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© Valen Analytics 2018 © Valen Analytics 20181 2018 Outlook Report: Property & Casualty Insurance www.valen.com

2018 OUTLOOKMARKET DYNAMICS IMPACTING PROPERTY & CASUALTY INSURANCE

© Valen Analytics 20182 2018 Outlook Report: Property & Casualty Insurance www.valen.com

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Over the past two years, we’ve reported on an important crossroads moment for the insurance industry. There’s been a wave of big announcements from Google, Overstock, and others about entering – and then exiting insurance. Many in the industry saw this as reinforcement that insurance is too complex, too regulated, and too capital intensive to penetrate from the outside.

Several analysts and other tech experts, Valen Analytics included, warned against that line of thinking. Primarily because the innovation economy is taking hold across all industries, and even if a few early efforts don’t pan out, disruption and innovation in insurance are here to stay. The rise to $1B in InsurTech investments in Q2 2017 is just one indicator. What we’ve seen since is an industry coming to terms with the reality that innovation is the new norm.

Now, a fundamental shift is playing out with polarizing viewpoints shaping the trajectory of the market. A persistent majority focuses on incremental improvements to existing operations, believing there will be plenty of time to react to any game-changing pivots. A growing minority sees an opportunity to disintermediate and build a new insurance landscape, fueled by technology innovation and a new paradigm in customer engagement. Where this heads and how quickly changes come is anyone’s guess, but there’s no doubt that different stakeholders in this industry are actively working to impact the future.

Insurance is facing a fundamental INDUSTRY DIVIDEInsurance is facing a fundamental INDUSTRY DIVIDE

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Source: CB Insights, Towers Watson

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http://www.valen.com


Viewpoints & battlegrounds4

5 Underwriting analytics trends

18 Sources & resources

INSIDE THIS REPORT

6 Customers & technologyThe customer dilemmaTechnology strategyInsurers rate their use of tech and cultureThe groupthink problem

17 Top considerations

12 Next gen performance metricsShifting market share in commercial linesRisk quality and price monitoringRisk quality and risk selectionPredicted/embedded profit


Analytically-driven insurers are expanding their use of data science to address inherent inefficiencies in the traditional cost structure. They are focused on better claims handling, improving the customer experience, and creating sustainable profits. These insurers have adopted new ways to increase profitability, create more relevant engagement with policyholders, and proactively identify issues throughout their book of business. These are the insurers who believe the future of insurance is being defined at this moment.

Conversely, other insurers believe innovation is an over-hyped fad, and do not think the fundamentals of insurance are experiencing any near-term threats. These insurers will continue to compete using traditional principles, waiting out the current wave of innovation as their winning long-term strategy.

Viewpoints defining innovation & competition

Technology

Performance

Competitive Battlegrounds

The Customer



Analytics trends inform the state of the industry

TOP 3

The divergence in viewpoints is particularly obvious when looking at the disparity between insurers who’ve adopted predictive analytics (arguably one of the most mature and familiar applications of insurance innovation) and those who have not. Valen’s annual underwriting analytics surveys from 2015 – 2017 show areas where the industry has remained consistent, while also demonstrating an enduring divide between analytics adopters and naysayers.

Using Predictive Analytics in Underwriting

2015

2016

2017

Yes

56%

No

66%

62%

44%

34%

38%61%

Average 3-year trend

Better Risk Assessment

More Accurate Pricing

84%

82%

72%

89%

72%

69%

Insurer Goals for Underwriting Analytics

2016 2017

Say Underwriters and Actuaries Remain at Odds Over Price

48%: Underwriters dismiss data for judgment41%: Actuarial rates are too high

32%: Underwriters are too optimistic/aggressive

28%: Actuarial rates are too conservative

Average 3-year trend

62%

Protect Against Adverse Selection

Source: Valen Analytics Underwriting Surveys 2015-2017


There is an increasing push and pull on insurers to rethink customer relationships, the customer experience, and how to best leverage technology.

