The ABCD of Emerging Technology

The ABCD of Emerging Technology

Alphabet Blocks A to D

Celent has mapped over 45 emerging technologies in P&C and a similar number in Life & Health. That's way too much for an insurer to handle and the pace of technological change outpaces the industry's capacity to absorb it. You could say though that there is a set of 4 emerging technologies with the most potential to profoundly affect insurance; the ABCD of emerging technology:

  • Artificial Intelligence
  • Blockchain
  • Cloud
  • Data (big and small)

The four altogether become a strong enabler for Digital. Digital interactions, digital products, digital claims, everything digital. Digital becoming important to meet the expectations of customers that want insurance to be simple, right now, as I want it, when I want it, and relevant to me. On the other hand, many consumers are still not being attracted by insurance; creating a protection gap. Digital comes as a possible response to close this gap, and in the process has the ability to profoundly change insurance as we know it. Actually, we may not call it insurance anymore. It may just be something that comes as a warranty of the product or service. Have I gone mad?

Imagine cars with assisted driving. There is an accident involving the autopilot function and the manufacturer claims no responsibility. Who is going to buy this car after that incident? No surprise then to see some car manufacturers, vested in automated driving, indicate that they will assume liability. Of course they will, and in the process what they are doing is to offer their customers a guarantee that the product will perform as indicated in the user manual. By being able to monitor the car status they are also able to prevent accidents or breakdown. So in the future will you get car insurance or a manufacturer warranty?

You can imagine any other product that can be monitored, for example as part of the IoT. All these products will generate data, and that data will enable their manufacturers to provide a service; in many cases that service will be a preventive one. See the trend here?

Today many digital initiatives in insurance still rely on the use of a call center. That's not digital because it implies human to human interaction. Each interaction needs of a human in the call center, so each interaction adds cost as there is no way you can make the human person be digital. The use of chatbots or robo-advisors enabled by artificial intelligence and natural language capabilities allow digital interactions, where each interaction can be taken simultaneously by a robot with no, or marginal, cost to do it. By robot don't think about a physical robot but software instead. Just as the one used by Lemonade to settle claims fast.

Artificial intelligence with machine learning capabilities also allows us to mess with a huge amount of data; discovering new patterns. The more information ingested to these machines the better answers you get. The more is used, the more it learns, the smarter it gets. Even most importantly, this technology today is very good at taking repetitive and predictable processes and doing it faster, better and cheaper than humans. You are smart, you don't need me to explain how this is relevant to insurance, do you?

Technology as the one described here is available on demand and in the cloud. Need more computing power? being in the cloud can solve that problem very easily. Pay as you go? cloud deployments make this technology available at a per use price. Basically cloud makes technology accessible to anyone.

Blockchain is the glue that can hold it all together. Digital and physical assets (that can be digitized) can be stored in the blockchain. The IoT could be linked to blockchain. Then, any rules applicable to digital transactions can rely on smart contracts. Finally by providing trust and provenance through a decentralized body blockchain becomes the basis to catapult digital in any scale, even when peers don't know each other.

Are you mastering the ABCD of emerging technology? Not yet? Don't be left behind; insurers around the world have already started. Want to find more about how insurers can take advantage of emerging technology and innovation? Contact me or any person at Celent. We will be happy to dive into this with you.

How Insurity’s Acquisition of Valen Could Create a Virtuous Analytics Circle

How Insurity’s Acquisition of Valen Could Create a Virtuous Analytics Circle
It’s open season on insurance technology acquisitions in general, and for Insurity in particular. Today’s announcement of Insurity’s acquisition of Valen Analytics is now Insurity’s fourth acquisition in a multi-year string: Oceanwide, Tropics, and in rapid succession Systema and Valen.   The potential for crossing selling among the five customer bases is obvious.   Less obvious, but of potentially even greater value, is Insurity’s ability to invite all of its insurer and other customers to use its Enterprise Data Solutions IEV solution as the gateway to Valen’s contributory database and Valen’s InsureRight analytic platform.   Insurity now has the scale and the means to create a virtuous analytics circle: individual customers contributing a lot of data through IEV to Valens and receiving back analytic insights to feed into their pricing, underwriting, and claims operations.   Good move.

Data in insurance is not only about technology

Data in insurance is not only about technology
In October 2015, I explained that insurers had to hire more data experts if they wanted to better leverage all sorts of data sources they can access nowadays. As I raised this point, I shared the result of a survey we launched in 2015 to identify whether insurance companies were hiring new types of profiles to complement their teams looking at data. For more on this, read the following post: Why the insurance industry needs more data scientists. In March last year, I explained that insurers attempt to hire more data expert had become a clear trend: Insurers are investing in data scientists. With the growing importance of data in insurance and taking into consideration all the activities currently happening around data notably supported by InsurTech companies, we identify that not only insurers are hiring highly qualified data experts but also that these people are getting more and more influential within their organization. Indeed when asked about the level of influence on key business decisions these experts (internal or external consultants) have in their organization it seems that data scientists are gaining more power ​(in % of insurance respondents; n=135): Actually, two categories of experts are gaining influence in insurance: data scientists and user experience specialists. We are not surprised by this result. Insurers deal with a greater amount of data and more sophisticated technologies, therefore they need to hire highly educated experts in order to valuably leverage this data and these technologies. In addition, insurers consider customer interaction to be a key element of their digitization efforts and this is the reason why they are giving more responsibilities to user experience specialists. We will soon publish a report detailing the result of an insurance survey on the use of consumer data and smart technologies. I recommend you take some time to read our report to better understand what insurers are doing around this topic.

