InsurTech: The Financing of Innovation, Transformation and Disruption Robert P. Hartwig, Ph.D., CPCU Clinical Associate Professor of Finance, Risk Management & Insurance Darla Moore School of Business ¨ University of South Carolina [email protected]¨ 803.777.6782 InsurTech Symposium Charlotte, NC June 20, 2018
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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 [email protected] ¨ 803.777.6782
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
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
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
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 $753
billion in policyholder surplus (a proxy for capacity)—which is at implies that the industry is overcapitalized by about 1/3
19.9%
19.8%
18.5%
17.1%
9.5%
7.3%
6.1%
4.2%
28.7%
0% 5% 10% 15% 20% 25% 30% 35%
Computer Services
Semiconductors
Information Services
Software (Internet)
Software (Systems & Application)
Health Information & Technology
P/C Insurance
Reinsurance
Life Insurance
*As of January 2018Source: Stern School, NYU accessed 6/18/18 at : http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/roe.html; Univ. of South Carolina Center for Risk and Uncertainty Management.
Low ROEs will keep the number of actual insurance start-ups low—and kill off
many others as well
ROEs: Insurance vs. Technology Sectors—A “Poison Pill”?
ROEs in the tech sector are much higher than for insurers. This is one reason why tech
•ROE figures are GAAP; 1Return on avg. surplus. Excluding Mortgage & Financial Guaranty insurers yields a 8.2% ROAS in 2014, 9.8% ROAS in 2013, 6.2%ROAS in 2012, 4.7% ROAS for 2011, 7.6% for 2010 and 7.4% for 2009; Sources: A.M. Best, ISO.
Profitability Peaks & Troughs in the P/C Insurance Industry, 1975 – 2018:Q1
Profitability = P/C insurer ROEs. 2011-16 figures are estimates based on ROAS data. Note: Data for 2008-2014 exclude mortgage and financial guaranty insurers.Source: NAIC, ISO, A.M. Best, USC RUM Center.
1977:19.0% 1987:17.3%
1997:11.6% 2006:12.7%
1984: 1.8% 1992: 4.5% 2001: -1.2%
10 Years10 Years
9 Years
ROEs in 2017 plunged to their lowest levels
since 2008.ROE
1975: 2.4%
2013 9.8%
2016 6.2%
2015: 8.4%
2017 5.0%
33
ROE: Property/Casualty Insurance by Major Event, 1987–2018:Q1
Excludes Mortgage & Financial Guarantee in 2008 – 2014. Sources: ISO, Fortune; USC RUM Center.
Sources: ISO, A.M .Best; Center for Risk and Uncertainty Management, University of South Carolina.
($ 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
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?
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”
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
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
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
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
•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.
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.
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.
(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.
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
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.
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
$ 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.
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
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.