Customers & Technology



Customer experience is at the heart of disruption

Multiple surveys within the industry show insurance executives recognize a lack of skills and experience in leading innovation within their companies. There are long standing cultural norms – like being risk averse and conservative - that make it difficult to drive change management initiatives. We see this playing out in at least three areas of note.

Today’s customer demands direct engagement and a modern experience, even if an insurer works predominantly through an agency force. Insurers who create a relationship with their paying customers will secure a leading role in transforming insurance and maintaining relevance for the long term.

NAIC and DOI consumer complaints consistently rank the claims experience as the main source of friction. Consumers feel ripped off when they pay for a service that makes them jump through hoops to prove they need it. Fraud prevention is clearly important, but does it come at a higher cost of customer dissatisfaction? Technology-based claims solutions are emerging to fix the industry’s number one sore spot.

While automation has gained some traction in personal lines, commercial insurers are behind, especially for the small commercial market. Many insurers are stuck not knowing how to cater to agents while moving into this market. Commissions are too low to be interesting or justify extensive human touch, and automation is the logical and viable answer. To succeed, it requires advanced processing technologies and analytics.

Is your customer the agent or the policyholder?

Fraud is less than 10% of P/C claims. Are we preventing it at the expense of customer satisfaction?

What is the opportunity cost of legacy tech, distribution and operational processes?

CustomerEngagement

Source: Coalition Against Insurance Fraud


Strategic goals driving technology

CAPITALLower investment returns drive the need to deploy capital for both primary insurers and reinsurers more effectively. It forces the industry to evaluate the flow of capital, which is clunky with multiple intermediaries between the source of capital and the paying customer.

Insurtech investment has surpassed $5.6B since 2011, with new technologies like AI and IoT spearheading the growth. While still a small percentage overall relative to a reinsurer’s balance sheet, company investments in InsurTech are increasingly being led by reinsurance. According to JLT Re and CB Insights, reinsurance investment in InsurTech has grown from a meager 5% of deals in 2012 to over 55% as of 2016. This should be a wake-up call for insurers, as this growth is an indicator of a shifting incumbent insurance environment.

CLAIMS & OPERATIONSThe expense load of today’s insurance operations is relatively high at 30-35%. According to the Insurance Information Institute, P/C insurers continue to be hit by price increases affecting claims costs (e.g., medical, auto, residential construction), that outpace overall inflation trends. This rising expense load begs for better efficiency to reduce costs and improve the customer experience.

UNDERWRITINGWith price competition at a high point and a large percentage of insurers choosing not to adopt analytics, it’s not surprising that A.M. Best and others point to continued challenges for commercial lines. High agency commissions at 12-15% keep the $100B small commercial market elusive. The entire quote to bind process can take 30-60 days, and in studies from Valen’s data consortium, we’ve shown that only 20% of what is quoted is bound.

Inherent inefficiencies drive technology investments THE DOMINANCE OF AMAZONPerhaps the best example of technology strategy in action today is Amazon. In 2016, Amazon’s total patents numbered 1,662, a 46% increase from the previous year.

• Low-profit expectations keep the cost of capital low. They enter new industries quickly with a dominant position play.

• Whole Foods acquisition makes Amazon a top 10 retailer, dominating growth in grocery.

• 43% of U.S. online retail sales, and 53% of e-commerce growth.

• 70M Amazon Prime members in 2017.

• Impressive “side businesses”.

• Ad division contributes 20% of profits. Bigger than Snapchat, half the size of Twitter.

• Content division spends $4.5B, compared to HBO’s $2.5B.

Sources: Business Insider, Scott Galloway, Stores.org



Insurers rate their own tech savvy

There are seemingly endless opinions about how equipped insurers are to be innovative and technology-driven. We decided to launch an annual survey allowing insurers to assess their organizations’ appetite and ability to foster innovation.

Agree/Disagree Strongly

Agree Agree Neutral Disagree

Our executive team doesn’t shy away from implementing new tools, even if it means disrupting current processes significantly.

23% 17%40% 20%

6%29% 6%32% 26%

Our current IT backlog makes it difficult to engage with new technology vendors.

