The Property/Casualty LandscapeProfitability, Growth – Disruption?Casualty Actuaries of the Southeast, Atlanta, September 26, 2016Download at www.iii.org/presentations

James Lynch, FCAS MAAA, Chief Actuary

Insurance Information Institute 110 William Street New York, NY 10038 Tel: 212.346.5533 jamesl@iii.org www.iii.org

Insurance Industry:Financial Update & Outlook

2015 Was a Reasonably Good Yearand Similar to 2014

2016: Smarting from Catastrophes

3

14

,17

8

5,8

40

19

,31

6

10

,87

0 20

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21

,86

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20

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-6,9

70

3,0

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30

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38

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44

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65

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7

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35

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-$20,000

-$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:Q

2

Milli

on

sP/C Industry Net Income After Taxes1991-2016:Q2 (preliminary)

*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. 2016:Q2 is annualized

Sources: A.M. Best; ISO, a Verisk Analytics company; Insurance Information Institute.

2005 ROE*= 9.6%

2006 ROE = 12.7%

2007 ROE = 10.9%

2008 ROE = 0.1%

2009 ROE = 5.0%

2010 ROE = 6.6%

2011 ROAS1 = 3.5%

2012 ROAS1 = 5.9%

2013 ROAS1 = 10.2%

2014 ROAS1 = 8.4%

2015 ROAS1 = 8.4%

Profits Are 28 Percent Below Last Year Through Two Quarters. Little

Cats, Weak Auto Results

4

Return on Equity by Financial Services Sector vs. Fortune 500, 2004-2015*

*GAAP basis.

Sources: ISO, a Verisk Analytics company; Fortune; Insurance Information Institute.

-2%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

04 05 06 07 08 09 10 11 12 13 14 15E

Fortune 500

P/C Insurers

Life Insurers

Commercial Banks

Banks and Insurers Have Substantially Underperformed the Fortune 500 Since the Financial Crisis.

Average: 2004–2014

Fortune 500: 13.9%

Commercial Banks: 9.8%

Life: 8.2%

P/C: 7.1%

5

Profitability Peaks & Troughs in the P/C Insurance Industry, 1975-2015

*Profitability = P/C insurer ROEs. 2011-14 figures are estimates based on ROAS data. Note: Data for 2008-2014 exclude mortgage and financial guaranty insurers.

Sources: Insurance Information Institute; Natl. Assoc. of Insurance Comm.; ISO, a Verisk Analytics company; A.M. Best, Conning.

2.4%

19.0%

1.8%

17.3%

4.5%

11.6%

-1.2%

12.7%

9.8%

8.4%

8.4%

-5%

0%

5%

10%

15%

20%

25%

75 77 79 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15

RO

E

7 Years

9 Years

History Suggests Next ROE Peak Will Be in 2016–2017, But Looks

Like 2013 Was Most Recent Peak.

6

Policyholder Surplus, 2006:Q4-2016:Q1

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.

Sources: ISO, a Verisk Analytics company; A.M. Best.

487497

513522518516

505

479

456

437

463

491

511

541531

545559

567559

539550

571568583587

608614624

653662

672674675672664

674676

$400

$450

$500

$550

$600

$650

$700

06:Q

4

07:Q

4

08:Q

4

09:Q

4

10:Q

4

11:Q

4

12:Q

4

13:Q

4

14:Q

4

16:Q

1

Bil

lio

ns

Surplus has not grown significantly in the last 7 quarters

The P/C Insurance Industry Entered 2016 in Very Strong

Financial Condition.

The Industry Now Has $1 of Surplus for Every $0.75 of NPW, Close to the Strongest

Claims-paying Status in its History.

2007:Q3Pre-Crisis Peak

Drop Due to Near-Record 2011 CAT Losses

Investments: The New [Grim] Reality

Investment Performance is a Key Driver of Profitability

Depressed Yields Will Necessarily Influence Underwriting & Pricing

8

Property/Casualty Insurance Industry Investment Income: 2000–20161

38.9

37.1 36.7

38.739.6

49.5

52.3

54.6

51.2

47.1 47.649.2

48.0 47.346.4

47.2

44.0

$30

$40

$50

$60

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

Due to persistently low interest rates, investment income continues to fall.

1 Investment gains consist primarily of interest and stock dividends. 2016 is I.I.I. estimate based on A.M. Best data. Sources: ISO. A.M. Best, Insurance Information Institute.

