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Commitment Beyond Numbers May 1, 2020 Panel Discussion COVID-19's Economic Impact on Driving Patterns and Automobile Insurance
Transcript of Pinnacle APEX Webinar - COVID-19's Economic Impact on ... › Portals › 0 › Site... · U.S....
Commitment Beyond Numbers
May 1, 2020
Panel Discussion
COVID-19's Economic Impact on Driving Patterns and Automobile Insurance
1
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Welcome – Housekeeping Items
2
About Our Panel
Brian Sullivan (Moderator)• Founder of Risk
Information Inc.• Editor of Auto Insurance
Report and Property Insurance Report
Roosevelt C. Mosley Jr., FCAS, MAAA, CSPA• Principal and Consulting
Actuary• Pinnacle Actuarial
Resources, Inc.
Don Hendriks• Predictive
Modeler• CARFAX
Matt Moore• Senior Vice
President• Highway Loss
Data Institute (HLDI)
Yiem Sunbhanich• Co-Founder
and CEO• TNEDICCA®
U.S. motor vehicle crash deaths and deaths per billion vehicle miles traveled1950-2016
30,000
35,000
40,000
45,000
50,000
55,000
60,000
1950 1960 1970 1980 1990 2000 20100
10
20
30
40
50
60
70
80
Motor vehiclecrash deaths
Crash deathsper billion vehiclemiles traveled
Great recession(Dec 2007 – June 2009)
Oil price shock(July 1990 – Mar 1991)
Iranian revolution(Jan 1980 – Nov 1982)
OPEC oil crisis(Nov 1973 – Mar 1975)
1950 1960 1970 1980 1990 2000 2010
Crash deaths perbillion vehicle miles traveled
Unemployment rate
Change in U.S. motor vehicle crash deaths per billion miles traveled and unemployment rate1950-2016
20%
15%
10%
5%
0%
-5%
-10%
-15%
-20%
80%
40%
0%
-40%
-80%
Speed affects the risk of crash occurrenceChange in crash risk vs. change in speed
84%
183%
38%
74%
0%
100%
200%
300%
400%
0% 50% 100% 150% 200%
Change in speed
Rural roads
Urban roads
0%
20%
40%
60%
80%
100%
0 12 25 37 50 62 75 87
Impact speed (mph)
55 60 65 70 7530 35 40 45 505 10 15 20 25 80 850
Speed affects crash severityFatality risk for passenger vehicle occupant by impact speed
NHTSA, 2005
40 mph
20 mph
Higher speeds yield greater risk – it’s just physics
40 mph
20 mph
Higher speeds yield greater risk – it’s just physics
0
10,000
20,000
30,000
40,000
0
500
1,000
1,500
2,000
1985 1990 1995 2000 2005 2010 2015
auto sales (10,000) HLDI vehicle series auto sales per HLDI series
Auto sales vs. vehicle series1982–2018 model years
auto sales (10,000)HLDI vehicle series
10
Vehicle use since CoViD-19 Lockdown
11
Vehicle use since CoViD-19 Lockdown
55% drop in need for service
12
Long-term impacts of Dot-Com Bubble and September 11 Attacks
13
Long-term impacts of Dot-Com Bubble and September 11 Attacks
Persistently lower mileage following September 11, 2001 terrorist attacks
14
Long-term impacts of the Great Recession of 2007
15
Long-term impacts of the Great Recession of 2007
Lower mileage for about 24 months following recession onset
16
Long-term impacts of the Great Recession of 2007
Lower mileage for about 24 months following recession onset
Return to pre-9/11 levels by end of 2011
17
Possible long-term impact of CoViD-19 Lockdown on vehicle use
18
Possible long-term impact of CoViD-19 Lockdown on vehicle use
Projected Average Daily Mileage2020-2024
Actual Best Case Medium
19
Possible long-term impact of CoViD-19 Lockdown on vehicle use
Projected Average Daily Mileage2020-2024
Actual Best Case Medium
Best case: Return to normal by year-end
20
Possible long-term impact of CoViD-19 Lockdown on vehicle use
Projected Average Daily Mileage2020-2024
Actual Best Case Medium
More Likely: Return to a new, lower normal by middle of 2021
Best case: Return to normal by year-end
TNEDICCA® works to improve traffic safety leveraging a proprietary crash location database from 39 states representing more than 91% of U.S. auto insurance premium. The company provides location risk score solutions based on more than 30 million crashes.
