Lost in Innovation?

Lost in Innovation?

So, how do you avoid getting lost in innovation? The simple (and maybe glib) answer might be to buy a map, a compass and start to plan your route. However, what do you do when there is no map, no obvious path to take and no-one to follow?

The last 24 months have seen an incredible amount of activity across the sector in experimenting with novel proposition concepts fuelled by emerging technologies in the internet of things, distributed ledgers and bot-driven artificial intelligence. Although each new concept shows promise, we are yet to experience a clear and obvious pattern for winning new clients or delivering a superior shareholder return using them. Many of the most exciting novel ideas (and many are genuinely exciting) are yet to see any real business volume behind them (see my earlier blog for additional context of what insurtech has to offer in defining the ‘dominant design’ for new tech-enabled propositions).

So, as an insurer faced with having to balance how much it should invest in these new concepts versus furthering the existing business in what is probably a highly successful and scalable model, two of the big questions we often hear from clients are: “Which of these nascent concepts are most likely to deliver real business value the fastest?” and “How much effort should I be devoting to exploring them today?” These are the questions that we looked to address at our latest event in London that we called ‘Lost in Innovation’, attended by just over 70 inquiring insurance decision makers.

Faced with uncertainty, we followed an agenda that focused on the things that an insurer can control, such as the innovation-led partnerships they enter, the skills they develop internally, the criteria used for measuring value, and the potential challenges ahead that they need to plan for.

Celent analyst Craig Beattie presenting on emerged software development approaches

Alongside presenting some of our latest research on the topic, we were joined on-stage by:

  • Matt Poll from NEOS (the UK’s first connected home proposition in partnership with Hiscox) shared his experience on the criteria for a successful partnership.
     
  • Jennyfer Yeung-Williams from Munich Re and Polly James from Berwin, Leighton, Paisner Law shared their experience and views on some of the challenges in the way of further adoption, including the attitude of the regulator and potential legal challenges presented by using personal data in propositions.
     
  • Dan Feihn, Group CTO from Markerstudy, presented his view of the future and how they are creating just enough space internally to experiment with some radical concepts – demonstrating that you don’t always need big budget project to try out some novel applications of new technologies.

So, what was the conclusion from the day? How do you avoid getting lost in innovation? Simply speaking, when concepts are so new that the direction of travel is unclear, a more explorative approach is required – testing each new path, collecting data and then regrouping to create the tools needed to unveil new paths further ahead until the goal is reached. Scaling concepts too early in their development (and before they are ready) may be akin to buying a 4×4 to plough through the scrub ‘on a hunch’ only to find quicksand on the other side.

Some tips shared to help feel out the way:

  • Partnerships will remain a strong feature of most insurer’s innovation activity over the next 12-24 months. Most struggle to create the space to try out new concepts. Also, realistically, many neither have the skills or the time to experiment (given that their existing capabilities are optimised for the existing business). Consequently, partnerships create a way to experiment without “upsetting the applecart”.
     
  • Hiring staff from outside of the industry can be a great way to change the culture internally and bring-in fresh new ideas…however, unless there is an environment in place to keep them enthused, there remains a risk of them turning ‘blue’ and adopting the existing culture instead of helping to change it.
     
  • There are several ways to measure value created by an initiative. The traditional approach is a classic ‘Return on Investment’ (RoI). However, RoI can be hard to calculate when uncertainty is high. To encourage experimentation, other approaches may be better suited, such as rapid low-cost releases to test concepts and gather data to feel the way. Framing these in terms of an ‘affordable loss’ may be another way to approach it – i.e. “What’s the maximum amount that I’m willing to spend to test this out?” – accepting that there may not be an RoI for the initial step. Although no responsible insurer should be ‘betting the house’ on wacky new concepts, reframing the question and containing exposure can sometimes be all that’s required to create the licence to explore.
     
  • There’s still an imbalance between the promise of technology and the reality of just how far end-customers and insurers are willing to go in pursuit of value. The geeks (or ‘path finders’) have rushed in first – but will the majority follows? Regardless, to avoid getting lost in the ‘shiny new stuff’, a focus on customer value, fairness and transparency around how data is being used need to be at the heart of each proposition – plus, recognising that the regulator will not be far behind.
     

