InsurTech: The Financing of Innovation,

Transformation and Disruption

Robert P. Hartwig, Ph.D., CPCUClinical Associate Professor of Finance, Risk Management & Insurance

Darla Moore School of Business ¨ University of South CarolinaRobert.Hartwig@moore.sc.edu ¨ 803.777.6782

InsurTech SymposiumCharlotte, NCJune 20, 2018

2

Why Most InsurTech Firms Will Failn Lack of Actual Knowledge of the Insurance Business:

w There is tremendous advantage to coming in with a fresh eye and seeing the gaps that insiders have become blind to, but…

w Structural nuances and idiosyncrasies of the business are many and are material

w Regulatory requirements constitute and an enormous barrier to entry and a found throughout the industry value chain– Sales (licensing requirements, fiduciary/suitability requirements)– Claims (e.g., Fair Claims Handling Acts)– Underwriting (permissible underwriting criteria, rates must not be

“unfairly discriminatory”)– Pricing ultimately needs to reflect underlying risk, cover all

expenses and provide a risk appropriate return on capital) (rates must not be “inadequate or excessive)

w Bottom Line: Actual insurance expertise is essential

3

Why Most InsurTech Firms Will Failn Lack of Understanding of the Economics of Insurance

w Insurance is oftentimes a low-margin business

w You just can’t charge as much for your product as you might think.

w Example: The average combined ratio in both the homeowners’ and personal auto market over the past decade was about 103.

w This means that whatever thin profit was earned by the insurer was derived from investment earnings, of which the start-up has little-to-none

w Also, if an InsurTech firm has an idea that claims will reduce claim costs but costs $20 per policy to introduce, the financials don’t work unless the cost reductions apply across the entire book of business, not just accounts with claims

w Other: Pricing is often cyclical—meaning timing is everything when it comes to a product launch or investment in an InsurTech venture

4

Why Most InsurTech Firms Will Failn Investors Don’t Understand the Insurance Industry

w Smart Money vs. Dumb Money

w Smart money comes with investors who understand the business and can help you with connections, advice, and insights to help you cross the hurdles

w Dumb money is just money — and often is worse than dumb if the investors don’t understand the sales/pricing cycle and regulatory environment in the insurance industry

w Dumb money may push you down a path that isn’t the best for your business because they’re looking for the short term returns and don’t understand that insurance is a longer term game than straight consumer plays

w Axiom: If you’re running out of cash, all money looks smart

5

Why Most InsurTech Firms Will Failn Failure to Recognize that the Cost-Benefit Analysis Is a

Long-Term Return for an Insurerw Many InsurTech firms claim they have an amazing product that

will reduce losses

w The carrier has large upfront costs to acquire, implement and rollout the product and then must wait to see how (or if) losses or expenses are actually reduced, probably using a staged rollout.

w Bottom Line: It clearly takes time (and money)for there to be a critical mass of benefit to overcome the day one costs. Not every carrier has an appetite for long term CBAs on unproven solutions

6

Why Most InsurTech Firms Will Failn Running Out of Cash

w All startups face the worry of running out of money and the hunt for VC cash is relentless

w The insurance industry doesn’t buy quickly. Sales cycles even on established products can run 18 months or longer.

n The Product Isn’t All that Novel, Unique or Betterw All InsurTech start-ups claim to be disruptorsw Reality Check: Many aren’t (e.g., another online portal for selling

insurance—but with a cool user interface)w If you’re placing your bets on buying traffic or Search Engine

Optimization, that bet will soon run outw Many apps or ideas are easily and quickly replicated by

incumbents

7

INDUSTRY DISRUPTORS

Technology, Society and the Economy Are All

Changing at a Rapid PaceReality vs. Drinking the Silicon Valley Kool Aid

7

8

The Insurance Industry Value Chain: Under Seige, Ripe for Disruption?

Source: Willis Capital Markets & Advisory; Univ. of South Carolina, RUM Center.

Who owns the data? Where does It flow? Who does the analytics? Who is the capital provider?

9

The Sharing Economy Has Grown—And Attracted Political Scrutiny

There’s no question that the hype around autonomous vehicles far exceeds the reality

10

The Internet of Things and the Insurance Industry

n The “Internet of Things” will create trillions in economic value throughout the global economy by 2025

n What opportunities, challenges will this create for insurers?

n What are the impact on the insurance industry “value chain”?Sources: McKinsey Global Institute, The Internet of Things: Mapping the Value Beyond the Hype,

June 2015; Insurance Information Institute.

11

Media is Obsessed with Driverless Vehicles: Often Predicting the Demise of Auto Insurance

By 2035, it is estimated that 25% of new vehicle

sales could be fully autonomous models

Source: Boston Consulting Group.

Questionsn Are auto insurers

monitoring these trends?n How are they reacting?n Will Google or (Amazon)

take over the industry? n Will the number of auto

insurers shrink?n How will liability shift?

13

Car Subscription Services: A Threat to Personal Auto?

n Liberty Mutual, Assurant, Chubb have struck multiple deals

n Volvo, Ford, Cadillac, Porsche, BMW and Mercedes-Benz have either launched or announced plans to launch car subscription models

Source: CB Insights accessed 3/14/18 at: https://www.cbinsights.com/research/insurance-car-subscription-partnerships/

14

Car Subscription Services: A Threat to Personal Auto?

n Ford’s Canvas programs states that it provides: BI & PD Liability $300K combined single limit), PIP, Med Pay, UI/UIM, Collision & Comprehensive ($500 deductible), Roadside Assistance, Rental Reimbursement

n No flexibility in coverage but can use own auto insurance as primary and Canvas as excess

Source: www.drivecanvas.com accessed 3/14/18.

15

Car Subscription Services: Insurers Partnering with US Car Subscription and Sharing Programs

Source: CB Insights accessed 3/14/18 at: https://www.cbinsights.com/research/insurance-car-subscription-partnerships/

The car subscription

service is tiny—and how much it

will grow is uncertain;For auto

manufacturers car subscriptions are

a variation on leasing. For auto

insurers, there is a more meaningful distinction (e.g.,

personal or commercial exposure)

18

INSURANCE TECHNOLOGY:FIN TECH ZEROES IN

Number and Value of Deals Is Increasing

An Industry that Has Always Been Accepting of Change and Innovation

19

Start-Up Financings in the US, 2006 – 2018*

n First-round financings are down sharply across the board, including InsurTech

n One reason: “The Kill Zone”n Tech giants (e.g., Google,

Amazon, Microsoft, Facebook) are quick to eliminate competitive threats by copying them or buying them early

n VCs are wary of investing if one of the “Giants” is likely to move into same space

n Does InsurTech have a “Kill Zone”?

Sources: The Economist,The Future of Tech Startups: Into the Danger Zone,June 2, 2018: https://www.economist.com/business/2018/06/02/american-tech-giants-are-making-life-tough-for-startups

20

InsurTech Investments by Investment Stage

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018.

Proportionately less investment at the earliest stage in recent quarters

Is the shrinkage

evidence of InsurTech’sKill Zone?

21

Private Technology Investments by (Re)Insurers, 2013 – 2018:Q1

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018.

There are proportionately fewer early-stage tech investments by

(re)insurers in Q1:2018

Is the decline evidence of InsurTech’sKill Zone?

US Venture Capital Funding (All Sectors),2012 – 2017

Value of Deals ($ Billions)

Source: CB Insights, Venture Capital Funding Report, 2017 accessed 6/15/18 at: https://www.cbinsights.com/research/report/venture-capital-q4-2017/

$33 $36

$59

$77

$61

$72

57865063

4624

5268

5052

5811

$0

$10

$20

$30

$40

$50

$60

$70

$80

$90

2012 2013 2014 2015 2016 20170

1000

2000

3000

4000

5000

6000

7000

Value of Deals Number of Deals

No. of Deals

VC funding across all sectors has been increased in 2017 though the number

of deals fell

US Venture Capital Funding (All Sectors),2016:Q2 – 2018:Q1

Value of Deals ($ Billions)

Source: CB Insights, Venture Capital Report, Q1 2018 accessed 6/15/18 at: https://www.cbinsights.com/research/report/venture-capital-q1-2018/

$18

$15$13

$15

$19$20 $21

$20

1206

1233

1371

13271342

1302

1362

1245

$0

$5

$10

$15

$20

$25

Q2:2016 Q3:2016 Q4:2016 Q1:2017 Q2:2017 Q3:2017 Q4:2017 2018:Q11100

1150

1200

1250

1300

1350

1400

Value of Deals Number of Deals

No. of Deals

VC funding across all sectors has been increasing slowly over the past year, though

the number of deals is down

24

THE STATE OF INSURTECH FUNDING TODAY

Number and Value of Deals Is Increasing

An Industry that Has Always Been Accepting of Change and Innovation

InsurTech Annual Financing,2011 – 2018:Q1

Value of Deals ($ Millions)

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018.