Key findings:
• Daily crash frequency continues its declining trend in April. April MTD is down by 49%.
• More populated counties experienced greater decline.
• Hourly crash data indicates drive time patterns have changed.
• The percentage of crashes resulting in an injury has not significantly changed.
• Vehicle speed at crash increased by 24% in April.
21
Summary
22Source: Crash frequency from TNEDICCA and Coronavirus confirmed cases from Ohio Department of Health
* Actual crash counts from 03/21/20 were adjusted for data report lag
Daily Crash Frequency in OhioCOVID-19 has significant impact on crash frequency
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
0
200
400
600
800
1,000
1,200
1,400
2/2
1/2
020
Fri
2/2
2/2
020
Sat
2/2
3/2
020
Sun
2/2
4/2
020
Mo
n2
/25
/20
20
Tu
e2
/26
/20
20
We
d2
/27
/20
20
Th
u2
/28
/20
20
Fri
2/2
9/2
020
Sat
3/1
/20
20 S
un
3/2
/20
20 M
on
3/3
/20
20 T
ue
3/4
/20
20 W
ed
3/5
/20
20 T
hu
3/6
/20
20 F
ri3
/7/2
02
0 S
at
3/8
/20
20 S
un
3/9
/20
20 M
on
3/1
0/2
020
Tu
e3
/11
/20
20
We
d3
/12
/20
20
Th
u3
/13
/20
20
Fri
3/1
4/2
020
Sat
3/1
5/2
020
Sun
3/1
6/2
020
Mo
n3
/17
/20
20
Tu
e3
/18
/20
20
We
d3
/19
/20
20
Th
u3
/20
/20
20
Fri
3/2
1/2
020
Sat
3/2
2/2
020
Sun
3/2
3/2
020
Mo
n3
/24
/20
20
Tu
e3
/25
/20
20
We
d3
/26
/20
20
Th
u3
/27
/20
20
Fri
3/2
8/2
020
Sat
3/2
9/2
020
Sun
3/3
0/2
020
Mo
n3
/31
/20
20
Tu
e4
/1/2
02
0 W
ed
4/2
/20
20 T
hu
4/3
/20
20 F
ri4
/4/2
02
0 S
at
4/5
/20
20 S
un
4/6
/20
20 M
on
4/7
/20
20 T
ue
4/8
/20
20 W
ed
4/9
/20
20 T
hu
4/1
0/2
020
Fri
4/1
1/2
020
Sat
4/1
2/2
020
Sun
4/1
3/2
020
Mo
n4
/14
/20
20
Tu
e4
/15
/20
20
We
d4
/16
/20
20
Th
u4
/17
/20
20
Fri
4/1
8/2
020
Sat
4/1
9/2
020
Sun
4/2
0/2
020
Mo
n4
/21
/20
20
Tu
e4
/22
/20
20
We
d4
/23
/20
20
Th
u4
/24
/20
20
Fri
4/2
5/2
020
Sat
4/2
6/2
020
Sun
Nu
mb
er
of C
on
firm
ed
Ca
se
s
Da
ily C
rash
Cou
nt
Confirmed Cases 2019 Actual Crash Count 2020 Actual Crash Count*
Mar 9
Governor declared
state of emergency
Mar 12
Schools close
Mar 15
Bars & restaurants
take out only
Mar 22
Governor announced
Stay At Home Order
23Source: TNEDICCA Note: Data updated as of 04/26/2020
* Actual crash counts were adjusted for data report lag
Daily Crash Frequency in Ohio 2019 vs. 2020April month-to-date is down 49%
-14%
5%
-25%
-44%
-49%
-60%
-50%
-40%
-30%
-20%
-10%
0%
10%Jan Feb Mar 1 - 31* Mar 14 - 31* Apr 1 - 25*
Percentage Change in Crash Frequency in Ohio2020 vs. 2019
24Source: TNEDICCA Note: Data updated as of 04/26/2020
* Country population numbers are in logarithmic scale.
