survey to compare current Group Life mortality from all causes of death to the baseline
expected all-cause mortality levels. The Committee recognizes the existence of limitations in the ability tocode deaths as COVID-19 related, within both the general population and Group Life exposures. Also, thesurvey seeks to analyze whether the pandemic has had indirect impacts on population mortality, beyond
deaths associated directly with the COVID-19 virus. Thus, tracking just Group Life deaths coded with acause of COVID-19 may not accurately measure the total impact of the pandemic.
The Committee asked carriers to provide segmentation data when feasible. However, the Committee did
not want the additional detailed data request to become so onerous that it materially delayed the survey
reporting process or shrank the number of carriers willing and able to participate. Thus, the survey included
high-level exposure and claims data for all 20 carriers, but many of the segmentation data are based on
results for just subsets of carriers.

Copyright © 2023 Society of Actuaries Research Institute6

Section 2: Overview
2.1 BACKGROUND
Carriers provided a complete set of monthly Group Life exposures dating back to January 2017, along with all Group
Life death claims reported in January 2017 or later. The reported death claims also identified the months of death,that is, incurred months.
Exposures and deaths during the three-year period of 2017–2019 were used to set baseline mortality expectations.
The dataset for this report encompasses all Group Life claims reported to participating carriers as of June 30, 2023.
Reported claims are easier to measure than incurred claims, but they do not tell the full story about Group Lifemortality through June 2023 because the reported claims in a given month include deaths from prior periods.
Therefore, claim reporting patterns from prior periods have been analyzed to develop completion factors, which areused to estimate incurred, but not yet reported, claims for each month. This enabled the Committee to estimate
incurred claims for each month up through June 2023.
As in prior reports, the most recent one-to-two incurral months should not be fully relied upon because of thematurity of the completion of reported claims, with the completion percentages for the most recent two months
falling in the 30%–35% and 70%–75% ranges, respectively. The Committee has observed significant reporting lag
volatility over the course of the study, resulting in volatility of incurred incidence development over time, especiallyin the most recent incurred months.

2.2 SCOPE
The following specifications were used to define claims and exposures within the survey:•

Include Group Term Life only; exclude Group Whole Life, Group Universal Life, Company-Owned Life
Insurance and 10- or 20-year Group Term, etc.

•

Include both list billed and self-administered business.

•

Include employee, spouse and child exposures and deaths.

•

Include both active and retired lives and claims.

•

Include death benefits only; exclude riders, interest payments and claims expenses.

•

Include only the life insurance benefit for accidental deaths; exclude any additional Accidental Death andDismemberment rider amounts.

•

Exclude Waiver of Premium disabilities, but include deaths from persons on Waiver of Premium status.

•

Portability and Conversion exposures and claims may be either included or excluded based on eachcompany’s internal reporting procedures.

Copyright © 2023 Society of Actuaries Research Institute7

2.3 SURVEY HIGHLIGHTS
Tables 2.1 through 2.41 display high-level incidence results for the second quarter of 2020 through the second
quarter of 2023 compared to the 2017–2019 baseline period for each combination of (a) incurred/reported basisand (b) count/amount basis as of June 30, 2023. In these tables, the number of COVID-19 claims has not beenadjusted for seasonality, but the ratios to baseline have. Monthly face amounts have been trended at a 2% annual
rate for low wage inflation years 2017-2019, and a 3% annual rate for high wage inflation years of 2020 and later.
See section 4.5 of this report for further discussion on the trend assumptions.
Table 2.1

COUNT-BASED INCURRED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE
2021

2022

Q1 2023

Q2 2023

Total / Baseline

Q2 2020–
Q4 2020118.9%

121.5%

105.5%

96.8%

COVID-19 Claims

46,64478,494

27,6202,376Count-Based

COVID / Baseline
Non-COVID / Baseline

14.6%
104.3%

18.4%
103.1%

6.1%
99.4%

2.0%
94.8%

99.4%

Q1-Q2
2023
98.1%

Q2 2020–
Q2 2023112.2%

700

3,076

155,834

0.6%

1.3%

11.0%

98.8%

96.8%

101.2%

Table 2.2

AMOUNT-BASED INCURRED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE (CLAIMS IN MILLIONS)
2021

2022

Q1 2023

Q2 2023

Total / Non-trended Baseline

Q2 2020–
Q4 2020125.2%

139.6%

118.9%

111.1%

Total / Trended Baseline

119.4%

129.6%

107.3%

98.4%

COVID-19 Claims (M)

1,721

3,998

1,124

COVID / Trended Baseline

14.1%

24.0%

Non-COVID / Trended Baseline

105.3%

105.6%

Amount-Based116.0%

Q1-Q2
2023
113.6%

Q2 2020–
Q2 2023125.7%

102.0%

100.2%

115.7%

68

24

93

6,935

6.2%

1.4%

0.5%

1.0%

12.5%

101.1%

97.0%

101.5%

99.2%

103.2%

Q2 2020–
Q2 2023113.2%

Table 2.3

COUNT-BASED REPORTED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE
2021

2022

Q1 2023

Q2 2023

Total / Baseline

Q2 2020–
Q4 2020115.3%

123.6%

108.9%

102.7%

95.3%

Q1-Q2
2023
99.0%

COVID-19 Claims

34,52881,44635,106

3,119

1,266

4,385

155,465

COVID / Baseline

11.2%

19.3%

7.8%

2.6%

1.1%

1.9%

11.1%

Non-COVID / Baseline

104.1%

104.3%

101.1%

100.1%

94.2%

97.1%

102.1%Count-Based

Table 2.4

AMOUNT-BASED REPORTED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE (CLAIMS IN MILLIONS)
2021

2022

Q1 2023

Q2 2023

Total / Non-trended Baseline

Q2 2020–
Q4 2020123.6%

140.6%

122.2%

116.8%

Total / Trended Baseline

118.0%

130.8%

110.5%

COVID-19 Claims (M)

1,369

3,986

1,457

COVID / Trended Baseline

11.7%

24.4%

Non-COVID / Trended Baseline

106.3%

106.4%

Amount-Based108.2%

Q1-Q2
2023
112.5%

Q2 2020–
Q2 2023
126.6%

103.7%

95.3%

99.5%

116.6%

101

34

134

6,946

8.0%

2.1%

0.7%

1.4%

12.8%

102.5%

101.6%

94.6%

98.1%

103.8%

1 A small number of COVID-19 claims received were dated before 2020. The Committee assumes these dates are data errors. They were not assigned to aparticular date in 2020 or later, and so these claims are excluded from Tables 2.1–2.4. They are, however, included in the total COVID claims in Section 5.

Copyright © 2023 Society of Actuaries Research Institute8

Reported incidence has decreased considerably since the first quarter of 2022. No months since March 2022 have
had a reported incidence more than 10% above baseline. Of particular note, all three months in the second quarterof 2023 have been below baseline, with April, May, and June reported incidence at 7%, 2%, and 5% below baseline,
respectively. All three months in the first quarter of 2023 were above baseline, but the maximum was in January at
5% above baseline.
It is important to note that incurred estimates for the most recent months lack credibility because of the low level ofcompletion of the data used at the time of this analysis. Group Life claim completion has been especially volatile
during the pandemic waves, driven both by the ultimate incurred levels fluctuating from month to month andcompany-specific claim-processing speeds fluctuating up and down because of increases or decreases in staffing
levels and build-up or build-down of claim backlogs.
From an incurred mortality viewpoint, all of the months from April 2020 through December 2022 showed excess
mortality2 versus baseline expectations except for March and April 2022. However, in the first half of 2023, allmonths except June were below baseline on an incurred basis, with each month ranging from 5% below baseline to
1% above baseline. December 2020, January 2021, August 2021 and September 2021 all had very high incurred
excess mortality spikes of 40% or more.
The 39-month period of April 2020 through June 2023 showed the following Group Life mortality results:••

Estimated reported Group Life claim incidence rates were up 13.2% on a seasonally-adjusted basis
compared to 2017–2019 reported claims.
Estimated incurred Group Life incidence rates were 12.2% higher than baseline on a seasonally-adjusted
basis. As noted above, the incurred incidence rates in May and June 2023 are based on fairly incomplete
data, so they are subject to change and should not be fully relied upon at this point.

Additional highlights include the following:••

Approximately 10% of all reported Group Life claims with death dates in the pandemic period were
determined to have a cause of death (COD) of COVID-19.
The Gray-Collar group had the lowest actual-to-expected ratios (A/E’s) relative to baseline over the
pandemic period at around 6%, followed by the Blue-Collar group at 10%. The White-Collar group
continued to have the highest mortality A/E relative to baseline at 16% during the pandemic period.

2For the purposes of this report, “excess mortality” refers to the percentage change in incidence rates observed during the pandemic compared to the

2017–2019 baseline period.

Copyright © 2023 Society of Actuaries Research Institute

9

•

•

•

Group Life mortality patterns by region have changed over time during the COVID-19 pandemic. The
Midwest had the highest excess mortality for the most recent quarter included in this update. The
following regions had the highest excess mortality in each quarter shown:o Q1 2021: Southeast (32%)
o Q2 2021: Southeast (10%)
o Q3 2021: Southeast (62%)
o Q4 2021: Midwest (32%)
o Q1 2022: Northeast (19%)
o Q2 2022: Northeast (2%)
o Q3 2022: Southeast (7%)
o Q4 2022: Northeast (8%)
o Q1 2023: Northeast (1%)
o Q2 2023: Midwest (6%)
Findings related to COD data showed incurred mortality increases in several causes during the pandemic
period, including accidents, liver, diabetes, and drug overdoses. Cardiovascular deaths were elevated in2020 and 2021, but these fell below baseline in 2022. Cancer and influenza/pneumonia incurred mortality
levels were down during the pandemic period as compared to baseline. Additional details are shown in
Section 6.
Early quarters of the pandemic period (Q2 and Q3 2020) showed the Group Life insured population studied
within this survey experienced a lower percentage of excess deaths than the U.S. population, as shown in
Table 2.5. Each quarter in 2021 showed higher excess mortality in the Group Life population than the U.S.
population. However, in the second quarter of 2022, this comparison reversed, and Group Life population
has shown lower excess mortality than the U.S. population in the most recent five quarters.
Table 2.5

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER•

Incurred
QuarterGroup Life

U.S.
Population

DifferenceQ1 2020

-1.4%

0.1%

-1.5%

Q2 2020

14.4%

19.8%

-5.4%

Q3 2020

14.9%

16.7%

-1.8%

Q4 2020

28.0%

25.6%

2.4%

Q1 2021

22.4%

17.0%

5.4%

Q2 2021

6.5%

4.9%

1.6%

Q3 2021

32.8%

23.3%

9.6%

Q4 2021

24.6%

18.9%

5.7%

Q1 2022

16.6%

15.3%

1.2%

Q2 2022

-1.3%

1.8%

-3.1%

Q3 2022

2.9%

7.0%

-4.1%

Q4 2022

4.2%

7.4%

-3.2%

Q1 2023

-3.2%

-1.5%

-1.7%

Q2 2023

-0.6%

-0.4%

-0.2%

Section 9 includes a comparison of proportional excess deaths in the Group Life market to the U.S.
population, segmented by sex, age and cause of death. Overall, the experience between the two
populations was quite similar but, in several instances, the experience differed:

Copyright © 2023 Society of Actuaries Research Institute

10

o
o
o
o

For the older ages (over age 65), Group Life mortality improved in 2022 and the first half of 2023
relative to 2020–2021 significantly more than in the U.S. population.
Group Life mortality for major cardiovascular disease also improved in 2022 relative to 2020–2021
more than in the U.S. population.
Mortality from cancer was significantly lower relative to 2017-2019 in the Group Life population thanthe U.S. population.
The proportional impact of death due to liver disease was much higher within the total U.S. population
than within the Group Life market through the entire pandemic period.

Copyright © 2023 Society of Actuaries Research Institute11

Section 3: Group Life Mortality Results—Reported Death Claims
3.1 REPORTED CLAIM INCIDENCE BY COUNT—ALL CAUSES
On a seasonally-adjusted basis, the second quarter of 2023 reported incidence by count was 95.3% of baseline
levels, with April, May and June coming in at 93.0%, 97.9% and 95.2% of baseline, respectively. The second quarterof 2023 figure of 95.3% is far and away the lowest reported claim figure since the start of the pandemic.
Reported overall Group Life claim incidence rates during the pandemic period, as shown in Figure 3.1, were up
approximately 13% compared to 2017–2019 reported claims. Reported claims are easier to measure than incurredbecause no estimation of completeness is required. However, reported claims do not explain the true economic
impact of what is happening in the claim experience of a particular reported period, because those reported claims
include deaths associated with prior periods, which may or may not have been accurately expected and accrued inprior period claim liabilities.
Figure 3.1

AGGREGATE REPORTED CLAIM INCIDENCE PER 1,000 BY CALENDAR YEAR AND MONTH3
4.80
4.40
4.00
3.60
3.20
2.80
2.40
Jan

Feb

Mar

2017
2021

Apr

May

Jun

Jul

2018
2022

Aug

Sep

2019
2023

Oct

Nov

Dec

2020

3 Incidence rates in Figure 3.1 have not been adjusted for seasonality.

Copyright © 2023 Society of Actuaries Research Institute

12Figure 3.2 is a different view of the data displayed in Figure 3.1 to illustrate the flow of excess reported mortality
over the entire pandemic period.
Figure 3.2

AGGREGATE REPORTED CLAIM INCIDENCE PER 1,000 BY CALENDAR MONTH 4
4.80
4.40
4.00
3.60
3.20
2.80

Jun-23

Dec-22Mar-23Jun-22

Sep-22

Dec-21

Mar-22Jun-21

Sep-21

Mar-21

Sep-20Dec-20Jun-20Dec-19Mar-20Jun-19Sep-19Dec-18Mar-19Jun-18

Sep-18Dec-17Mar-18Jun-17

Sep-17

Dec-16

Mar-172.40

12 per. Mov. Avg. (Reported Incidence)

3.2 REPORTED CLAIM INCIDENCE BY COUNT—COVID-19 VERSUS ALL OTHER CAUSES
A total of 155,465 COVID-19 death claims were reported during the pandemic period. Roughly 74% of the COVID-19
claims were for Basic Group Life coverage and roughly 26% for Supplemental/Voluntary coverage, with both figures
including active employees and retirees. Note that the exposures and claim counts for insureds with both Basic andSupplemental/Voluntary coverage were included in both product lines. Thus, some deaths were counted as both
Basic and Supplemental/Voluntary deaths, so the total number of Group Life insureds with COVID-19 deaths is lessthan 155,465.
Table 3.1 shows the total death claim incidence level (mortality rate) for each quarter during the pandemic relative
to the baseline period metric. The table also shows a relativity for COVID-19 claims and non-COVID claims. As thetable illustrates, COVID-19 claims do not fully explain the increase in reported claim incidence over the baseline
period.
Table 3.1

COUNT-BASED REPORTED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE
2021

2022

Q1 2023

Q2 2023

Total / Baseline

Q2 2020–
Q4 2020115.3%

123.6%

108.9%

102.7%

COVID-19 Claims

34,52881,44635,106COVID / Baseline

11.2%

19.3%

Non-COVID / Baseline

104.1%

104.3%Count-Based

95.3%

Q1-Q2
2023
99.0%

Q2 2020–
Q2 2023113.2%

3,119

1,266

4,385

155,465

7.8%

2.6%

1.1%

1.9%

11.1%

101.1%

100.1%

94.2%

97.1%

102.1%

4 Incidence rates in Figure 3.2 have not been adjusted for seasonality.

Copyright © 2023 Society of Actuaries Research Institute13

Reported claim details by month are shown in Table 3.2, along with calculated monthly reported incidence rates.
Note that a small number of COVID-19 claims have reported dates of death in 2019 or prior, which are likely due todata errors.
Table 3.2

REPORTED CLAIMS AND INCIDENCE RATES, 2017 THROUGH Q2 2023
Report Date

6/1/23
5/1/23
4/1/23
3/1/23
2/1/23
1/1/23
12/1/22
11/1/22
10/1/22
9/1/22
8/1/22
7/1/22
6/1/22
5/1/22
4/1/22
3/1/22
2/1/22
1/1/22
12/1/21
11/1/21
10/1/21
9/1/21
8/1/21
7/1/21
6/1/21
5/1/21
4/1/21
3/1/212/1/21
1/1/21
12/1/20
11/1/20
10/1/20
9/1/208/1/207/1/206/1/205/1/204/1/203/1/202/1/201/1/202017-2019Baseline
2019 Monthly
2018 Monthly
2017 Monthly

