2013 valen powerpoint template - amazon s3 · 2016-05-16 · insurance technology is hot © 2016...

Predictive Analytics May 16, 2016 ǀ AAM Investment Conference

Dax Craig, CEO

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Software Company…or Insurance Agency?

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Insurance technology is hot

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$2.65B Insurance Tech

Investment 2015

$85M 2010

But, it was hot in the dot com era too

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1990’s 2016

CHANNELPOINT

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Meeting Expectations NOT

Sources: Comscore 2013 online auto insurance shopping report Google customer survey and focus group feedback

Shopping for auto insurance is generally unpleasant and time consuming.

Painful: “Somewhere between a root canal and watching ....”

I don’t like having to repeat 20 steps each time.

What happens today when consumers are dissatisfied?

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Innovators see an opportunity to make the world better, faster and cheaper for

customers…

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…and they go after the incumbent’s market

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And here’s how it goes…

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Break-through

New Thinking Catalyst

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Break-through

New Thinking Catalyst

Untapped credit market

DATA Market

segmentation

CUSTOMER ANALYTICS

Information-based Strategy

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Break-through

New Thinking Catalyst

Nonstandard auto

DATA Predictive analytics

CUSTOMER ANALYTICS

Pricing algorithm

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in pricing

leads to

Predictive analytics

adverse selection for competitors

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Results: Top 10 now have 71% Market Share

50% 55%

60%

71%

1980 1990 2000 2014

Personal Auto Top 10 Market Share

Source: Insurance Information Institute

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Results: Market Share Shakeup in Commercial

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Break-through

New Thinking Catalyst

Interest rate

P2P Lending Securitization

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Why?

Why?

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Calls 2016 an Innovation Crossroads

for Insurance

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The need to make up low investment performance with underwriting profit is a

tremendous issue facing the industry

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At the same time

analytically-

driven insurers

are winning the

market share

game

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And insurance tech disruption is hitting an all time high

How Does Predictive Analytics Help Insurers Win?

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Predictive Analytics = tool to combine with human expertise

No predictions are 100% Facilitate evidenced-

based decisions Know your customers,

know what you insure

© 2016 Valen Analytics, Inc.

-

5,000,000

10,000,000

15,000,000

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25,000,000

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0%

50%

100%

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250%

1 2 3 4 5 6 7 8 9 10Risk Score

Written Premium Underwriter

Art Only = Good Results A

ctua

l Los

s R

atio

Writ

ten

Pre

miu

m

Underwriter only lift = 50%

75%

125%

Good Risk Quality Bad

© 2016 Valen Analytics, Inc.

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0%

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1 2 3 4 5 6 7 8 9 10Good Risk Quality Bad

Written Premium Predictive Model

Science Only = Better Results A

ctua

l Los

s R

atio

Writ

ten

Pre

miu

m

Model only lift = 125%

50%

175%

© 2016 Valen Analytics, Inc.

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0%

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1 2 3 4 5 6 7 8 9 10

Good Risk Quality Bad Written Premium Underwriter / Model Combination

Art + Science = Best Results A

ctua

l Los

s R

atio

Writ

ten

Pre

miu

m

Underwriter + Model lift = 185%

25%

210%

Early Wins with Analytics: LR improvement

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79%

75%

57% 55%

48%

69% 66%

61% 59%

54%

2011 2012 2013 2014 2015

Accident Year Net Incurred Loss Ratio

Industry Avg Compared to Valen Clients

Source: SNL (Annual Statement Data)

Valen Customer Avg Industry Average

Loss

Rat

io

2x difference

Early Wins with Analytics: Premium Growth

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20%

47%

63%

82%

8% 15%

21% 26%

2011 2012 2013 2014 2015

Direct Written Premium Growth

Industry Avg Compared to Valen Clients

Source: SNL (Annual Statement Data)

Valen Clients Industry

DW

P G

row

th

3x difference

Key Takeaways

Customers demanding change: make or break time for

insurers

Data analytics is the engine of disruption and innovation

– across industries

Competitive advantage comes from combining analytics,

expertise and strategy

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Valen.com 800-280-3304

1730 Blake St., Suite 300 Denver, CO 80202

Dax Craig Dax.Craig@valen.com linkedin.com/in/daxcraig

© 2016 Valen Analytics, Inc.