Percentage Change by County in Ohio 2020 vs. 2019**
More populated counties experienced greater decline
** For 2020, the data is from Friday 3/20 to Saturday 4/18. For 2019, the data is from Friday 3/22 to Saturday 4/20.
-80%
-70%
-60%
-50%
-40%
-30%
-20%%
ch
ang
e in
cra
sh
co
un
ts
Population*
25Source: TNEDICCA Note: Data updated as of 04/26/2020
Hourly Crash Frequency During Week Days in Ohio 2020 vs. 2019*
Drive time patterns have changed
* For 2020, the data is from Friday 3/20 to Saturday 4/18. For 2019, the data is from Friday 3/22 to Saturday 4/20.
0
10
20
30
40
50
60
70
80
12 a
.m.
1 a
.m.
2 a
.m.
3 a
.m.
4 a
.m.
5 a
.m.
6 a
.m.
7 a
.m.
8 a
.m.
9 a
.m.
10 a
.m.
11 a
.m.
12 p
.m.
1 p
.m.
2 p
.m.
3 p
.m.
4 p
.m.
5 p
.m.
6 p
.m.
7 p
.m.
8 p
.m.
9 p
.m.
10 p
.m.
11 p
.m.
Average Hourly Crash CountsDuring Monday - Friday
2019 2020
26Source: TNEDICCA Note: Data updated as of 04/26/2020
* Daily injury ratio is based on 5-day moving average
Daily Injury Crash Ratio in Ohio 2020 vs. 2019Injury crashes have declined proportionately
15%
17%
19%
21%
23%
25%
27%
29%
31%
1/5
/20
20 S
un
1/7
/20
20 T
ue
1/9
/20
20 T
hu
1/1
1/2
020
Sat
1/1
3/2
020
Mo
n
1/1
5/2
020
We
d
1/1
7/2
020
Fri
1/1
9/2
020
Sun
1/2
1/2
020
Tu
e
1/2
3/2
020
Th
u
1/2
5/2
020
Sat
1/2
7/2
020
Mo
n
1/2
9/2
020
We
d
1/3
1/2
020
Fri
2/2
/20
20 S
un
2/4
/20
20 T
ue
2/6
/20
20 T
hu
2/8
/20
20 S
at
2/1
0/2
020
Mo
n
2/1
2/2
020
We
d
2/1
4/2
020
Fri
2/1
6/2
020
Sun
2/1
8/2
020
Tu
e
2/2
0/2
020
Th
u
2/2
2/2
020
Sat
2/2
4/2
020
Mo
n
2/2
6/2
020
We
d
2/2
8/2
020
Fri
3/1
/20
20 S
un
3/3
/20
20 T
ue
3/5
/20
20 T
hu
3/7
/20
20 S
at
3/9
/20
20 M
on
3/1
1/2
020
We
d
3/1
3/2
020
Fri
3/1
5/2
020
Sun
3/1
7/2
020
Tu
e
3/1
9/2
020
Th
u
3/2
1/2
020
Sat
3/2
3/2
020
Mo
n
3/2
5/2
020
We
d
3/2
7/2
020
Fri
3/2
9/2
020
Sun
3/3
1/2
020
Tu
e
4/2
/20
20 T
hu
4/4
/20
20 S
at
4/6
/20
20 M
on
4/8
/20
20 W
ed
4/1
0/2
020
Fri
4/1
2/2
020
Sun
4/1
4/2
020
Tu
e
4/1
6/2
020
Th
u
4/1
8/2
020
Sat
4/2
0/2
020
Mo
n
4/2
2/2
020
We
d
Inju
ry C
rashe
s / T
ota
l C
rashe
s
Daily Injury Crash Ratio in Ohio
2019 2020
Mar 9
Governor declared
state of emergency
Mar 22
Governor announced
Stay At Home Order
27Source: TNEDICCA
* For April 2020, data is up to 04/28/2020
Estimated Vehicle Speed 2020 vs. 2019Vehicle speed at crash increased by 24% in April
21.8
27.1
15
20
25
30
Jan Feb Mar Apr*
mile
s p
er
hou
r
Estimated Vehicle Speed in Ohio
2019 2020
Note: Data updated as of 04/28/2020
28
Fast Track Property Damage Claim Data
600,000
700,000
800,000
900,000