$140$350 $270

$870

$2,670

$2,212

$724

$1,690

66

200

91

4628

122

173

63

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

2011 2012 2013 2014 2015 2016 2017 2018:Q1 020406080100120140160180200220

Value of Deals Number of Deals

No. of Deals

Insurance tech deals reached a new record in 2017 with 2018 on

track to set new highs

About 60% of all InsurTech deals in 2017 were at the

early stage!

Number of InsurTech Deals: P/C vs L/H2013 – 2018:Q1

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018; USC RUM Center.

37

6268

57

81

23

117

3228

121

4356

0

20

40

60

80

100

120

140

2013 2014 2015 2016 2017 2018:Q1

L/H P/C

No. of Deals In recent years, the

majority of InsurTech deals have been P/C-related

Many early InsurTech firms were launched in wake of

2010’s ACA legislation, which created an online marketplace (starting in 2014) for insurance and seemed to create market

opportunities for start-ups (e.g. Oscar)

27

InsurTechs Are Focusing on Distribution and Pricing

Source: Panorama by McKinsey, “Insurance Beyond Digital: The Rise of Ecosystems and Platforms,” Jan. 2018.

InsurTech firms across all insurance

segments tend to focus on

Distribution. It is telling that very few InsurTech firms are actually insurers.

Why Are So Few InsurTech Start-Ups Actual Insurers (Risk Bearers)

n Barriers to Entry: Starting an actual insurance company requires significant resources in terms of:w Capitalw Technologyw Regulatory compliance capabilitiesw High customer acquisition costsw Human capital (i.e., experienced insurance industry execs)

n Competition: Both personal and commercial lines of insurance are intensely competitivew HHI Values for auto insurance ~900 - 1000 in most statesw HHI Values for home insurance ~700 in most statesw DoJ: HHI Values < 1500 not concentrated

Why Are So Few InsurTech Start-Ups Actual Insurers (Risk Bearers)

n Margins Are Thin: Profitability in the insurance industry is fallingw P/C insurance industry ROEs fell for the 4th consecutive year

in 2017 (to 5.0%) and could fall again in 2018 (2.4% in Q1)

n Overcapitalization: The P/C and Life insurance industries are both over capitalizedw The p/c insurance industry finished 2017 with a record $753

billion in policyholder surplus (a proxy for capacity)—which is at implies that the industry is overcapitalized by about 1/3

19.9%

19.8%

18.5%

17.1%

9.5%

7.3%

6.1%

4.2%

28.7%

0% 5% 10% 15% 20% 25% 30% 35%

Computer Services

Semiconductors

Information Services

Software (Internet)

Software (Systems & Application)

Health Information & Technology

P/C Insurance

Reinsurance

Life Insurance

*As of January 2018Source: Stern School, NYU accessed 6/18/18 at : http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/roe.html; Univ. of South Carolina Center for Risk and Uncertainty Management.

Low ROEs will keep the number of actual insurance start-ups low—and kill off

many others as well

ROEs: Insurance vs. Technology Sectors—A “Poison Pill”?

ROEs in the tech sector are much higher than for insurers. This is one reason why tech

companies are unlikely to be interested in

bearing insurance risk anytime soon

P/C Industry Net Income After Taxes1991–2018:Q1

n 2005 ROE= 9.6%n 2006 ROE = 12.7%n 2007 ROE = 10.9%n 2008 ROE = 0.1%n 2009 ROE = 5.0%n 2010 ROE = 6.6%n 2011 ROAS1 = 3.5%n 2012 ROAS1 = 5.9%n 2013 ROAS1 = 10.2%n 2014 ROAS1 = 8.4%n 2015 ROAS = 8.4%n 2016 ROAS = 6.2%n 2017 ROAS =5.0%n 2018 ROAS = 2.4%

•ROE figures are GAAP; 1Return on avg. surplus. Excluding Mortgage & Financial Guaranty insurers yields a 8.2% ROAS in 2014, 9.8% ROAS in 2013, 6.2%ROAS in 2012, 4.7% ROAS for 2011, 7.6% for 2010 and 7.4% for 2009; Sources: A.M. Best, ISO.

$14,178

$5,840$19,316

$10,870 $20,598

$24,404 $36,819

$30,773

$21,865

$3,046

$30,029

$62,496

$3,043

$35,204

$19,456 $3

3,522

$63,784

$55,870

$56,826

$42,924

$36,123

$17,384

$38,501

$20,559

$44,155

$65,777

-$6,970$28,672

-$10,000

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18*

Net income fell sharply in 2017

as high CAT losses took

their toll

$ Millions

-5%

0%

5%

10%

15%

20%

25%

75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

Profitability Peaks & Troughs in the P/C Insurance Industry, 1975 – 2018:Q1

Profitability = P/C insurer ROEs. 2011-16 figures are estimates based on ROAS data. Note: Data for 2008-2014 exclude mortgage and financial guaranty insurers.Source: NAIC, ISO, A.M. Best, USC RUM Center.

1977:19.0% 1987:17.3%

1997:11.6% 2006:12.7%

1984: 1.8% 1992: 4.5% 2001: -1.2%

10 Years10 Years

9 Years

ROEs in 2017 plunged to their lowest levels

since 2008.ROE

1975: 2.4%

2013 9.8%

2016 6.2%

2015: 8.4%

2017 5.0%

33

ROE: Property/Casualty Insurance by Major Event, 1987–2018:Q1

Excludes Mortgage & Financial Guarantee in 2008 – 2014. Sources: ISO, Fortune; USC RUM Center.

-5%

0%

5%

10%

15%

20%

87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18*

P/C Profitability Is Influenced Both by

Cyclicality and Volatility

Hugo

Andrew, Iniki

Northridge

Lowest CAT Losses in 15 Years

Sept. 11

Katrina, Rita, Wilma

4 Hurricanes

Financial Crisis*

(Percent)

Record Tornado Losses

Sandy

Low CATs

Harvey, Irma, Maria,

CA Wildfires

34

Policyholder Surplus, 2006:Q4–2018:Q1

Sources: ISO, A.M .Best; Center for Risk and Uncertainty Management, University of South Carolina.

($ Billions)$487.1

$496.6

$512.8

$521.8

$478.5

$455.6

$437.1 $463.0 $490.8

$511.5 $540.7

$530.5

$544.8

$559.2

$559.1

$538.6

$550.3

$567.8

$583.5

$586.9

$607.7

$614.0

$624.4 $653.4

$671.6

$673.9

$675.2

$674.2

$673.7

$676.3 $700.9

$717.0 $752.5

$734.1

$662.0

$570.7

$566.5

$505.0

$515.6

$517.9

$400

$450

$500

$550

$600

$650

$700

$750

$800

06:Q4

07:Q1

07:Q2

07:Q3

07:Q4

08:Q1

08:Q2

08:Q3

08:Q4

09:Q1

09:Q2

09:Q3

09:Q4

10:Q1

10:Q2

10:Q3

10:Q4

11:Q1

11:Q2

11:Q3

11:Q4

12:Q1

12:Q2

12:Q3

12:Q4

13:Q1

13:Q2

13:Q3

13:Q4

14:Q1

14:Q2

14:Q3

14:Q4

15:Q2

15:Q4

16:Q1

16:Q4

17:Q2

17:Q4

18:Q1

Financial Crisis

Surplus (Capacity) as of 12/31/17 reached a new

record of $752.5B despite heavy CAT losses

2010:Q1 data includes $22.5B of paid-in capital from a holding company parent for one insurer’s investment in a non-insurance business .