Raw Submitted Numbers
Reported Claims
Premium($ 000)
Total
COVID
33,951267
1,871,102
37,860434
1,877,852
35,058565
1,911,386
42,030900
1,921,002
37,786975
1,883,563
42,163
1,244
1,934,365
36,945943
1,824,668
35,834919
1,808,505
34,832956
1,815,888
36,0131,156
1,817,245
39,4301,343
1,807,194
35,9661,211
1,816,599
37,7081,266
1,812,229
37,1691,568
1,815,153
37,8002,412
1,817,729
49,5066,139
1,808,172
46,2748,493
1,807,139
47,7728,700
1,803,927
44,423
7,042
1,765,067
41,5907,085
1,707,329
44,1829,573
1,720,116
47,171
10,175
1,709,594
41,654
4,878
1,703,536
36,466
1,849
1,723,203
40,0292,760
1,727,820
36,7083,531
1,736,904
41,6194,950
1,740,571
50,692
8,209
1,729,881
47,48910,3601,722,093
48,348
11,034
1,716,491
46,526
8,065
1,687,891
36,656
3,689
1,666,831
38,6862,814
1,668,634
38,681
3,167
1,671,782
38,2403,452
1,674,383
39,627
2,944
1,694,220
39,526
3,184
1,683,613
38,655
4,033
1,739,128
40,846
3,180
1,695,716
37,818157
1,699,598
36,414
3
1,726,512
39,3594
1,688,956

Life Years Exposed(000)
By Month
Yearly Avg
11,241
11,356
11,20911,356
11,41911,356
11,425
11,356
11,211
11,356
11,631
11,356
11,292
11,217
11,17011,217
11,222
11,217
11,215
11,217
11,20011,217
11,30011,217
11,237
11,217
11,202
11,217
11,254
11,217
11,12011,217
11,235
11,217
11,158
11,217
11,203
10,873
10,837
10,873
10,824
10,873
10,746
10,873
10,812
10,873
10,79010,873
10,874
10,873
10,907
10,873
10,916
10,873
10,874
10,873
10,867
10,873
10,82910,873
10,96010,993
10,86910,993
10,775
10,993
10,84910,993
10,894
10,993
10,982
10,993
10,946
10,993
11,46910,993
10,88910,993
10,978
10,993
11,297
10,993
11,00910,993Calculated Amounts
Annual Incidence
per 1,000(Lives Basis)
2.99
3.33
3.09
3.70
3.33
3.71
3.29
3.19
3.11
3.21
3.52
3.21
3.36
3.31
3.37
4.41
4.13
4.26
4.09
3.83
4.06
4.34
3.83
3.35
3.68
3.38
3.83
4.66
4.37
4.45
4.23
3.33
3.52
3.52
3.48
3.60
3.60
3.52
3.72
3.44
3.31
3.58

34,6591

1,592,757

10,713

10,7133.24

3.24

100.0%

35,49434,73833,74411
01,647,480
1,589,156
1,541,634

10,884
10,685
10,572

10,884
10,685
10,572

3.26
3.25
3.19

3.27
3.25
3.20

100.9%
100.4%
98.7%

Adjusted for
Seasonality
Total Total/Baseline
3.08
95.2%
3.17
97.9%
3.01
93.0%
3.31
102.2%
3.27
100.9%
3.40
105.2%
3.55
109.7%
3.53
109.0%
3.12
96.4%
3.55
109.5%
3.41
105.5%
3.35
103.5%
3.46
107.0%
3.15
97.3%
3.29
101.5%
3.94
121.8%
4.05
125.1%
3.91
120.6%
4.41
136.1%
4.22
130.5%
4.08
126.2%
4.79
148.0%
3.72
115.0%
3.50
108.3%
3.79
117.2%
3.21
99.2%
3.73
115.3%
4.17
128.7%
4.29
132.4%
4.08
126.0%
4.58
141.4%
3.69
114.1%
3.55
109.6%
3.90
120.4%
3.39
104.7%
3.78
116.7%
3.71
114.8%
3.35
103.6%
3.63
112.2%
3.08
95.2%
3.15
97.2%
3.29
101.7%

Copyright © 2023 Society of Actuaries Research Institute14

3.3 REPORTED CLAIM INCIDENCE BY AMOUNT—ALL CAUSES
Reported overall Group Life claim incidence rates by amount during the pandemic period were up 26.6% compared
to 2017–2019 raw reported amounts, as shown in the first row of Table 3.3. The second row of Table 3.3 shows the
pandemic period mortality increase by amount drops to 16.6% when incorporating a face amount trend
assumption, which recognizes anticipated face amount growth as salaries and associated Group Life coverageamounts increase over time. Monthly face amounts have been trended at a 2% annual rate for low wage inflation
years 2017-2019, and a 3% annual rate for high wage inflation years of 2020 and later. The A/E ratio by trended
amount is approximately 3%-4% higher than the A/E ratio by count. Supporting details and further discussion of thetrend amount assumptions are documented in Section 4.5 of this report.

3.4 REPORTED CLAIM INCIDENCE BY AMOUNT—COVID-19 VERSUS ALL OTHER CAUSES
Table 3.3

AMOUNT-BASED REPORTED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE (CLAIMS IN MILLIONS)
2021

2022

Q1 2023

Q2 2023

Total / Non-trended Baseline

Q2 2020–
Q4 2020123.6%

140.6%

122.2%

116.8%

Total / Trended Baseline

118.0%

130.8%

110.5%

COVID-19 Claims (M)

1,369

3,986

1,457

COVID / Trended Baseline

11.7%

24.4%

Non-COVID / Trended Baseline

106.3%

106.4%

Amount-Based108.2%

Q1-Q2
2023
112.5%

Q2 2020–
Q2 2023
126.6%

103.7%

95.3%

99.5%

116.6%

101

34

134

6,946

8.0%

2.1%

0.7%

1.4%

12.8%

102.5%

101.6%

94.6%

98.1%

103.8%

Copyright © 2023 Society of Actuaries Research Institute15

Section 4: Group Life Mortality Results—Estimated Incurred Death Claims
4.1 INCURRED CLAIM INCIDENCE BY COUNT—ALL CAUSES
A completed estimate of incurred incidence rates by count indicates that excess mortality for the pandemic period
was approximately 12% higher than the 2017–2019 baseline incurred incidence. Figure 4.1 displays the various
monthly estimated incurred incidence rates.
Figure 4.1

AGGREGATE INCURRED5 CLAIM INCIDENCE PER 1,000 BY CALENDAR YEAR AND MONTH
5.20
4.90
4.60
4.30
4.00
3.70
3.40
3.10
2.80
Jan

Feb

Mar
2017
2021

Apr

May

Jun
2018
2022

Jul

Aug
Sep
2019
2023

Oct

Nov
2020

Dec

Current estimates for the second quarter of 2023 incurred incidence rates indicate that mortality was 99.4% ofbaseline on a seasonally-adjusted count basis. The monthly results within the second quarter of 2023 show April and
May estimated incurred mortality slightly below baseline at 97.3% and 99.9%, respectively, while June is above
baseline at 101.0%. The May and June results are still highly incomplete and likely to change as more months ofreported claims are revealed.
The current view of the first quarter of 2023 results indicates incurred mortality was 96.8% of baseline, with each of
the three months of the quarter coming in below baseline.

5 Adjusted for assumed completion.

Copyright © 2023 Society of Actuaries Research Institute

16

Figure 4.2 is a different view of the data displayed in Figure 4.1 to illustrate the flow of estimated excess incurredmortality over the entire pandemic period.
Figure 4.2

AGGREGATE INCURRED6 CLAIM INCIDENCE PER 1,000 BY CALENDAR MONTH7
5.20
4.90
4.60
4.30
4.00
3.70
3.40
3.10
Apr-23

Dec-22Aug-22

Apr-22

Dec-21

Aug-21

Apr-21

Dec-20Aug-20

Apr-20Dec-19Aug-19Apr-19Dec-18Aug-18Apr-18Dec-17Aug-17

Apr-17

Dec-162.80

12 per. Mov. Avg. (Incurred Incidence)

4.2 INCURRED CLAIM INCIDENCE BY COUNT—COVID-19 VERSUS ALL OTHER CAUSES
Similar to reported claim metrics, Table 4.1 shows that COVID-19 claims do not fully explain the increase in incurredclaim incidence on a count basis. COVID-19 claims account for roughly 90% of the excess incurred Group Lifemortality during the second quarter of 2020 through the second quarter of 2023, with the other 10% coming fromclaims that were not coded with COVID-19 as the cause of death.
Table 4.1

INCURRED EXCESS MORTALITY BY CLAIM COUNT COMPARED TO 2017–2019 BASELINE
2021

2022

Q1 2023

Q2 2023

Total / Baseline

Q2 2020–
Q4 2020118.9%

121.5%

105.5%

96.8%

COVID-19 Claims

46,64478,494

27,6202,376Count-Based

99.4%

Q1-Q2
2023
98.1%

Q2 2020–
Q2 2023112.2%

700

3,076

155,83411.0%
101.2%

COVID / Baseline

14.6%

18.4%

6.1%

2.0%

0.6%

1.3%

Non-COVID / Baseline

104.3%

103.1%

99.4%

94.8%

98.8%

96.8%

6 Adjusted for assumed completion.
7 Incidence rates in Figure 4.2 have not been adjusted for seasonality.

Copyright © 2023 Society of Actuaries Research Institute17

Incurred claim details by month are shown in Table 4.2, along with calculated monthly incurred incidence rates.
Note that a small number of COVID-19 claims have incurred dates of death in 2019 or prior, which are likely due todata errors.
Table 4.2

INCURRED CLAIM COUNTS AND INCIDENCE RATES, 2017 THROUGH Q2 2023
Incurral Date

6/1/23
5/1/23
4/1/23
3/1/23
2/1/23
1/1/23
12/1/22
11/1/22
10/1/22
9/1/22
8/1/22
7/1/22
6/1/22
5/1/22
4/1/22
3/1/22
2/1/22
1/1/22
12/1/21
11/1/21
10/1/21
9/1/21
8/1/21
7/1/21
6/1/21
5/1/21
4/1/21
3/1/212/1/21
1/1/21
12/1/20
11/1/20
10/1/20
9/1/208/1/207/1/206/1/205/1/204/1/203/1/202/1/201/1/202017-2019 Baseline
2019 Monthly
2018 Monthly
2017 Monthly

Raw Submitted Numbers
Average Incurred
Average
Claim Counts
Premium($ 000)
Total
COVID
11,60925,72730,15933,73032,296
38,66039,64236,09035,83534,43235,16535,897
34,12235,41333,85637,19840,42553,48946,80842,23444,531
48,63947,15337,00934,992
37,34837,22539,435
41,14854,44453,44743,87639,40436,61339,85140,16336,11839,47544,691
38,67535,35638,48434,75734,90534,79534,572

42
145
309
514
615
1,095
1,140
747
770
869
1,203
1,139
878
712
590
1,652
5,999
11,452
8,054
5,730
7,914
12,68010,048
1,959
1,354
2,470
3,053
3,334
6,779
14,523
13,359
7,197
3,107
2,395
3,707
3,748
1,971
3,891
7,162
1,086
23
63
2
3
2
1

1,871,102
1,877,852
1,911,386
1,921,002
1,883,563
1,934,365
1,824,668
1,808,505
1,815,888
1,817,245
1,807,194
1,816,599
1,812,229
1,815,153
1,817,729
1,808,172
1,807,139
1,803,927
1,765,067
1,707,329
1,720,116
1,709,594
1,703,536
1,723,203
1,727,820
1,736,904
1,740,571
1,729,881
1,722,093
1,716,491
1,687,891
1,666,831
1,668,634
1,671,782
1,674,383
1,694,220
1,683,613
1,739,128
1,695,716
1,699,598
1,726,512
1,688,956
1,592,757
1,647,480
1,589,156
1,541,634

Average
Life Years
Exposed(000)
11,241
11,20911,41911,425
11,211
11,631
11,292
11,170
11,222
11,215
11,20011,300
11,237
11,202
11,254
11,120
11,235
11,158
11,203
10,837
10,824
10,746
10,812
10,79010,874
10,907
10,916
10,874
10,867
10,82910,96010,86910,775
10,84910,894
10,982
10,946
11,46910,88910,978
11,297
11,00910,713
10,884
10,685
10,572

Calculated Amounts
AverageAnnualAdjusted forCompleted
Incidence
Seasonality
Claim
per 1,000
Total Total/Baseline
Counts(Lives Basis)
35,0473.12
3.28
101.0%
35,989
3.21
3.24
99.9%
35,549
3.11
3.16
97.3%
37,300
3.26
3.08
95.0%
34,689
3.09
3.15
97.1%
40,934
3.52
3.19
98.3%
41,346
3.66
3.45
106.4%
37,3993.35
3.40
104.8%
36,961
3.29
3.29
101.3%
35,385
3.16
3.36
103.5%
36,035
3.22
3.33
102.6%
36,691
3.25
3.33
102.6%
34,7933.10
3.26
100.3%
36,0393.22
3.25
100.2%
34,404
3.06
3.10
95.6%
37,747
3.39
3.21
98.8%
40,976
3.65
3.71
114.4%
54,1624.85
4.40
135.6%
47,3494.23
3.99
122.8%
42,686
3.94
4.00
123.3%
44,9684.15
4.15
127.8%
49,077
4.57
4.86
149.8%
47,5434.40
4.55
140.2%
37,2903.46
3.54
109.2%
35,2333.24
3.41
105.0%
37,581
3.45
3.48
107.3%
37,435
3.43
3.48
107.2%
39,6383.65
3.44
106.1%
41,3383.80
3.87
119.3%
54,6725.05
4.58
141.0%
53,6504.90
4.63
142.7%
44,021
4.05
4.13
127.1%
39,5203.67
3.67
113.1%
36,7053.38
3.61
111.3%
39,9383.67
3.80
117.2%
40,185
3.66
3.76
115.9%
36,1383.30
3.48
107.3%
39,497
3.44
3.49
107.5%
44,7164.11
4.18
128.8%
38,696
3.52
3.34
102.8%
35,376
3.13
3.09
95.1%
38,505
3.50
3.18
98.0%
34,7763.25
3.25
100.0%
34,924
3.21
3.21
98.9%
34,8143.26
3.26
100.3%
34,591
3.27
3.27
100.8%

Copyright © 2023 Society of Actuaries Research Institute18

4.3 INCURRED CLAIM INCIDENCE BY AMOUNT—ALL CAUSES
Overall, seasonally-adjusted incurred Group Life claim incidence rates by amount during the pandemic period wereup 25.7% compared to 2017–2019 raw incurred amounts, as shown in row 1 of Table 4.3. Row 2 of Table 4.3 shows
the pandemic period mortality increase by amount drops to 15.7% when incorporating a face amount trend
assumption, which recognizes anticipated face amount growth as salaries and associated Group Life coverageamounts increase over time. Monthly face amounts have been trended at a 2% annual rate for low wage inflation
years 2017-2019, and a 3% annual rate for high wage inflation years of 2020 and later.
The increase in incidence rates by raw amount has been materially greater than the corresponding increase inincidence rates by count, with the raw amount impact consistently being 12%-15% higher on an additive basis. Prior
iterations of this report suggested the difference was likely driven by salary and face amount inflation over the fiveyear period, along with changes in age and gender mix and the relatively higher excess mortality being incurred at
typical working ages (where face amounts are greater).
The new trend component suggests most, but not all, of the difference between amount and count mortality impact
can, indeed, be explained by salary increases and corresponding face amount increases over time. Incurredmortality by trended amount during 2023 is roughly 2%-3% higher than incurred mortality by count. Incurredmortality by trended amount peaked at roughly 15% greater than incurred mortality by count in the third quarter of2021, and the additional mortality for trended amount versus count for the entire pandemic period is 3.5% on an
additive basis (15.7% by trended amount versus 12.2% by count).