In summary, the journey ahead needs to be less about the ‘what’ (with all of its bells, whistles and shiny parts) and more about the ‘how’ (deep in the culture of the firm and its willingness to experiment – even in small ways) – at least while the map to future value is being still being drawn.

Celent continues to research all of these topics, including assessing the different technologies and techniques that insurers can use. Feel free to get in touch to discuss how Celent could assist your organisation further.

Celent clients will be able to access the presentations from the event via their Celent Account Manager.

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.

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.

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.

Why the insurance industry needs more data scientists

Why the insurance industry needs more data scientists
Celent will soon be publishing an update to our 2013 report Perceptions and Misconceptions of Big Data in Insurance. In this report we looked at various elements in relation to the role and perception of data in insurance to understand where the industry was in terms of adoption of data-related technologies and more particularly Big Data. To do so we used what we call our Big Data Maturity Model. This model uses seven dimensions to categorize the industry in terms of their maturity level when it comes to adopting Big Data: Figure 1 big data   We came across an interesting article recently in the Insurance Journal that said insurers needed to hire more Big Data professionals. While we agree with this statement, we have already noticed in the early results of our 2015 survey (still in progress) that insurers have now more data scientist experts as shown in the following figure: Figure 2 data tools Technology is not enough and insurers have understood that if they want to make the most of data-related technologies they need to hire highly skilled people with solid knowledge of machine learning, statistics and predictive analytics. This is an interesting early finding and we look forward to provide our members with more on our seven model dimensions soon. Stay tuned!

The world’s most connected human

The world’s most connected human
I recently read about Chris Dancy, Chief Digital Officer and Senior Vice President of Healthways, Inc. and “The world’s most connected human.” In my line of business and as an avid NPR listener, I really should have heard of him earlier than now. If you haven’t heard of him and you are reading this blog, you should know about him, too. Chris utilizes up to 700 sensors, devices, applications, and services to track, analyze, and optimize his very existence every minute of every day. I listened to a few of his interviews (I am a curious person!) and found that he has been doing this self-tracking for nearly six years. You can really say he was on the cutting edge of this idea of a quantified self before most people even heard of the FitBit. According to Chris, this quantification enables him to see the connections of otherwise invisible data. As a result, he has experienced dramatic upgrades to his health, productivity, and quality of life. So what does he track? In a NPR interview while wearing five sensors (FitBit, Nike Field band, BodyMedia sensor, Wahoo TICKR, and his phone) Chris talked about how he has become ‘one with the data’ because he has seen the benefits of understanding his moods, heart rate, and overall health. He admitted that it’s not for everyone, but being a data junkie he said this behavior fit right into his interests. He expanded what he measured because he was interested in the data for which companies are willing to give discounts. If a company was willing to give him a $600 discount for seeing a doctor, going to the gym, and eating better, he wanted to know what data were they considering and what benefits he would derive as a result of knowing what the data said. He also said something very key: “If you can measure it, someone will and that someone should be you.” So why has he intrigued me so much? Because he said in 2013 that he believed the idea of a quantified self would be ubiquitous in five years. And it would expand beyond the fitness worlds and health care implications to the physical workplace and other industries. He saw sensors as being omnipresent in giving people feedback while they work. Examples could be environmental sensors that let someone change the lighting in their office to reflect a mood one had while on vacation or track ambient sound so that the sensor notifies you to reflect on the tone of voice used in a conversation. The goal, of course, is to have a more productive work environment. Chris Dancy’s rationale for wanting to know more about the data companies use to give discounts intrigues me the most. Many health insurance companies give discounts for proving that you lead an active lifestyle and for years now, consumers have been able to send driving data to auto insurance firms who offer reduced rates for good driving via a dongle that is plugged into their car’s onboard diagnostics port. Recently this practice moved into the realm of life insurance. John Hancock has become the first life insurer to offer ratepayers a discount when they use Fitbit wristbands that enable exercise tracking. John Hancock policyholders who wear a Fitbit and connect it to the internet can get discounts of up to 15% on their life insurance policy as part of Hancock’s partnership with Vitality, a service provider that integrates wellness benefits with life insurance. I already consider myself a quantified being because I track my fitness daily through my FitBit, and use that data to push myself to walk more and be more active. I am not sure I believe that my work environment needs sensors to make me more productive at work, but maybe they would. I don’t share my FitBit data with anyone yet, but I would be willing in the right circumstances. My insurers are not asking for my data which to me means that many insurers are not ready to accept the data. As mentioned above, John Hancock is the first life insurer; maybe others are soon to follow.  Will it happen in the next three years?  My gut instinct says no but I hope to be proven wrong. IBM’s Watson Health Cloud suggests that the medical industry is looking more deeply into how to capture, analyze, and use the multitude of medical data that is created every year, some of which is from fitness trackers and other sensors.  Maybe Watson’s analysis and cloud availability of data will yield better methods of underwriting for insurance. Yet, going back to Chris Dancy . . . during one of the NPR broadcasts Robert Wachter, author of the Digital Doctor, said that today very little of the extraordinary amount of data Chris was capturing is truly useful to doctors or insurers. I guess if that changes, Chris will be ready.