Drop due to near-record 2011 CAT losses

Capacity/Capital “shocks” typically do not on their own drive a sustained firming of

the pricing environment

Why Are So Few InsurTech Start-Ups Actual Insurers (Risk Bearers)n Law of Large Numbers: The larger the number of

policyholders (exposure units), the more likely it is that the actual loss equals the expected loss and thus the standard deviation of the mean falls.w In economic terms, this means there are economies of scale

in insurance that derive from the pooling of riskw Start-ups are not immune to the LLN. All else equal,

incumbents and large insurers will have an advantage over small start-ups

w For a small start-up insurer to “disrupt” the industry, their advantages in product design, efficiency, risk assessment, marketing, etc., need to be large enough to overcome the disadvantages of being on the losing end of the LLN

If Actually Bearing Insurance Risks Is So Difficult, What Do InsurTechs Actually DO?n Insurance Carriers

w Since 2013, only 4% of P/C start-ups and 8% of L/H start-ups were formed as insurance carriers (i.e., risk-bearers)

n Distributionw Since 2013, 62% of P/C start-ups and 46% of L/H start-

ups have focused on Distribution (i.e., sale of insurance)

n Business-to-Business (B2B)w Since 2013, 34% of P/C start-ups and 46% of L/H start-

ups have focused on B2B solutionsw B2B start-ups focus on a wide range of insurer activities

and functions such as analytics, claims, underwriting, IoT and more

37

Composition of Loss and Expense Components for Key P/C Lines*

13.7% 9.8% 12.1% 15.3%8.2% 12.8% 12.8% 6.5%

17.4% 16.5% 17.0% 17.8% 24.9%

62.4%60.1%60.9%64.7%60.0%

12.1%10.4%

0%

20%

40%

60%

80%

100%

120%

All Lines Personal Auto Homeowners Commercial Auto Workers Comp

Loss LAE Commission & Brokerage Expense Other Underwriting Expenses

Percent

*Figures are averages for the 10-year period from 2007-2016.Source: A.M. Best Aggregates and Averages, 2017 Edition; Univ. of South Carolina RUM Center.

Bearing risk is challenging, so few InsurTechstart-ups are actual insurers. Instead many

focus on the ~40% of premiums associated with the sale/distribution, claims or underwriting

expenses

39.9% out of 99.9%

38.7% out of

103.4%

39.6% out of

100.5%

42.7% out of

102.8%

46.7% out of

109.1%

38

P/C InsurTech Transactions by Subsector

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018.

Distribution consistently

accounts for the majority of P/C transactionsB2B share is

growingActual carrier start-ups are quite rare

39

L/H InsurTech Transactions by Subsector

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018.

Distribution and B2B account for

roughly equal shares of L/H

transactions since 2013, though that may be changing

B2B share is shrinking

Actual carrier start-ups are quite rare

40

Private Technology Investments by (Re)Insurers, 2013 – 2018:Q1

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018.

Tech investments by (re)insurers have been

increasing steadily. Not all investments are

directly related to insurance

41

Start-Up InsurTech Investments by Top 25 P/C Insurers, 2015 - 2017*

*As of June 23, 2017.Sources: NAIC from CB Insights at https://www.cbinsights.com/blog/largest-pc-insurers-rank-startup-investments/

USAA and AmFam lead in P/C InsurTech

investment

10 of the Top 25 P/C insurers have made InsureTech start-up investments since 2015.—but there is little correlation between size and number of

investments within this group

Sample InsurTech Deals: 2018:Q1

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018.

Company Insurer DescriptionAmerican Well Allianz Telemedicine, wearable sensorsBetterview Munich Re Drone imagery, data and analysis for

MR’s clientsRoost Erie Smart water/freeze detection products to

HO customersJauntin AIG Pay-as-you-go travel insuranceBunker Chubb Develop new products for small

commercial marketTencent WeSure MetLife Online travel insuranceLyric Axa Airbnb-like service (stays in iconic apts.)Socotra USAA Policy admin service to automate

underwriting, quoting binding Gabi Northwest

MutualHO and auto price comparison platform

Red Balloon Security

American Family

Cyber security for embedded and smart devices, including cars, office equip.

44

CASE STUDY 1

The Curious Case of Insurance, IoTand the Smart Home

What Went Wrong?

45

IoT, Smart Home & Insurancen In 2014-2015, the integration

of IoT technologies, smart homes and insurance seemed like a sure thing

n A number of insurers rushed in to offer discounts to homeowners adopting these technologies on a trial basis

n Since then, initiatives have stalled. Why?w Consumers unlikely to buy

hundreds of dollars of smart sensors (smoke, water, etc.)

w Confusing standards for gear are intimidating for average consumer

w Cost/benefit not obviousSource: StaceyOnIot.com, Why insurance firms are stalling on IoT, June 11, 2018.

46

CASE STUDY 2

The Curious Case of Softbank, Masayoshi Son, Silicon Valley—

and Swiss Re

47

Softbank and Swiss Re: What Happened? n In 2014-2015, the integration

of IoT technologies, smart homes and insurance seemed like a sure thing

n A number of insurers rushed in to offer discounts to homeowners adopting these technologies on a trial basis

n Since then, initiatives have stalled. Why?w Consumers unlikely to buy

hundreds of dollars of smart sensors (smoke, water, etc.)

w Confusing standards for gear are intimidating for average consumer

w Cost/benefit not obviousSource: StaceyOnIot.com, Why insurance firms are stalling on IoT, June 11, 2018.

48

InsurTech Investors

Who Invests in What—and Why

Instry that is Interested in Hiring New Talent, Especially those with Data/Analytics Skills

48

49

Who Are the Most Successful InsurTechInvestors To Date—and for the Future?

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018. Drawn from InsurTech Investor Survey.

Traditional (Independent) VCs are viewed as the

most successful to date, but Corporate/

Incumbents are viewed as the

favorites over the long run

50

Who Will Provide the Most Funding to InsurTechs in the Years Ahead?

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018. Drawn from InsurTech Investor Survey.

With success comes funding.

Corporate/ Incumbent VCs are expected to be the main provider of

capital to InsurTechfirms in the years

ahead

A shift to Corporate/Incumbent VCs funding suggests that “smart money” will play a larger role and that (re)insurers in particular are making focused investments to

suit their own needs

51

InsurTechs Want to Partner with What They Perceive to Be “Smart Money”

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018. Drawn from InsurTech Investor Survey.

InsurTechsbelieve

Corporate VCs offer them the best chances for success,

though traditional VCs

will still be necessary to

meet full capital needs

52

How Do Corporate VCs Benefit InsurTechs?

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018. Drawn from InsurTech Investor Survey.

InsurTechsbelieve

Corporate VCs add the

greatest value in the area of

Product Development

53

Which InsurTech Segments Are the Primary Focus for VCs?

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018. Drawn from InsurTech Investor Survey.

Data & Analytics

followed by Distribution

and Claims are the primary investment

focus of VCs

54

Which InsurTech Segments Are the Most Attractive to VCs?

Source: CB Insights,Quarterly InsurTech Briefing,, Q1 2018. Drawn from InsurTech Investor Survey.

VCs believe that Data & Analytics

followed by Product &

Distribution and Business

Process Enhancement are the most

attractive subsectors for

investment

Observation on Venture Capital Investment Patterns, Practices and Preferencesn Actual Risk-Bearing Insurer Start-Ups Are Rare and

Nobody Including VCs Is Clamoring for this to Changew Implication: The near-term likelihood of a major tech usurper

invading the traditional P/C or Life insurance industry and bearing actual insurance risk is remote– The economics of such a transaction would likely destroy

shareholder value in the tech firm– Such a transaction would likely be rejected using traditional NPV or

IRR methods

n Nature of InsurTech Investment Is Far More Complimentary to Insurer Operations than it Is Disruptivew Implication: Much of what InsurTechs are doing can viewed as

an outsourcing of tech R&D. Insurers will adopt (acquire) or copy these technology if NPV is positive. – This is a very efficient way to manage tech investments– Options increase, less likely to be stuck with in a tech dead-end

Observation on Venture Capital Investment Patterns, Practices and Preferencesn InsurTechs Prefer to Partner with “Smart Money”

Investorsw Implication: Over the longer run, (re)insurers/large brokers

could account for the majority of InsurTech deals, along with some of the largest VCs with in-house insurance industry expertise– Increased presence of incumbents suggests a widening “Kill Zone”

for insurance startups

n InsurTech Start-Ups Go Where (They Think) the Money Isw Implication: With ~40% of premium dollar going to something

other than pure losses, it’s easy to see how InsurTechs would be drawn to areas such as Distribution – But these solutions are easily replicated or acquired– Data Analytics, Business Process Enhancement offer ongoing

opportunities to gain competitive and efficiency enhancementsSource: University of South Carolina, Center for Risk and Uncertain Management.

Observation on Venture Capital Investment Patterns, Practices and Preferencesn Valuations Are Likely Inflated: Pain to Come

w Implication: Over the longer run, (re)insurers/large brokers could account for the majority of InsurTech deals, along with some of the largest VCs with in-house insurance industry expertise– Increased presence of incumbents suggests a widening “Kill Zone”

for insurance startups

n “Cool” Ideas Aren’t Enough*w Implication: Shift toward practical applications with an

emphasis on measurable results (ROI)– Neither InsurTech firms nor investors have endless time or money

for experimentation

*This point adapted from: PropertyCasualty360.com, InsurTech starups wane, but funds still pour into maturing market, Sam Friedman, April 10, 2018.

Source: University of South Carolina, Center for Risk and Uncertain Management.