4.4 INCURRED CLAIM INCIDENCE BY AMOUNT—COVID-19 VERSUS ALL OTHER CAUSES
Table 4.3 displays both raw amount- and trended amount-based incurred incidence results versus baseline. The
trended amount results are further split into COVID-19 and non-COVID impacts. Similar to the findings on incidenceby count, Table 4.3 shows that COVID-19 claims do not fully explain the increase in incurred claim incidence on atrended amount basis.
Table 4.3

AMOUNT-BASED INCURRED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE
2021

2022

Q1 2023

Q2 2023

Total / Non-trended Baseline

Q2 2020–
Q4 2020125.2%

139.6%

118.9%

111.1%

Total / Trended Baseline

119.4%

129.6%

107.3%

COVID-19 Claims (M)

1,721

3,998

1,124

Amount-Based116.0%

Q1-Q2
2023
113.6%

Q2 2020–
Q2 2023125.7%

98.4%

102.0%

100.2%

115.7%

68

24

93

6,935

COVID / Trended Baseline

14.1%

24.0%

6.2%

1.4%

0.5%

1.0%

12.5%

Non-COVID / Trended Baseline

105.3%

105.6%

101.1%

97.0%

101.5%

99.2%

103.2%

4.5 DEVELOPMENT OF FACE AMOUNT TREND ASSUMPTION
The Committee has observed that premium per life has been increasing throughout the experience period,
indicating average face amount insured has likely been increasing as well. The decision was made to build in an
expected trended amount adjustment by calendar year to enhance the amount-based A/E metric. Wage data fromthe Federal Reserve is summarized in Table 4.4, with the rightmost column displaying the median nominal wage
data, which is the sum of the real median wage change plus the CPI change. Based on this data, the Committee
decided to trend expected amounts by 2% for years 2017-2019 and 3% for years 2020-2023. Trended claim
amounts were increased prior to January 2020, and reduced for January 2020 forward, with January 1, 2020 being
used as the pivot point for this calculation. The impact of adding this trend adjustment to the amount-based A/E
was an average reduction by incurred calendar year as follows: 6% for quarters two through four of 2020, 10% for

Copyright © 2023 Society of Actuaries Research Institute192021, 12% for 2022, and 13% for quarters one and two of 2023. With this trended amount adjustment, theexperience now reflects that the most meaningful impact of increased average severity occurred in 2021, but has
been relatively muted otherwise.
These annual amount adjustment values are dampened from the raw wage data, as we acknowledge certain Group
Life plans offer flat dollar benefits that do not increase annually. The same adjustment is applied by reported year
and incurred year for simplicity. The assumption for future experience years will be monitored as wage data
emerges. The Committee did consider differentiating this adjustment by age band and/or retirees as older ages
often have flat benefit amounts, but the data and workbook limitations precluded this from being a viable
possibility.
Table 4.4

U.S. WAGE DATA

2017

Average Hourly
Earnings Change8
2.7%Median Real Weekly
Wage Change9
-1.1%

CPI
Change102.1%Median Nominal
Wage Change
1.0%

2018

3.6%

2.9%

2.4%

5.3%

2019

2.9%

2.0%

1.8%

3.8%

2020

5.5%

4.1%

1.2%

5.3%

2021

5.0%

-4.0%

4.7%

0.7%

2022

4.8%

0.3%

8.0%

8.3%

Year

8 https://fred.stlouisfed.org/series/CES0500000003
9 https://fred.stlouisfed.org/series/LES1252881600Q
10 https://www.minneapolisfed.org/about-us/monetary-policy/inflation-calculator/consumer-price-index-1913-

Copyright © 2023 Society of Actuaries Research Institute20

4.6 OTHER DRIVERS OF AMOUNT VERSUS COUNT MORTALITY DIFFERENCES
Figure 4.3 below shows a stacked bar graph of incurred excess mortality, broken out by the count- and trended
amount-based impacts. In addition, the percentage of U.S. population COVID-19 deaths occurring under age 65 arelayered on top of this graph. The strong correlation between the amount-based excess and the under age 65 COVID19 deaths may provide support for the hypothesis that a younger average death age of Group Life claims is a key
component in driving higher amount-based excess mortality.
Figure 4.3

75%

49.0%

60%

42.0%
35.0%

45%

28.0%
30%
21.0%
15%

14.0%

0%

7.0%

-15%

0.0%

GL Count based Excess% of U.S. COVID-19 deaths < Age 65

Excess Mortality

GROUP LIFE EXCESS INCURRED MORTALITY – COUNT AND TRENDED AMOUNT IMPACTS

GL Amount Additional Excess% of U.S. COVID-19 deaths < Age 65

Copyright © 2023 Society of Actuaries Research Institute21

The Committee also attempted to quantify the impact of changes in age and sex distribution over time, as displayedin Table 4.5. For each calendar year, the figures below show what the total average trended benefit would havebeen had we matched the 2022 average amounts by sex and age, but used the baseline distribution by sex and age.
For 2022 as an example, the average trended amount would have been 36,514 rather than 37,731, so the impact ofthe distribution alone was 3.3%. This suggests that, if the distribution for age and sex matched the baseline period,
the trended amount-based A/E would have been 3.3% lower than what we observed. The analysis also suggests thatthe big jump in 2021 mortality by trended amounts versus count was due to more than the ages of the deaths.
Table 4.5

ESTIMATE OF IMPACT OF CHANGE IN AGE AND SEX DISTRIBUTION OVER TIME ON AMOUNT-BASED A/E
Year11

2020

2021

2022

2023

(A) Trended amount-based A/E minus count-based A/E

0.3%

6.5%

1.3%

2.1%

(B) Actual average trended amount37,36739,67137,73137,969(C) Trended amount using baseline sex/age distribution(D) Impact of baseline distribution on trended amount-based
A/E(E) Residual difference between trended amount-based A/E
and count-based A/E [(A) minus (D)]36,64736,65436,51435,840

2.0%

8.2%

3.3%

5.9%

-1.7%

-1.6%

-2.0%

-3.8%

11 2020 through 2022 represent full calendar years, including months in 2020 prior to the pandemic period. 2023 includes January through June 2023.

Copyright © 2023 Society of Actuaries Research Institute22

Section 5: Estimated Incurred Mortality Results by Segment
Analysis of results by segment will focus on claim count experience for simplicity and credibility. Results by claim
amount generally follow similar patterns as the results by claim count.
The following notes apply to the data presented in this section:
•
•

•

•

•

Claims and A/E ratios are presented on an incurred basis. The “expected” basis is the 2017–2019 baseline.
Although most companies were able to provide segment detail, some did not. Results by Company Size
reflect all companies. Results for Industry reflect approximately 97% of total company claims, results for
Geography reflect 98% of total company claims, and results by Age reflect approximately 91% of totalcompany claims. Note that these percentages are expressed relative to baseline claim counts.
The total claim counts and A/E ratios in each subsection include only the data from companies that
produced the breakout being analyzed. For example, the “All Industries” row in Table 5.2 includes only datafrom companies that were able to supply claims data by Industry. This can result in differences in the total
A/E ratios across the various tables.
The “% COVID” columns in the tables below show the monthly average COVID claims during the pandemic
period as a percentage of the average total monthly claims from the 2017–2019 baseline period. The “%
Non-COVID” column in the Age tables reflects excess mortality due to non-COVID claims.
The “% Count” columns in the tables below show the proportion of baseline claims in each segment. For
some segments, claims were submitted with an “Unknown” segmentation value. The unknowns and theirratios are usually omitted from the tables, but are included in the totals. Unknowns tend to account for asmall percent of the total.

For formatting purposes, the quarterly information for older periods may be either aggregated or dropped fromsome tables in this section; see prior iterations of this report for information on quarterly excess mortality for theseolder periods.

Copyright © 2023 Society of Actuaries Research Institute23

5.1 INDUSTRY
Table 5.1 displays quarterly A/E mortality ratios by industry collar. The White-Collar category has experienced ahigher A/E ratio than the Blue- and Grey-Collar industries over the entire pandemic period, and this relationship has
been relatively consistent across time. All three categories showed peak excess mortality in the third quarter of2021. Grey-Collar has had the lowest A/E ratio since the fourth quarter of 2021, including ratios below 100% for fiveconsecutive quarters.
Table 5.1

EXCESS MORTALITY BY INDUSTRY COLLAR
Industry
Collar
Blue
Grey
White
All Collars12

Q1
2021
123%
118%
123%
122%

Q2
2021
106%
104%
107%
107%

Q3
2021
129%
133%
138%
133%

Q4
2021
125%
121%
125%
125%

Q1
2022
115%
107%
120%
116%

Q2
2022
97%
89%
104%
99%

Q3
2022
101%
93%
108%
103%

Q4
2022
102%
90%
112%
104%

1Q
2023
94%
84%
102%
97%

2Q
2023
96%
86%
105%
100%

4/206/23
110%
106%
116%
113%

%
COVID
11.7%
11.9%
11.1%
11.5%

%
Count
40%
19%
40%
100%

Tables 5.2 and 5.3 show more detailed industry results for the top 10 industry segments by number of COVID claims.
These are the same top 10 industry groupings and in the same order from the prior public report. Public
Administration (White-Collar), Manufacturing–Auto, Airplanes (Blue-Collar), Misc. Services (Grey-Collar) and
Educational Services (White-Collar) have had the highest A/E ratios since April 2020. Manufacturing–Heavy, Steel(Blue-Collar) had the lowest A/E ratio of the top 10 industries. In these tables, “B," “W,” and “G” refer to Blue-Collar,
White-Collar, and Grey-Collar, respectively.
Table 5.2

EXCESS MORTALITY FOR TOP 10 INDUSTRIES BY NUMBER OF COVID CLAIMS
Industry
W-Public Administration
B-Transport; Communication; Utilities
B-Manufacturing - Auto, Airplanes
B-Manufacturing - Heavy; Steel
W-Educational Services
W-Doctors’ Offices
G-Manufacturing - Paper; Drugs
G-Retail - Trade
G-Wholesale Trade
G-Misc Service/Data Processing
All Industries13

Q1
2021
122%
119%
130%
111%
122%
118%
124%
118%
103%
126%
122%

Q2
2021
107%
102%
118%
96%
106%
103%
106%
101%
96%
113%
107%

Q3
2021
146%
129%
131%
113%
135%
131%
127%
137%
120%
152%
133%

Q4
2021
135%
121%
140%
115%
116%
113%
122%
121%
115%
125%
125%

Q1
2022
133%
113%
129%
100%
106%
109%
109%
104%
97%
120%
116%

Q2
2022
113%
97%
108%
85%
97%
95%
85%
82%
86%
106%
99%

Q3
2022
110%
100%
112%
88%
116%
100%
89%
92%
87%
109%
103%

Q4
2022
119%
100%
117%
90%
113%
100%
88%
89%
84%
103%
104%

1Q
2023
111%
93%
108%
81%
102%
90%
81%
84%
78%
95%
97%

2Q
2023
114%
95%
122%
75%
112%
95%
76%
84%
90%
97%
100%

4/206/23
122%
109%
120%
99%
114%
109%
104%
102%
103%
116%
113%

12 Includes only companies that provided Industry splits; see second bullet at the beginning of Section 5.
13 Includes only companies that provided Industry splits; see second bullet at the beginning of Section 5.

Copyright © 2023 Society of Actuaries Research Institute24

Table 5.3

COVID CLAIMS FOR TOP 10 INDUSTRIES BY NUMBER OF COVID CLAIMS
Industry
W-Public Administration
B-Transport; Communication; Utilities
B-Manufacturing - Auto, Airplanes
B-Manufacturing - Heavy; Steel
W-Educational Services
W-Doctors’ Offices
G-Manufacturing - Paper; Drugs
G-Retail - Trade
G-Wholesale Trade
G-Misc Service/Data Processing
All Industries14

4/206/23
122%
109%
120%
99%
114%
109%
104%
102%
103%
116%
113%

%
COVID
10.8%
11.7%
12.0%
10.6%
10.9%
11.8%
10.5%
12.7%
11.4%
13.4%
11.5%

%
Count
14%
13%
9%
9%
6%
6%
6%
4%
5%
3%
100%

#
COVID
20,677
20,405
14,46012,328
9,378
8,998
8,291
7,371
7,013
5,775
153,436

It should be noted that the high A/E ratios for Public Administration are driven by experience in the Executive,
Legislative and General Government segment (Standard Industry Classification [SIC] codes 9100–9199). This
segment does not include police and fire and consistently represents more than 80% of claims in the broader Public
Administration segment.

5.2 GEOGRAPHY
Results by Geography appear to be consistent with broad population results in terms of timing of regional spikes
across the country, as shown in Table 5.4. The Southeast shows the highest overall A/E ratio since April 2020, as wellas the highest percentage of claims identified as COVID. Smaller differences were seen in A/E ratio by region startingin early 2022, but more material differences can be seen in recent quarters, with the West region being favorable
and the Midwest being the most unfavorable in the second quarter of 2023.
Table 5.4

EXCESS MORTALITY BY GEOGRAPHIC REGION
Region
NortheastWest
MidwestSoutheast
All Regions15

Q1
2021
123%
130%
108%
132%
122%

Q2
2021
108%
105%
105%
110%
107%

Q3
2021
116%
132%
117%
162%
134%

Q4
2021
122%
127%
132%
123%
125%

Q1
2022
119%
114%
117%
118%
116%

Q2
2022
102%
101%
97%
99%
99%

Q3
2022
100%
104%
102%
107%
103%

Q4
2022
108%
104%
103%
106%
105%

Q1
2023
101%
96%
94%
99%
97%

Q2
2023
100%
86%
106%
104%
100%

4/206/23
113%
112%
110%
117%
113%

%
COVID
9.7%
11.3%
10.9%
13.6%
11.5%

%
Count
21%
15%
28%
35%
100%

14 Includes only companies that provided Industry splits; see second bullet at the beginning of Section 5.
15 Includes only companies that provided Geography splits; see second bullet at the beginning of Section 5.

Copyright © 2023 Society of Actuaries Research Institute25

A closer look at the states with the highest number of COVID claims in Tables 5.5 and 5.6 shows results that areconsistent with the regional results in Table 5.4. Three Southeast states (Georgia, Tennessee, and Florida)
contributed to the high cumulative A/E for the Southeast. The high A/E ratios in Michigan and Illinois contributed tothe deterioration in Midwest results in the second quarter of 2023. Similarly, the low A/E ratio for California is in linewith the favorable West result for the quarter.
Table 5.5

EXCESS MORTALITY FOR TOP 10 STATES BY NUMBER OF COVID CLAIMSStateTX - Southeast
CA - WestFL - Southeast
MI - Midwest
OH - Midwest
GA - Southeast
PA - Northeast
IL - Midwest
NY - Northeast
TN - Southeast
All States16

Q1
2021
137%
149%
127%
109%
111%
146%
121%
108%
131%
130%
122%

Q2
2021
104%
103%
116%
116%
100%
117%
108%
102%
109%
116%
107%

Q3
2021
159%
129%
185%
110%
115%
178%
114%
112%
112%
159%
134%

Q4
2021
117%
114%
118%
144%
136%
133%
132%
118%
116%
136%
125%

Q1
2022
114%
116%
114%
115%
114%
121%
116%
115%
116%
126%
116%

Q2
2022
97%
100%
101%
99%
89%
104%
99%
94%
101%
100%
99%

Q3
2022
104%
103%
109%
104%
95%
114%
97%
98%
96%
112%
103%

Q4
2022
100%
102%
104%
102%
97%
109%
107%
101%
107%
115%
105%

Q1
2023
96%
97%
102%
97%
88%
107%
98%
91%
97%
99%
97%

Q2
2023
102%
80%
102%
114%
97%
115%
99%
107%
96%
105%
100%

4/206/23
115%
112%
118%
113%
106%
125%
111%
108%
113%
120%
113%

Table 5.6

COVID CLAIMS FOR TOP 10 STATES BY NUMBER OF COVID CLAIMSStateTX - Southeast
CA - WestFL - Southeast
MI - Midwest
OH - Midwest
GA - Southeast
PA - Northeast
IL - Midwest
NY - Northeast
TN - Southeast
All States17

4/206/23
115%
112%
118%
113%
106%
125%
111%
108%
113%
120%
113%

%
COVID
16.1%
11.7%
11.3%
11.7%
11.7%
14.8%
10.2%
9.6%
9.1%
14.1%
11.5%

%
Count
8%
6%
6%
6%
5%
3%
5%
5%
4%
3%
100%

#
COVID
17,794
10,026
9,376
8,956
7,750
6,814
6,778
6,514
5,491
4,958
155,976

5.3 AGE AND SEXPrevious versions of this report contained exhibits comparing mortality by Sex. Since the second quarter of 2022,
there has been a material increase in claims reported with a Sex of “Unknown,” which distorts comparisons to thebaseline period. Thus, this subsection now only contains results split by age.
For the Age segment, excess mortality for the pandemic period was also split between COVID and non-COVID
claims. For example, for the 45–64 age group, the 15.9% COVID and 4.5% non-COVID total 20.4% excess mortality,
which equates to the 120.4% A/E ratio since April 2020. The 65+ age band continues to have lower A/E ratios than
younger age bands, and all the excess mortality for this age group (which includes retirees) can be explained byclaims coded as COVID. The 0–44 age band exhibited the highest A/E ratio across the pandemic period and has

16 Includes only companies that provided Geography splits; see second bullet at the beginning of Section 5.
17 Includes only companies that provided Geography splits; see second bullet at the beginning of Section 5.

