Spring Awakening

Spring means many things for different people. For some it’s the start of the baseball season; for others it’s daffodils, tulips and azaleas season.  For me, spring represents the start of the insurance conference season.  This year is no exception, and over the past couple of months I have attended several insurance events.

Kicking off the season, and in this case a few days earlier than the official start of spring, was the Celent Innovation and Insight Day, which I wrote about in this blog.  Up next was the SAS Financial Services Executive Summit, and for more about this event read this article. Later in April was the Insurance Data Management Association conference, as well as two Insurance & Technology roundtables on telematics.

A common theme throughout all of these events was data and analytics. However, as I spoke to delegates and customers at these events, they indicated that they are drowning in data but starving for information.  Those carriers who have implemented telematics programs are struggling to collect and analyze this explosion of “new” data. Other companies are battling to make actionable business decisions from their existing data. While some insurance executives do not trust the information in their legacy systems and data warehouse, and are considering data governance programs.

To better understand how insurance companies are using predictive analytics, analyst firm Strategy Meets Action launched a survey on the analytical lifecycle and operationalizing analytics. The results of this survey will be available later in the summer.

Finally, rounding out the season was the ACORD / LOMA conference in Las Vegas. SAS was fortunate to have three SAS customers speak at this event. Brett Starr from Cincinnati Insurance entertained the audience on the topic of creating an analytical sandbox with some great quotes including:  “actuaries are the Wal-Mart of data” and “insurers must be data gymnasts with the flexibility to stretch data in many different directions”. Mike Rowell spoke about how Alfa Mutual is using data to better understand customer loyalty and calculate customer lifetime value. Finally AXA Equitable’s Matt Christensen talked about how his organization is better serving their customers by using speech analytics to analyze the information in their call centres.

Spring is seen as the season of re-growth, and based on the optimism from these events, insurers are also sensing growth and expansion in their future.

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

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What insurers can learn from Starbucks

There are many people who think that insurance is fast becoming a commodity, with little differentiation between products, and where consumers choose their insurer purely on the basis of price. However a cup of coffee is a commodity, and yet Starbucks can sell a cup of coffee for $4 or more. The reason for Starbucks’ success is often cited as the customer experience. Thus could an insurance company create a unique customer experience to differentiate itself from its peers?

Customer-centricity is not a new concept, but it has taken on increasing importance in today’s business environment, marked by empowered consumers who want to interact with a brand on their own terms.

For many organizations, the challenge lies in finding innovative ways to capture the “voice of the customer” and infuse customer insights across all business functions, from the point of sale to the call center, in order to create business value. But most insurance companies continue to be product focused, rather than customer or segment-focused.

So to create a customer experience that competitors cannot match requires three overarching elements:

  • Having a holistic understanding of the customer
  • Using that knowledge to define tailored products and communications
  • Interacting with agents and customers more effectively, with more personalized service

Every interaction with a customer represents an opportunity to get data to support these goals.  Never before could insurance companies compile so much information about customers and markets, transform that information into predictive insights, and guide the investment of resources with precision.

 

To build an exceptional customer experience can be complex,  download the white paper “Six steps to an unmatched customer experience” to learn more about how insurers can create a more valuable customer relationship. It summarizes the key six steps that an insurer must take to be successful, which are:

  1. Create a 360 –degree view of customer
  2. Understand the customer better
  3. Make marketing more efficient
  4. Provide quality leads to agents
  5. Manage the brand more proactively
  6. Deliver a better real-time experience

Like Starbucks, whether insurance consumers are willing to pay an increased premium for exceptional customer service has yet to be determined. Though we know it does increase customer loyalty. One company mixing insurance and coffee is State Farm. They have created a concept called “Next Door” where customers can hang out, talk with Financial Consultants while enjoying a great cup of coffee.

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

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More the merrier – Sharing ideas across financial services

The old adage “there is no I in team” is never more true than in today’s collaborative society. People and organizations share knowledge via wikis. They share advice, opinions and answer questions via social media. Recently I read about a case where a manager asked a new employee to do some research and then reprimanded the employee for using social media.  The manager’s perception was that the employee was wasting time, but in fact the employee had gotten a multitude of new answers on how to solve this problem because he had asked his network, which was much wider than any information resource internal to the company.