58

Unicorn Sightings: New and Total Number of US-Based Unicorns (all sectors), 2008 – 2018*

73

107122

144 139

4 4 4 10 11 12

42 4323

331111 14 18 26 33 39

020406080

100120140160

08 09 10 11 12 13 14 15 16 17 18*

Total No. of Unicorns New Unicorns

*Through May 15, 2018.Source: CBS Marketwatch, May 23, 2018: https://www.marketwatch.com/story/why-the-end-is-coming-soon-for-the-biggest-tech-bubble-weve-

ever-seen-2018-05-22

The total number of Unicorns

appears to be declining in 2018

The peak of the unicorn bubble is already passed. This is one (of several) signals that many tech

startups are overvalued.

Unicorn Cash: Cash Raised by Unicorns and Number of VC Funds Closing, 2008 – 2018*

Capital Raised ($ Billions)

*Through May 15, 2018.Source: CNBC.com, May 22, 2018 at https://www.cnbc.com/2018/05/22/tech-bubble-is-larger-than-in-2000-and-the-end-is-coming.html

$1 $1 $1

$6

$2

$14

$18$19

$9

$18

$330

7657

80

72

2777

25 23

10

$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

$20

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018*0

10

20

30

40

50

60

70

80

90

Capital Raised ($B) Number of Funds Closed

No. Closed Funds

Capital raised by unicorns peaked in

2016

Unicorns not only becoming more

rare, they’re ability to raise cash is

stalling

Reasons Why Start-Up Valuations Are Falling and Will Continue to Falln Rising Interest Rates: Low interest rates made risky

investments of every variety more attractive—including tech start-ups. With yields of risk-free and corporate debt rising, VC investments are less attractive

n IPO Busts: A number of companies that have gone public (or plan to) have seen their valuations plummet (pre- and post-IPO; e.g., SNAP: $17à$14; Blue Apron: $10à$3, FitBit: $45à$7)

n Profits Matter: 76% of companies that went public in 2017 were unprofitable, the highest since 81% at the peak of the dot-com boom in 2000 (Ritter, 2017)

n Entrenched Incumbents Are Learning: Sector leaders are learning to quickly copy or adopt new technologies, allowing them to sustain their competitive advantage through disruption

*Through May 15, 2018.Source: CNBC.com, May 22, 2018 at https://www.cnbc.com/2018/05/22/tech-bubble-is-larger-than-in-2000-and-the-end-is-coming.html

61

IPOs with EPS<0 Is at Post Dot-Com Bust High

Source: Initial Public Offerings: Updated Statistics, Jay Ritter, University of Florida, Warrington School of Business. Data as of 1/17/2018 accessed at: https://site.warrington.ufl.edu/ritter/files/2018/01/IPOs2017Statistics_January17_2018.pdf

Proportion of IPO firms with negative profits rivals

Dot-Com era bust

62

Talent Wars

Can the Insurance Industry Win the War for Talent?

Insurance is Not the Only Industry that is Interested in Hiring New Talent, Especially those with

Data/Analytics Skills

62

Can Insurers Win the War for Talent?

Source: Business Insurance, 2017 Risk Management and Insurance Schools Ranking and Directory,

The number of RMI

majors is up sharply

Overall employment

is up too

Can Insurers “Win” the War on Talent?n Hiring Needs: The industry has a stated need of hiring

some 400,000 people over the next several years

n Inclusive Approach: The industry’s approach has been to suggest that virtually everyone, from any background can build a rewarding career in the insurance industry

n So Far, So Good: To date, the industry’s diligence and efforts seems to be meeting with successw Insurers seem generally to be successful in their overall

recruiting efforts

n Amica Does an Especially Job:w Good job articulating career path and uniqueness of Amica

as a company; Strong campus presence

65

P/C Insurance Industry Financial Overview

CATS, Non-CAT Underwriting Losses Impacted Insurer Balance Sheets

Industry Remains Strong

65

P/C Industry Net Income After Taxes1991–2018:Q1

n 2005 ROE= 9.6%n 2006 ROE = 12.7%n 2007 ROE = 10.9%n 2008 ROE = 0.1%n 2009 ROE = 5.0%n 2010 ROE = 6.6%n 2011 ROAS1 = 3.5%n 2012 ROAS1 = 5.9%n 2013 ROAS1 = 10.2%n 2014 ROAS1 = 8.4%n 2015 ROAS = 8.4%n 2016 ROAS = 6.2%n 2017 ROAS =5.0%n 2018 ROAS = 2.4%

•ROE figures are GAAP; 1Return on avg. surplus. Excluding Mortgage & Financial Guaranty insurers yields a 8.2% ROAS in 2014, 9.8% ROAS in 2013, 6.2%ROAS in 2012, 4.7% ROAS for 2011, 7.6% for 2010 and 7.4% for 2009; Sources: A.M. Best, ISO.

$14,178

$5,840$19,316

$10,870 $20,598

$24,404 $36,819

$30,773

$21,865

$3,046

$30,029

$62,496

$3,043

$35,204

$19,456 $3

3,522

$63,784

$55,870

$56,826

$42,924

$36,123

$17,384

$38,501

$20,559

$44,155

$65,777

-$6,970$28,672

-$10,000

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18*

Net income fell sharply in 2017

as high CAT losses took

their toll

$ Millions

-5%

0%

5%

10%

15%

20%

25%

75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

Profitability Peaks & Troughs in the P/C Insurance Industry, 1975 – 2018:Q1

Profitability = P/C insurer ROEs. 2011-16 figures are estimates based on ROAS data. Note: Data for 2008-2014 exclude mortgage and financial guaranty insurers.Source: NAIC, ISO, A.M. Best, USC RUM Center.

1977:19.0% 1987:17.3%

1997:11.6% 2006:12.7%

1984: 1.8% 1992: 4.5% 2001: -1.2%

10 Years10 Years

9 Years

ROEs in 2017 plunged to their lowest levels

since 2008.ROE

1975: 2.4%

2013 9.8%

2016 6.2%

2015: 8.4%

2017 5.0%

68

ROE: Property/Casualty Insurance by Major Event, 1987–2018:Q1

Excludes Mortgage & Financial Guarantee in 2008 – 2014. Sources: ISO, Fortune; USC RUM Center.

-5%

0%

5%

10%

15%

20%

87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18*

P/C Profitability Is Influenced Both by

Cyclicality and Volatility

Hugo

Andrew, Iniki

Northridge

Lowest CAT Losses in 15 Years

Sept. 11

Katrina, Rita, Wilma

4 Hurricanes

Financial Crisis*

(Percent)

Record Tornado Losses

Sandy

Low CATs

Harvey, Irma, Maria,

CA Wildfires

69

P/C Insurance Industry Combined Ratio, 2001–2018:Q1*

* Excludes Mortgage & Financial Guaranty insurers 2008--2014. Including M&FG, 2008=105.1, 2009=100.7, 2010=102.4, 2011=108.1; 2012:=103.2; 2013: = 96.1; 2014: = 97.0.; 2017 (est.) based on actual 104.1 through Q3 (Q3 combined ratio alone was 110.7). Sources: A.M. Best, ISO (2014-2016); Figure for 2017 from ISO.

95.7

99.3101.1

106.5

102.5

96.4 97.0 97.8100.7

103.7101.0

92.6

100.898.4

100.1

107.5

115.8

90

100

110

120

01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

As Recently as 2001, Insurers Paid Out

Nearly $1.16 for Every $1 in Earned Premiums Relatively

Low CAT Losses, Reserve Releases

Heavy Use of Reinsurance Lowered Net

Losses

Relatively Low CAT Losses, Reserve Releases

Higher CAT

Losses, Shrinking Reserve

Releases, Toll of Soft

Market

Sandy Impacts

Lower CAT

Losses

Best Combined Ratio Since 1949 (87.6)

Avg. CAT Losses,

More Reserve Releases

Cyclical Deterioration

Sharply higher CATs are driving

large underwriting losses and

pricing pressure

71

Policyholder Surplus, 2006:Q4–2018:Q1

Sources: ISO, A.M .Best; Center for Risk and Uncertainty Management, University of South Carolina.