Copyright © 2023 Society of Actuaries Research Institute26

consistently shown the highest A/E by quarter since the middle of 2021. The 45–64 age band has the highest excess
mortality directly attributable to COVID (15.9%), whereas the 0–44 age band has the highest excess mortality fromnon-COVID causes (17.7%), as shown in Table 5.7.
Table 5.7

EXCESS MORTALITY BY AGE BAND
Age

Q1
2021

Q2
2021

Q3
2021

Q4
2021

Q1
2022

Q2
2022

Q3
2022

Q4
2022

Q1
2023

Q2
2023

4/206/23

%
COVID

0-44
45-64
65+
All Ages18

120%
130%
120%
122%

130%
115%
100%
107%

180%
161%
116%
133%

143%
142%
116%
125%

125%
124%
113%
117%

120%
102%
96%
99%

127%
106%
100%
104%

119%
106%
103%
105%

111%
99%
96%
98%

122%
110%
94%
101%

128%
120%
108%
113%

10.7%
15.9%
9.7%
11.5%

NonCOVID
%
17.7%
4.5%
-1.8%
1.5%

%
Count
8%
28%
64%
100%

The greater age band detail in Table 5.8 provides further insight on excess mortality by age. The working-age
population continues to see the highest A/E ratios. The 35–44 age band continues to have the highest cumulative
A/E during the pandemic and has the highest non-COVID excess mortality as well. It is worth noting that "nonCOVID" claims could include claims that are an indirect result of COVID, but are not coded as such in the data.
Table 5.8

EXCESS MORTALITY BY DETAILED AGE BAND
Age
0-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
All Ages19

Q1
2021
101%
118%
129%
132%
129%
130%
122%
111%
122%

Q2
2021
119%
132%
134%
118%
114%
107%
105%
92%
107%

Q3
2021
127%
179%
201%
179%
152%
130%
119%
104%
133%

Q4
2021
112%
137%
158%
150%
138%
124%
122%
107%
125%

Q1
2022
99%
127%
135%
128%
122%
116%
121%
105%
117%

Q2
2022
105%
122%
124%
107%
100%
95%
102%
91%
99%

Q3
2022
120%
131%
128%
112%
103%
99%
107%
94%
104%

Q4
2022
110%
117%
123%
110%
103%
102%
111%
99%
105%

Q1
2023
100%
111%
116%
101%
97%
92%
103%
92%
98%

Q2
2023
115%
119%
126%
117%
107%
96%
101%
87%
101%

4/206/23
111%
128%
135%
125%
118%
112%
113%
102%
113%

%
COVID
2.4%
8.7%
15.0%
17.4%
15.2%
12.3%
10.1%
7.8%
11.5%

NonCOVID
%
9.1%
19.7%
19.9%
8.0%
2.7%
-0.5%
3.1%
-6.3%
1.5%

%
Count
2%
2%
4%
9%
18%
17%
20%
27%
100%

18 Includes only companies that provided Age splits; see second bullet at the beginning of Section 5.
19 Includes only companies that provided Age splits; see second bullet at the beginning of Section 5.

Copyright © 2023 Society of Actuaries Research Institute27

Tables 5.9 and 5.10 were added in the previous public report to separate out each quarter’s excess mortality by age
band into the COVID and non-COVID components. These views show that the third quarter of 2021 Delta wave
onset had significant excess mortality across all typical working age bands from 25 to 64, due to both COVID andnon-COVID causes. The fourth quarter of 2021 continued to show very high COVID deaths in the 25 to 64 age bands,
whereas the non-COVID excess mortality moderated. Starting in the second quarter of 2022, COVID deaths across all
age groups have been relatively lower, but non-COVID mortality continues to be elevated in several age groups,
including 25–44. Note that recent period deaths may continue to shift from non-COVID to COVID as COD coding
becomes more complete.
Table 5.9

EXCESS MORTALITY BY DETAILED AGE BAND—COVID ONLY
Age
0-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
All Ages20

Q1
2021
3%
11%
18%
28%
31%
29%
24%
18%
24%

Q2
2021
2%
6%
11%
13%
11%
7%
5%
2%
7%

Q3
2021
7%
35%
62%
59%
38%
21%
11%
7%
24%

Q4
2021
5%
22%
41%
43%
34%
22%
14%
8%
21%

Q1
2022
4%
13%
19%
27%
25%
21%
18%
12%
19%

Q2
2022
1%
1%
2%
2%
2%
2%
3%
3%
2%

Q3
2022
1%
1%
2%
2%
2%
3%
4%
4%
3%

Q4
2022
0%
1%
2%
1%
2%
2%
3%
4%
3%

Q1
2023
1%
1%
1%
1%
1%
2%
3%
3%
2%

Q2
2023
0%
0%
0%
0%
0%
1%
1%
1%
0%

4/206/23
2%
9%
15%
17%
15%
12%
10%
8%
12%

Table 5.10

EXCESS MORTALITY BY DETAILED AGE BAND – NON-COVID ONLY
Age
0-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
All Ages21

Q1
2021
98%
108%
111%
104%
98%
101%
99%
94%
99%

Q2
2021
117%
126%
123%
106%
103%
100%
100%
89%
100%

Q3
2021
120%
144%
139%
120%
113%
109%
108%
98%
110%

Q4
2021
107%
115%
117%
107%
104%
102%
109%
99%
104%

Q1
2022
95%
114%
115%
101%
98%
95%
103%
93%
98%

Q2
2022
104%
121%
122%
105%
98%
93%
99%
89%
97%

Q3
2022
120%
130%
125%
110%
101%
96%
103%
90%
100%

Q4
2022
109%
116%
122%
108%
102%
99%
107%
95%
102%

Q1
2023
100%
110%
115%
100%
96%
90%
99%
89%
95%

Q2
2023
115%
119%
126%
117%
106%
96%
100%
86%
100%

4/206/23
109%
120%
120%
108%
103%
99%
103%
94%
102%

20 Includes only companies that provided claims split by Age; see second bullet at the beginning of Section 5.
21 Includes only companies that provided claims split by Age; see second bullet at the beginning of Section 5.

Copyright © 2023 Society of Actuaries Research Institute28

5.4 COMPANY SIZE
Contributing companies were assigned a size indicator of Large, Medium, or Small per the criteria described inAppendix C.2.5. Results since April 2020 have indicated higher excess mortality (and higher percentage claims
identified as COVID) by decreasing company size. However, the results by Company Size are generally of the same
magnitude and are usually consistent in pattern from quarter to quarter. Ratios for Large Companies have tended to
be lower than those of other companies for most quarters. The spread by Company Size has narrowed since 2021,
and the second quarter of 2023 is only the second quarter during the study period in which Medium companies
exhibited the lowest A/E ratio (96%).
Table 5.11

EXCESS MORTALITY BY COMPANY SIZECo Size
Large
Medium
Small
All

2Q-4Q
2020
118%
125%
124%
119%

Q1
2021
122%
121%
130%
122%

Q2
2021
106%
108%
111%
106%

Q3
2021
131%
139%
146%
133%

Q4
2021
123%
128%
133%
125%

Q1
2022
115%
118%
123%
116%

Q2
2022
98%
102%
102%
99%

Q3
2022
102%
105%
104%
103%

Q4
2022
104%
105%
109%
104%

Q1
2023
96%
97%
100%
97%

Q2
2023
100%
96%
108%
99%

4/206/23
112%
115%
118%
112%

%
COVID
11.2%
12.4%
12.7%
11.5%

%
Count
79%
16%
4%
100%

Copyright © 2023 Society of Actuaries Research Institute29

Section 6: Detailed Cause of Death
Participating companies were asked to categorize claims by 15 cause of death (COD) groupings. A survey of thecompanies was completed prior to these requests to identify what groupings would be feasible to provide datingback to 2017. This survey, along with CDC cause of death groupings, informed the groupings presented in thisreport. The mapping of these COD groups can be found in Appendix E.
Approximately 30% of claims still fall into the “All Other/Unknown” group. One challenge is that three of the 20
companies were not able to provide more detailed COD information back to 2017 than what was part of the original
survey, and other companies did not track one or more ICD-10 diagnosis code(s) consistently over the course of thestudy period, so some claims that otherwise would have been allocated to one of the new COD categories werelabeled as “Unknown.”
The graphs in Figures 6.1 and 6.2 show excess mortality relative to baseline (2017–2019), ranked by the COD withthe most claim counts at the top (All Other/Unknown) and the fewest at the bottom (Alzheimer’s). The graphs havebeen split into two parts, with the top seven CODs in the first and the bottom seven in the second. Note that the
COVID-19 COD is not shown in these figures because there is no baseline mortality for COVID-19 from 2017 to 2019.
Also, the 2023 incurred periods are incomplete with respect to COD; it is expected that the All Other/Unknowncategory will decrease in excess mortality and other categories will increase in the 2023 periods as COD reporting
matures over time.
Figure 6.1

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—TOP SEVEN CAUSES OF DEATH
All Other / Unknown
Cardiovascular
CancerRespiratory
Accidents (Other)
SuicideAccidents (MV)
20%
2Q23

40%

60%

1Q23

2022

80%
2021

100%
2020

2019

120%
2018

140%

160%

180%

2017

Copyright © 2023 Society of Actuaries Research Institute30

Figure 6.2

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—BOTTOM SEVEN CAUSES OF DEATH
Cerebrovascular
Liver
Drug Overdose
Homicide
Diabetes
Flu/Pneum.
Alzheimer’s
20%
2Q23

40%

60%

1Q23

2022

80%
2021

100%
2020

2019

120%
2018

140%

160%

180%

2017

The Committee notes that Cancer mortality rates dropped over the period of 2017–2022. Excess mortality for
Accidents, both Motor Vehicle and Other, was 5%–15% higher than baseline in years 2021 and 2022. Diabetes andLiver deaths, often cited comorbidities with COVID-19 deaths, appeared to be elevated 5%–20% during much of thepandemic period. Lastly, “deaths of despair,” particularly Drug Overdose and Homicides, increased between 40%–
55% and 15%–20%, respectively, during the pandemic years.
Figure 6.3 displays the COD distribution in the 2017–2019 baseline period by count. Approximately half of the 2017–2019 baseline Group Life claims were Cardiovascular or Cancer. The top 10 COD groupings (excluding All
Other/Unknown) covered approximately two-thirds of all Group Life baseline claims. Although Figure 6.2 shows
substantial percentage increases in the Liver, Diabetes, Drug Overdose and Homicide causes of death during the
pandemic period, Figure 6.3 indicates that these causes constituted a relatively low percentage of overall deaths.

Copyright © 2023 Society of Actuaries Research Institute31

Figure 6.3

GROUP LIFE CAUSE OF DEATH DISTRIBUTION, 2017–2019 BASELINE, BY COUNTAll Other / Unknown
Major Cardiovascular Diseases
CancerRespiratory

31.0%

6.9%

Accidents (Non-Motor Vehicle)
SuicideAccidents (Motor Vehicle)
Cerebrovascular, Including Stroke

22.9%

Liver
Diabetes
Influenza and Pneumonia
27.0%

Drug Overdose
Homicide
Alzheimer’s

Beginning with this iteration of the report, the Committee is including additional excess mortality graphs by cause ofdeath that show a breakdown for three different age groupings, 0-44, 45-64, and 65-99. See Figures 6.4 through 6.9
below. These graphs mirror the graphs shown earlier in this section, but not all carriers provided age detail for
claims, so the cohort of carriers used to develop these age grouping graphs represents roughly 93% of the claims
used to develop those for the total claims in Figures 6.1 and 6.2. Similar to the graphs shown above, the graphs
have been split into two parts, with the top seven CODs in the first and the bottom seven in the second for each of
the age groupings. Also, the 2023 incurred periods are incomplete with respect to COD; it is expected that the All
Other/Unknown category will decrease in excess mortality and other categories will increase in the 2023 periods as
COD reporting matures over time.
Figure 6.4

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—TOP SEVEN CAUSES OF DEATH AGES 0-44

All Other / Unknown
Cardiovascular
Accidents (Other)CancerAccidents (MV)
SuicideDrug Overdose
20%
2Q23

40%

60%

80%

1Q23

2022

2021

100%
2020

120%

2019

2018

140%

160%

180%

2017

Copyright © 2023 Society of Actuaries Research Institute

32

Figure 6.5

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—BOTTOM SEVEN CAUSES OF DEATH AGES 0-44

Homicide
Respiratory
Liver
CerebrovascularDiabetes
Flu/Pneum.
Alzheimer’s
20%
2Q23

40%

60%

1Q23

2022

80%
2021

100%
2020

2019

120%
2018

140%

160%

180%

2017

The Committee notes that, for the 0-44 age band, the All Other/Unknown category shows the highest excess
mortality (237%22) for the most recent quarter relative to other age bands. As noted above, as COD reporting
matures over time, this excess will decrease and the excess for other categories will increase. In the top sevencauses, Cardiovascular, Accidents (Motor Vehicle and Other), and Drug Overdose all appear to be meaningful
contributors to the excess mortality for this age band. While Cancer appears to show some improvement, theimprovement is not as pronounced as the other two age bands. For the bottom seven causes, all of the causes
appear to show some material excess mortality at different points in the pandemic, but note that many of thesecauses have quite low death counts in the baseline period (e.g., Alzheimer’s), so even a low amount of deaths can
produce a fairly heightened actual-to-expected ratio.

22 To keep the scaling of the graphs consistent, the maximum percentage shown in Figure 6.4 is 185%.

Copyright © 2023 Society of Actuaries Research Institute

33

Figure 6.6

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—TOP SEVEN CAUSES OF DEATH AGES 45-64

All Other / Unknown
CancerCardiovascular
Respiratory
Accidents (Other)
SuicideAccidents (MV)
20%
2Q23

40%

60%

80%

1Q23

2022

2021

100%
2020

120%

2019

2018

140%

160%

180%

2017

Figure 6.7

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—BOTTOM SEVEN CAUSES OF DEATH AGES 45-64

Liver
Cerebrovascular
Drug Overdose
Diabetes
Flu/Pneum.
Homicide
Alzheimer’s
20%
2Q23

40%

60%

1Q23

2022

80%
2021

100%
2020

2019

120%
2018

140%

160%

180%

2017

The Committee notes that, for the 45-64 age band, Cardiovascular, Respiratory, and Accidents (Other) appear to be
noteworthy contributors to excess mortality from the top seven causes. For Cancer, unlike the 0-44 age band, the45-64 age band shows a steady, more pronounced improvement over the course of the pandemic. For the bottom
seven causes, many of the causes appear to show some material excess mortality at different points in the
pandemic, but as was the case with the previous age band, many of these causes have quite low death counts in thebaseline period, so even a low amount of deaths can produce a fairly heightened actual-to-expected ratio.

Copyright © 2023 Society of Actuaries Research Institute

34

Figure 6.8

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—TOP SEVEN CAUSES OF DEATH AGES 65-99

All Other / Unknown
Cardiovascular
CancerRespiratory
Accidents (Other)
Cerebrovascular
Liver
20%
2Q23

40%

60%

1Q23

2022

80%
2021

100%
2020

2019

120%
2018

140%

160%

180%

2017

Figure 6.9

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—BOTTOM SEVEN CAUSES OF DEATH AGES 65-99

Flu/Pneum.
SuicideDiabetes
Alzheimer’s
Accidents (MV)
Drug Overdose
Homicide
20%
2Q23

40%

60%

1Q23

2022

80%
2021

100%
2020

2019

120%
2018

140%

160%

180%

2017

The Committee notes that, for the 65-99 age band, Accidents (Other) is the COD with the most pronounced excess
among the top seven causes. Like the 45-64 age band, Cancer shows a fairly steady improvement over the course of
the pandemic. Interestingly, the other CODs in the top seven (Cardiovascular, Respiratory, Cerebrovascular, andLiver) do not show the level of excess mortality seen in the other two age bands. Presumably, COVID may havedisplaced some of these causes of death for the 65-99 age band. As noted for the other age bands, for the bottom
seven causes, the number of deaths can be somewhat low, so even a low amount of deaths can produce a fairly

Copyright © 2023 Society of Actuaries Research Institute35heightened actual-to-expected ratio. One notable observation is that the excess mortality percentage for Drug
Overdose has been high throughout the pandemic period for the 65-99 age band, despite this cause of death being
typically associated with younger age groups.