Smartphones, Apps, and Other Stuff

Smartphones, Apps, and Other Stuff

In 1985 when I was a kid in school, one of my favorite TV shows was Robotech, also known as Macross in some regions. They had the technology (alien technology by the way) to transform fighter planes into mechanical robots (a bit like Transformers), however they did not have either cellphones or smartphones. Instead, they had mobile cabs that would travel around the city looking out for when to pick the person up. Not to mention, in some episodes, they even had some kind of Google glasses. It was all very cool stuff in 1985.

Fortunately for us all, today we have our own smart stuff in the form of a super computer in our pockets – being the smartphone. Many of us no longer need to run to a red box to make a call; and a long with smartphones we have data usage, internet, and apps.

The great challenge with smartphones for insurers, is how to engage with customers in this mobile world; that is, how to make apps attractive to them beyond the basic proposition of moving consumers to the mobile channel in order to lower the operating cost.

In insurance, availability of mobile apps varies by region and by country, so does functionality.  In most countries property and casualty insurers are taking the lead, especially to connect to auto insurance policy holders to provide them with a very array of self-servicing features through the app. In many countries, insurers need to work with the regulators hand in hand to find the best ways to boost financial inclusion and the use of insurance through digital channels.

In a recent Celent’s report, we found that at least 80% of P&C insurers in the United States, the United Kingdom, Spain, and Portugal offer apps to their clients"

In Latin America availability of consumer-focused apps in insurance grew from 21% in 2013 to 39% in 2016"

So we expect in the following years that Latin American insurers keep up other regions. Not to mention that Insurers are very interested in mobility and they plan to invest in this technology.  To learn more about this report, please click here.

Going back to my story, there were occasions where the main character couldn't be contacted because there were no mobile phones, only robots, and maybe the outcome of the story might have changed.  It was 1985 for a story created much earlier; more than 30 years ago, but now mobility, artificial intelligence, robotics, and analytics are a reality.

Technology is playing a very important role enabling insurers to engage customers, and as part of the insurance industry, we need to be aware of these advancements. If you are interested in insurance technology and want to know more of case studies around world, Celent will be awarding the best technological initiatives in our 2017 Innovation & Insight Day in Boston on April 4, 2017

Also, if you are or know of an insurance company which exhibits best practices in the use of technology, please click here and complete the nomination form. Submissions are being accepted until December 16, 2016.  Categories include:

  • Digital and Omnichannel
  • Legacy and Ecosystem Transformation
  • Innovation and Emerging Technologies
  • Operational Excellence
  • Data Analytics

For more information about the Model Insurer program click here, leave a comment, or email me directly at lchipana@celent.com. I’d be more than happy to talk with you. The Celent team and I are looking forward to hearing from you and meeting you in person at the 2017 Innovation & Insight Day.

The Rise and Rise of Analytics in Insurance

The Rise and Rise of Analytics in Insurance

As noted in our prior research insurance has always been an industry that relies on advanced analytics and has always sought to predict the future (as it pertains to risk) based on the past. (For research on advanced analytics in insurers see here, here and here).

As observed in the last post here analytics, AI and automation has been a key focus of InsurTech firms but do not assume that the investment is limited to newbies and start-ups. I have for a few years now been attending and following the Strata+Hadoop conferences and others focused on advanced analytics and the broad range of tools and opportunities coming out of the big data organisations. This last week I attended a conference focused on the insurance industry and was surprised to see the two worlds have finally, genuinely overlapped – just take a look at the sponsors.

As Nicolas Michellod and I have noted in the past, insurers have already been investing in these technologies but only those that have made the effort to speak “insurance”. What the conversations at Insurance Analytics Europe (twitter feed) demonstrated was a new focus on core data science tools and capabilities. This continued the theme from DIA Barcelona (twitter) earlier in the year.

The event followed InsTech London’s meeting (Twitter) looking at data innovation and it’s opportunities for Lloyd’s, the London market and the TOM initiative. Here the focus was on InsurTech firms that would partner on analytics, would sell data or would enable non-data scientists to benefit from advances in machine learning, predictive analytics and other advanced analytics disciplines.

While this trend of democratising advanced analytics was discussed by analytics heads and CDO’s at the analytics conference the focus was much more on communicating value, surfacing existing capability and tools within the organisation and to put it bluntly, getting better at managing data.

In short – AI, Analytics, Machine Learning, Automation – these were all hot topics at InsurTech Connect and similar events but for the insurers out there – don’t assume these are purely the domain of InsurTech. Insurers are increasingly investing in these capabilities which in turn is attracting firms with a great deal to offer our industry. For those big data firms that ruled out insurance as a target market a couple of years ago – look again, the appetite is here.

As a techy and AI guy of old I am deeply enthused by this focus and excited to see what new offerings come out of the incumbent insurers and not just InsurTech.

Do have a look at the aware machine report and the blog too. We’re increasing our coverage in this area so if you have a solution focused on this space please reach out to Nicolas, Mike or myself so we can include you and for the insurers look out for a report shortly.

 

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.