(Billions)Investment income is

still below its 2007 pre-crisis peak

9

4.85

4.44

4.03

4.59 4.50 4.494.20

3.933.73 3.83 3.68

3.433.65

3.18

0%

1%

2%

3%

4%

5%

6%

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

P/C Insurer Portfolio Yields,2002-2015

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

Even as Prevailing Rates Rise in the Next Few Years, Portfolio Yields Are Unlikely to Rise Quickly,

Since Low Yields of Recent Years Are “Baked In” to Future Returns.

P/C Carrier Yields Have Been Falling for Over a Decade,

Reflecting the Long Downtrend in Prevailing Interest Rates.

10

U.S. Treasury Security Yields:A Long Downward Trend, 1990-2016*

*Monthly, constant maturity, nominal rates, through April 2016.

Sources: Federal Reserve Bank at federalreserve.gov/releases/h15/data.htm; National Bureau of Economic Research (recession dates); Insurance Information Institute.

Bonds Constitute Slightly More Than 2/3 of P/C Industry Investments.Roughly 36% of P/C Bonds Are in 1-5-Year Durations, So They Will Respond to Rising Interest

Rates in Just a Few Years. But Nearly Half of the Bond Portfolio is in 5-Year or Longer Durations, Which Will Take Longer to Rise.

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

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

2-Yr Yield

10-Yr Yield

■ Recession

Despite the Fed’s December 2015 Rate Hike,

Yields Remain Low Though Short-term Yields Have Seen Some Gains.

Yields on 10-year U.S. Treasury Notes Have Been Essentially Below 5% for a Full Decade.

11

Distribution of Bond Maturities,P/C Insurance Industry, 2005-2015

Sources: National Association of Insurance Commissioners’ data, sourced from S&P Global Market Intelligence;Insurance Information Institute.

16.0%

16.0%

15.2%

15.7%

15.6%

16.0%

14.9%

16.6%

16.5%

16.8%

16.3%

28.8%

29.5%

30.0%

32.4%

36.4%

39.5%

41.2%

40.4%

38.8%

37.1%

35.8%

34.1%

34.1%

33.8%

31.2%

29.0%

27.1%

27.3%

27.6%

29.3%

30.8%

33.7%

13.6%

13.1%

12.9%

12.7%

11.9%

11.2%

10.4%

9.8%

9.8%

9.6%

9.0%

7.6%

7.4%

8.1%

8.1%

7.1%

6.2%

6.2%

5.7%

5.7%

5.7%

5.1%

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Two main shifts over these years:From 2007 to 2011-12, from bonds with longer maturities to bonds with shorter maturities.

But beginning in 2013, the reverse.Note, however, that the percentages in bonds with maturities over 10 years continues to drop.

<1 yr 1 – 5 years 5 – 10 years 10-20 20>

1212

New Money vs. Embedded Yields,U.S. Insurers, 1983-2012

p: Preliminary Estimate

Sources: NCCI, Insurance Information Institute.

11.1%

1.7%

9.2%

3.5%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

11%

12%

198

3

198

4

198

5

198

6

198

7

198

8

198

9

199

0

199

1

199

2

199

3

199

4

199

5

199

6

199

7

199

8

199

9

200

0

200

1

200

2

200

3

200

4

200

5

200

6

200

7

200

8

200

9

201

0

201

1

201

2

201

3

201

4

201

5p

Pre-Tax New Money Yield

Pre-Tax Embedded Yield

P/C Carrier Yields Have Been Falling for Over a Decade,

Reflecting the Long Downtrend in Prevailing Interest Rates.

As long as new money rates are below the rates of maturing bonds, the portfolio yield will continue to sink.

13

0.3

0.9

2.3

2.72.9 3.0

1.7

2.1

3.43.7 3.8 3.9

0%

1%

2%

3%

4%

5%

6%

16F 17F 18F 19F 20F 21F 16F 17F 18F 19F 20F 21F

Yie

ld

Interest Rate Forecasts: 2016-2021

Sources: Blue Chip Economic Indicators (8/10 for 2016 and 2017; for 2018-2021 3/16 issue); Insurance Information Institute.

A “Normalization” of Interest Rates is Unlikely Until 2019, More than a Decade After the Onset of the Financial Crisis.

Note how flat the Yield Curve is Expected to be.

3-Month Treasury 10-Year Treasury

The End of the Fed’s QE Program in 2014 and its First Rate Increase in Dec.

2015 Have Yet to Push Longer-term Yields Much Higher

Underwriting Performance

15

Net Premium Growth (All P/C Lines): Annual Change, 1971-2016

Shaded areas denote “hard market” periods

Sources: FRED Economic Data for GDP; A.M. Best (1971-2013), ISO (2014-15); NAIC data sourced from S&P Global Market Intelligence for 2016:Q2, Insurance Information Institute calculations.