6%29% 6%32% 26%

When it comes to enterprise software or technology, we are more likely to stick with a brand/company we know because people are already familiar with how it works and don’t have to learn new functionality.

Source: Valen Analytics Innovation Continuum Survey 2017

55%Somewhat or

highly resistant

Reaction from front line employees when new technologies are rolled out.

New functionality and features that will make us more efficient and effective in the long run is a top consideration when making a new technology purchase.

79%

Strongly Disagree


Insurers rate their own tech culture

31%

44%

16%

9% We have a high tolerance fortaking limited risks andunderstanding the potentialreward.

We cautiously test new ideas. At the worst we’ll learn what NOT to do in the future.

We are very careful. Only when anidea has been vetted verythoroughly will we want to pursueit.

We leave the risk-taking to others.We think the fundamentals ofinsurance are stable.

When it comes to taking risks to pursue an idea, my organization is best described as:

Sources: Valen Analytics Innovation Continuum and Underwriting Analytics Surveys 2017

When a new, innovative idea comes from front-line employees or middle managers, how would you characterize its likelihood of being put into practice?

Very likely

Somewhat likely

Unlikely Very unlikely

I don’t know

Say it is very or moderately difficult to attract data and analytics talent. 75%

#1 reason is geography. It’s difficult to find suitable candidates in their local area.



The need to watch out for groupthink

Groupthink is the tendency to seek consensus instead of fostering dissent. It’s the practice of thinking or making decisions as a group in a way that discourages creativity or individual responsibility. As technology investments grow from new entrants and incumbents, insurers are wise to remain open and proactive to the changing marketplace as it evolves.

WHO SAID IT FIRST?Standing on stage, a technology icon pulled a new device out of his pocket. It was so much smaller than competing products that no one in the room could believe their eyes. The founder had a flair for theatrical product launches, and was known for blending science and art with an obsession for design. He is famous for saying, “We give people products they do not even know they want.”

The man urged people to think differently. Despite redefining multiple industries, he was unceremoniously forced out of his company. Who was it? Edwin Land, the founder of Polaroid.

Polaroid was at the top of their game in pioneering the digital camera. But, because of an unbreakable groupthink inside the organization, they failed to listen to the market and ultimately let others monetize the digital photography revolution. They did not listen to people internally who believed consumer behavior was radically changing. Instead, they chose to believe their legacy of market-leading innovation would protect their future position.

Source: The Originals, by Adam Grant

Avoid confirmation biasDon’t seek information that supports a position you already prefer.

Don’t hire first for cultural fitLeads you to bring in people who think in similar ways to your existing employees.

Find devil’s advocatesInvite people with genuinely different views into the conversation.

AVOIDING GROUPTHINK

Experiment a lotGenerate more ideas to get beyond conventional thinking.


The competitive landscape is changing and becoming more sophisticated. There’s a new wave of performance metrics giving insurers new capabilities to dominate market share growth.

Next Generation Metrics



In their 2017 negative outlook for commercial lines, A.M. Best set the stage for what we see playing out in workers’ compensation: “The need to manage through the continuing downward period in the underwriting cycle will be particularly challenging for companies that have failed to adopt the advanced analytics and enhanced data that enable their competitors to more effectively select and price business and manage claims.”

Several of the insurers with significant market share increases are known as profitable, analytically-driven competitors. SNL and Fitch Ratings previously did a similar analysis comparing 2009 to 2014, and there are significant changes just two years later when you compare 2009 and 2016. Texas Mutual no longer appears on this list, while Old Republic and AmTrust have been added. It signifies the volatility that is expected to continue in the race for profitable market share. It highlights the rapid speed of change, and how the differing views and strategies of incumbents reflect market dynamics.

Top competitors grab more market share

Market share is changing rapidly


Analytically-driven insurers know more

Average Price Deviation

Average policy pricing is on a downward trend, about 10% over a 5-year period.