Keeping with this theme of collaboration last week I attended the SAS Financial Services Executive Summit in Cary and on the agenda was a “fun” crowdsourcing exercise using Spigit. During this exercise the delegates were given the task to ideate on the topic of “How might we harness the masses of digital & social data to cultivate the next generation of millennial customers to make our businesses prosper?” Amazingly in just 15 minutes the approximately 80 delegates were able to come up with over 300 ideas. After some voting, collaboration and even “investing” in these ideas, the winning suggestion was “Free Financial Services for positive tweets”. This may sound like a crazy idea, but why should carriers spend millions on paid advertising when they could get their customers to become ambassadors for their organization with their comments about good service?

Some other notable examples of collaboration and crowdsourcing in the insurance industry are:

  • Allstate who used Kaggle, the world's largest community of data scientists. These data scientists compete with each other to solve complex data science problems. Hence Allstate challenged this community with predicting which of their current customers will stay insured with them for an entire policy term.
  •  In 2010, Progressive sponsored a global competition by X PRIZE that awarded $10M to three teams that were able to build more efficient cars that could achieve at least 100MPGe in real world driving conditions.

Like the proverb “from tiny acorns mighty oak trees grow”, innovation often begins with small ideas and matures over time.

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

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6 steps to data quality and success

This week marks the beginning of the Baseball season. Go Red Sox. Over the years baseball has always been run by numbers and with today’s “sabermeterics” there appears to be statistics for nearly everything in the game. There is WAR (Wins above replacements), WHIP (Walks plus hits per innings pitched) even LIPS (Late innings pressure situation).

Another industry run by numbers and statistics is, of course, insurance. Insurance companies use analytics to gain insights into risk, cause of loss and resulting claims. Success and profitability depend on the quality of data. However, at best, insurance data can be described as inconsistent; and with the onslaught of Big Data, data quality will be more important than ever to insurers.

Fortunately the path to high quality and rich data is not difficult to define, and the goal is easily within the reach of most insurers.

To create a solid and repeatable data quality process you need to follow 6 simple steps:

Plan

  • Step 1 – Define the business terms and define the data sources you will use
  • Step 2 – Conduct data profiling to discover what your current data contains

Act

  • Step 3 – Design business rules for checking your data to ensure it is valid and complete
  • Step 4 – Execute your business rules by embedding them  into your operational systems and data integration processes

Monitor

  • Step 5 – Measure and monitor the actual state of your data against what is expected and how it trends over time. Tasks will be triggered to improve your data as needed.
  • Step 6 – Make the required updates and enhancements to your data, systems and processes to improve them.

German insurer, Allianz, implemented SAS Dataflux technology and experienced a 15% improvement in data quality. According to Rolf Neuerburg, Data Governance Manager at Allianz, not only does high quality data ensure Solvency II compliance, but it provides them with greater operational efficiency and competitive advantages .

Albert Einstein once said that “Genius is 1% inspiration and 99% hard work”. While ex-baseball player Yogi Berra is quoted as saying  “Baseball is ninety percent mental and the other half is physical”. Analytical genius is about 80% data quality and 20% expert analysis. At the end of the day, insurers who focus on data capture, data accuracy and data completeness not only improve their own profitability, but also prepare themselves for increased scrutiny as new insurance regulation looms on the horizon.

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

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Chicken or the egg?

The old adage “What comes first the chicken or the egg?” could easily be used as a metaphor for the analytical lifecycle.

Many will argue that data comes first. Insurance is a data-centric industry. Insurance companies collect data for a specific purpose or transaction via policy administration and underwriting systems, claims management applications, and billing and finance solutions. Data is rarely gathered specifically for the purpose of analytics. Instead, analytics becomes a secondary use  for data generated for another purpose.

However strategic decisions are made at the executive and board level to set the insurance organization’s long-term strategy. Hence business analysts will argue that that you must first identify the business problem. Start with the end goal in mind, i.e. the decision, and then determine the data needed to support that decision.

There is not really a right or wrong answer to the question “What comes first the chicken or egg?’; neither can really survive without the other.  Similarly, the analytical lifecycle should be considered a closed-loop process (see diagram).

 

This process consists of data preparation, data exploration and discovery, plus model creation and validation. Up next is getting the results to the right people at the right time, and learning from the results to refine the process. Hence for insurers to survive and thrive, they need both data and analytics.

To learn more on this topic download the white paper “Manage the Analytical Life Cycle for Continuous Innovation”

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

 

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Insurance technology is cool…really it is!