($ Billions)$487.1

$496.6

$512.8

$521.8

$478.5

$455.6

$437.1 $463.0 $490.8

$511.5 $540.7

$530.5

$544.8

$559.2

$559.1

$538.6

$550.3

$567.8

$583.5

$586.9

$607.7

$614.0

$624.4 $653.4

$671.6

$673.9

$675.2

$674.2

$673.7

$676.3 $700.9

$717.0 $752.5

$734.1

$662.0

$570.7

$566.5

$505.0

$515.6

$517.9

$400

$450

$500

$550

$600

$650

$700

$750

$800

06:Q4

07:Q1

07:Q2

07:Q3

07:Q4

08:Q1

08:Q2

08:Q3

08:Q4

09:Q1

09:Q2

09:Q3

09:Q4

10:Q1

10:Q2

10:Q3

10:Q4

11:Q1

11:Q2

11:Q3

11:Q4

12:Q1

12:Q2

12:Q3

12:Q4

13:Q1

13:Q2

13:Q3

13:Q4

14:Q1

14:Q2

14:Q3

14:Q4

15:Q2

15:Q4

16:Q1

16:Q4

17:Q2

17:Q4

18:Q1

Financial Crisis

Surplus (Capacity) as of 12/31/17 reached a new

record of $752.5B despite heavy CAT losses

2010:Q1 data includes $22.5B of paid-in capital from a holding company parent for one insurer’s investment in a non-insurance business .

Drop due to near-record 2011 CAT losses

Capacity/Capital “shocks” typically do not on their own drive a sustained firming of

the pricing environment

72

Brief P/C Insurance Growth Overview and Outlook

Drivers of Growth in 2018

Economic Growth Fuels Exposure & Record CAT Losses Are Pressuring Rates

Price Competition Remains Rational While Others Look Toward M&A

72

73

-5%

0%

5%

10%

15%

20%

25%

71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

Net Premium Growth (All P/C Lines): Annual Change, 1971—2018F(Percent)

1975-78 1984-87 2000-03

*Shaded areas denote “hard market” periodsSources: A.M. Best (1971-2013), ISO (2014-17).

Net Written Premiums Fell 0.7% in 2007 (First Decline

Since 1943) by 2.0% in 2008, and 4.2% in 2009, the First 3-Year Decline Since 1930-33.

2018F: 4.5%2017: 4.6%2016: 2.7%2015: 3.5%2014: 4.2

2013: 4.4%2012: +4.2%

Outlook2017E: 4.1%2018F: 4.5%

Y-o-Y Growth Rates, Direct Premiums Written, Commercial vs. Personal Lines,

2012:Q4 - 2017:Q3

0%

1%

2%

3%

4%

5%

6%

7%

12:Q

1

12:Q

212

:Q3

12:Q

4

13:Q

113

:Q2

13:Q

3

13:Q

414

:Q1

14:Q

2

14:Q

3

14:Q

415

:Q1

15:Q

2

15:Q

315

:Q4

16:Q

1

16:Q

216

:Q3

16:Q

4

17:Q

117

:Q2

17:Q

3

Personal LinesCommercial Lines

Sources: NAIC, via SNL Financial; ISO; Insurance Information Institute calculations.

Since 2014, personal lines Direct Premiums Written have generally grown faster than commercial lines DPW, and that growth has been less volatile.

Personal Lines growth is more

than 3 times that of

Commercial Lines

77

M&A Trends

Consolidation Among P&C (Re)Insurers and Within

Distribution Channels Will Likely Continue at a Modest Pace

78

U.S. INSURANCE MERGERS AND ACQUISITIONS,P/C SECTOR, 1994-2016 (1)

$5,100

$11,534

$8,059

$30,873

$19,118

$40,032

$1,249

$486

$20,353

$425

$9,264

$35,221

$13,615

$16,294

$3,507 $6,419

$12,458

$4,685

$4,393

$6,723

$40,006

$8,498

$55,825

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16

Tran

sact

ion

valu

es

0

20

40

60

80

100

120

140

Num

ber of transactions

($ Millions)

(1) Includes transactions where a U.S. company was the acquirer and/or the target.

Source: Conning proprietary database.

M&A activity in the P/C sector in 2015 totaled $39.6B, its highest level since

2000, but fell sharply in 2016 in dollar terms

AXA its acquisition of XL Ltd. on 3/5/19

for $15.3B

79

U.S. INSURANCE MERGERS AND ACQUISITIONS:DISTRIBUTION, 1996-2017 (1)

$1,934

$2,720

$55,903

$1,633

$542

$689

$446

$60

$212

$944

$15,205

$5,812

$615 $1,727

$2,271

$4,225 $8,246

$2,581

$18,695

$4,204

$6,594

$7$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

Tran

sact

ion

valu

es

0

100

200

300

400

500

600

Num

ber of transactions

($ Millions)

(1) Includes transactions where a U.S. company was the acquirer and/or the target.

Source: Conning proprietary database.

M&A activity in the Distribution sector in 2017 totaled $6.6B, up (56.9%) from $4.2B in 2016; The

number of deals hit a record high 565 in 2017

THE ECONOMY

80

The Strength of the Economy Will Greatly Influence Growth in Insurers’ Exposure

Base Across Most Lines—Including Auto and Home

How Is “Trumponomics” Impactingthe Industry?

80

83

US Real GDP Growth*

* Estimates/Forecasts from Blue Chip Economic Indicators.Source: US Department of Commerce, Blue Economic Indicators 5/18; Center for Risk and Uncertainty Management, Univ. of South Carolina.

2.7%

1.8%

-1.8%

1.3%

-3.7%

-5.3%

-0.3%

5.0%

2.3%

2.2% 2.6%

2.4%

0.1%

2.5%

1.3%

4.1%

2.0%

1.3%3.1%

0.4%2.7%

1.8%3.5%

-0.9%

4.6%

4.3%

2.1%

2.0% 2.6%

2.0%

0.9%

0.8% 1.4%3.5%

2.1%

1.2%3.1%

3.2%

2.9%

2.2% 3.2%

3.0%

2.8%

2.5%

2.5%

2.2%

2.0%

-8.9%

4.5%

1.4%

4.1%

1.1% 1.8% 2.5% 3.6%

3.1%

-9%

-7%

-5%

-3%

-1%

1%

3%

5%

7%

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

08:1

Q08

:2Q

08:3

Q08

:4Q

09:1

Q09

:2Q

09:3

Q09

:4Q

10:1

Q10

:2Q

10:3

Q10

:4Q

11:1

Q11

:2Q

11:3

Q11

:4Q

12:1

Q12

:2Q

12:3

Q12

:4Q

13:1

Q13

:2Q

13:3

Q13

:4Q

14:1

Q14

:2Q

14:3

Q14

:4Q

15:1

Q15

:2Q

15:3

Q15

:4Q

16:1

Q16

:2Q

16:3

Q16

:4Q

17:1

Q17

:2Q

17:3

Q17

:4Q

18:1

Q18

:2Q

18:3

Q18

:4Q

19:1

Q19

:2Q

19:3

Q19

:4Q

Demand for Insurance Should Increase in 2018-19 as GDP Growth Continues at a Steady and Perhaps Accelerating Pace and Gradually

Benefits the Economy Broadly

Real GDP Growth (%)

Recession began in Dec, 2007

The Q4:2008 decline was the steepest since the Q1:1982 drop of 6.8%

2018 GDP forecasts were revised upwards by ~0.4%

due to tax reform, but effects wane in 2019

First consecutive

quarters of 3%+ GDP growth since 2014

84

US Unemployment Rate Forecast4.5%

4.5% 4.6% 4.8% 4.9% 5.4% 6.1%6.9%

8.1%

9.3% 9.6% 10.0%

9.7%

9.6%

9.6%

8.9% 9.1%

9.1%

8.7%

8.3%

8.2%

8.0%

7.8%

7.7%

7.6%

7.3%

7.0%

6.6%

6.2%

6.1%

5.7%

5.6%

5.4%

5.2%

5.0%

4.9%

4.9%

4.9%

4.7%

4.7%

4.4%

4.3%

4.1%

4.1%

4.0%

3.9%

3.7%

3.7%

3.6%

3.6%

3.6%

9.6%

4%

5%

6%

7%

8%

9%

10%

11%

07:Q1

07:Q2

07:Q3

07:Q4

08:Q1

08:Q2

08:Q3

08:Q4

09:Q1

09:Q2

09:Q3

09:Q4

10:Q1

10:Q2

10:Q3

10:Q4

11:Q1

11:Q2

11:Q3

11:Q4

12:Q1

12:Q2

12:Q3

12:Q4

13:Q1

13:Q2

13:Q3

13:Q4

14:Q1

14:Q2

14:Q3

14:Q4

15:Q1

15:Q2

15:Q3

15:Q4

16:Q1

16:Q2

16:Q3

16:Q4

17:Q1

17:Q2

17:Q3

17:Q4

18:Q1

18:Q2

18:Q3

18:Q4

19:Q1

19:Q2

19:Q3

19:Q4

Rising unemployment eroded payrolls

and WC’s exposure base.

Unemployment peaked at 10% in late 2009.