-5%

0%

5%

10%

15%

20%

25%

71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11 1416:Q2

NPW Growth

Nominal GDP Growth

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.

2016: 2.6%2015: 3.4%2014: 4.1%2013: 4.4%2012: 4.2%

Outlook

2016F: 4.0%

2017F: 3.8%

1975–78 1984–87 2000–03

16

LOB 2016 2015 % Chg From Year Earlier

Personal Auto Liab 62.5 59.1

Homeowners 46.4 45.3

PhysDam (PA, CA) 46.4 43.4

GL (incl Products) 32.9 32.1

WC 29.5 28.8

Fire & Allied Lines 17.3 18.3

CMP 20.2 20.1

Comm Auto Liab 12.8 12.3

Other 32.9 32.4

Total 300.9 291.8

5.8%

2.3%

7.1%

2.4%

2.5%

-5.5%

0.5%

4.2%

1.5%

3.1%

P/C Direct Written Premium by Line(Billions of Dollars)

Through Q2

Sources: NAIC data from S&P Global Intelligence, Insurance Information Institute.

17

P/C Insurance Industry Combined Ratio, 2001-2016:Q2*

Q2 2016 Estimate is Preliminary

*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.

Sources: A.M. Best; ISO, a Verisk Analytics company; 2010-2014 is from A.M. Best P&C Review and Preview, February 16, 2016; 2015from I.I.I/PCI/ISO; 2016 Estimate from I.I.I. based on S&P Global Market Intelligence data.

107.5

100.1

98.4

100.8

92.6

95.7

101

99.3

101.1

106.5

102.5

96.4 97.097.8

99.8

90

100

110

120

02 03 04 05 06 07 08 09 10 11 12 13 14 15 16:Q2

As Recently as 2002, Insurers Paid Out

Nearly $1.08 for Every $1 in Earned Premium.

Best Combined

Ratio Since 1949 (87.6)

Lower CAT

Losses

3 Consecutive Years of U/W Profits; 1st time

since 1971-73

LotsaSmall CATs, Auto

18

AY vs. CY Combined Ratio, (Excl. Guaranty Lines) 1996-2015

2015 Figures Preliminary. Sources: NAIC data from S&P Global Intelligence, Insurance Information Institute.

10

6.2

10

2.1

10

6.3

10

8.8

111

.2

11

6.9

10

8.4

10

1.0

99

.1

10

1.5

93

.3

94

.8

10

1.1

99

.3

10

1.0

10

6.5

10

2.4

96

.9

97

.6

98

.3

108.5

105.8

108.8109.5

110.8

113.2

102.2

97.396.4

101.0

95.097.1

104.9

102.7

104.2

110.0

105.4

99.898.5

100.1

90

95

100

105

110

115

120

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

Co

mb

ine

d R

ati

o

Calendar Year

Accident Year

Three Consecutive Years of Deteriorating Combined Ratios, Despite Light Cat Losses. AY2015 Above 100.

Higher AY → Favorable DOP

Hurricane IkeTuscaloosa, Joplin

Tornadoes

19

Personal Lines Combined Ratio, 1996-2015

2015 Figures Preliminary. Sources: NAIC data from S&P Global Intelligence, Insurance Information Institute.

10

5.1

99

.9

10

2.9

10

4.6

111

.7

11

0.9

10

5.3

98

.5

94

.3

96

.4

94

.1

97

.6

10

4.7

10

2.6

10

2.7

10

7.8

10

2.6

98

.3

99

.5

10

0.7

109.4

104.3

106.5107.1

113.3

111.0

105.3

100.2

96.999.0

97.2

100.1

107.0

105.8

106.1

111.7

106.5

101.4

99.7

102.7

90

100

110

120

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

Co

mb

ine

d R

ati

o

Calendar Year

Accident Year

Lack of Catastrophes Let Personal Lines Writers Post Underwriting Profit Two Years In a Row. CY15>100, Despite Lack of Cats.