Copyright © 2023 Society of Actuaries Research Institute36

Section 7: Exposure Trends
7.1 PREMIUMSThe Committee reviewed the premiums submitted for the study to determine if the premium exposure was stableor exhibited volatility during the experience period. Figure 7.1 indicates a gradual increase in premium exposure
during the experience period, as expected when wage inflation is considered. Supplemental premium is growing at afaster rate and, if current trends continue, supplemental premium will become the majority in the next few years.
The 2023 premiums in Figure 7.1 are reported premiums through June 2023. The overall trends in premium by year
shown below are consistent, which is helpful for validating the premium data used for calculating premium per life
(PPL) metrics and estimating covered lives when carriers could not provide this information.
Figure 7.1

REPORTED PREMIUM ($ BILLIONS) BY YEAR, 2017–2023
12.0

9.8

9.0

8.7

10.0

10.3

10.1

10.5
9.4

9.8

10.5 10.2

10.9 10.8

2021

2022

11.5 11.3

8.0
6.0
4.0
2.0
2017

2018

2019

2020

Basic

2023
(Annualized)

Supplemental

Copyright © 2023 Society of Actuaries Research Institute37

7.2 LIVESThe Committee also reviewed life-years of exposure (LYE) reported for the study. Figure 7.2 shows LYE from 2017
through the second quarter of 2023. A slight drop in LYE occurred in 2021, possibly because of disruptions from the
COVID-19 pandemic. Otherwise, basic LYE was relatively stable during the experience period, and supplemental LYE
has been increasing gradually.
Figure 7.2

LIFE-YEARS OF EXPOSURE (MILLIONS) BY YEAR, 2017–2023

120.0
100.0

98.3

97.6

96.2

95.4

99.2

96.5

100.4

80.0
60.0
31.5

40.0

33.0

32.0

35.4

33.9

33.6

35.9

20.0
2017

2018

2019

2020
Basic

2021

2022

2023

Supplemental

Table 7.1 shows average premium per LYE based on the data provided for the study along with the change from theprior year. In 2020, the average premium per LYE increased by 0.5% for Basic coverages, which is lower than any
other period and likely related to the sharp increase in unemployment. Basic coverage increased significantly in thefirst half of 2023, which may suggest carriers are increasing rates. Supplemental has outpaced Basic in growth inmost periods. 2020 and 2021 could be because consumers may have elected for additional coverage as the
pandemic was at its peak.
Table 7.1

AVERAGE PREMIUM PER LIFE-YEARS OF EXPOSURE BY YEAR AND COVERAGE TYPE
Year

Average Premium per LYE

Change in Average Premium per LYE

2017

Basic
$102.8Supplemental$276.3

Basic
NA

Supplemental
NA

2018

$104.8$280.5

1.9%

1.5%

2019

$106.0$285.8

1.1%

1.9%

2020

$106.5$292.3

0.5%

2.3%

2021

$109.1$299.6

2.5%

2.5%

2022
Q1-Q2 2023

$110.4$114.9$305.2$313.9

1.2%
4.1%

1.9%
2.9%

Copyright © 2023 Society of Actuaries Research Institute38

Table 7.2 shows average exposure per LYE and the change from the prior year. In 2021, the average exposure per
LYE decreased by 1.8% for Basic coverages, but increased 0.9% for Supplemental coverages. Before 2021, thechanges in average premium per LYE were limited, with most of the exposure growth coming from the
Supplemental line. The 4.3% increase in the Supplemental average exposure per LYE in 2022 may be attributed to
employees increasing their Supplemental benefit amounts because of the COVID-19 pandemic and above-average
wage growth.
Table 7.2

AVERAGE LIFE-YEARS OF EXPOSURE BY YEAR AND COVERAGE TYPE
Year

Average LYE
BasicSupplemental

Change in Average LYE
BasicSupplemental

2017

95,40831,454

NA

NA

2018

96,16732,049

0.8%

1.9%

2019

97,62332,979

1.5%

2.9%

2020

98,27133,645

0.7%

2.0%

2021

96,53533,943

-1.8%

0.9%

2022

99,19635,410

2.8%

4.3%

Q1-Q2 2023

100,375

35,8981.2%

1.4%

Copyright © 2023 Society of Actuaries Research Institute39

Section 8: Company Variations
8.1 VARIATIONS IN COVID-19 MORTALITY RESULTS
The survey showed that all participating companies had elevated Group Life mortality experience during the
pandemic. However, the level of excess mortality varied between carriers. To provide insight into the dispersion ofindustry experience, Tables 8.1 and 8.2 provide the quartile baseline and pandemic experience, ranked by highest
implied excess mortality percentage (by claim count) to lowest over the full pandemic period. The quartile incidence
rates and excess mortality ratios are the weighted average of the five contributing companies’ incidence rates ineach quartile. In previous reports, the companies who had the highest increase in incidence also had the higher
baseline incidence. This was mostly coincidental and, as we return to more normal levels of incidence, is no longer
the case.
Table 8.1

QUARTERLY SEASONALLY-ADJUSTED INCURRED INCIDENCE RATES (BY COUNT)—COMPANY QUARTILES
2021

2022

Q1 2023

Q2 2023

2.360

Q2 2020–
Q4 2020
2.991

3.166

2.644

2.431

Quartile 2

3.774

4.464

4.508

4.109

Quartile 3

2.870

3.365

3.438

2.905

Quartile 4

4.095

4.558

4.519

Total

3.246

3.860

3.945

Quartile

Baseline

Quartile 1

2.471

Q1-Q2
2023
2.451

Q2 2020–
Q2 2023
2.850

3.805

4.001

3.903

4.277

2.550

2.510

2.530

3.114

3.737

3.449

3.460

3.455

4.120

3.424

3.142

3.227

3.184

3.643

Table 8.2

QUARTERLY SEASONALLY-ADJUSTED INCURRED A/E RATIOS (BY COUNT)—COMPANY QUARTILES
2021

2022

Q1 2023

Q2 2023

2.360

Q2 2020–
Q4 2020
126.8%

134.2%

112.0%

103.0%

3.774

118.3%

119.4%

108.9%

100.8%

Quartile 3

2.870

117.3%

119.8%

101.2%

Quartile 4

4.095

111.3%

110.4%

Total

3.246

118.9%

121.5%

Quartile

Baseline

Quartile 1
Quartile 2

104.7%

Q1-Q2
2023
103.9%

Q2 2020–
Q2 2023120.8%

106.0%

103.4%

113.3%

88.9%

87.5%

88.2%

108.5%

91.3%

84.2%

84.5%

84.4%

100.6%

105.5%

96.8%

99.4%

98.1%

112.2%

Copyright © 2023 Society of Actuaries Research Institute40

8.2 VARIATIONS IN COVID-19 CLAIM CODING PROCEDURES
Participating carriers were asked about the data sources and procedures they used to determine whether a claim
should be coded as a COVID-19 cause of death. Eighteen of the 20 carriers in the survey provided details on theirclaim coding procedures, and the Committee learned the following:•

Seventeen of the 18 respondents included the claim as a COVID-19 death if COVID-19 appeared anywhereon the death certificate.
• Eight of the 18 appeared to do everything in their power to research all available sources to create an
exhaustive tracking of all claims where COVID was a contributing cause. These companies used five or
more of the following sources to identify whether a death was caused by COVID-19:
o Primary cause of death on death certificate
o Secondary cause of death on death certificate
o Claim formo Communication with employer or beneficiaryo Obituaryo Communication with medical examiner or funeral home
• One carrier coded claims with cause of COVID-19 only when COVID-19 was identified as the primarycause of death on the death certificate.
• The other nine participating carriers generally classified a death as COVID-19 if it appeared anywhereon the death certificate.

8.3 VARIATIONS IN CLAIM REPORTING PATTERNSAppendix D.4 documents that incurred claim completion rates varied significantly from company to company. Upon
analyzing the differences, the 20 contributing companies were grouped into five “reporting speed” groups based on
similar reporting patterns.
The Committee investigated whether the company reporting speed groupings would be correlated to company size.
However, this was not the case. The Large, Medium and Small companies are well dispersed among the fivereporting speed categories.

Copyright © 2023 Society of Actuaries Research Institute41

Section 9: Comparisons to General U.S. Population Mortality Results
9.1 AGGREGATE EXCESS MORTALITY COMPARISONS
From April 2020 through June 2023, 155,834 incurred COVID claims were estimated to be in the Group Life survey
data, compared with approximately 1.13 million COVID deaths in the U.S. population during the same time span
according to the Centers for Disease Control and Prevention (CDC). 23
Past studies that compared insured mortality to population mortality have found that mortality among insured lives
tended to be lower. In particular, the SOA’s 2016 Group Term Life Mortality Study 24 found that, in the key working
ages, insured mortality was between 30% and 40% of general population mortality. This is often considered to be afunction of the fact that an employee generally is in good health to be actively at work, often has access to healthcare and tends to have a higher level of income (which is correlated with better health). Because the mortality rates
between the two populations tend to differ, the Committee analyzed the relative impact of the COVID-19 pandemic
on the Group Life data and the U.S. population by considering excess death percentages, defined as the percentage
increase in mortality rate over a baseline expectation.
The excess deaths in the Group Life data were determined via a comparison to average death rates in the Group Life
data from the 2017–2019 baseline, adjusted for seasonality. For the U.S. population, the Committee considered two
different expectation bases. The first basis was expected deaths published by the CDC 25, which were developed
using Farrington surveillance algorithms and historical data26 (CDC method). For the second method, the Committee
estimated expected deaths by computing the average CDC deaths from 2017 through 2019 and adjusting thisaverage for changes in U.S. population size, changes in the U.S. population demographic mix by age and sex, and thetrend for death rates by age group (Committee method).
Table 9.1 shows the evolution of this comparison by quarter using the Committee method for U.S. population
results. The observed pattern is that the Group Life proportional excess mortality was below the U.S. population
results at the start of the pandemic, then higher from the fourth quarter of 2020 through the first quarter of 2022,
and then again below the U.S. population levels from the second quarter of 2022 and later.
Please note that there are some differences from numbers in the prior report. The Group Life results for periods in2022 are now substantially more complete. For example, in the last report, we estimated excess mortality in the
fourth quarter of 2022 at 5% and this now has completed to 4.2%. Due to the CDC’s discontinuance of weekly
summaries by sex and age, the source of information has been changed to the CDC’s summaries of deaths bymonth, sex, and age.27 This change produced only minor changes in the U.S. population numbers. Note that there
are still significant completion estimates used for the first quarter of 2023, and especially for the second quarter of2023, so these numbers may complete differently.

23 National Center for Health Statistics, Provisional Death Counts for Coronavirus Disease 2019 (COVID-19),https://www.cdc.gov/nchs/nvss/vsrr/covid19/index.htm.
24 Society of Actuaries, 2016 Group Term Life Mortality Study & Tables, https://www.soa.org/resources/experience-studies/2016/2016-group-lifemortality-study/.
25 National Center for Health Statistics. Excess Deaths Associated with COVID-19, https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm.
26 More information can be found in the technical notes on the National Center for Health Statistics website, where the CDC publishes excess deaths:
https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm#techNotes.
27 https://data.cdc.gov/NCHS/Provisional-COVID-19-Deaths-by-Sex-and-Age/9bhg-hcku

Copyright © 2023 Society of Actuaries Research Institute42

Table 9.1

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER
Incurred
QuarterGroup Life

U.S.
Population

DifferenceQ1 2020

-1.4%

0.1%

-1.5%

Q2 2020

14.4%

19.8%

-5.4%

Q3 2020

14.9%

16.7%

-1.8%

Q4 2020

28.0%

25.6%

2.4%

Q1 2021

22.4%

17.0%

5.4%

Q2 2021

6.5%

4.9%

1.6%

Q3 2021

32.8%

23.3%

9.6%

Q4 2021

24.6%

18.9%

5.7%

Q1 2022

16.6%

15.3%

1.2%

Q2 2022

-1.3%

1.8%

-3.1%

Q3 2022

2.9%

7.0%

-4.1%

Q4 2022

4.2%

7.4%

-3.2%

Q1 2023

-3.2%

-1.5%

-1.7%

Q2 2023

-0.6%

-0.4%

-0.2%

9.2 EXCESS MORTALITY COMPARISON BY AGE
Most participants in the Group Life Survey provided a distribution of claims by age, but were not able to provide a
distribution of exposure by age. For this reason, the comparisons below show claim counts unadjusted by any
changes in exposure by age. The seasonality adjustment, which was determined in aggregate for all ages, has also
been removed to show a more direct comparison. Removing the seasonal adjustment does produce slightly
different excess ratios than what was reported above in Table 5.7.
Table 9.2 shows the actual-to-baseline ratios by broad age group. These excess percentages have been adjusted foroverall changes in exposure, but not for seasonal differences, either in total or by age.
Please note that the prior version of this report also had segmentation by sex, but we have seen a much higher
proportion of claims submitted with an unknown sex. These deaths with unknown sex are disproportionately fromolder-aged claims so, when segmenting by age, we see artificially low mortality levels at the older ages. For thisreason, we have dropped this segment.
Since not all carriers supply age, the “All Ages” results will differ slightly from the totals elsewhere in this report.

Copyright © 2023 Society of Actuaries Research Institute43

Table 9.2

EXCESS DEATH PERCENTAGES BY BROAD AGE GROUP28
Age

Population

Q2-Q4
2020

FY 2021

Q1 2022

Q2 2022

Q3 2022

Q4 2022

Q1 2023

Q2 2023

15-44

Group Life

21.6%

42.9%

31.8%

17.0%

22.4%

20.8%

16.7%

18.9%

15-44

U.S. Pop.

29.0%

40.7%

31.7%

22.4%

26.7%

24.4%

16.9%

19.2%

15-44

Difference

-7.4%

2.2%

0.2%

-5.4%

-4.2%

-3.5%

-0.1%

-0.3%

45-64

Group Life

21.3%

37.0%

30.9%

-0.3%

2.0%

7.3%

3.3%

7.5%

45-64

U.S. Pop.

19.1%

26.1%

24.9%

0.3%

2.1%

7.0%

0.7%

-4.0%

45-64

Difference

2.3%

10.9%

6.0%

-0.6%

-0.1%

0.3%

2.6%

11.5%

65-99

Group Life

14.9%

13.1%

18.8%

-6.7%

-4.5%

4.9%

0.2%

-8.4%

65-99

U.S. Pop.

21.0%

16.6%

28.2%

1.9%

5.1%

15.7%

11.9%

1.7%

65-99

Difference

-6.1%

-3.6%

-9.3%

-8.7%

-9.6%

-10.9%-11.8%-10.1%All Ages

Group Life

17.2%

22.1%

23.2%

-3.0%

-0.5%

6.8%

2.4%

-1.8%

All Ages

U.S. Pop.

21.1%

19.9%

27.7%

2.9%

5.8%

14.6%

10.0%

1.7%

All Ages

Difference

-3.9%

2.2%

-4.5%

-5.9%

-6.3%

-7.7%

-7.7%

-3.5%

When considering the totals by age, the Group Life population generally has better experience than the U.S.
population at the younger and older ages while, in the age band from 45-64, the U.S. population has better
experience than the Group Life population except in the second quarter of 2022.
Note also that the 2023 Group Life results were as of June 30, 2023 and, therefore, include a significant completion
assumption. This assumption is determined in aggregate and may not be appropriate by age. For example, theCommittee suspects that deaths for younger ages are reported more quickly than for older ages and, thus, the 2023
results will likely not end up as unfavorable for the 15-44 age band. However, the 2022 results are fairly complete
and still show significantly lower excess mortality for the older ages.
One of the observations from both the Group Life Survey and the U.S. population results is that the deaths werehigher than expected through the first quarter of 2022 for all age groups and have remained higher than expected
for the 15-44 age group, even after excluding explicit COVID-19 deaths. This comparison is captured in Table 9.3

28 Because there are an immaterial amount of 0-14 year-olds in the Group Life population, the U.S. population ages 15-44 is used for comparison. For

consistency, the Group Life population uses the same age range label. For the U.S. population “All Ages” row, ages 0-14 are excluded.

Copyright © 2023 Society of Actuaries Research Institute44

Table 9.3

EXCESS DEATH PERCENTAGES, EXCLUDING COVID-19, BY BROAD AGE GROUP
AgePopulation

Q2-Q4
2020

FY 2021

Q1 2022

Q2 2022

Q3 2022

Q4 2022

Q1 2023

Q2 2023

15-44

Group Life

13.0%

20.0%

17.9%

15.4%

20.9%

19.7%

15.9%

18.8%

15-44

U.S. Pop.

22.5%

27.2%

18.8%

20.6%

24.3%

22.6%

15.5%

18.7%

15-44

Difference

-9.5%

-7.2%

-0.9%

-5.2%

-3.4%

-2.9%

0.4%

0.0%

45-64

Group Life

5.0%

6.4%

6.4%

-1.9%

0.0%

5.8%

2.1%

7.0%

45-64

U.S. Pop.

5.0%

6.0%

2.5%

-2.1%

-1.4%

4.3%

-1.6%

-4.9%

45-64

Difference

0.1%

0.4%

3.9%

0.2%

1.4%

1.5%

3.7%

11.9%

65-99

Group Life

0.4%

0.2%

3.0%

-9.1%

-8.2%

1.7%

-2.7%

-9.2%

65-99

U.S. Pop.

3.5%

3.4%

7.2%

-1.6%

-1.0%

10.3%

6.8%

-0.1%

65-99

Difference

-3.1%

-3.2%

-4.2%

-7.4%

-7.2%

-8.6%

-9.5%

-9.1%

All Ages

Group Life

2.7%

3.5%

5.1%

-5.1%

-3.6%

4.3%

0.2%

-2.4%

All Ages

U.S. Pop.