* = actual; = forecastsSources: US Bureau of Labor Statistics; Blue Chip Economic Indicators (5/18 edition); Risk and Uncertainty Management Center, University of South Carolina.

2007:Q1 to 2019:Q4F*

Unemployment forecasts have been revised modestly downwards. Optimistic

scenarios put the unemployment as low as 3.2% by Q4 2019.

Jobless figures have been revised

downwards for 2018/19

At 3.8%, the unemployment

rate is at an 18-year low

85

Number of Unemployed Persons per Job Opening, Feb. 2003—Apr. 2018*

*Seasonally adjustedNote: Recessions indicated by gray shaded columns.Sources: US Bureau of Labor Statistics JOLTS survey: at http://www.bls.gov/jlt/; National Bureau of Economic Research (recession dates); Center for Risk and Uncertainty Management, University of South Carolina.

0

1

2

3

4

5

6

7

'03 '04 '05 '06 '07 '08 '09 '10 '11 '12 '13 '14 '15 '16 '17 '18

At the height of the recession,

there were nearly 7 job seekers for

every one opening

Today, there are just 0.9 job seekers

for every one opening, the lowest

ratio in history

Unemployed Persons per Job Opening

The Economy Drives P/C InsuranceIndustry Premiums: 2006:Q1 – 2017:Q2Direct Premium Growth (All P/C Lines) vs. Nominal GDP: Quarterly Y-o-Y Pct. Change

Sources: SNL Financial; U.S. Commerce Dept., Bureau of Economic Analysis; I.I.I.

-6%

-3%

0%

3%

6%

9%

12%

2006:Q1

2006:Q3

2007:Q1

2007:Q3

2008:Q1

2008:Q3

2009:Q1

2009:Q3

2010:Q1

2010:Q3

2011:Q1

2011:Q3

2012:Q1

2012:Q3

2013:Q1

2013:Q3

2014:Q1

2014:Q3

2015:Q1

2015:Q3

2016:Q1

2016:Q3

2017:Q1

DWP y-o-y change y-o-y nominal GDP growth

Direct Written Premiums track Nominal GDP—not quarter by quarter but overall fairly well.

87

Consumer Confidence Index:Jan. 1987 – Apr. 2018

Source: The Conference Board; Wells Fargo Research.

Outlook: Consumers are optimistic about the future, which is consistent with expectations for stronger economic growth (consumers account for nearly 70% of all spending in the economy). Should positively influence

growth of insurable exposures.

The Conference Board’s Consumer Confidence Index stood at 128.7 in April, close to its

post-recession high

90

(Millions of Units)

New Private Housing Starts, 1990-2023F

1.48

1.47 1.62 1.64

1.57 1.60 1.71 1.85 1.96 2.07

1.80

1.36

0.91

0.55 0.59 0.610.78 0.92 1.00 1.11 1.17 1.20 1.31 1.35 1.40 1.43 1.45 1.48

1.351.46

1.29

1.20

1.011.19

0.3

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2.1

90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18F19F20F21F22F23F

Source: U.S. Department of Commerce; Blue Chip Economic Indicators (5/18 for 2018-19; 10/17 for 2019-23F; Insurance Information Institute.

Insurers Are Continue to See Meaningful Exposure Growth in the Wake of the “Great Recession” Associated with Home Construction: Construction Risk

Exposure, Surety, Commercial Auto; Potent Driver of Workers Comp Exposure

New home starts plunged 72% from 2005-2009; A net

annual decline of 1.49 million units, lowest since records began

in 1959

Job growth, low inventories of existing homes, still-low mortgage

rates and demographics should continue to stimulate new home

construction for several more years

92

16.9

16.5

16.1

13.2

10.411.6 12

.714.4 15

.5 16.4 17

.417.5

17.2

17.0

16.7

16.7

16.7

16.7

16.9

16.9

16.617.117.517.8

17.4

910111213141516171819

99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18F19F20F21F22F22F

(Millions of Units)

Auto/Light Truck Sales, 1999-2023F

New auto/light truck sales fell to the lowest level since the

late 1960s. Forecast for 2014-15 is still below 1999-2007 average of 17 million units,

but a robust recovery is well underway.

Job growth and improved credit market conditions

boosted auto sales to near record levels in

recent years

Truck, SUV purchases remain strong but have slumped a bit

Yearly car/light truck sales are slowing slightly, as demand tapers following the recovery from the recession. PP Auto premium might

grow by 3.5% - 5%.

Sales have returned to pre-

crisis levels

Source: U.S. Department of Commerce; Blue Chip Economic Indicators (5/18 for 2018-19; 10/17 for 2019-23F; Insurance Information Institute.

93

Personal Lines Growth Drivers

Rate and Exposure are Both Presently Important

Growth Drivers

94

Top Growth Factors: Personal Linesn Rate: Favorable rate trends in both auto and home

w Adverse severity trends are pressuring personal auto

w Record CAT losses in 2017 will further pressure comprehensive

n Economic Strength: Economic growth, supported by low unemployment, rising consumer confidence are supporting strength in new auto sales, new home construction, tax cuts

n Household Formation: Millennials are finally becoming car and home buyers in larger numbers, driving exposures upward

n High Net Worth Consumers: This segment has seen consistent (and profitable) growth as the “wealth effect” grows

n Driving More: Americans are behind the wheel more than ever

n Market Discipline: Major personal lines insurers remain generally price disciplined

95

Monthly Change in Auto Insurance Prices, 1991–2018*

*Percentage change from same month in prior year; through Apr. 2018; seasonally adjustedNote: Recessions indicated by gray shaded columns.Sources: US Bureau of Labor Statistics; National Bureau of Economic Research (recession dates); Insurance Information Institutes.

-2%

0%

2%

4%

6%

8%

10%

'90 '91 '92 '93 '94 '95 '96 '97 '98 '99 '00 '01 '02 '03 '04 '05 '06 '07 '08 '09 '10 '11 '12 '13 '14 '15 '16 '17 '18

Cyclical peaks in PP Auto tend to occur roughly every 7-10 years (early 1990s,

early 2000s, early and late 2010s)

“Hard” markets often tend to occur during recessionary

periods

Last pricing peak occurred in late

2010 at 5.3%, falling to 2.8% by Mar. 2012

Apr. 2018 reading of 9.0% is up from 6.7%

a year earlier. Recent rate trends are the strongest

since 2002-2003.

96

Personal Auto Insurance: Key CPI Cost Component Changes: 2018 vs. 2017*

Source: US Bureau of Labor Statistics; USC Center for Risk and Uncertainty Management.

Percentage Change (%)

4.0% 4.0%2.7%2.1%

9.0%

2.4%

0.1%

-0.7%-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

Ove

rall C

PI

Mot

or V

ehic

leIn

sura

nce

Mot

or V

ehic

leBo

dy W

ork

Mot

or V

ehic

leR

epai

rs

Mot

or V

ehic

lePa

rts

Out

patie

ntH

ospi

taliz

atio

n

Inpa

tient

Hos

pita

lizat

ion

Pres

crip

tion

Dru

gs

* April 2018 vs. April 2017.

Apr. 2018 reading of 9.0% is up from 6.7%

a year earlier. Current rate trend is strongest

since 2002-2003.

Hospitalization costs continue to

drive severity

97

Personal Auto Insurance: Key CPI Cost Component Changes: 2008 – 2017

Source: US Bureau of Labor Statistics; USC Center for Risk and Uncertainty Management.

Percentage Change (%)

3.8%

30.6%

13.8%

54.3%

22.8%

9.5%5.4%

0%

10%

20%

30%

40%

50%

60%

Ove

rall

CPI

Mot

orVe

hicl

eIn

sura

nce

Mot

orVe

hicl

eBo

dy W

ork

New

Vehi

cles

New

Car

s

Use

d C

ars

Med

ical

Car

e Ite

ms

The price of auto insurance increased by

nearly four times the overall pace of inflation

from 2008-2017 as frequency and severity trends deteriorated as

the economy recovered and vehicles repair and

medical costs rose

98

$119.7

$128.0 $139.7 $151.2

$159.6

$158.5

$157.2

$160.1

$163.3

$168.1

$174.9

$183.5

$192.5 $206.6 $220.0 $234.0

$160.3

$159.6

$157.3

$100

$120

$140

$160

$180

$200

$220

$240

$260

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17E 18F

PP Auto premiums written continue to recover from a period of flat growth attributable to the weak economy impacting new vehicle sales, car choice, and increased

price sensitivity among consumers

Sources: A.M. Best (1990-2016); USC RUM (2017F-2018F).