Higher AY → Favorable DOP

2005: Last Year of Adverse Development

Tuscaloosa, Joplin Tornadoes

20

Commercial Lines Combined Ratio, 1996-2015

2015 Figures Preliminary. Sources: NAIC data from S&P Global Intelligence, Insurance Information Institute.

10

7.8

10

4.8

111

.3

11

3.6

11

3.0

11

9.8

11

0.1

10

2.9

10

2.4

10

0.9

92

.1

92

.8

97

.4

97

.8

10

0.8

10

4.4

10

3.8

96

.8

97

.3

96

.6

108.3108.5

111.8 112.6110.0

112.9

99.1

94.6 95.4 97.4

93.095.4

103.0

100.4

103.6

107.4105.4

99.198.1 97.8

85

95

105

115

125

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

Co

mb

ine

d R

ati

o

Calendar Year

Accident Year

Low Cat Losses Contribute to Favorable Combined Ratios.

10 Consecutive Years of Favorable Development.

21

Development on Prior, 1996-2015

2015 Figures Preliminary. Sources: NAIC data from S&P Global Intelligence, Insurance Information Institute.

-6.4

-9.1

-9.9

-4.6

0.3

11

.1

22

.3

14

.1

10

.5

0.6

-7.0

-8.3

-1.9

-18

.5

-10

.5

-12

.7

-12

.2

-14

.5

-9.4

-7.3

-2.5%

-3.4%

-3.7%

-1.7%

0.1%

3.6%

6.4%

3.6%

2.5%

0.1%

-1.6% -1.9%

-0.4%

-4.3%

-2.5%-2.9%

-2.7%

-3.1%

-1.9%-1.4%

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

-30

-20

-10

0

10

20

30

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

DoP

(% o

f N

EP

)

DoP

($ b

illio

ns)

All Year DoP

Dop/NEP

Reserve Releases Keep Getting Smaller. 2015 Affected by a Single Company’s $3B Reserve Hit.

10 Consecutive Years of Favorable Development.

22

CY Development on Prior by LOB

2015 Figures Preliminary. Sources: NAIC data from S&P Global Intelligence, Insurance Information Institute.

152 205

-840

40

-863

84399

-883

-1,231

-115

1,655

-505 -671-773

3

1,217

604 516

-271

-2,353

-35%

-25%

-15%

-5%

5%

15%

25%

-3,000

-2,000

-1,000

0

1,000

2,000

3,000

CommAutoLiab

CMP HO/FO MPL(C-M)

OL(C-M)

OL(Occ)

Products PPAL Re Liab WC

% o

f 2

01

5 N

EP

Do

P($

mil

lio

ns)

2014 DoP 2015 DoP 2015 DoP/NEP

Several Liability Lines (Auto, GL, Products) Had Reserve Spikes. WC Was an Exception.

23

-1.8

1.3

-3.7

-8.9

-5.3

-0.3

1.4

5.0

2.3 2.22.6 2.4

0.1

2.5

1.3

4.1

2.0

1.3

3.1

0.4

2.7

1.8

4.5

3.5

-0.9

4.64.3

2.1

0.6

3.9

2.0

0.9 0.81.2

3.5

2.3 2.2 2.3 2.2 2.1

-10%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

08:1Q 09:1Q 10:1Q 11:1Q 12:1Q 13:1Q 14:1Q 15:1Q 16:1Q 17:1Q

Rea

l G

DP

Gro

wth

“GDP now” estimate as

of August 12

U.S. Real GDP Growth,* Quarterly

*Estimates/Forecasts (gold bars) from Blue Chip Economic Indicators.

Sources: U.S. Department of Commerce, Blue Chip Economic Indicators 8/10; Insurance Information Institute.

Demand for Insurance Should Increase Slowly in 2016 as GDP Growth Continues at a Steady, Albeit Moderate Pace

and Gradually Benefits the Economy Broadly

The Q4:2008 Decline was the Steepest Since the Q1:1982 Drop of 6.8%.

For Some (Currently Unknown) Reason, in the Post-recession Period, Frequently Q1 has Been a

Weak Quarter

Recession Began in Dec. 2007 and

Ended in June 2009

24

P/C Direct Incurred Loss Ratio by LOB

Through Q2

Sources: NAIC data from S&P Global Intelligence, Insurance Information Institute.

LOB 2016 2015 Chg From Year Earlier

Personal Auto Liab 72 68

Homeowners 56 55

PhysDam (PA, CA) 67 64

GL (incl Products) 52 51

WC 54 59

Fire & Allied Lines 56 55

CMP 51 48

Comm Auto Liab 64 62

Other 44 42

Total 59 57

4

1

3

1

(5)

1

3

3

2

2

Positive Number = Bad News

Commercial Rates*

Steady Going

*These Publicly Available Estimates May Differ SubstantiallyFrom Events In Individual States and Markets

26

Commercial Lines Rate Change by Quarter(vs. Year Earlier)

Sources: Willis Towers Watson Commercial Lines Insurance Pricing Survey, Insurance Information Institute.