4.9%

5.4%

7.0%

-0.4%

0.5%

9.9%

5.7%

0.1%

All Ages

Difference

-2.2%

-1.8%

-1.9%

-4.7%

-4.0%

-5.6%

-5.6%

-2.6%

For the older ages, the Group Life and U.S. population deaths, excluding COVID-19, were below expectations
starting in the second quarter of 2022 and forward, except for the fourth quarter of 2022. The Group Life
experience also is proportionally worse in ages 45-64, but otherwise somewhat better than the U.S. population at
younger and older ages. The larger differences in the second quarter of 2023 should be considered unsettled due tothe importance of the completion assumptions.
To visualize the differences by age over time, Figures 9.1 through 9.6 show ratios of actual total and non-COVID
deaths to baseline expectations by month and age group. Results in the second quarter of 2023 should beconsidered uncertain.
Figure 9.1

EXCESS DEATH PERCENTAGES ALL DEATHS, UNDER AGE 45

Jun-23

Dec-22Mar-23Jun-22

Sep-22

Dec-21

Mar-22Jun-21

Sep-21

Dec-20Mar-21

Jun-20

Sep-20Dec-19U.S. Population

Mar-20Jun-19Sep-19Dec-18Jun-18

Sep-18Dec-17Mar-18Jun-17

Sep-17

Dec-16

Mar-17Mar-19Group Life

200%
190%
180%
170%
160%
150%
140%
130%
120%
110%
100%
90%
80%

Copyright © 2023 Society of Actuaries Research InstituteDec-16

Jun-19Dec-20Dec-17

Sep-21

Jun-21

Mar-21

Dec-20

Sep-20Jun-20Mar-20Dec-19Sep-19Jun-19Mar-19Dec-18

Sep-18Jun-18Mar-18Dec-22Mar-23Jun-23

Dec-22Mar-23Jun-23Jun-22
Sep-22Jun-22
Sep-22

Dec-21

U.S. Population
Mar-22EXCESS DEATH PERCENTAGES ALL DEATHS, AGES 45-64

Dec-21Figure 9.3

Mar-22

Sep-21

Jun-21

Mar-21

Group Life

Sep-20Jun-17
Sep-17

Group Life

Jun-20Mar-20Dec-19Sep-19

200%
190%
180%
170%
160%
150%
140%
130%
120%
110%
100%
90%
80%
Mar-19Dec-16
Mar-17140%

Dec-18

Sep-18Jun-18Mar-18Dec-17

Sep-17

Jun-17Mar-1745

Figure 9.2

EXCESS DEATH PERCENTAGES EXCLUDING COVID-19, UNDER AGE 45
U.S. Population

130%

120%

110%

100%

90%

80%

Copyright © 2023 Society of Actuaries Research InstituteDec-16

Jun-19Dec-20Dec-17

Sep-21

Jun-21

Mar-21

Dec-20

Sep-20Jun-20Mar-20Dec-19Sep-19Jun-19Mar-19Dec-18

Sep-18Jun-18Mar-18Dec-22Mar-23Jun-23

Dec-22Mar-23Jun-23Jun-22
Sep-22Jun-22
Sep-22

Dec-21

U.S. Population
Mar-22EXCESS DEATH PERCENTAGES ALL DEATHS, AGES 65 AND OVER

Dec-21Figure 9.5

Mar-22

Sep-21

Jun-21

Mar-21

Group Life

Sep-20Jun-17
Sep-17

Group Life

Jun-20Mar-20Dec-19Sep-19

200%
190%
180%
170%
160%
150%
140%
130%
120%
110%
100%
90%
80%
Mar-19Dec-16
Mar-17140%

Dec-18

Sep-18Jun-18Mar-18Dec-17

Sep-17

Jun-17Mar-1746

Figure 9.4

EXCESS DEATH PERCENTAGES EXCLUDING COVID-19, AGES 45-64
U.S. Population

130%

120%

110%

100%

90%

80%

Copyright © 2023 Society of Actuaries Research Institute47

Figure 9.6

EXCESS DEATH PERCENTAGES EXCLUDING COVID-19, AGES 65 AND OVER
Group Life

140%

U.S. Population

130%
120%
110%
100%
90%

Jun-23

Dec-22Mar-23Jun-22

Sep-22

Dec-21

Mar-22Jun-21

Sep-21

Dec-20Mar-21

Jun-20

Sep-20Dec-19Mar-20Jun-19Sep-19Dec-18Mar-19Jun-18

Sep-18Dec-17Mar-18Jun-17

Sep-17

Dec-16

Mar-1780%

For older ages, the Group Life experience has been consistently better than the U.S. population throughout the
pandemic, with the gap widening in recent periods. For ages 45-64, the experience is quite consistent between thetwo populations. The divergence in the second quarter of 2023 is likely due to completion uncertainty.
The Committee looked at the effect that the different age distributions had on the relationship between the U.S.
population and Group Life results. The Committee compared actual total excess deaths for the U.S. population towhat the total excess deaths would have been had the distribution of claims by age matched what we observed forGroup Life. This produced very little difference in the total excess, meaning that age distribution alone does not
explain much of the difference in excess mortality between the two populations over time.
9.3 EXCESS MORTALITY COMPARISON BY CAUSE OF DEATH
Carriers were asked to provide 15 different causes of death, including COVID-19. The CDC provides detailed causesof death (ICD-10 Codes), which can be mapped to the 15 Group Life CODs using the definitions listed in appendix E.
Using information furnished by the Group Life survey participants and the CDC, the Committee investigateddifferences in excess mortality by cause of death. Both the CDC and Group Life datasets tended to have a high levelof unknown causes for more recent deaths because it often takes time to investigate the actual causes. The CDC
suppresses deaths due to external causes for six months to allow time to do a full assessment. For this reason, thissection includes only deaths through the end of 2022.
Seasonality can be very important for causes of death, so rather than rely on the overall seasonal adjustments
described earlier in this report, the Committee compared deaths in the years 2020–2022 to the same months in thebaseline period. For example, the first quarter of 2021 was compared to the average from the first quarters of theyears 2017 through 2019.

Copyright © 2023 Society of Actuaries Research Institute

48

Table 9.4 compares the causes of deaths between the two populations. These excess percentages have beenadjusted for overall changes in exposure, but not for seasonal differences, either in total or by diagnosis.
Table 9.4

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER, ALL AGES

Cause of Death

Baseline Percent ofClaimsPercent Change in Claim Counts
2020
Group
U.S.
Life
CDC
7.5%
9.7%

2021
Group
U.S.
Life
CDC
9.9%
10.7%

2022
Group
U.S.
Life
CDC
11.4%
23.0%

All Other / Unknown

31.1%

U.S.
CDC
23.2%

Major Cardiovascular Diseases

26.5%

23.1%

1.9%

5.4%

1.6%

4.6%

-4.3%

4.8%

Cancer

22.9%

21.1%

-4.5%

-0.6%

-6.0%

-0.6%

-13.0%-1.0%

Respiratory

6.9%

7.8%

-1.7%

-3.5%

-4.4%

-7.6%

-7.1%

-5.3%

Accidents (non-motor vehicle)

3.0%

3.2%

9.3%

7.8%

14.7%

15.3%

12.5%

6.7%

Suicide

2.2%

1.7%

-5.8%

-4.6%

0.2%

-0.5%

-4.2%

0.3%

Accidents (motor vehicle)

1.9%

1.4%

-0.1%

5.5%

10.7%

16.8%

5.4%

8.9%

Cerebrovascular, including stroke

1.8%

5.2%

2.6%

7.1%

-3.7%

8.2%

-13.1%

8.9%

Liver

1.1%

1.5%

3.9%

18.8%

14.8%

29.5%

5.7%

24.4%

Drug Overdose

0.6%

1.8%

44.4%

40.5%

56.8%

65.1%

41.9%

57.3%

Diabetes

0.6%

3.0%

23.0%

18.4%

4.9%

19.0%

4.3%

15.7%

Influenza & Pneumonia

0.6%

1.9%

14.6%

-3.4%

-3.8%

-24.8%-17.4%-17.5%

Homicide

0.6%

0.7%

18.1%

27.3%

19.1%

34.0%

16.4%

21.8%

Alzheimer’s

0.2%

4.3%

32.1%

9.2%

2.4%

-3.4%

-2.7%

-3.4%

Total Excluding COVID-19

100.0%

100.0%

2.6%

5.4%

3.0%

5.3%

-0.6%

7.5%

COVID-19

0.0%

0.0%

11.2%

12.2%

18.6%

14.5%

6.3%

6.4%

Total

100.0%

100.0%

13.8%

17.6%

21.6%

19.7%

5.7%

13.8%

Group Life

There is no baseline expectation for COVID-19, so these are compared to the total deaths across all causes. The
causes are sorted by total baseline claims for Group Life. The All Other/Unknown category is a larger percentage ofthe overall deaths for Group Life because some carriers were not able to provide all causes of death consistently
back to 2017, as described in Section 6. All U.S. population deaths have an established cause, except for those listed
as ill-defined (ICD-10 R99). The higher proportion in the category in 2022 are likely still due to deaths for which thecause has not yet been established.
There are some differences between the distribution of excess death causes between the two sources. Group Life
excess deaths are generally lower for drug overdose, liver disease, cerebrovascular, major cardiovascular diseases,
homicides and cancer, and relatively higher for Alzheimer’s, non–motor vehicle accidents, and flu and pneumonia.

Copyright © 2023 Society of Actuaries Research Institute49

The percentage change can be misleading because a high percentage increase can be caused by relatively few
excess deaths when the overall death level in the category is small. Table 9.5 gives a similar view, except that theexcess deaths for each cause are divided by the total baseline death expectations. For example, in the Group Lifedata, the excess deaths due to major cardiovascular disease in 2021 were 0.5% of the baseline expectation.
Table 9.5

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER
Baseline Percent ofClaimsNumber of Excess Deaths Divided by Total Baseline
2021
Group
U.S.
Life
CDC
3.1%
2.5%

2022
Group
U.S.
Life
CDC
3.5%
5.3%

1.2%

0.4%

1.1%

-1.1%

1.1%

-0.1%

-1.4%

-0.1%

-3.0%

-0.2%

-0.3%

-0.3%

-0.6%

-0.5%

-0.4%

0.3%

0.4%

0.5%

0.4%

0.2%

-0.1%

-0.1%

0.0%

0.0%

-0.1%

0.0%

1.4%

0.0%

0.1%

0.2%

0.2%

0.1%

0.1%

5.2%

0.0%

0.4%

-0.1%

0.4%

-0.2%

0.5%

1.1%

1.5%

0.0%

0.3%

0.2%

0.4%

0.1%

0.4%

Drug Overdose

0.6%

1.8%

0.3%

0.7%

0.3%

1.2%

0.3%

1.0%

Diabetes

0.6%

3.0%

0.1%

0.6%

0.0%

0.6%

0.0%

0.5%

Influenza & Pneumonia

0.6%

1.9%

0.1%

-0.1%

0.0%

-0.5%

-0.1%

-0.3%

Homicide

0.6%

0.7%

0.1%

0.2%

0.1%

0.2%

0.1%

0.1%

Alzheimer’s

0.2%

4.3%

0.1%

0.4%

0.0%

-0.1%

0.0%

-0.1%

100.0%

100.0%

2.6%

5.4%

3.0%

5.3%

-0.6%

7.5%

Cause of Death

2020
Group
U.S.
Life
CDC
2.3%
2.3%

All Other / Unknown

Group
Life
31.1%

U.S.
CDC
23.2%

Major Cardiovascular Diseases

26.5%

23.1%

0.5%

Cancer

22.9%

21.1%

-1.0%

Respiratory

6.9%

7.8%

-0.1%

Accidents (non-motor vehicle)

3.0%

3.2%

0.3%

Suicide

2.2%

1.7%

Accidents (motor vehicle)

1.9%

Cerebrovascular, including stroke

1.8%

Liver

Total Excluding COVID-19
COVID-19

0.0%

0.0%

11.2%

12.2%

18.5%

14.5%

6.3%

6.4%

Total

100.0%

100.0%

13.8%

17.6%

21.6%

19.7%

5.7%

13.8%

Aside from COVID-19, we see that All Other/Unknown is the largest contributor to excess deaths in all three years
and for both populations. The Committee does not have any details on these claims from the Group Life survey, butthese details are available for the U.S. population (see Table 9.6 below).
The next-largest contributor to excess deaths has generally been major cardiovascular disease, with the exception of
the experience for the Group Life population in 2022, when this COD had deaths below baseline. The increase in
drug overdoses is more significant within the U.S. population than Group Life, whereas liver disease (cirrhosis) iselevated in both populations. Diabetes deaths are elevated in both populations, but represent a much smaller
proportion of deaths for Group Life. Non-motor vehicle accidents are elevated in all years and in both populations.

Copyright © 2023 Society of Actuaries Research Institute50

To help visualize the dynamics, Figures 9.7 through 9.12 show deaths relative to the baseline by cause and monthfor the two populations. The deaths are compared to the same month in the baseline period. Since many causes ofdeath on recent deaths remain unknown, the charts show results up through the end of 2022.
Figure 9.7

DEATHS RELATIVE TO BASELINE—MAJOR CARDIOVASCULAR DISEASE
Group Life

120%

U.S. Population

110%

100%

90%

Dec-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Dec-20Mar-21

Jun-20

Sep-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

Figure 9.7 shows that, during 2022, there was a significant drop-off in cardiovascular deaths in the Group Life
population, while the U.S. population still shows excess mortality from this cause comparable to that seen in 2020
and 2021.
Figure 9.8

DEATHS RELATIVE TO BASELINE—DRUG OVERDOSES

Dec-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Dec-20Mar-21

Sep-20Jun-20Mar-20Dec-19Jun-19U.S. Population

Sep-19Mar-19Sep-18Jun-18Dec-17Mar-18

Sep-17

Jun-17Mar-17

Dec-16

Dec-18Group Life

200%
190%
180%
170%
160%
150%
140%
130%
120%
110%
100%
90%
80%

Copyright © 2023 Society of Actuaries Research Institute

51

Drug overdoses remain significantly elevated in both populations. Note that, while the proportional increases are
similar, overdoses comprise a higher percentage of total deaths in the U.S. population, so the excess is moremeaningful for this group.
Figure 9.9

DEATHS RELATIVE TO BASELINE—ALL OTHER/UNKNOWNGroup Life

130%

U.S. Population

120%
110%
100%
90%

Dec-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Dec-20Mar-21

Jun-20

Sep-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

These deaths show a similar pattern of increase. Note that, for the Group Life data, there are claims where thecause is not known, whereas most of the U.S. population deaths are from causes that do not fall into the othercategories.
Figure 9.10

DEATHS RELATIVE TO BASELINE—LIVER DISEASE
Group Life

150%

U.S. Population

140%
130%
120%
110%
100%
90%

Dec-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Dec-20Mar-21

Sep-20Jun-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18

Sep-17

Jun-17Mar-17

Dec-1680%

Copyright © 2023 Society of Actuaries Research Institute

52

Figure 9.10 shows that the proportional impact of liver disease was more significant for the U.S. population than forGroup Life.
Figure 9.11

DEATHS RELATIVE TO BASELINE—DIABETESGroup Life

160%

U.S. Population

150%
140%
130%
120%
110%
100%
90%
Dec-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Dec-20Mar-21

Jun-20

Sep-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

Figure 9.11 shows that, in 2021 and 2022, there was considerably higher excess mortality from diabetes in the U.S.
population than the Group Life population.
Figure 9.12

DEATHS RELATIVE TO BASELINE—CANCER
Group Life

110%

U.S. Population

100%

90%

Dec-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Dec-20Mar-21

Sep-20Jun-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18

Sep-17

Jun-17Mar-17

Dec-1680%

Figure 9.12 shows cancer declining fairly significantly during the pandemic period for Group Life, but not for the U.S.
population.

Copyright © 2023 Society of Actuaries Research Institute53

Since the All Other/Unknown category is significantly elevated, the Committee researched the most prominent ICD10 codes that make up this group in the U.S. population. Table 9.6 shows the top 20 codes for excess deaths, sorted
by excess deaths in 2020 and 2021. 2022 and 2023 were not included because the cause for some deaths may not
yet be determined.
Table 9.6

U.S. POPULATION EXCESS MORTALITY BY ICD-10 CODE FOR “ALL OTHER/UNKNOWN”
ICD-10 Description

Excess Deaths
2020

2021

Senile degeneration of brain, not elsewhere classified

13,58918,480Parkinson’s disease

6,538

4,807

Essential (primary) hypertension

3,931

4,237

Unspecified severe protein-energy malnutrition

2,821

4,631

Hyperlipidemia, unspecified

3,136

4,007

Vascular dementia, unspecified

3,355

2,641

Mental and behavioral disorders due to use of alcohol, harmful use

2,117

2,827

Mental and behavioral disorders due to use of alcohol, dependence syndrome

2,063

2,631

Hypertensive renal disease with renal failure

1,822

2,290

Unspecified protein-energy malnutrition

1,692

2,294

Chronic kidney disease, stage 5

1,616

2,107

Metabolic disorder, unspecified

1,090

2,046

Urinary tract infection, site not specified

902

1,975

Other obesity

1,246

1,547

Coronavirus infection, unspecified

1,887

708

Obesity, unspecified

972

1,586

Other specified degenerative diseases of nervous system

1,375

1,136

Acute renal failure, unspecified

395

2,097

Gastrointestinal hemorrhage, unspecified

1,009

1,405

Fatty (change of) liver, not elsewhere classified

796

1,229

Many of these conditions appear to be due to general poor health that may have been exacerbated by COVID-19.