Much has been written about how the insurance industry is a laggard compared to many other industries, especially when it comes to technology. In fact I remember a 2010 report that surveyed the usage of social media in 30 different industries. Insurance came in 28th, ahead of only Zoos and Funeral Homes. So it beat animals and dead people!

But things are changing. Over the past ten days I have attended two conferences that highlighted technology innovation within insurance.

The first event was the Celent Insight and Innovation Day in Boston.  One session I found fascinating was “What’s Next? Deliberate Insurance Innovation”. This session discussed how technology is reshaping the insurance industry. For example, a Japanese insurance company is using GPS information from a smartphone to trigger location based insurance offers, such as hole-in-one insurance if the insured was on a golf course, or travel insurance if the insured is at an airport. Another instance of how advances in technology are helping insurers is the usage of radio-frequency identification devices (RFID). These are being implanted into animals to track and identify livestock, thereby helping insurers rate and price farm insurance more accurately.

Technology innovation can come in many shapes and sizes. Commercial insurance company, CNA, was recognized as a Celent Model Insurer of the Year for their usage of SAS Fraud Framework for Insurance, specifically link analysis software for combating claims fraud.

The second event I recently attended was the SAS Analyst Conference in Steamboat Springs. This is one of my favorite events of the year, not just because of the location, but the opportunity to learn about new SAS solutions, most of which have applicability for insurance companies. SAS Executives spoke about how SAS In-memory analytics solutions are opening new opportunities for insurers in the areas of telematics and price optimization.

Insurance technology might not be as cool as “Google Glass” or “ Apple’s iWatch” but innovation is happening in the insurance industry, and faster than you would think.

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

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Telematics – A new business model

Much has been written about the pros and cons of using telematics – and many insurers have made a business case for implementing usage-based insurance in the auto industry. However, the challenge often ignored is how to store and analyze this explosion of data created by these activities.

First of all, let’s consider the amount of data automotive telematics devices are expected to generate. Every second a telematics device will produce a data record. This data record will include information such as date, time, speed, longitude, latitude, acceleration or deceleration (g-force), cumulative mileage and fuel consumption. Depending on the frequency and length of the trips, these data records or data sets can represent approximately 5 to 15 MB of data annually, per customer. With a customer base of just 100,000 vehicles, this represents over 1 terabyte of data per year!

Secondly, once all this data is collected, insurance companies will need to analyze this vast amount of “new” . By using data exploration and analytics, insurers will be able to rank and weigh hundreds of new variables generated by telematics to develop highly accurate telematics pricing models based on a driver’s past and forecasted driving behavior. For example, insurers could use a correlation matrix to quickly identify which variables are related, and to determine the strength of the relationship.

Insurance companies cannot rely on traditional data mining technology to analyze all of this new data. Due to the sheer size of telematics data, insurers must consider a distributed, in-memory environment to display the results of data exploration and analysis in a way that is meaningful but not overwhelming.

Finally the idea of using telematics data to generate personalized pricing and provide meaningful risk information appears simple. In reality, it is very complex to achieve this goal – and it requires the use of high-performance analytics. The velocity of big data coming into an organization, especially that arising from telematics, can be very difficult to manage. The ability to quickly access and process varying velocities of data is critical. Insurance companies should consider a “stream it, score it, store it” approach. This approach enables analytics to be applied on the front end to first sift out the meaningful telematics data from the unimportant data, or the “noise.”

Telematics on its own will not revolutionize the insurance industry. Read the white paper “Telematics: How Big Data is Innovating Auto Insurance” on why information management and analytics are essential tools to help insurers succeed with these projects.

NOTE: Article also featured on Live Insurance News

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

 

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Why Solvency II feels like Groundhog Day.

Over the past few years I have written many articles on Solvency II with the anticipation that the directive would come into effect at the end of this year. However when it comes to Solvency II it seems Insurance companies are feeling like Bill Murray in the movie “Groundhog Day”. No matter what they do each day at work, when they wake up the next day nothing has changed, the deadline is still two years away .

With the latest delay, Insurance companies should not despair and put their Solvency II projects on hold, but take advantage of what they have already implemented; especially in the areas of data management and reporting.

A good data management strategy is a prerequisite for meeting Solvency II regulations. Article 48 of the Solvency II directive requires insurance companies to proactively assess the sufficiency and quality of data used to calculate technical provisions. Combining a regulatory challenge with a proactive approach can yield benefits well beyond just meeting the regulatory requirements. One insurance company that took this approach was Ecclesiastical Insurance. They are using SAS Dataflux Data Management Platform to not only meet the rigorous data requirements of Solvency II, but they are also  experiencing benefits such as a reduction in the cost of claims leakage, thanks to more accurate and complete data.

