Changing the Landscape of Customer Experience with Advanced Analytics

Changing the Landscape of Customer Experience with Advanced Analytics

That timeless principle – “Know Your Customer” – has never been more relevant than today. Customer expectations are escalating rapidly. They want transparency in products and pricing; personalization of options and choices; and control throughout their interactions.

For an insurance company, the path to success is to offer those products, choices, and interactions that are relevant to an individual at the time that they are needed. These offerings extend well beyond product needs and pricing options. Customers expect that easy, relevant experiences and interactions will be offered across multiple channels. After all, they get tailored recommendations from Amazon and Netflix – why not from their insurance company?

Carriers have significant amounts of data necessary to know the customer deeply. It’s there in the public data showing the purchase of a new house or a marriage. It’s there on Facebook and LinkedIn as customers clearly talk about their life changes and new jobs.


One of the newest trends is dynamic segmentation. Carriers are pulling in massive amounts of data from multiple sources creating finely grained segments and then using focused models to dynamically segment customers based on changing behaviors.

This goes well beyond conventional predictive analytics. The new dimension to this is the dynamic nature of segmentation. A traditional segmentation model uses demographics to segment a customer into a broad tier and leaves them there. But with cognitive computing and machine learning an institution can create finely grained segments and can rapidly change that segmentation as customer behaviors change.

To pull off this level of intervention at scale, a carrier needs technology that works simply and easily, pulling in data from a wide variety of sources – both structured and unstructured.

The technology needs to be able to handle the scale of real-time analysis of that data and run the data through predictive and dynamic models. Models need to continuously learn and more accurately predict behaviors using cognitive computing.

Doing this well allows an carrier to humanize a digital interaction and in a live channel, to augment the human so they can scale, allowing the human to focus on what they do best – build relationships with customers and exercise judgment around the relationship.

Sophisticated carriers are using advanced analytics and machine learning as a powerful tool to find unexpected opportunities to improve sales, marketing and redefine the customer experience. These powerful tools are allowing carriers to go well beyond simple number crunching and reporting and improve their ability to listen and anticipate the needs of customers.

Using private consumer data in insurance: Mind the gap!

Using private consumer data in insurance: Mind the gap!

Insurance is no different to other industries when it comes to capturing valuable data to improve business decisions. At Celent we have already discussed how and where in their operations insurance companies can leverage private consumer data they can find on social networks, blogs and so on. For more information you can read a report I have published this year explaining Social Media Intelligence in insurance.

Actually there are various factors influencing insurers' decision to actively use private consumer data out there including among others regulation, resources adequacy, data access and storage. I think that an ethical dimension will play a more important role going forward. More precisely I wonder whether consumers and insurers' perceptions about the use of private consumer data are divergent or similar:

  • What do consumers really think about insurance companies using their private data on social networks and other internet platforms?
  • What about insurers; does it pose an issue for them?

In order to assess this ethical dimension, we have asked both insurers worldwide and also consumers (in the US, UK, France, Germany and Italy) what where their view on this topic. To insurers, we simply asked them what best described their opinion about using consumer data available on social networks (Facebook, Twitter, LinkedIn, etc.) and other data sources on the internet (blogs, forums, etc.). To consumers, we asked what were their opinions about insurers using these open data sources for tracking people potentially engaged in fraud or criminal activity.

The following chart shows the result and indicates that there is a big gap between the two sides:

UseConsumerData

Overall what is good for consumers is not necessarily good for insurers. In the same way, what insurers want is not always in line with what consumers expect from their insurers. Going forward the question for insurance companies will be the find the right balance between the perceived value of private consumer data and customers' satisfaction. In addition, it will be tough for them to figure out the impact (pros and cons) of all factors at play in the decision to invest in technologies allowing for the efficient use of private consumer data accessible on the Internet.

At Celent, we are trying to define a framework that can help them structure their reasoning and make an optimal decision. So more to come in the coming weeks on this topic…

The privacy bomb and cost of personal data debt

The privacy bomb and cost of personal data debt

I often hear architects talk about technical debt but it strikes me that a different debt is waiting for insurers.

Imagine a world where the regulator says that a customer owns data about the customer, regardless of where it is stored. The key observation here is the decoupling of ownership and control with storage. Most regulators have gone nearly this far and made statements about consumer ownership of consumer data, so perhaps it's not out of step with reality. This is discussion so far but perhaps the technology hasn't caught up with the intent. If we ignore the limits of technology …

There are perhaps 3 models emerging:

  • A. The data remains where it is and is controlled from there. Requires APIs…
  • B. The data moves as customer moves. Requires data standards…
  • C. Customer data is held in a shared environment. Requires APIs and data standards

Let's take a moment to really think that through for an insurer. If you hold data about a customer in your systems, that data is owned by another party. Ownership here is a complex word – it implies but is not limited to controlling access to the data, determining appropriate use of the data, revoking access to the data, determining how long that data is kept.