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
19
75
/1
19
76
/1
19
77
/1
19
78
/1
19
79
/1
19
80
/1
19
81
/1
19
82
/1
19
83
/1
19
84
/1
19
85
/1
19
86
/1
19
87
/1
19
88
/1
19
89
/1
19
90
/1
19
91
/1
19
92
/1
19
93
/1
19
94
/1
19
95
/1
19
96
/1
19
97
/1
19
98
/1
19
99
/1
20
00
/1
20
01
/1
20
02
/1
20
03
/1
20
04
/1
20
05
/1
20
06
/1
20
07
/1
20
08
/1
20
09
/1
20
10
/1
20
11
/1
20
12
/1
20
13
/1
20
14
/1
20
15
/1
20
16
/1
20
17
/1
20
18
/1
20
19
/1
Cla
im C
ou
nts
year_qtr
Property Damage Claim Counts
Oil embargo – 1979
Dot com bubble – 2000
Mortgage crisis – 2007
COVID-19 –2020
29
Fast Track Property Damage Paid Loss Data
600,000
1,000,600,000
2,000,600,000
3,000,600,000
4,000,600,000
5,000,600,000
6,000,600,000
19
75
/1
19
76
/1
19
77
/1
19
78
/1
19
79
/1
19
80
/1
19
81
/1
19
82
/1
19
83
/1
19
84
/1
19
85
/1
19
86
/1
19
87
/1
19
88
/1
19
89
/1
19
90
/1
19
91
/1
19
92
/1
19
93
/1
19
94
/1
19
95
/1
19
96
/1
19
97
/1
19
98
/1
19
99
/1
20
00
/1
20
01
/1
20
02
/1
20
03
/1
20
04
/1
20
05
/1
20
06
/1
20
07
/1
20
08
/1
20
09
/1
20
10
/1
20
11
/1
20
12
/1
20
13
/1
20
14
/1
20
15
/1
20
16
/1
20
17
/1
20
18
/1
20
19
/1
Pai
d L
oss
es
year_qtr
Property Damage Paid Losses
Oil embargo – 1979
Dot com bubble – 2000
Mortgage crisis – 2007
COVID-19 –2020
30
Fast Track Property Damage Exposure Data
-
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
40,000,000
19
75
/1
19
76
/1
19
77
/1
19
78
/1
19
79
/1
19
80
/1
19
81
/1
19
82
/1
19
83
/1
19
84
/1
19
85
/1
19
86
/1
19
87
/1
19
88
/1
19
89
/1
19
90
/1
19
91
/1
19
92
/1
19
93
/1
19
94
/1
19
95
/1
19
96
/1
19
97
/1
19
98
/1
19
99
/1
20
00
/1
20
01
/1
20
02
/1
20
03
/1
20
04
/1
20
05
/1
20
06
/1
20
07
/1
20
08
/1
20
09
/1
20
10
/1
20
11
/1
20
12
/1
20
13
/1
20
14
/1
20
15
/1
20
16
/1
20
17
/1
20
18
/1
20
19
/1
Exp
osu
re
year_qtr
Property Damage Exposure
Oil embargo – 1979
Dot com bubble – 2000
Mortgage crisis – 2007
COVID-19 –2020
31
Economic Variables Used to Project Cost and Frequency Trends
Business
•Corporate profit
• Industrial production
•Small business optimism
•GDP
Employment
•Total hours worked
•Unemployment rates
•Unemployment persistency
Transportation
•Fuel use
•Fuel rate
•New vehicle CPI
•Petroleum demand
•New vehicle sales
Housing•Mortgage rate
•New single family home sales
Consumer•Retail sales
•Consumer confidence
Economic •Treasury rates
32
Number of Paid Claims vs. Number Unemployed Less Than 5 Weeks
R² = 0.6563
600,000
700,000
800,000
900,000
1,000,000
1,100,000
1,200,000
1,300,000
1,400,000
1.50 2.00 2.50 3.00 3.50 4.00 4.50