Copyright © 2023 Society of Actuaries Research Institute54

9.3 EXCESS MORTALITY COMPARISON BY GEOGRAPHIC REGIONThe CDC method described above for U.S. population expected deaths enables a comparison of excess death
percentages by month and geographic region. Tables 9.7 and 9.8 display the excess death percentages by quarterand region for the U.S. population and the Group Life survey data, respectively. The “Total Excl. Other” row shows
the weighted average A/E ratio for claims that could be allocated to the four regions.
Table 9.7

U.S. POPULATION EXCESS DEATH PERCENTAGE BY QUARTER AND GEOGRAPHIC REGION
RegionMidwest
Northeast
Southeast
West
Total Excl. Other
Total

Q2–Q4
2020
20.9%
25.0%
20.6%
18.7%
21.2%
21.1%

12.7%
11.2%
22.6%
20.7%

Q1
2022
19.3%
17.6%
23.1%
21.0%

Q2
2022
-0.4%
-0.1%
2.7%
3.6%

Q3
2022
4.4%
3.7%
9.8%
11.3%

Q4
2022
8.1%
7.7%
8.7%
12.8%

Q1
2023
-0.5%
0.8%
3.7%
5.0%

Q2
2023
-0.9%
-2.1%
0.6%
2.3%

Q2 2020–
Q2 2023
10.9%
11.3%
15.2%
14.9%

17.7%
17.6%

20.7%
20.7%

1.6%
1.7%

7.6%
7.7%

9.2%
9.2%

2.5%
2.5%

0.0%
0.1%

13.4%
13.4%

2021

% of Total
COVID Deaths
21.2%
21.4%
38.1%
19.3%
99.4%
100.0%

Table 9.8

GROUP LIFE COVID-19 SURVEY EXCESS DEATH PERCENTAGE BY QUARTER AND GEOGRAPHIC REGION
RegionMidwest
Northeast
Southeast
West
Total Excl. Other
Total

Q2–Q4
2020
18.0%
23.5%
19.8%
19.4%
20.0%
19.0%

15.3%
17.4%
31.7%
23.4%

Q1
2022
16.9%
18.7%
17.8%
14.2%

Q2
2022
-3.2%
2.1%
-1.1%
1.3%

Q3
2022
1.7%
0.1%
7.0%
3.8%

Q4
2022
3.1%
8.1%
5.6%
3.7%

Q1
2023
-5.6%
0.5%
-0.7%
-3.8%

Q2
2023
6.2%
-0.5%
4.1%
-13.9%

Q2 2020–
Q2 2023
10.3%
13.0%
16.8%
12.1%

22.8%
21.6%

17.2%
16.2%

-0.6%
-1.3%

3.5%
2.9%

5.1%
4.2%

-2.3%
-3.2%

0.9%
-0.6%

13.4%
12.4%

2021

% of Total
COVID Deaths
26.2%
17.6%
41.0%
15.3%
99.6%
100.0%

Copyright © 2023 Society of Actuaries Research Institute55

Figure 9.13 shows excess death percentages by region for both the Group Life data and the U.S. population data.
Figure 9.13

EXCESS DEATH PERCENTAGES BY GEOGRAPHIC REGION, APRIL 2020 THROUGH JUNE 2023

For the April 2020 through June 2023 period, the Southeast showed the highest excess mortality for both the Group
Life data and the U.S. population. The Midwest experienced the lowest excess mortality for both datasets during the
pandemic period, though significant variations by season have been seen. For the Group Life data, the Southeast
was the only region with higher-than-average excess mortality. The largest contrast between the Group Life data
and the U.S. population data was in the West, where the U.S. population has excess mortality 2.8% (additive) higher
than the U.S. population.

Copyright © 2023 Society of Actuaries Research Institute

56

Section 10: Reliance and Limitations
In producing this report, the Committee relied upon data furnished by contributing companies and data publishedby the CDC. The Committee would like to stress that the data presented in this survey are emerging. Contributing
companies may true up these data over time. The Committee also notes that carriers submitted data in different
formats; it is possible that the homogenization of data submissions could introduce some unintended distortion in
the survey results. The reader should review the limitations noted throughout the report.

Copyright © 2023 Society of Actuaries Research Institute57

Section 11: List of Participating Companies
The Committee would like to thank the following companies that submitted data and made this COVID-19 mortality
survey possible:
Aflac
Dearborn National
Elevance
Guardian
The Hartford
Lincoln Financial Group
MetLife
Mutual of Omaha
New York Life Group Benefit Solutions
OneAmerica
Principal Financial
Reliance Standard
Renaissance
Securian Financial Group
Standard Insurance GroupSunLife Financial Group
SymetraUnum
USAbleVoya

Copyright © 2023 Society of Actuaries Research Institute

58

Appendix A: 2020 SOA Group Term Life COVID-19 Mortality Survey Data Request
PurposeThis is the data request for a Group Term Life Claim study intended to allow a quick assessment of the impact of the
COVID-19 pandemic on the Group Life industry—primarily by measuring the extra mortality occurring during the
pandemic as compared to prior periods. This high-level study will become a valuable data source for Group Life
insurers, since the industry wide COVID-19 claims will be significantly more credible than the claims experience forany one carrier.
TimingWe are requesting the initial data submission be provided by Friday, June 19th. We acknowledge that this is a tightturnaround, but due to the rapidly changing environment, time is of the essence. Please let us know ASAP if you
have a problem with this date or any element of this request. We plan to act quickly on the data—releasing an initialsummary report to participating carriers the week of July 6th.
The initial data request is for data from January 2017 through May 2020. We also plan to update the study monthly
throughout the duration of the pandemic. Please consider this when you build your queries for the initial request, sothat the monthly updates are easier to produce. We request that updates be submitted by the 3rd Friday of eachmonth. Contributors will receive a detailed summary report of their submitted data with some analysis of all thecontributed data after each monthly submission. The SOA will also be releasing summary reports of the aggregatedresults periodically throughout the duration of the study.
General Comments
Our goal is to measure patterns and trends rather than actual mortality rates. For the data request, this means weare more interested in how things change by month than whether they are 100% accurate or even consistent withother carrier submissions. We understand this data assembly will take some effort, and want to minimize
unnecessary data manipulation. To this end, please develop your submission as best you can to align with ourrequest, but more importantly, please ensure it is consistent over subsequent monthly updates.
Claim Data Request
Broadly, we are requesting summarized death claim information for your group life business with limited
segmentation. The limited segmentation will support further analysis/validation of observed trends. We hope all
carriers will be able to provide the Baseline data below. Please also provide the Segmentation if feasible, but we can
include your submission in the study even if these components are not readily available.
1. Baseline—The essential data requested is claim counts by incurred month, reported month, productsegment, and limited cause of death. Ideally, claim amounts can also be provided.
• Product Segment = Basic Life, Supp/Optional/Voluntary Life, and Retiree Life
• Cause of Death = COVID, Accident, and All Other
2.

Segmentation—We are also requesting claim counts and amounts for three separate segments—industry,
state, and age/sex. Data for each requested segment would be further split into the product and cause ofdeath categories referenced above.
• Industry = 2-digit SIC code is ideal• State = Based on residence, or work location if residence not available• Age/Sex = M/F/U, and 10-year age bands

Copyright © 2023 Society of Actuaries Research Institute

59

Claim Data Specifics
Again, as we will be looking at trends and patterns rather than actual mortality, it is most important that yoursubmission be consistent month to month. Nevertheless, the ideal submission should consider the following specificcriteria:• Include only group term life business. Exclude any GUL/GVUL, COLI/BOLI, 10/20-year group term, etc.
• Include both self-administered and list-billed business• Include employee, spouse, and child claims• Include or exclude portability and conversion claims—whichever is easier—based on your company
reporting.
• Include deaths from persons on waiver of premium; exclude active waivers• Include only death claims; exclude counts or amounts for various riders, especially living benefit riders or
critical illness riders• Include only the life insurance amount for accidental deaths• Exclude any interest payments or expenses
Exposure Data Request
As stated, this is not a mortality rate study, and we do not intend to calculate mortality rates. The purpose of
exposure data is to help explain and validate any observed trends. As with claims, we are requesting both high-level
exposure data, as well as exposure data by segment. However, the most critical information is exposures by month.
1.

Baseline—The essential data requested is earned premium by report month and product segment.
Optional data would include exposed lives by month.
• Product Segment = Basic Life, Supp/Optional/Voluntary Life, and Retiree Life

2.

Segmentation—We are also requesting exposure data for the segments—industry, state, and age/sex. Datafor each requested segment would be further split by product.
• Industry = 2-digit SIC code is ideal• State = Based on residence, or work location if residence not available• Age/Sex = M/F/U, and 10-year age bands

Exposure Data Specifics
We recognize that it can be difficult to provide exposed lives data, which is why we have selected earned premium
as the primary exposure metric. Exposed lives is certainly a valuable addition if it is available. As with claims, westress the importance of consistency month to month, and reiterate that we are interested in the information you
can provide with relative ease. Some specific (ideal) considerations include:• Include only group term life business. Exclude any GUL/GVUL, COLI/BOLI, 10/20-year group term, etc.
• Include or exclude premium for accident riders depending on how they are handled in your system; just be
consistent and identify what is included.
• Include both self-administered and list-billed business.
• For exposed lives, we recognize that some data (list billed groups, for example) may be more current andaccurate than other data. Please provide your best representation of exposed lives, and identify any
particular limitations or special considerations in your submission.
Final Notes on Requested Data
We intend to turn around results rapidly to maximize value on internal decision-making for participating carriers.
With that in mind, we have tried to keep the request as simple as possible. We have tried to define exactly what weare requesting, but if your own tracking does not align and the customization is difficult, then please provide what
you normally track rather than trying to match our definitions. The period-over-period change will be most valuable,

Copyright © 2023 Society of Actuaries Research Institute60

so consistency is more important than precise definitions. We understand there can be nuances in how carrierscount claims and track exposures, but we think the recently observed changes will be valuable. If you have any
questions at all about what we are asking, please reach out.
PLEASE NOTE: YOUR DATA SUBMISSIONS SHOULD NOT CONTAIN ANY INDIVIDUAL POLICY LEVEL INFORMATION.
PLEASE SEND ONLY THE AGGREGATED SUMMARY INFORMATION REQUESTED.
SOA staff will be receiving and compiling your submissions and the SOA is not able to receive any personal
information on your policyholders.
Reports
Our minimal request is for the monthly results without industry, geographic, or demographic segmentation. Pleaseprovide the additional segment data as you are able, and we will return cross-industry information consistent withyour submission. We do not plan to provide individual carrier-level experience.
We plan to show cross-industry extra mortality by calendar month. We will compare the most recent months to theprior periods, including prior months, and the same month a year ago.
We will not show individual carrier experience, but may comment on the consistencies of changes across carriers.
Technical Notes
The accompanying Excel workbook contains specific templates for the data submission. You can use the Excel
templates or submit data in a format of your choosing. The workbook includes an “Outline” tab to guide yoursubmission.
Please return the submission via e-mail to Korrel Crawford at kcrawford@soa.org. If you have concerns about filesecurity, please contact her and she will provide you with an alternate means of submitting data in a more secure
fashion.