Private Passenger Auto InsuranceNet Written Premium, 2000–2018F

$ Billion

PPA NWP volume in 2017 was up an estimated $62.8B or 39.9% since the

2009 trough; By 2017 the gain is expected to be $76.8B or 48.9%

PPA will generate $10B - $14B in new premiums annually

through 2018

Direct Premiums Written: Pvt. Passenger Auto Percent Change by State, 2007-2016

Source: NAIC data, sourced from S&P Global Market Intelligence, Insurance Information Institute.

59.8

51.6

48.5

45.6

42.8

42.8

41.6

41.1

40.6

40.4

40.2

35.5

33.3

32.7

32.6

32.2

32.2

31.7

30.8

30.0

29.5

29.3

29.3

29.0

28.8

28.7

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

TX CO ND MI OK SC GA UT SD FL NE TN OR WI LA AL IA US MO KY DE KS NC NY ID IN

Top 25 States

Direct Premiums Written: Pvt. Passenger AutoPercent Change by State, 2007-2016

Source: NAIC data, sourced from S&P Global Market Intelligence, Insurance Information Institute.

28.6

27.9

26.8

26.7

26.5

26.2

26.0

26.0

25.9

24.5

24.5

24.3

22.6

22.6

22.3

22.1

21.6

21.6

19.0

18.2

15.7

14.1

13.9

13.7

10.7

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

VA AR MT DC WA NJ RI MN MD MS CA OH WY IL NV MA AZ NM CT PA NH VT AK WV ME

Bottom 25 States

105

Homeowners InsuranceNet Written Premium, 2000–2018F

$45.8$49.5

$52.2$54.8 $55.2

$61.1$63.5

$66.9$71.9

$77.0$79.5 $80.2 $81.5

$82.7

$57.5$56.2

$32.4

$40.0

$35.2

$30$35$40$45$50$55$60$65$70$75$80$85$90$95$100

00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17E 18F

Sources: A.M. Best; USC RUM Center.

$ Billions Homeowners insurance NWP continues to rise (up 152% 2000-2017E) despite very little unit

growth during the real estate crash. Reasons include rate increases, especially in coastal

zones, ITV endorsements (e.g., “inflation guards”), compulsory for mortgaged properties

and resumption of home building activity

The Homeowners line will generate about

$1.5B in new premiums annually through 2018

Direct Premiums Written: Homeowners MPPercent Change by State, 2007-2016

Source: NAIC data, sourced from S&P Global Market Intelligence, Insurance Information Institute.

85.7

82.9

82.0

78.7

77.9

75.0

74.3

69.0

68.4

66.7

66.3

65.1

65.1

63.3

63.0

62.2

61.9

55.5

55.5

53.4

52.3

51.9

50.8

50.1

49.6

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

SD OK CO NE ND WY MT MN TN GA KS MO AR TX IA KY WI DE ID NM IN UT OH SC NC

Top 25 States

Direct Premiums Written: Homeowners MPPercent Change by State, 2007-2016

Source: NAIC data, sourced from S&P Global Market Intelligence, Insurance Information Institute.

47.9

47.0

46.4

45.5

45.2

44.9

43.3

42.4

42.0

41.0

40.9

40.3

39.3

38.9

38.2

37.4

34.3

33.8

31.7

30.3

27.2

26.8

18.9

17.5

17.4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

CT RI VA ME NJ AL MS WA MD MA US NH PA WV OR LA AZ NY DC AK MI VT CA HI NV

Bottom 25 States

108

State of the Personal Lines Market

Auto Frequency and Severity Are an Immediate Challenge

Homeowners Majorly Impacted by CATs in 2017

108

109

Return on Net Worth: All P-C Lines vs. Homeowners & Pvt. Pass. Auto, 1990-2016*

*Latest available.**Excludes 1992, the year of Hurricane Andrew. If 1992 is included the resulting homeowners RNW is 2.2%Sources: NAIC; Insurance Information Institute.

-10%

-5%

0%

5%

10%

15%

20%

25%

90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16

US All LinesUS HomeUS PP Auto

(Percent)Average RNW: 1990-2016*

All P-C Lines: 7.7% PP Auto: 7.6%

Homeowners: 4.9%**

Homeowners is Now Outperforming Pvt.Pass. Auto and P-C Industry as a Whole. HO Volatility is Associated Primarily With Coastal Exposure Issues

Excluding 1992’s Hurricane Andrew

Return on Net Worth: US Personal Auto, 2005-2016

0.7%

13.1%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Personal Fortune 500

Rising claim costs have been a factor in keeping auto insurer

ROEs quite low

110

Auto Insurance Profitability Remains Well Below Pre-Crisis Levels (12% vs. ~1%) and Far Below the Fortune 500 (13% vs. ~1%)

.SOURCE: National Association of Insurance Commissioners.

Private Passenger Auto Combined Ratio: 1993–2017

101.7

101.3

101.3

101.0

109.5

107.9

104.2

98.4

94.3

95.1

95.5 98.3 100.2

101.3

101.0

102.0

102.1

101.6

102.3

104.6

106.3

103.5

99.5 101.1

103.5

80

85

90

95

100

105

110

115

93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

Private Passenger Auto Underwriting Performance Is Showing the Strains of Rising Frequency (and Severity) Trends in Many States

112Sources: A.M. Best (1990-2017); USC RUM Center.

Commercial Auto Combined Ratio: 1993–2017

112.1

112.0

113.0

115.9

102.7

95.2

92.9

92.1

92.4 94.1 96.8 99.1

97.8

103.4

106.8

106.7

103.3 108.8

110.4

111.011

8.1

115.7

116.2

80

85

90

95

100

105

110

115

120

125

95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

Commercial Auto Results Are Challenged as Rate Gains Have Yet to Fully Offset Adverse Frequency and Severity Trends

113Sources: A.M. Best (1990-2017); USC RUM Center.

Homeowners Insurance Combined Ratio: 1990–2017

113.0

117.7

158.4

113.6

101.0 109.4

108.2

111.4 121.7

109.3

98.2

94.4 100.3

89.0 95.6

116.6

105.8

106.9122.3

104.1

90.4

92.4

91.9

93.2107.0118.4

112.7 121.7

80

90

100

110

120

130

140

150

160

170

90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

1

Homeowners Performance Had Improved Markedly Since 2011/12’s Large Cat Losses…until 2017’s Record

Catastrophe Loss Activity.

114

Hurricane Ike

Hurricane Sandy

Record tornado activity

Hurricane Andrew

Sources: A.M. Best (1990-2017); USC RUM Center.

Hurricanes Harvey,

Irma, Maria, CA Wildfires

116

Claim Trends in Private Passenger Auto Insurance

Rising Frequencies and Severities in Many Coverages

Will that Pattern Be Sustained?

117

Bodily Injury: Severity Trend Is Up, Frequency Decline Returning?

2.1% 1.7%3.6%

1.8%

4.3%5.6%

7.7%

-5.4%-3.8% -4.0% -4.2%

-2.2%

0.0%

-1.1%

3.4%

0.0%

-2.2%

3.0%2.0%

5.9%5.7%4.7%

2.9%1.1%

0.0% 0.0%

-8%-6%-4%

-2%0%2%4%

6%8%10%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017*

Severity Frequency

Annual Change, 2005 through 2017*

BI Severity Trend is a Major Cost Driver

*2017 figure is for the 4 quarters ending 2017:Q4.Source: ISO/PCI Fast Track data; Insurance Information Institute

118

Property Damage Liability: Severity Up and Frequency Flat

1.8% 1.9%

4.1%3.5%

6.3% 6.0%

3.9%

-1.6%

-3.5% -3.4%

0.6% 0.6%

-0.3%

1.4% 1.4%0.8%

-1.4%

2.9%3.6%

2.0% 2.0%

-0.4%

0.4%0.9% 1.2%0.3%

-4%

-2%

0%

2%

4%

6%

8%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017*

Severity Frequency

Annual Change, 2005 through 2017*

Severity/Frequency Trends Have Been Volatile, But Rising Severity since 2011 Is a Concern

*2017 figure is for the 4 quarters ending 2017:Q4.Source: ISO/PCI Fast Track data; Insurance Information Institute

120

Collision Coverage: Severity & Frequency Trends Are Both Higher in 2017*

2.8%1.3%

4.2%

1.4%

5.7% 5.1%

-0.1%

-1.8%

-3.6%

2.5%

-2.4% -1.8%

4.4%

1.2% 1.2%

3.9%3.1%

0.1% 0.5%

-2.3%

-0.1%-0.2%-1.4%-0.5%

0.9%2.3%

-6%

-4%

-2%

0%

2%

4%

6%

8%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017*

Severity Frequency

Annual Change, 2005 through 2017*

The Recession, High Fuel Prices Helped Temper Frequency and Severity, But that Trend Clearly Reversed, Consistent with Experience from Past Recoveries—Until Flattening in 2017