Scenario A
What if the storers are obliged to provide these controls to the owner of the data and actually – what if that obligation exists regardless of whether that owner is a customer?

Such a scenario may make it prohibitive for insurers to capture and store data directly. What would the world look like in such a scenario? Insurers would request access to customers data and have to disclose why they want the data, what they will do with it and perhaps the algorithms used  in order to offer products. Such a world might favour insurers with simpler pricing algorithms that are more expensive but customers understand what is being done with the data.

If we take it a step further, in theory there would be intermediaries emerge who help manage consumer data and help consumers simply share their data with trusted partners. I would suggest most people would not dig into the detail of who is sharing what so a service that says, "we've found these 15 services that only use the data in these ways and we've packaged that up for you" would be most welcome.

If however, we take existing businesses into this world then suddenly enterprises will be faced with the issue of how do they offer appropriate controls and management around the data already in place.

The standard already exists for sharing information in this way leveraging OAUTH as is used by Twitter, LinkedIn, Google and Facebook.

Scenario B
The cost for doing migration and conversion will lie with the party holding the data. A different type of debt.

This is the model the insurance industry is assuming will come to pass but it requires shared data standards which are harder to implement than API standards. There is also the issue of potentially lossy data migrations – I.e. The quality of the data is reduced in the migration – will this be 'OK' from a regulatory point of view?

Further this is more confusing for a consumer since the mechanism and means to manage access to the data will change each time there is a move. An approach intended to increase portability and movement could become an inhibitor as consumers grow concerned about retraining.

In theory though, this would allow insurers to differentiate on trust and service – a place where they already play.

Scenario C
The greatest challenge with a shared environment is who is the trusted party? Google, Twitter, Facebook and LinkedIn among others have made moves into authentication but they don't hold all the data and regulators in multiple countries are seeking to grasp control and this is a topic for Insurtech startups as well.

Some see Blockchain as a possible solution – the data in a shared open place, but secured and encrypted.

At this point this seems like the least likely solution, requiring the greatest cooperation and investment from the industry and governments. Regulators at this point seem to be supporting the other two.

Which will come to pass
There is a clear trend with private data becoming more valuable, but the cost of storing it is becoming more onerous. Regardless of which of the scenarios comes to pass or if some other scheme emerges – insurers must balance the cost of storing the data and the value it may bring now and in the future.

Internet of Things – NBA edition, round 2

Internet of Things – NBA edition, round 2

For those of you that follow our blog, you may have read my post from April 8th, entitled Internet of Things – NBA edition. If not, then I’d suggest you click the title and read that post first.

Given we’re in round 1 of the playoffs, this post feels even more timely. The basic premise of the first post revolved around the use of wearables in sports, more specifically during games. As it turns out, there was recently a follow-up article on ESPN.com:

NBA union, wearable tech company Whoop to meet Tuesday

As I mentioned, the use of wearables goes well beyond just the technology, particularly to the ownership of the data.

I particularly liked the quote from the Whoop CEO, Will Ahmed: "…let's not deprive athletes of in game analysis. It's their careers at stake and data is not steroids."

As wearables get to be more and more ubiquitous, it will be interesting to follow their use. We see the benefit in insurance programs, such as Hancock’s Vitality, but the ultimate use of the information shows so much opportunity to truly change our lives. It will be fun to follow.

Internet of Things — NBA edition

Internet of Things — NBA edition

It is not often that I get to reference an article from ESPN for a blog post, but as March Madness is complete and we’re coming close to the NBA playoffs, this topic resonated with me.

The article, entitled Why the NBA slapped the wrist of Matthew Dellavedova, focuses on the use of wearable technology by NBA players. Not exactly an insurance topic, but it brings up many topics that do apply to our industry. It is also a fun read.

In a nutshell, a company has created a super-wearable for use by athletes called the Whoop (pronounced without the W). It is unique in that it not only captures current information, but more importantly trends in information. It focuses on my more than just activity during the game, but includes other areas such as sleep monitoring, including the impact of late evening caffeine.

The reason Matthew Dellavedova was slapped on the proverbial wrist was wearing a Whoop on that wrist during a game.

Now there are some obvious reasons why that might be a bad idea, particularly if that wrist came in contact with another player in the eye, or other sensitive area.

But the interest from the insurance perspective is narrower (although that could be a pretty big claim).