Second Quarter: <1% Decreases: WC, Property, D&O. ‘Meaningful’ Increases: Commercial Auto – similar to prior two quarters

1312

9

5

3

0

-1 -1-2 -2 -2 -2

-1 -1

-3-4

-5 -5-6 -6

-5-4

-3

-1

10 0

-1 -1 -1 -1

12 2

3

56 6

7 76 6

54

3 32 2

1 1 1<1<1

-10%

-5%

0%

5%

10%

15%

20%

2003:Q2 2004:Q4 2006:Q2 2007:Q4 2009:Q2 2010:Q4 2012:Q2 2013:Q4 2015:Q2

22 Consecutive Quarters ofRate Increases

27

Commercial Lines Rate Change by Month(vs. Year Earlier)

Sources: MarketScout, Insurance Information Institute.

Rates Are as Stable as They’ve Been in 15 Years. Modest Declines This Year but That May Be Ebbing. August: -1%

-20%

-10%

0%

10%

20%

30%

40%

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

Jul-0233%

Feb-050%

Dec-07-16%

Sep-135%

79 Months of Rates < 0%37 Months of Rates > 0%

3 Straight Months: -4%; Recent Months -1%

Not Much of a Hard Market, by Historic Standards

Catastrophes

29

U.S. Insured Catastrophe Losses

*Estimate through first quarter.

Note: 2001 figure includes $20.3B for 9/11 losses reported through 12/31/01 ($25.9B 2011 dollars). Includes only business and personal property claims, business interruption and auto claims. Non-prop/BI losses = $12.2B ($15.6B in 2011 dollars).

Sources: Property Claims Service, a Verisk Analytics business; Insurance Information Institute.

$14.4

$5.0$8.2

$38.9

$9.1

$27.2

$13.0$11.3

$3.9

$14.8$11.9

$6.3

$35.8

$7.8

$16.8

$34.7

$75.7

$10.9$7.7

$30.1

$11.8$14.9

$34.6$36.1

$13.1

$15.5$15.0$13.5

$0

$10

$20

$30

$40

$50

$60

$70

$80

$90

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*

Billi

on

s (

$2

01

5)

Thru Q2: 20% Above

10-Yr Average

2013/14/15 Were Welcome Respites from 2011/12, Which WereAmong the Costliest Years for Insured Disaster Losses in U.S. History.

Longer-term Trend is for More – Not Fewer – Costly Events.

2012 was the 3rd Most Expensive Year Ever for

Insured Cat Losses.

30

12/01/09 - 9pm

Combined Ratio Points Associated with Catastrophe Losses: 1960 – 2015

*2010s represent 2010-2015.

Notes: Private carrier losses only. Excludes loss adjustment expenses and reinsurance reinstatement premiums. Figures are adjusted for losses ultimately paid by foreign insurers and reinsurers.

Source: ISO (1960-2009); A.M. Best (2010-16:Q2); Insurance Information Institute.

0.8 1.1

1.1

0.1

0.9

3.6

8.1

2.7

1.6

5.0

2.6

4.6

9.6

8.0

3.5 4

.03.5

5.5

0

2

4

6

8

10

12

19

60

19

62

19

64

19

66

19

68

19

70

19

72

19

74

19

76

19

78

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

00

20

02

20

04

20

06

20

08

20

10

20

12

20

14

20

16:Q

2

The Catastrophe Loss Component of Private Insurer Losses Has Increased Sharply in Recent Decades

Avg. CAT Loss Component of theCombined Ratio

by Decade

1960s: 1.04 1970s: 0.85 1980s: 1.31 1990s: 3.39 2000s: 3.52 2010s: 5.46*

Combined Ratio Points Catastrophe losses as a share of

premium reached a record high in 2011

31

7,600

550

440

410

360

340

290

280

260

250

- 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000

Texas

Nebraska

Missouri

Arkansas

Illinois

Virginia

Kansas

Indiana

Montana

New York

Tough Year for Texas –flooding and four major

hailstorms!

States Hit by Cats, First Half 2016(Millions of Dollars)

Source: Property Claim Services.

Auto Insurance

Rising Frequency, Severity Pinching the Largest P/C Line

33

Net Combined Ratio, 2005-2015

Source: National Association of Insurance Commissioners data, sourced from S&P Global Market Intelligence;Insurance Information Institute.

Loss Ratios Have Been Rising for a Decade. 2015 Return on Net Worth is Likely Close to Zero or Negative.