pd
_pai
d_c
laim
s
ue_num_lt5
Property Damage Number of Claims
pd_paid_claims Linear (pd_paid_claims)
33
Economic Projections
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
2019/1 2019/2 2019/3 2019/4 2020/1 2020/2 2020/3 2020/4 2021/1 2021/2 2021/3 2021/4
ue
_nu
m_1
5p
lus
year_qtr
Moody's Projections - Number Unemployed for 15 or More Weeks
ue_num_15plus Baseline Alternative 0 Alternative 1 Alternative 3 Alternative 4
34
Economic Projections – Previous Peak
0
2
4
6
8
10
12
14
16
18
19
75
/1
19
76
/1
19
77
/1
19
78
/1
19
79
/1
19
80
/1
19
81
/1
19
82
/1
19
83
/1
19
84
/1
19
85
/1
19
86
/1
19
87
/1
19
88
/1
19
89
/1
19
90
/1
19
91
/1
19
92
/1
19
93
/1
19
94
/1
19
95
/1
19
96
/1
19
97
/1
19
98
/1
19
99
/1
20
00
/1
20
01
/1
20
02
/1
20
03
/1
20
04
/1
20
05
/1
20
06
/1
20
07
/1
20
08
/1
20
09
/1
20
10
/1
20
11
/1
20
12
/1
20
13
/1
20
14
/1
20
15
/1
20
16
/1
20
17
/1
20
18
/1
20
19
/1
20
20
/1
20
21
/1
ue
_nu
m_1
5p
lus
year_qtr
Moody's Projections - Number Unemployed for 15 or More Weeks
ue_num_15plus Baseline Alternative 0 Alternative 1 Alternative 3 Alternative 4
2010/2 –8.98
35
• Drop in mileage driven is not the same across the board
– Essential workers
• Rebound in mileage will be even more varied
– Phased reopening plan
– Individual companies are developing their own schedules
– Work at home options
– Concerns with public modes of travel
• Current and projected economic conditions are like nothing we have seen in the past 40 years
Projections – Why the Future Will Not be Like the Past
36
Projection – Expected Loss
3,000,000,000
3,200,000,000
3,400,000,000
3,600,000,000
3,800,000,000
4,000,000,000
4,200,000,000
4,400,000,000
4,600,000,000
4,800,000,000
5,000,000,000
20
19
/4
20
20
/1
20
20
/2
20
20
/3
20
20
/4
20
21
/1
20
21
/2
20
21
/3
20
21
/4
20
22
/1
20
22
/2
20
22
/3
20
22
/4
20
23
/1
20
23
/2
20
23
/3
20
23
/4
20
24
/1
20
24
/2
20
24
/3
20
24
/4
Pro
ject
ed
Pai
d L
oss
es
Year_Quarter
Projected Property Damage Losses for Next Five Years
Baseline Alternative 0 Alternative 1 Alternative 3 Alternative 4
Estimated drop in losses: 30 – 35%
Length of recovery varies
New normal
37
Join Us for the Next APEX Webinar
38
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• Please complete our survey
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• Visit the Resource Knowledge Center at Pinnacleactuaries.com
Final Notes
Commitment Beyond Numbers 39
Thank You for Your Time and Attention
Roosevelt Mosley
Don Hendriks
Matt Moore
Yiem Sunbhanich
Brian Sullivan