For many insurers, reporting is often the final hurdle to compliance. But this should not be the case. If insurers focus only on compliance with Solvency II QRTs, they will miss out on the extra benefits of a business intelligence solution that can support additional internal reporting requirements.

At the end of the movie, Bill Murray’s character uses his knowledge of that day’s experience not just for his own gain, but more importantly to help the local community. Insurance companies should consider Solvency II in the same light. Lessons learnt from this exercise will help carriers in many other aspects of their business than just risk management, and as in the movie, eventually everyone “lives happily ever after”.

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions follow me on Twitter.

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20 Questions – Answers insurance executives need in 2013.

Like many of my readers, I spent many hours traveling during the festive period. During one long car journey, I decided to play some “old-fashioned” games with my family, instead of having them stare at a TV screen or play endless videos games.  One such game was “20 Questions”.  For those of you unfamiliar with this game, one player selects a subject or object, such as a famous person, place, movie etc.; the other players then each take turns asking a question which can be answered with a simple "Yes" or "No." The players then have 20 questions to guess the subject.

Later during the journey when my children were back to watching their movies, it got me thinking, “What are the 20 questions that insurance executives should be asking in 2013”?

Here is my list:

  1. How can I increase market share?
  2. What products are competitively priced?
  3. How can I maximize the revenue for a book of business based on price elasticity?
  4. What is the average time from quote to policy issuance? By region, agent, underwriter?
  5. What is my premium revenue by product and  region ?
  6. What are my customers saying about us?
  7. What is the customer’s next best offer?
  8. Which customers are most likely to let their policies lapse?
  9. How can I maximize campaign profitability given budget constraints, offer restrictions etc.?
  10. Which claims are most likely to be subrogated or involve litigation?
  11. How are my loss-adjustment expenses trending by region, product etc.?
  12. What is the optimal adjustor allocation to maximize customer satisfaction and minimize claims severity?
  13. What is the percentage of claims pending to claims processed?
  14. Who is committing fraud, especially organized fraud?
  15. How many referrals did our SIU team receive last month? How many were accepted vs. rejected?
  16. How closely do our capital reserves match our risk profile?
  17. What is our risk exposure to a catastrophe by region?
  18. Who are my profitable agents?
  19. What is the agent attrition percentage?
  20. What distribution channel is the most cost-effective?

The answers to these questions will vary by insurance company, geographic region, line of business etc. However there is a common trait that links these questions – data and analytics - without them, insurers will not have the answers. To learn more about how analytics can help, read Analytical P&C Insurer or Analytical Life Insurer.

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

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Year in review – Why SAS is the DBs

As the year draws to a close it is typical to think back over the past 12 months. As I was doing this exercise last week I began reminiscing about an interesting course I attended by SAS’ Legal Department. This course focused on what can and cannot be written in marketing collateral, especially regarding unsubstantiated statements.

So as I contemplate the successes of SAS in the insurance industry in 2012, my mind began to wander about that “grey” area of marketing and advertising.

How did Papa Johns prove “better ingredients, better pizza”?

Or my personal favorite from the 80’s, did Heineken beer really “Refreshes the parts other beers cannot reach”? If so, how did they prove it? (Those of you not familiar with this campaign check out this YouTube clip from one of their most popular commercials).

There are even claims that Santa Claus uses SAS. For evidence check out this YouTube clip.

Hence as I review SAS’ highlights from 2012. I have sufficient proof to state that:

Does this mean that I have enough evidence to state that SAS is the Dog’s B******s or even the  Bee’s Knees? I will be contacting Legal next week to find out.

Finally, I would like to wish all my readers a Happy New Year and I am looking forward to spreading the word about analytical innovation in insurance in 2013.

I’m Stuart Rose, Global Insurance Marketing Principal at SAS. For further discussions connect with me on LinkedIn and Twitter.

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  • About this blog

    We’re a group of analytics practitioners from the insurance industry. Among us, we have more than 50 years’ experience advising insurance companies across the globe in applying analytics and business intelligence technologies to solve business problems. In this blog, we’ll talk about fraud, risk, regulations, customer value and more, all with an eye toward minimizing losses and maximizing profits.
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