92.1% 92.5%

94.3%

96.8%

99.5%

98.1%

103.6%

107.0% 106.9%

103.4%

108.8%

95.1%95.6%

98.3%

100.2%101.3% 101.0%

102.0% 102.1%101.6%

102.5%

104.6%

90%

95%

100%

105%

110%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Commercial Personal

34

Why Personal Auto Loss Ratios are Rising: Severity & Frequency by Coverage, 2016 vs. 2015

*Four quarters ending in March.

Source: ISO, a Verisk Analytics company; Insurance Information Institute.

Across All Personal Coverage Types (Except Comprehensive) in 2015, Frequency and Severity Rose. This Pattern is Continuing in 2016.

4.3%

6.8%

4.6%

5.6%

0.0%

2.2% 2.3%

8.5%

0.8%

0.0%0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

Bodily Injury Property DamageLiability

PIP Collision Comprehensive

Severity Frequency

Annual Change, 2016 Over 2015*

Claim Trends by Coverage

Focus on Collision

36

Collision Claims: Frequency TrendingHigher in 2015

Annual Change, 2005 through 2015

Source: ISO, a Verisk Analytics company; Insurance Information Institute.

For a Long Time, Claim Frequency Was Falling, But Since 2010 This Trend Seems to Have Reversed.

-1.8%

-3.6%

2.5%

-2.4%

-1.4%

-0.5%

0.9%

-1.8%

2.4%

4.4%

0.8%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

37

Collision Claims: Severity Trending Higher in 2009-2015

Annual Change, 2005 through 2015

Source: ISO, a Verisk Analytics company; Insurance Information Institute.

The Great Recession and High Fuel Prices Helped to Temper Claim Severity, But These forces Have Clearly Reversed,

Consistent with Experience from Past Recoveries.

3.9%

3.1%

0.1% 0.5%

-2.3%

-0.1%

2.8%

1.3%

4.1%

1.3%

5.7%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

What’s Driving These Trends?

Frequency; Severity

39

America is Driving More Again: 2000-2016Percent Change, Miles Driven*

*2000-2015: Moving 12-month total vs. prior year. 2016 data through May 2016, the latest available, vs. May 2015.Sources: Federal Highway Administration; National Bureau of Economic Research (recession dates); Insurance Information Institute.

2.5%

1.8%2.1%

1.2%

2.5%

0.8% 0.8%0.6%

-1.8%

-0.7%

0.4%

-0.5%

0.6% 0.6%

1.3%

3.4% 3.4%

2000 2002 2004 2006 2008 2010 2012 2014 2016

-2.5%

-1.5%

-0.5%

0.5%

1.5%

2.5%

3.5%

Fastest Growth Since Late

1990s

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

40

More Miles Driven=> More Collisions, 2006-2016Billions of Miles Driven in Prior Year

Sources: Federal Highway Administration; Rolling four-quarter average frequency from ISO, a Verisk Analytics company; Insurance Institute for Highway Safety; Insurance Information Institute.

The More Miles People Drive, the More Likely They are to Get in an Accident, Helping Drive Claim Frequency Higher.

5.5

5.6

5.7

5.8

5.9

6.0

2,800

2,850

2,900

2,950

3,000

3,050

3,100

3,150

3,200

06

:Q1

06

:Q3

07

:Q1

07

:Q3

08

:Q1

08

:Q3

09

:Q1

09

:Q3

10

:Q1

10

:Q3

11:Q

1

11

:Q3

12

:Q1

12

:Q3

13

:Q1

13

:Q3

14

:Q1

14

:Q3

15

:Q1

15

:Q3

16

:Q1

Miles Driven (left axis)

Collision Claim Frequency (right axis)

Overall Collision Claims Per 100 Insured Vehicles

Recession

41

Why Are People Driving More Miles?Cheap Gas?Billions of Miles Driven in Prior Year

Sources: Federal Highway Administration; Energy Information Administration; Insurance Institute for Highway Safety; Insurance Information Institute.

Gas Prices Don’t Seem Correlated With Miles Driven.

$1.5

$2.0

$2.5

$3.0

$3.5

$4.0

$4.5

2,850

2,900

2,950

3,000

3,050

3,100

3,150

06

:Q1

06:Q

3

07

:Q1

07

:Q3

08

:Q1

08

:Q3

09

:Q1

09

:Q3

10

:Q1

10

:Q3

11

:Q1

11

:Q3

12

:Q1

12

:Q3

13

:Q1

13

:Q3

14

:Q1

14

:Q3

15

:Q1

15

:Q3

Miles Driven (left axis) Gas Prices (right axis)

Average Price Per Gallon

Recession

42

Why Are People Driving More Miles?Jobs?Billions of Miles Driven in Prior Year

Sources: Federal Highway Administration; Seasonally Adjusted Employed from Bureau of Labor Statistics; Insurance Institute for Highway Safety; Insurance Information Institute.