The challenge is the use of wearables isn’t covered in the current contract, which was negotiated well before wearables became a thing. So the issues include:

  • Marketing rights – what happens if the wearable in use is different than the ‘official wearable of this sports league?
  • Ownership of data – This is the big one for our industry. Does the player own their data? If so, that data may have value and they may need to be reimbursed for the data.
  • Use of the data – this is another big issue. If the data could potentially predict an injury, or the likelihood of an injury, this could affect the value of the player, lowering their total contract.
  • Security of the data – This one isn’t mentioned in the article, but what if a competitive team hacked your data. Worse a dishonesty bookie or bettor hacked your data. It would be interesting to know that LeBron was having breathing difficulties the afternoon before a game, wouldn’t it?

These are just some examples, but we can see how they could come across to insurance. If an insurance company wants my health data or my driving data, there better be a significant quid pro quo. Some auto insureres address this with a signing bonus when you enroll in their telematics program, essentially buying your data. Other programs offer you discounts for this information, if you do what you’re supposed to do (drive safely, exercise more). This gets more complicated as wearables evolve. The use of this data in underwriting could dramatically affect your premiums, but if you own the data and refuse to provide it, what happens? What are the legal ramifications of a declined life insurance policy because of wearable data?

For the average consumer, the security of the data really isn’t an issue and I’ve said this before. If a hacker really wants to know that I didn’t walk my expected 10,000 steps today (after all, I work from home, there are only so many steps I can take), than they are welcome to that data. I feel the same about a lot of health data. My cholesterol level isn’t something that could be used to steal my identity.

Just as driverless cars have ethical and legal issues to resolve, so do the expanded use of the Internet of Things in our industry.

Insurers are investing in data scientists

Insurers are investing in data scientists
A few weeks ago I described a few results of a survey we have launched during the last quarter of last year around the role and importance of data in insurance. My blog post can be found here. Since then we have published a report summarizing the findings of this survey that our members can find here. An interesting trend we identified based on this survey was the need for insurers to hire more data scientists with advanced degrees and strong background in data and computer science. Indeed we think technology is not enough nowadays and insurers need to also invest in people with deep skills in this domain. I recently came across the following article from INN: Sentry Insurance Gifts $4 Million to Grow Data Science. It seems to validate our findings and I expect to see more of these kinds of initiatives going forward.

Social media intelligence and insurance – don’t listen to everything if you want to hear something

Social media intelligence and insurance – don’t listen to everything if you want to hear something
In a 2011 report titled Using Social Data in Claims and Underwriting: Creating a Social Risk Profile, Celent looked at how insurers could leverage social networks to do a better job in claims and underwriting. Since then, we have been looking at vendors who can complement insurers internal data with external data sources including social media data and this in the frame of different applications that go beyond underwriting and claims. We notably have profiled and will continue to profile vendors active in the predictive analytics space and for which data sources are as important if not more important than pure features and functions they offer as part of their system. Using social media data in insurance has become more important over the past few years and what can be called now social media intelligence goes beyond a simple technology that taps in all sorts of social network data sources. Indeed for many people social media intelligence or what people also call social media listening purely consists in screening social networks to get data that can complement internal data to make a better business decision. Actually this definition is too succinct and does not include all key phases a proper social media intelligence strategy should include: ScreenHunter_496 Feb. 29 10.29 So we define social media intelligence as the strategy consisting in:
  1. Defining strategic objectives that are dependent not only on internal but external data,
  2. Defining a referential or a group of topics, relevant social media platforms as well as a geographic and language scope to be considered for the analysis,
  3. Filtering and analyzing social media data regularly (real time, daily, monthly but it is generally a continuous process)
  4. Implementing an action plan leveraging findings derived from the data analysis to achieve the strategic objectives initially defined.
We think insurers can learn from project and use cases other industries have gone for in the Social Media Intelligence space and we are interested to better understand how these examples can generate fruitful ideas for insurers. Stay tuned as Celent will be covering this topic in more detail in the near future.

US patents in 2015 – who are the leaders?