Historically, book quality is monitored by looking at pricing statistics and how they have changed by quarter or annually. A traditional approach: “We need to improve loss ratio by three points to hit our goal next year, so we will increase price by five points. And, we will measure pricing on renewal policies to monitor how we are tracking to getting five additional points of price this year.”

This strategy is just begging for adverse selection, and ignores an important detail: what’s happening to the quality of the book? It might look very positive if prices are up 5% annually, but not if risk quality (measured by

Risk Quality Score - Weighted Average

Average risk score has increased by 2 full points, resulting in a 10% deterioration in expected loss ratio on the

equivalent exposure.

Commercial lines insurer

expected loss ratio) is 10% worse. Conversely, if pricing is flat, but book quality has improved by 10%, it’s great news that will never be reflected in the price monitoring statistics.

Putting these two views together reveals that the exposure-adjusted loss ratio is increasing rather dramatically over a five year period (orange line). Simultaneously, the discretionary pricing is falling, resulting in the “as priced” loss ratio increasing at an even more rapid rate (blue line). Analytically-driven insurers know that price monitoring must also include a simultaneous measure of risk quality to see the whole picture.

Price Monitoring + Risk Quality

Predicted loss ratio trend on final “as priced” premium

Predicted loss ratio trend on manual premium

Source: Valen Analytics

They know it’s not enough to simply do price monitoring



Tying profitability to specific decisions

Non-Renewed DeclinedBound

Lower Risk Higher Risk

Renewal Book by Risk Quality

Lower Risk Higher Risk

Regional commercial lines insurer BEFORE AND AFTERRisk selection decisions

Leveraging leading indicators that come from data science, insurers now monitor how decisions affect portfolio risk quality and profitability. For instance, take this risk selection analysis that shows a before and after view from a regional commercial lines insurer. In this example, an analysis of the 2013 portfolio shows there were no risk selection considerations in renewal decisions. There was no increase in lost business at the high-risk end of the scale; it’s flat regardless of risk quality.

When comparing that with the lower graph from 2016, it is apparent that risk selection is now being practiced. From 2013 to 2016, the bind rates decreased as the risk quality measure deteriorated. And, non-renewals made up most of the highest-risk business.

The insurer made these improvements by leveraging analytics, which allowed them to show the future predicted performance of individual policies to inform underwriter decision-making. Arming an experienced team of underwriters with this advanced analysis, enabled them to make more profitable decisions for renewals and new business growth.

2013

2016



One thing hasn’t changed with all the innovation from data analytics – insurers still measure success using profit as the ultimate indicator. If analytics can’t be translated into bottom-line profit, adoption and acceptance will suffer. Perhaps the simplest way to translate model predictive power into results is through the use of embedded profit. This metric is the predicted profit for a single policy based on projected loss ratio vs. actual premium quoted. One of the key benefits of embedded profit is that it is applicable to business quoted and bound, quoted and lost, or non-renewed.

Because embedded profit is a forward-looking statistic, it gives a real-time prediction of future profits, without the 6-12 month lag typically found in other insurance profitability measures. For instance, when insurers estimate the impact of strategic initiatives, it’s easy to see the impact on the production side: premium changes can be measured instantly. However, getting a read on profit impact requires waiting 6-12 months for losses to begin to emerge. Even then, the final analysis is not clear, as the loss data is simply not mature until 18 months or more have elapsed.

Quantifying analytics ROI


This example of embedded profit is shown at the level of a single underwriter. It’s measuring the impact of a change in strategy in the second half of the year. For the first half of the year, policies are being written at approximately the break-even price indicated by the model – embedded profit in the book is flat. In the second half of the year, however, average policy price begins to rise above the break-even price. The result is an accumulation of well-priced policies that will earn a bottom-line profit. The blue bar at the end shows the cumulative profit for the entire year. Measuring embedded profit allows an insurer to assess the impact of data analytics in real-time.