A four year old’s employment records (or how not to handle a data breach)

A four year old’s employment records (or how not to handle a data breach)
Yesterday one of my four year old twins received a letter from a major health insurance carrier (we’ll leave them nameless, tempting as it is). The letter states that the carrier had a data breach and that his information may have been included. The list was pretty extensive, including name, address, telephone number, email address, date of birth, social security number and employment history. That’s a pretty big list and everything you need to steal an identity. They assure me that no health information was shared, but I think they have their priorities wrong. I don’t care if the thief knows I have high cholesterol, but I do care that they have my social security number. I admit I am curious about the employment history of my four year old – I think he has been holding out on me. I wondered how he had so many Legos. The challenge? We’ve never had a policy from this particular carrier. Their FAQ site (a whopping four pages of minimal information) says it could have been because they process for other carriers, but nope, none of them either. So I set out to find out more information, particularly whether others in the family were affected, since we are all on the same policy (Mom, Dad and five small kids). I started my quest at 8:45am, on the website, and then the phone center opened at 9am. What a frustrating two hours. After talking to 11 people, from 4 different companies, do I know the answer to any of the questions? Not a single one. It all started with the vendor that the problem was outsourced too. I feel for those phone clerks, as they were provided almost no information. I then found a way to the carrier (a blog post in its own right), who didn’t know any more, but managed to transfer me to two other insurance companies, neither of whom had a clue why as they didn’t have a breach and I was never their customer. My concern is that this means they don’t even know what was stolen, where it was stolen, who’s information was stolen and more. If they don’t know that about me, what about you? I honestly don’t know how you protect yourself. You can’t really go off the grid. I could do without credit cards, and go to cash, but I can’t do without utilities or health insurance. I also understand that identity theft is big business, but the protections taken by major companies feel so lax. This is the FIFTH major breach of our family in less than 18 months. My credit card, from a major bank, has been replaced three times (only one breach was their own). So to the point of the post, for those still with me: If I was responsible for data security at any of these firms, I’d fire myself. There are solid, dependable companies doing security work. If you r company has not hired one to test your security, do it. Do it today. You should be doing penetration tests, at least annually. You should have solid company policies on data access, and that access should be extremely limited. People need information to do their jobs, but they don’t need all the information. Does your company have a data governance policy? If not, start today. We all know that IT budgets are limited and that our user communities, including our customers, want more and broader access. I just caution that you move with speed, but not without safeguards. Everything can be breached. Your firewalls, your apps, your website and even, as in the case of one breach, your cash registers. More important than all of this, though, is how you handle the breach when it occurs. Even with the most amazing safeguards, some pretty smart people, and governments, are hacking into private data. When it occurs, it should not be a shock to your company. You shouldn’t mobilize a task force after it happens. You should never consider this an IT problem – it is a major problem for the most senior levels of your company, and your reputation. Your company probably has, I hope, an IT Disaster Recovery (DR) plan. Does it include a data breach? Many don’t. They worry about floods, power outages, even pandemics, but not a data breach. Even if your DR plan does include data breach, are the actions your company will take fully laid out? If you are going to use a vendor, have they been chosen and briefed and is the conduit of key information already prepped? Is the spokesman for your company prepared and ready to speak publicly immediately? In my case, the time between the public announcement of the breach and the time we received the letter was over three months. Three months! Hopefully this post will cause at least one reader to start asking questions in their company and that those questions will be well received. You don’t want to be the next company in the news, do you?