US patents in 2015 – who are the leaders?
I thought this chart from the firm Statista was interesting and topical given my post from last week. What particularly caught my eye was their observation that IBM is number one for the 23rd straight year. In addition, over 2,000 of their patents focus on cloud computing and cognitive computing, both areas of particular interest to insurance and the broader financial services industry. And for those that wonder (like me), Apple was in 11th place, just 18 patents short of 10th.   Infographic: Top 10 U.S. Patent Recipients | Statista You will find more statistics at Statista

Insurance companies are embracing technology — for investment

Insurance companies are embracing technology — for investment
Celent frequently observes that many insurers, particularly in the Life space, are running aging, if not antique, software systems. They rely heavily on mainframe systems, often in languages such as COBOL that are becoming more difficult to support. The positive news is that our research shows continued growth, if modest, in IT budgets with modernization and innovation a frequent focus. With this as the foundation, it is interesting to see continued growth in insurance company’s venture capital arms in financial services oriented technology, or Fintech. Industry research shows an incredible growth path in Fintech start-ups, from a modest 400 or so in 2010 to over 12,000 in 2014. While the numbers are not yet in, we expect the 2015 numbers to continue this dramatic growth path. The insurers with venture capital arms are too numerous to list, but are a who’s who in the industry. Examples include AXA Strategic Ventures, MassMutual Ventures, American Family Ventures, and Transamerica Ventures. While many of the examples are US-based, it is a global phenomenon. A great example is Ping An Ventures, a subsidiary of the Chinese insurance company Ping An. Celent tracks many of the insurance related investments and we see several focus areas. One is in financial management and modeling, such as Roboadvisors, across both Life and Health. Good examples include Northwestern Mutual’s acquisition of Learnvest and AXA Strategic Ventures and MassMutual Venture’s investment in Limelight Health. MassMutual is also the parent company of Haven Life, a fully online sales organization dedicated to Life insurance. Other hot areas, not surprisingly, include analytics and the ever popular Internet of Things. The most recent investment, announced just yesterday, is AXA Strategic Ventures’ investment in Neura. Neura’s tagline is “Enrich your products with personalized insights from the lives of people who use them”. While a little heavy on the buzzwords, the basic view is that Neura analyzes data about you and recommends personalizations based on that information. The basic premises appears to link the Internet of Things, such as your Fitbit, to your social media presence, to your calendar and more. There are, of course, other companies overlapping this space (with 12,000 new companies, you would expect competition), such as Vitality and Life.io. The competition is encouraging, as it fosters continuous innovation. As the Millennials now outnumber Baby boomers (at least in the US), new technologies to engage them in insurance can be game changers. I am particularly intrigued with the technology companies, like these, that are focusing on changing the entire approach to Life insurance. The life insurance sale has always been focused on a negative experience – death of a love one. No one wants to talk about dying, and everyone wants to believe they will live many more years. When I talk to people that are just reaching an age where they really need life insurance, I get push back, and a lot of it, about everything else more important in their lives. My response that they need to protect their family often falls on deaf ears. By changing the discussion from “you are going to die”, to “how can we help you live longer”, we are opening up a much more comfortable discussion. In addition, this is a generation that will share everything on social media, to the point of embarrassment, so asking for more information to make their experience more intimate should be fairly easy. The investments and technology are exciting. It is wonderful to see insurance organizations finally catching the technology wave, after lagging for so long. Whether it be the Internet of Things, Usage based insurance, Micro insurance, behavioral underwriting or more, the staid insurance industry is breaking out. Some technologies are even a bit fun, such as the expanded usage of drones. Now before I get you too excited about the reinvention of insurance, I suggest you read a counterpoint to this post, from my colleague Donald Light, entitled A long time ago in a galaxy far far away, I went to a two hour meeting to reinvent insurance. He makes some very valid points about the managing our excitement. Another colleague, Craig Beattie, shares a similar bit of skepticism in his post What if… the insurance industry didn’t innovate? I guess I am forever the optimist and want to believe the excitement and change is real.

California DMV flashes yellow light for driverless cars

California DMV flashes yellow light for driverless cars
As a long time resident of the Golden State, let me say that the words “fair,” “judicious,” “California,” and “DMV” just don’t appear together in the same sentence. But, I’ll break precedent and say that the  California DMV’s new draft regulations for driverless cars are (overall) fair and judicious. The regs begin to address the knotty social and legal issues of safety and liability. Manufacturers and a third party tester must certify the ability of a driverless car to meet specified safety and performance requirements. Operators (who used to be called drivers, back in the day) must be able to take control of the car and will be responsible for all traffic violations. It looks like the larger issue for insurers and trial lawyers of “who gets sued” is not directly addressed by the draft regs. Additional parts of the regulations include:
  • Special licensing for driver/operators
  • Obtaining driver/operator consent for collecting information “not necessary for the safe operation of the car” (hello interior-facing dashboard cams)
  • Ongoing reporting requirements by the manufacturers on the vehicles’ performance and safety
  • And, sign of the times, the vehicles must be able to detect and respond to cyber attacks
Some manufacturers may be (privately) impatient. But the reality is that these regs provide a path for broader deployment into a litigious and worried society of technologies still in the R&D stages.