Embedded Profit Over Time

$7,000

DEC

$6,000

$5,000

$4,000

$3,000

$2,000

$1,000

$0

in thousands

Pred

icte

d/Em

bedd

ed P

rofit

JAN CUMULATIVE TOTAL

The best evaluation of the impact of a predictive model is on bottom-line profit (a.k.a. Predicted or Embedded Profit)



Top considerations in 2018

Key P/C stakeholders are making bets on where the industry is headed, their market position, and how best to respond to change.

Whatever your perspective on where the industry is headed, now is a time for organizational alignment. Is your executive team driving toward the same strategic goals for the next 5-10 years? Are there measurable outcomes that allow you to track the progress and execution of that strategy over time?

Organizational mindset

Given long-standing issues of investment income and capital deployment, how are you monitoring the actions of reinsurers, hedge funds and other investors? And, how are your traditional competitors changing their go to market strategies? Incumbents have large impacts on market dynamics that can be harder to see until there’s significant momentum underway.

Market shifts from incumbents

What core competencies are required for an insurance company 5-10 years from now? Identify where you need to develop new skills, recruit new talent, and create the culture required to retain a more diverse workforce.

Core competencies


Sources1. “Q2 Insurtech Funding Rises to $1B: Willis Towers Watson/CB Insights Report.” Insurance Journal, July 24, 2017.

2. Valen Analytics 2015 Underwriting Analytics Survey, September 2015.

3. Valen Analytics 2016 Underwriting Analytics Survey, July 2016.

4. Valen Analytics 2017 Underwriting Analytics Survey, October 2017.

5. “The Originals.” Adam Grant, February 2016.

6. “By the numbers: fraud statistics.” Coalition Against Insurance Fraud. 2017.

7. Viewpoint report: “InsurTech: Rebooting (re)insurance.” JLT Re, 2017.

8. “Inflation Watch - October 2017.” Insurance Information Institute, November 15, 2017.

9. “Amazon accounts for 43% of US online retail sales.” Business Insider, February 3, 2017.

10. “How Amazon is Dismantling Retail.” Scott Galloway, L2 Inc. April 17, 2017.

11. “Top 100 Retailers: The Nation’s Retail Power Players 2017.” Stores.org. 2017.

12. “Commercial Lines Outlook Remains Negative as Market Conditions Become Increasingly Competitive Across the

Segment.” A.M. Best, December 2016.

13. Valen Analytics 2017 Innovation Continuum Survey, October 2017.

Resources• The Punch List:

Implementing Analytics Guide walks you through three key areas to a successful roll-out of your next analytics project.

• This Week in Analytics Blog summarizes all the relevant news about data analytics in insurance to share the most important highlights.

• Links to Valen’s research in this report are included in the “Sources” information to the left. Our entire resource library is available online.


https://www.insurancejournal.com/news/international/2017/07/24/458672.htm

http://www.insurancefraud.org/statistics.htm

https://www.iii.org/article/inflation-watch-october-2017

http://www.businessinsider.com/amazon-accounts-for-43-of-us-online-retail-sales-2017-2

https://www.youtube.com/watch?v=3MOwRTTq1bY

https://stores.org/stores-top-retailers-2017/

http://learn.valen.com/NP-Punchlist_Implementing-Analytics-Guide.html



http://valen.com/category/this-week-in-analytics/

www.valen.com/blog

www.valen.com/resource-center


About Valen AnalyticsValen Analytics, an Insurity company, is a provider of proprietary data,

analytics and predictive modeling for property and casualty insurers. We work

with insurers who are actively looking to utilize modern approaches to pricing,

risk selection, claims triage, and premium fraud. Our customers are focused

on increasing competitive pressures, fighting adverse selection with innovative

solutions, and raising awareness for the impending “experience gap” with

initiatives such as Insurance Careers Month. Our customers span many lines

of business including Homeowners, Personal Auto, Workers’ Compensation,

Commercial Auto, Commercial Package, Commercial Property, and BOP.

Learn more about Valen at www.valen.com.

http://insurancecareertrifecta.org/


2018 outlook - valen analyticslearn.valen.com/rs/331-lit-031/images/2018 outlook... · valen’s...

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