People Drive to and from Work and Drive to Entertainment. Out of Work, They Curtail Their Movement.

120

125

130

135

140

145

2,850

2,900

2,950

3,000

3,050

3,100

3,150

06

:Q1

06:Q

3

07

:Q1

07

:Q3

08

:Q1

08

:Q3

09

:Q1

09

:Q3

10

:Q1

10

:Q3

11

:Q1

11

:Q3

12

:Q1

12

:Q3

13

:Q1

13

:Q3

14

:Q1

14

:Q3

15

:Q1

15

:Q3

Miles Driven (left axis) # Employed (right axis)

Millions Employed

Recession

43

Comparing Gas Prices, Employment onCollision Frequency Through 2015

Sources: Seasonally Adjusted Employed from Bureau of Labor Statistics; Energy Information Administration; Rolling Four-Qtr Avg. Frequency from Insurance Services Office; Insurance Information Institute.

Gas Price vs.

Collision Frequency

Number Employed vs.

Collision Frequency

5.50

5.55

5.60

5.65

5.70

5.75

5.80

5.85

5.90

5.95

6.00

1.75 2.75 3.75

Co

llis

ion

Fre

qu

en

cy

Gasoline Price per Gallon

5.50

5.55

5.60

5.65

5.70

5.75

5.80

5.85

5.90

5.95

6.00

135 140 145 150 155

Co

llis

on

Fre

qu

en

cy

Millions Employed

44

More People Working and Driving=> More Collisions, 2006-2016Number Employed, Millions

Sources: Seasonally Adjusted Employed from Bureau of Labor Statistics; Rolling four-quarter average frequency from ISO, a VeriskAnalytics company; 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.

5.5

5.6

5.7

5.8

5.9

6.0

120

125

130

135

140

145

06

:Q1

06

:Q3

07

:Q1

07

:Q3

08

:Q1

08

:Q3

09

:Q1

09

:Q3

10

:Q1

10

:Q3

11:Q

1

11

:Q3

12

:Q1

12

:Q3

13

:Q1

13

:Q3

14

:Q1

14

:Q3

15

:Q1

15

:Q3

16

:Q1

Number Employed (left axis)

Collision Claim Frequency (right axis)

Overall Collision Claims Per 100 Insured Vehicles

Recession

45

Severity: Driving Fatalities are RisingAnnual Change in Motor Vehicle Deaths

Sources: National Safety Council, Insurance Information Institute.

-7.0%

-5.9%

2.2%

1.5%2.0%

0.7%

-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%

-12%

-10%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

Driving Has Been Getting Safer for Decades, But Recent Trend is Discouraging—38,300 Deaths in 2015.

Seatbelt Use Rose to 62% of Drivers, From 49% in ‘90

Big Drop-off Due to the Great Recession

On the Horizon

Sharing Economy and Disruption

47

What Is A Value Chain?Example: Local Newspapers

Printing PressGather

Information (News, Ads)

Create Product

(Publish the Newspaper)

Distribute Product

(Deliver the Newspaper)

Improve World

Provide Information to Local Audience

This Industry Was Radically Disrupted by the Internet. Its Barriers to Entry Were Destroyed. Is Insurance Next?

48

62

1852

389

6

52

30

0

10

20

30

40

50

60

0

200

400

600

800

1000

1200

1400

1600

1800

2000

Investment Deals

12/01/09 - 9pmeSlide – P6466 – The Financial Crisis and the Future of the P/C

Investment ($ Millions)

SOURCES: CB Insights, Insurance Information Institute.

Insurance Technology Financing –Change Is Coming

Deals

Investment In Insurance Tech Is Rising. Number of Deals Reached A Record in First Quarter.

49

Insurance Tech Activity by Area of Interest, 2013 – 2016:Q1

38 30 51 68

6270

4932

0

10

20

30

40

50

60

70

80

90

100

2013 2014 2015 2016:Q1Non-Health Insurance Tech Health Insurance Tech

Silicon Valley, Venture Capitalists Have Insurance Industry in Their Sights. Most Will Fail. Some Will Succeed.

Source: CB Insights at https://www.cbinsights.com/blog/insurance-tech-overview-q1-2016/; Insurance Information Institute.