Copyright © 2023 Society of Actuaries Research Institute61

Appendix B: Geography and Industry Code Mappings
Table B.1

GEOGRAPHY CODE MAPPINGS
Abbreviation

State/Province Name

Division

RegionAA

U.S. Armed Forces–Americas

Division 11: Unknown

Other

AB

Alberta

Division 10: Canada

Other

AE

U.S. Armed Forces–Europe

Division 11: Unknown

Other

AK

AlaskaDivision 09: Pacific

West

AL

AlabamaDivision 06: East South Central

Southeast

AP

U.S. Armed Forces–Pacific

Division 11: Unknown

Other

AR

Arkansas

Division 07: West South Central

SoutheastAS

American Samoa

Division 09: Pacific

Other

AZ

Arizona

Division 08: Mountain

West

BC

British Columbia

Division 10: Canada

Other

CA

California

Division 09: Pacific

West

CO

Colorado

Division 08: Mountain

West

CT

Connecticut

Division 01A: Southern New England

Northeast

DC

District of Columbia

Division 02: Middle Atlantic

Northeast

DE

DelawareDivision 02: Middle Atlantic

NortheastFL

FloridaDivision 05: South Atlantic

SoutheastFM

Micronesia

Division 09: Pacific

Other

GA

Georgia

Division 05: South Atlantic

Southeast

GU

Guam

Division 09: Pacific

Other

HI

Hawaii

Division 09: Pacific

West

IA

Iowa

Division 04: North Central

MidwestID

Idaho

Division 08: Mountain

West

IL

Illinois

Division 03: Great Lakes

MidwestIN

Indiana

Division 03: Great Lakes

MidwestKS

KansasDivision 04: North Central

MidwestKY

KentuckyDivision 06: East South Central

Southeast

LALouisiana

Division 07: West South Central

SoutheastMA

Massachusetts

Division 01A: Southern New England

Northeast

MB

Manitoba

Division 10: Canada

Other

MD

MarylandDivision 02: Middle Atlantic

Northeast

ME

Maine

Division 01B: Northern New England

NortheastMH

Marshall Islands

Division 09: Pacific

Other

MI

Michigan

Division 03: Great Lakes

MidwestMN

Minnesota

Division 04: North Central

MidwestMO

Missouri

Division 04: North Central

MidwestMP

Northern Mariana Islands

Division 09: Pacific

Other

MS

Mississippi

Division 06: East South Central

Southeast

MT

Montana

Division 08: MountainWest

Copyright © 2023 Society of Actuaries Research Institute62

Abbreviation

State/Province Name

Division

RegionNB

New Brunswick

Division 10: Canada

Other

NC

North Carolina

Division 05: South Atlantic

Southeast

ND

North Dakota

Division 04: North Central

MidwestNE

Nebraska

Division 04: North Central

MidwestNH

New Hampshire

Division 01B: Northern New England

Northeast

NJ

New Jersey

Division 02: Middle Atlantic

Northeast

NL

Newfoundland and Labrador

Division 10: Canada

Other

NM

New Mexico

Division 08: Mountain

West

NS

Nova Scotia

Division 10: Canada

Other

NU

Nunavut

Division 10: Canada

Other

NV

NevadaDivision 08: Mountain

West

NW

Northwest Territories

Division 10: Canada

Other

NY

New York

Division 02: Middle Atlantic

Northeast

OH

Ohio

Division 03: Great Lakes

MidwestOK

Oklahoma

Division 07: West South Central

Southeast

ON

Ontario

Division 10: Canada

Other

OR

OregonDivision 09: Pacific

West

Other

Other

Division 11: Unknown

Other

PA

Pennsylvania

Division 02: Middle Atlantic

NortheastPE

Prince Edward Island

Division 10: Canada

Other

PR

Puerto Rico

Division 05: South Atlantic

Other

PW

Palau

Division 09: Pacific

Other

QC

QuebecDivision 10: Canada

Other

RI

Rhode Island

Division 01A: Southern New England

Northeast

SC

South Carolina

Division 05: South Atlantic

Southeast

SD

South Dakota

Division 04: North Central

MidwestSK

Saskatchewan

Division 10: Canada

Other

TN

Tennessee

Division 06: East South Central

Southeast

TX

Texas

Division 07: West South Central

SoutheastUN

Unknown

Division 11: Unknown

Other

Unknown

Unknown

Division 11: Unknown

Other

UT

Utah

Division 08: Mountain

West

VA

Virginia

Division 05: South Atlantic

Southeast

VI

U.S. Virgin Islands

Division 05: South Atlantic

Other

VT

Vermont

Division 01B: Northern New England

Northeast

WA

Washington

Division 09: Pacific

West

WI

Wisconsin

Division 03: Great Lakes

MidwestWVWest Virginia

Division 02: Middle Atlantic

Northeast

WY

Wyoming

Division 08: Mountain

West

YK

Yukon

Division 10: Canada

Other

Copyright © 2023 Society of Actuaries Research Institute63

Table B.2

INDUSTRY CODE MAPPINGS
Two-Digit
Standard
Industrial CodeIndustry Group

Collar Color

00

Unknown/Invalid

Unknown01

Agricultural; Forestry; Fishing

Blue

02

Agricultural; Forestry; Fishing

Blue

03

Agricultural; Forestry; Fishing

Blue

04

Agricultural; Forestry; Fishing

Blue

05

Agricultural; Forestry; Fishing

Blue

07

Agricultural; Forestry; Fishing

Blue

08

Agricultural; Forestry; Fishing

Blue

09

Agricultural; Forestry; Fishing

Blue

10

MiningBlue

11

MiningBlue

12

MiningBlue

13

MiningBlue

14

MiningBlue

15

Construction

Blue

16

Construction

Blue

17

Construction

Blue

18

Construction

Blue

19

Construction

Blue

20

Manufacturing—Food

Blue

21

Manufacturing—Food

Blue

22

Manufacturing—Clothes; Textile; Wood

Blue

23

Manufacturing—Clothes; Textile; Wood

Blue

24

Manufacturing—Clothes; Textile; Wood

Blue

25

Manufacturing—Clothes; Textile; Wood

Blue

26

Manufacturing—Clothes; Textile; Wood

Blue

27

Manufacturing—Paper; Drugs

Gray

28

Manufacturing—Paper; Drugs

Gray

29

Manufacturing—Paper; Drugs

Gray

30

Manufacturing—Paper; Drugs

Gray

31

Manufacturing—Paper; Drugs

Gray

32

Manufacturing—Paper; Drugs

Gray

33

Manufacturing—Heavy; Steel

Blue

34

Manufacturing—Heavy; Steel

Blue

35

Manufacturing—Heavy; Steel

Blue

36

Manufacturing—Heavy; Steel

Blue

37

Manufacturing—Auto, Airplanes, Precision Equipment

Blue

38

Manufacturing—Auto, Airplanes, Precision Equipment

Blue

39

Manufacturing—Auto, Airplanes, Precision Equipment

Blue

Copyright © 2023 Society of Actuaries Research Institute64

Two-Digit
Standard
Industrial CodeIndustry Group

Collar Color

40

Transport; Communication; Utilities

Blue

41

Transport; Communication; Utilities

Blue

42

Transport; Communication; Utilities

Blue

43

Transport; Communication; Utilities

Blue

44

Transport; Communication; Utilities

Blue

45

Transport; Communication; Utilities

Blue

46

Transport; Communication; Utilities

Blue

47

Transport; Communication; Utilities

Blue

48

Transport; Communication; Utilities

Blue

49

Transport; Communication; Utilities

Blue

50

Wholesale Trade

Gray

51

Wholesale Trade

Gray

52

Retail—Trade

Gray

53

Retail—Trade

Gray

54

Retail—Trade

Gray

55

Retail—Trade

Gray

56

Retail—Trade

Gray

57

Retail—Trade

Gray

58

Retail—Trade

Gray

59

Retail—Trade

Gray

60

Banks and Securities

White

61

Banks and Securities

White

62

Banks and Securities

White

63

Insurance; Other Finance

White

64

Insurance; Other Finance

White

65

Insurance; Other Finance

White

66

Insurance; Other Finance

White

67

Insurance; Other Finance

White

68

Insurance; Other Finance

White

69

Insurance; Other Finance

White

70

Hotels/Personal Services

Grey

71

Hotels/Personal Services

Grey

72

Hotels/Personal Services

Grey

73

Misc. Service/Data Processing

Grey

74

Misc. Service/Data Processing

Gray

75

Misc. Service/Data Processing

Gray

76

Misc. Service/Data Processing

Gray

78

Misc. Service/Data Processing

Gray

79
80

Misc. Service/Data Processing
Doctors’ Offices

Gray
White

81

Legal Services

White

Copyright © 2023 Society of Actuaries Research Institute65

Two-Digit
Standard
Industrial Code82

Industry Group

Collar Color

Educational Services

White

83

Social Services

White

84

Museums and Membership Organizations

White

85

Museums and Membership Organizations

White

86

Museums and Membership Organizations

White

87

Engineering, Architecture, Business Consulting

White

88

Engineering, Architecture, Business Consulting

White

89

Engineering, Architecture, Business Consulting

White

90

Public Administration

White

91

Public Administration

White

92

Public Administration

White

93

Public Administration

White

94

Public Administration

White

95

Public Administration

White

96

Public Administration

White

97

Public Administration

White

99

Unknown/Invalid

Unknown

Unknown

Unknown/Invalid

Unknown

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66

Appendix C: Survey Methodology and Documentation
C.1 DOCUMENTATION
Participating companies provided both claims and exposure data on a monthly basis. The initial data request can befound in Appendix A. For claims information, the following fields were requested:
•
•
•
•
•
•

Incurred Month
Reported Month
Product Type
Cause of Death
Number of Claims
Total Claim Amount Covered/Paid

For exposure information, the following fields were requested:••••

Exposure Month
Product Type
Exposed Premium
Number of Inforce Lives

In addition to the above “core” request, participants were also optionally asked to provide the above information
split by state, age/sex grouping and industry (two-digit SIC code). The lone exception is that Reported Month was
not requested for the claims portion of these three more granular cuts of the data.
Below is a summary of the key processing assumptions and decisions for each of these fields.
Claims–Incurred Month
Incurred Months were generally used as provided without adjustment. The primary exception was thatdata with an Incurred Month after the as-of-date were excluded. For example, for the December 2022 datasubmissions, claims with an Incurred Month of January 2023 were excluded.
Claims–Reported Month
Claims with a Reported Month before the Incurred Month were adjusted by setting the Reported Monthequal to the Incurred Month.
Claims–Product Type
Carriers were asked to provide data with one of three Product Types: Employee Basic, Employee
Supplemental/Voluntary and Retiree Life. All alternative codes received for the Product Type field weresent as data questions to carriers and ultimately mapped to one of these three principal product types.
Notably, dependent claims were mapped to one of the two employee types, depending on the code
received.

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67

Claims–Cause of Death
Contributors were asked to identify claims as due to one of the 15 cause of death groupings shown inAppendix E.
Claims–Number of Claims and Total Claim Amount Covered/Paid
Claims by Reported Date were processed as is without adjustment. However, on an incurred basis, theclaims needed to be adjusted with completion factors as described in Section C.2.1; otherwise, theincidence rates in recent periods would be understated.
Exposure–Exposure Month and Product Type
Processing for these fields was analogous to the corresponding claims fields.
Exposure–Exposed Premium
The proximity of the survey request to the reporting dates of the data requested presented somechallenges in the monthly collection process because recent exposure data may be unavailable. For
example, one carrier indicated that their premium information for December 2022 was incomplete;therefore, the average premiums for July through September 2022 were imputed for December 2022 forthis carrier.
Exposure–Number of Inforce Lives
Not all carriers provided the Number of Inforce Lives. For these carriers, this field was imputed using the
average premium per life (PPL) from carriers that supplied both premiums and lives. A separate PPL was
calculated for each year and product type, and the missing Number of Inforce Lives was populated by
dividing the provided premium by the PPL appropriate to the year and product type for which the premium
was earned. The Committee acknowledges that PPL varies by company and that the exposure completion
methodology may result in an aggregate incidence rate that differs materially from the actual level ofincidence, but the Committee does not expect that it distorted the trends monitored in this study.
Segment Information–State CodeState codes that did not match a listing of valid U.S. state, U.S. overseas territory or Canadian province
codes were sent as data questions to the contributors. Some records with indeterminate codes after thisquestioning process were mapped to an “unknown” category.
Segment Information–Age and Sex
Companies provided age information according to the following categories: 0–24, 25–34, 35–44, 45–54,
55–64, 65–74, 75–84 and 85+. These age groupings were then lumped into the following broader
groupings: 0–44, 45–64 and 65+. Sex information was collected as male, female and unknown.

Copyright © 2023 Society of Actuaries Research Institute68

Segment Information–Industry
For the Industry field, contributors were asked to provide two-digit SIC codes. Codes that did not match alist of valid two-digit SIC codes were sent as data questions to the contributor for resolution. Some records
with indeterminate codes after this questioning process were mapped to an “Unknown” category.

C.2 RESULTS PROCESSING AND REVIEW
C.2.1 COMPLETION OF CLAIMSA table of claim counts by Incurred Month and Reported Month was compiled to develop completion factors.
Month-to-month completion factors were estimated using the accumulated totals for a particular incurred month inconsecutive reported months. Some seasonal variation was observed in the completion factors, so adjustments tothe factors for calendar month were incorporated.
The total completion factors were computed by cumulatively applying the month-to-month completion factors to all
subsequent months. For example, the total completion factor for a claim in month 0 is the factor for month 0 to 1,
times the factor for month 1 to 2, times the factor for month 2 to 3, and so forth. In total, 36 months of completion
were used.
Completion factors vary by calendar month, reflecting the seasonal nature of claim reporting and claim processing
speeds. The Committee also incorporated factor variation by reporting speed groups. The rate at which thecontributing companies’ claims were completed was analyzed and categorized into five groups, with three to fivecompanies in each reporting speed group.

C.2.2 BROADER CLASSIFICATION OF SEGMENT INFORMATIONFor credibility and confidentiality reasons, the industry codes and state codes were grouped into broader segments
for analysis. State codes were mapped to one of 11 divisions, with the New England division split into northern andsouthern portions. The state codes were also mapped to four broader U.S. regions (Northeast, Midwest, Southeast,West), with Canada, overseas territories and unknown codes grouped into a fifth “Other” region.
The two-digit SIC codes were organized into 23 different groupings, and then more broadly into one of four codes
by collar color (White, Gray, Blue, Unknown).
A table showing the details of these mappings can be found in Appendix B.

C.2.3 UNKNOWN CLAIM DIAGNOSISThe Unknown claim diagnosis category is artificially large for September 2022 through December 2022. This is
primarily because of the newness of these claims and a reflection of the claim adjudication lifecycle. It is notuncommon to find an additional time lag between the claim reporting date and the point in the claim adjudication
process when the COD is known, allowing for the claim to be categorized. As claims data have been collected andrefreshed each month, the Committee has observed that the concentration of claims with an unknown COD
decreases as the number of months between the original reporting date and the data collection date increases.

Copyright © 2023 Society of Actuaries Research Institute69

C.2.4 COVID-19 CLAIMS FROM 2019 OR EARLIER
The data show a handful of COVID-19 claims with dates of death in 2019 or earlier. The Committee believes thatthese are coding errors where incorrect COD codes were supplied. These claims remain in the data as submitted
without adjustment.

C.2.5 GROUPINGS BY COMPANY SIZETo review results by company size (see Section 5.4), contributors were split into three groups based on annualized
premium amounts from 2019. The Small group consists of companies with less than $300 million in 2019 premiums,
the Medium group consists of companies with between $300 million and $1 billion, and the Large group consists ofcompanies with more than $1 billion. The breakpoints were chosen to ensure at least six companies in each group.
The Small group contains six companies, and the Medium and Large groups contain seven companies each.

Copyright © 2023 Society of Actuaries Research Institute

70

Appendix D: Completion Factor Development
D.1 BY CLAIM COUNT
Historic Group Life claim reporting patterns by claim count have been studied to develop completion factors. Claims
were batched into a claim triangle with incurred month on the horizontal axis and reported month on the verticalaxis. Lag is defined as the number of months between when a death occurs and when the claim is reported to acarrier. Thus, a death that was both incurred and reported in August 2020 would have a lag of zero, whereas a death
incurred in June 2020, but reported in August 2020, would have a lag of two, and so on.
The completion factors for previous iterations of this report were based on the total set of claims by all causes fromall 20 participating carriers, with incurred dates of January 2017 or later and reported dates up through September
2020. Since that time, completion factors have been reviewed periodically. Faster reporting patterns during 2023
made it clear that an update to the completion factors was needed. The revised completion factors used in thedevelopment of this report included data for claims reported up through April 2023. The new completion factors
had material impacts on estimated incurred claim results for the most recent two months, but only minor impacts
for older periods.
Month-to-month completion factors were developed using the accumulated totals for a particular incurred monthin consecutive reported months. Seasonal variations were observed during the first two months of lag, so
adjustments to the factors for calendar month were incorporated. The total completion factors, as displayed inTable D.1, were computed by cumulatively applying the month-to-month completion factors to all subsequentmonths.

Copyright © 2023 Society of Actuaries Research Institute71

Table D.1

ESTIMATED COMPLETION FACTORS BY NUMBER OF MONTHS OF LAG AND CALENDAR MONTH
Lag
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35

Jan.
3.15011.4586
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Feb.
3.33251.40991.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006

Mar.
3.04481.40991.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Apr.
3.04481.40991.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006May
3.04481.40991.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006June
3.04481.40991.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006July
2.95471.3682
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Aug.
2.75491.40991.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Sep.
2.95471.3682
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Oct.
2.86601.40991.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Nov.
3.15011.4586
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Dec.
3.5533
1.40991.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006

Copyright © 2023 Society of Actuaries Research Institute72

D.2 BY FACE AMOUNTOur analysis showed that larger face amount claims report faster than lower face amount claims. Thus, over time,
the average face amount for an incurral month decreased as claims continued to be reported in later months. For
example, the average face amount of claims reported in the first month of an incurral period might be $40,000 but,three years later, might be $36,000. This would imply that an adjustment factor of 90% is needed to moreaccurately complete the total claim amounts.
The development of average claim amounts over time was studied from 2017 to 2019 for each month, and a set offactors was developed to adjust the projected claim amounts in future reports. Table D.2 shows a summarizedversion of the resulting adjustment factors. These adjustment factors have since been incorporated into thecompletion factors used within this report.
Table D.2

AVERAGE CLAIM AMOUNT ADJUSTMENT FACTORS BY REPORTING LAG MONTH (ILLUSTRATIVE)
Reporting Lag Month
0
1
2
3
10
20
35

Adjustment to Average Size
86.0%
92.7%
95.8%
97.2%
99.1%
99.7%
100.0%

D.3 BY CAUSE OF DEATH
It was unknown early in the pandemic whether COVID-19 claims would be reported more quickly or slowly thanother claims. Assignment of the COD is typically later in the claim adjudication cycle then reporting of the claim, so
COVID claims, in general, were expected to complete a bit more slowly than average claims because of the need tocomplete that step in the adjudication cycle. For deaths in June 2020 through February 2021, it appears that COVID19 claims were being reported at roughly the same rate as the non-COVID-19 set of claims (see Table D.3). The
Committee has reviewed the relative reporting speed of COVID-19 claims at multiple intervals during the pandemic
and has concluded that it is not materially different than average; for this reason, the analysis has not been revisitedfor this report.
Table D.3

CHAIN-LINK FACTORS FOR DEATHS IN JUNE 2020–FEBRUARY 2021
Lag Months
0
1
2
3
0–3

COVID

All Other Causes

COVID/All Other Causes

2.188
1.203
1.062
1.031
2.888

2.202
1.198
1.068
1.034
2.916

99.3%
100.4%
99.4%
99.7%
99.1%

Copyright © 2023 Society of Actuaries Research Institute73

D.4 BY COMPANY REPORTING SPEED
The Committee observed that incurred claim completion rates varied significantly from company to company. Upon
analyzing the differences, the 20 contributing companies were grouped into five “reporting speed” groups based on
similar reporting patterns. In tandem with the update to total completion factors described in Appendix D.1, theCommittee reviewed lag factors by company, resulting in the recategorization of a few companies relative to prioriterations of this report.
The completion patterns for the five groups were compared to the aggregate completion factors and expressed as
adjustments in Table D.4. The Committee observed that the differential in completion time was material for the firstsix reporting months for each incurred period. Further, the Committee did not discern any credible difference in the
speed by incurral calendar month; hence, only one vector of adjustments is provided for each group. These
adjustments provide a more representative picture for the individual company reports and, to a lesser extent,
improve the predictive fit of completed claims in total.
Table D.4

COMPLETION ADJUSTMENT FACTORS BY REPORTING SPEED GROUP
LagGroup 1

Group 2

Group 3

Group 4

Group 5Aggregate

0
1
2
3
4
5

81.6%
96.3%
100.0%
95.9%
101.1%
108.0%

91.9%
97.4%
101.9%
103.5%
98.5%
97.1%

106.0%
97.8%
97.5%
95.2%
108.5%
102.7%

140.8%
102.0%
96.8%
98.2%
101.4%
109.9%

217.8%
112.0%
98.5%
96.3%
101.8%
102.2%

100.0%
100.0%
100.0%
100.0%
100.0%
100.0%

Copyright © 2023 Society of Actuaries Research Institute

74

Appendix E: Cause of Death Mapping
Table E.1

CAUSE OF DEATH MAPPING
COD Group
No.
1
2
3

4

Group Name

ICD10 Codes

ICD-9 Codes

CancerDiabetes
Influenza andPneumonia
Major
Cardiovascular
Diseases

C00–C97
E10–E14140–239
249–250
480–488 (pneumonia and influenza) or
487–488 (just influenza)

5

COVID-19

6

Accidents (Motor
Vehicle)7

Accidents (Non–Motor Vehicle)

8910

Suicide
Homicide
Liver

11

Drug Overdose

12
13
14
15

All Other/
Unknown
Respiratory
Cerebrovascular,
Including Stroke
Alzheimer’s

J09–J18

I00–I09, I11, I13, I20–I51
U07.1, U07.2, B97.29, B97.26, Z03.818,
Z20.828, Underlying Cause of Death
V02–V04, V09.0, V09.2, V12–V14, V19.0–
V19.2, V19.4–V19.6, V20–V79, V80.3–
V80.5, V81.0–V81.1, V82.0–V82.1, V83–
V86, V87.0–V87.8, V88.0–V88.8, V89.0,
V89.2
W00–X59, Y86, V01, V05–V06, V09.1,
V09.3–V09.9, V10–V11, V15–V18, V19.3,
V19.8–V19.9, V80.0–V80.2, V80.6–V80.9,
V81.2–V81.9, V82.2–V82.9, V87.9, V88.9,
V89.1, V89.3, V89.9, V90–V99, Y85
U03, X60–X84, Y87.0
U01–U02, X85–Y09, Y87.1
K70, K73–K74
This is a subset of accident, assault, suicide
and undetermined and requires more thanthe primary COD to identify: X40–44, X60–
64, X85 or Y10–Y14 in combination with anyof the following multiple COD codes: T40.9,
T40.1, T40.2, T40.3, T40.4 or T40.6

393–429

Not applicable

E810–E829

Subset of 800–959 and 978–999, alongwith supplemental E-codes

E950–E959
E960–E969
570–573

960–977 and E930–E949

J00–J08, J19–J98

All claims/codes not in groups 1–11 or
13—15
460–479 and 489-–519

I60–I69G30

430–438 and V12.54
331

All claims not in groups 1–11 or 13–15

Copyright © 2023 Society of Actuaries Research Institute75

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