*Four quarters ending with 2017 Q4. Source: ISO/PCI Fast Track data; Insurance Information Institute

121

Comprehensive Coverage: Frequency and Severity Trends Are Volatile

15.4% 15.3%

-14.6%

6.5%

-1.3%

21.6%

8.7%

-9.8%-6.3%

1.3%5.8%

-8.9%-5.6%

2.1%

-0.6%

15.5%

-1.4% -1.5%

12.6%

-8.1%-5.9% -2.1%

3.5%

-3.1%

1.8%6.2%

-20%-15%-10%-5%0%

5%10%15%20%25%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017*

Severity Frequency

Annual Change, 2005 through 2017*

Weather Creates Volatility for Comprehensive Coverage. Comprehensive Losses Were Up 24.1% in Q3:2017 Due Largely to

Hurricanes Harvey and Irma

Severe weather is a principal cause of the spikes in both

frequency and severity

*2017 figure is for the 4 quarters ending with 2017:Q4.Source: ISO/PCI Fast Track data; Insurance Information Institute

124

Loss Ratio Analysis:Private Passenger Auto

Insurance

Lost Ratios Have Generally Risen Over the Past Several Years

Private Passenger Auto Combined Ratio: 1993–2017

101.7

101.3

101.3

101.0

109.5

107.9

104.2

98.4

94.3

95.1

95.5 98.3 100.2

101.3

101.0

102.0

102.1

101.6

102.3

104.6

106.3

103.5

99.5 101.1

103.5

80

85

90

95

100

105

110

115

93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17

Private Passenger Auto Underwriting Performance Is Showing the Strains of Rising Frequency (and Severity) Trends in Many States

125Sources: A.M. Best (1990-2017); USC RUM Center.

126

Combined Liability and Phys. DamageLoss Ratio Down: Private Passenger Auto, 2012 – 2017*

79.7% 80.2% 80.1%

82.6%

86.6%

82.2%

76%

78%

80%

82%

84%

86%

88%

2012 2013 2014 2015 2016 2017*

Loss Ratio

The Loss Ratio Across All Physical Damage Coverages Has Trended Generally Upward for Years

*2017 figure is for the 4 quarters ending in 2017:Q4Source: ISO/PCI Fast Track data; Insurance Information Institute

127

All Liability Coverages Loss Ratio Is Falling:Private Passenger Auto, 2012 – 2017*

82.3%

85.0%83.1%

87.7%

91.3%

86.0%

76%

78%

80%

82%

84%

86%

88%

90%

92%

2012 2013 2014 2015 2016 2017*

Loss Ratio

Bodily Injury Loss Ratios Have Trended Generally Upward for Years

*2017 figure is for the 4 quarters ending in 2017:Q4Source: ISO/PCI Fast Track data; Insurance Information Institute

128

All Phys. Dam Coverages Loss Ratio Down:Private Passenger Auto, 2012 – 2017*

72.2%

74.5%75.3%

78.1%

79.8%

76.4%

68%

70%

72%

74%

76%

78%

80%

82%

2012 2013 2014 2015 2016 2017*

Loss Ratio

The Loss Ratio Across All Physical Damage Coverages Has Trended Generally Upward for Years—Until Recently

*2017 figure is for the 4 quarters ending in 2017:Q4Source: ISO/PCI Fast Track data; Insurance Information Institute

129

Collision Loss Ratio Trending Upward:Private Passenger Auto, 2010 – 2017*

76.9%

73.8%

67.7%69.3% 69.4%

73.5%74.9%

76.7%

62%

64%

66%

68%

70%

72%

74%

76%

78%

2010 2011 2012 2013 2014 2015 2016 2017*

Loss Ratio

Collision Loss Ratios Were Trending Steadily Upward Until 2017

*2017 figure is for the 4 quarters ending in 2017:Q4Source: ISO/PCI Fast Track data; Insurance Information Institute

130

Comprehensive Loss Ratio Is Elevated:Private Passenger Auto, 2010 – 2017*

88.2%

71.0%76.5%

71.4%

85.8%89.6%

0%10%20%30%40%50%60%70%80%90%100%

2012 2013 2014 2015 2016 2017*

Loss Ratio

The Comprehensive Loss Ratio Stands at Mulit-Year High, Pushed Upward in 2017 by Record CAT Activity

*2017 figure is for the 4 quarters ending in 2017:Q4Source: ISO/PCI Fast Track data; Insurance Information Institute

131

A Few Factors Driving Adverse Private Passenger Auto Loss Trends

More Jobs, Better Economy, More People Driving, More Expensive

Cars, Higher Speed Limits…

America is Driving More Again: 2000-2017Percent Change, Miles Driven*

*Moving 12-month total vs. prior year through December. Sources: Federal Highway Administration; Insurance Information Institute.

1.7%2.1%

1.5%

2.2%1.9%

1.0%0.4% 0.3%

-2.1%

-0.3%

0.8%

-0.3%

0.1%0.6%

1.9%

2.7%

1.2%

2001 2003 2005 2007 2009 2011 2013 2015 2017*-2.5%

-1.5%

-0.5%

0.5%

1.5%

2.5%

3.5%

Fastest Growth in More Than a

Decade

Tremendous Growth In Miles Driven. The More People Drive, the More Frequently They Get Into Accidents.

More People Working and Driving=> More Collisions, 2006-2017:Q2Number Employed, Millions

Sources: Seasonally Adjusted Employed from Bureau of Labor Statistics; Rolling four-quarter average frequency from Fast Track Monitoring System; Insurance Information Institute.

When People are Out of Work, They Drive Less. When They Get Jobs,They Drive to Work, Helping Drive Claim Frequency Higher.

5.25.35.45.55.65.75.85.96.06.16.2

120

125

130

135

140

145

150

06:Q

1

06:Q

3

07:Q

1

07:Q

3

08:Q

1

08:Q

3

09:Q

1

09:Q

3

10:Q

1

10:Q

3

11:Q

1

11:Q

3

12:Q

1

12:Q

3

13:Q

1

13:Q

3

14:Q

1

14:Q

3

15:Q

1

15:Q

3

16:Q

1

16:Q

3

17:Q

1

Number Employed (left axis)Collision Claim Frequency (right axis)

Overall Collision Claims Per 100 Insured Vehicles

Recession

Does Spending on Vehicles Affect Claim Severity?

Annual Change, 2005 through 2017

Source: Fast Track Monitoring System; Bureau of Labor Statistics Consumer Expenditure Survey (vehicle purchases –net outlay) Insurance Information Institute.

As the Economy Has Gotten Better, People Are Spending More on Vehicles – When Those Cars Are in Accidents, Severity Increases.

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Collision Severity (left scale)

Previous 6-yr avg vehicle purchases (right scale)

138

-0.4%

0.1%

-2.5%

2.2%

1.0%

3.6%

-1.4%

0.4% 0.9%

-0.1%

-3.0%

-9.5%

-9.0%

-2.4% -0.1%

3.1%

-2.9%

0.1%

8.0%

5.0%

-1.0%

-7.0%

-5.9%

2.2%

1.5% 2.0%

0.7%

-12%-10%-8%-6%-4%-2%0%2%4%6%8%10%

91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17E

Annual Change (%)

*2017 estimate from NSC data.Source: National Safety Council.

Motor vehicle deaths saw their

largest increase in 50 years in 2016

U.S. Annual Change in Automobile Deaths, 1991- 2017E*

Driving Has Been Getting Safer For Decades, But Recent Trend Is Discouraging—40,200 Deaths in 2016—Little Improvement in 2017

Sharp increase in

use of seatbelts

Steep drop due to less

driving during the Great

Recession

2015/16 is the largest 2-year escalation in

53 years

139

The First Human to Be Killed by an Autonomous Vehicle…And It Appears the Human Was at Fault…Maybe On the night of March

18, 2018 in Tempe, AZ, 49-year old Elaine

Herzberg was struck and killed by a self-driving Uber vehicle

while crossing the road pushing a bicycle. She

is believed to be the first human to be killed

by an autonomous vehicle.

Claims Quandary?Tempe Police Chief Sylvia Moir: “I suspect preliminarily it appears

that the Uber would likely not be at fault in this accident.” But then Moir added: “I won’t rule out the potential to file charges against

the [backup driver] in the Uber vehicle.”

Source: TheVerge.com at: https://www.theverge.com/2018/3/20/17142672/uber-deadly-self-driving-car-crash-fault-police

Thank you for your timeand your attention!

Twitter: twitter.com/bob_hartwigFor a copy of this presentation, email me at robert.hartwig@moore.sc.edu

142