(Percent)

With the ACA in the rear view window, non-health

insurance tech accounts for the majority of investment

50

The (Re)Insurance Value ChainWhere Could Disruption Lie?

Brains + Bank

Account

Create Policy/ Treaty

Market Policy/ Treaty

Write Risk

Price Risk

Perform Loss

Control

Settle Claims

Improve World

Protecting People & Organizations

Most Links in the Value Chain Have the Potential to Be Disrupted in Next 10 Years.

51

Alternative CapitalPotentially Disrupting the Bank Account

Source: Aon Benfield Analytics; Insurance Information Institute.

17 22 19 22 24 28 39 50 64 72 73

368 388321

378447 428

466490

511 493 507

385410

340

400

470 455

505540

575 565 580

0

100

200

300

400

500

600

700

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Q1-16

Glo

ba

l R

ein

su

ran

ce

Ca

pita

l

Alternative Capital Traditional Capital

(Billions of USD)

Alternative capacity has grown 263% since 2008. It has more than tripled in the past six years.

52

25

8

4

36

0

5

10

15

20

25

30

35

40

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Q1-16

Cat Bonds Sidecars ILWs Collateralized Re

(Billions of USD)

Alternative CapitalPotentially Disrupting the Bank Account

Source: Aon Benfield Analytics; Insurance Information Institute.

Collateralized Reinsurance and Catastrophe Bonds Currently Dominate the Alternative Capital Market.

53

The InternetWill It Disrupt Marketing?

SOURCES: The New Age of Insurance Aggregators, http://insurancethoughtleadership.com/the-new-age-of-insurance-aggregators/; Insurance Information Institute November 2015 Pulse Survey.

But Customers Still Like Agents Lead Generators

InsWeb, NetQuote, Insurance.com

Site allows comparison shopping, sells lead to insurer

Call Center Agencies

SelectQuote, Goji

Call center employs agents

Digital agencies

Esurance, Policy Genius

Quote and buy online

Did You Compare Prices When Your Auto Policy Was Up for Renewal?

50%

39%

37%

69%

29%

1%

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

Talk to Agent

Online

By Phone

Any Method

None of These

Don't Know

5454

Pricing Disruptor: The Fragmented Risk

The Insurance Contract Is Being Split

into Tiny Pieces.

By-peril HO insurance – Rate Water, Theft,

Liability Risk Separately

The Sharing/“On-Demand” Economy –

Personal Exposures Become Commercial

Exposures, Then Switch Back

Pay By Mile Insurance – Exposure Basis

for Auto – Vehicle-Mile Replaces Vehicle-

Year

Expect More As

Computers Get Stronger

Data Storage Gets Cheaper

Information Collection Grows

5555

The Internet of Things

Gathering Big Data Affects

Underwriting

Pricing

Monitoring Could Affect

Loss Control

Pricing?

56

As For The Future…

Image sources, clockwise: Nest, Jawbone, Automatic, Lumo, Apple, PSFK

IoT Could Disrupt UW, Claims, Loss Control

57

Peer-to-Peer (P2P) InsuranceTaking on the Entire Value Chain

CEO Daniel Schreiber

The Business Model

Resembles Mutuals/Reciprocals

20% of Premium to Expenses, 80% to Cover Risk.

Risk Pool for Each Charity

Leftover Pool Money Goes to Charity.

May Deter Fraud – You Wouldn’t Cheat Your Favorite Charity!

Our Chief Behavioral Officer, Professor Dan Ariely, says that “If you tried to create a system to bring out the worst in humans, it would look a lot like the insurance of today.”

Source: “UberX-ing Insurance : Is Peer-to-Peer Insurance Viable?”,

presentation by Jay Sarzen, Aite Group at Drinker Biddle Insurance

Conference, June 21, 2016; Financial Times; www.lemonade.com.

58

Lemonade’s P2P ModelExample: Renters’ Insurance (HO-4)

59

Lemonade’s P2P Model

Who Holds the Risk?

Captive? Front?

How Are Charitable Pools Separated?

Segregated Cell Captive?

Who Gets the Float?

Insurer, Reinsurer or Charity?

Who Gets the Tax Deduction (Worth More Than the Float)?

Questions

60

Summary

The industry is in good financial shape with several years of modest profits.

Interest rates look like they’ll stay low

Recent years have had modest cats; U.S. This year hurt by severe weather

Auto costs are rising (both frequency and severity)

Disruption provides opportunities and challenges throughout the value chain

Thank you for your timeand your attention!www.iii.org

Download at www.iii.org/presentations