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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

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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

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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

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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

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/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

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/1

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/1

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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

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8

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12

14

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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

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/3

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/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

• We’d like your feedback and suggestions

• Please complete our survey

• For copies of this APEX presentation

• Visit the Resource Knowledge Center at Pinnacleactuaries.com

Final Notes

Commitment Beyond Numbers 39

Thank You for Your Time and Attention

Roosevelt Mosley

RMosley@pinnacleactuaries.com

Don Hendriks

Matt Moore

Yiem Sunbhanich

Brian Sullivan

DonHendriks@carfax.com

mmoore@hldi.org

Yiem.Sunbhanich@tnedicca.com

bpsullivan@riskinformation.com

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