Does Google Know Your Religion?

Does Google Know Your Religion?
An industry contact recently told me that her phone popped up the following “creepy” message one Sunday morning: “9 minutes’ drive time to St. XXXX Church.” This, of course, was a predictable result of Google Now keeping track of where and when she regularly went, and nobly trying to help her get to her regular 8:30 a.m. Mass on time. What makes it creepy is that most people put religion (and politics? and sex?) on a mental “Off Limits” list. Deeply personal issues like these are risky fodder at cocktail parties, and equally risky subjects for automated, data-driven insights. An application like Google Now doesn’t understand the issue unless its human coders are prescient enough to realize there are some connections we humans simply don’t want our devices to make on our behalf. But now the string of unintended consequences has begun. My contact told her story in a room full of people. The consensus reaction around the table was, “Google keeps track of where you drive, and even figures out what’s there? That’s over the top.” What else, we wondered, would the app notice about us and dispassionately reflect back via pop-up message? Some bland examples: “You’re almost out of gin, and there’s a liquor store nearby…” “Your wife won’t be home for another hour, and Melrose Place is on channel 7 right now…” “You’ve been getting a lot of emails from XXXXX—perhaps you should ask him/her out?” The conversation took us quickly from ambivalence to unease. Others in that group probably mentioned their unease to their spouses and colleagues and friends. As I write, an ever-widening circle of people is developing reasons to be suspicious and uncomfortable about Google Now—which, by the way, is a perfectly excellent and useful app about 99 percent of the time! It’s a grand example of the problem we’ll face as we try to harness the power of big data. Years ago, when desktop publishing first became a technical reality for business users, a friend of mine who was a professional designer put a sign on her wall: “Power Ability.” She was telling people that just because they could publish their own office newsletters, crammed with cutsie clip-art, didn’t mean that they should. Someone might want to give Google the same sort of advice, especially when church locations are involved.

Experimenting with external data: What's the real motivation?

Experimenting with external data: What's the real motivation?
Recently, we held a UK CIO Roundtable on the myths versus realities of ‘Big Data’.  The roundtable was made up of a mix of insurers from both the P&C and Life industry. I guess that it will come as no surprise that finding new ways to extract insight from data is a hot topic.  In a low interest rate environment, improving results from the core disciplines of sales, underwriting and expense management take on a greater level of importance within many firms, and data is at the heart of this. For many firms, the business drivers for investment in data and analytics have not really changed in recent years, i.e.
  • Risk mitigation – Minimising the frequency and impact of losses, through fraud detection and loss scenarios.
  • Growth / Maintaining market position – Identifying profitable segments and understanding the propensity to take a particular course of action.
  • Improving service – Identifying ways to improve the quality of service through ensuring that the right data is in the right place at the right time to aid decision making.
What has changed, however, is the increased focus on using data to make a difference to business performance coupled with a growing interest in the search for and use of new alternative external sources of data to augment with existing internal data, such as social profiles, health app data, public records, etc. Unsurprisingly, many of the firms represented stated that they were active in experimentation with new external data sources, albeit on a small scale.  What I personally found fascinating was when one insurer, having been questioned about the motivation for experimentation in new sources of data, gave the following refreshingly honest answers:
  • Competitive threat – Concern that a competitor or start-up could use data in a way that threatens their current position, rendering the way they underwrite and service customers obsolete.  Telematics in auto-insurance and use of public health records & personal health tracker apps for enhanced annuities being two examples.
  • Regulatory threat – Concern that local market regulators may extend anti-discrimination laws to prevent the use of existing rating factors used for pricing risk, such as age.  The origins for this concern were triggered by the European Union’s decision to implement the Gender Directive that came into law at the end of last year. (For non-EU citizens, the Gender Directive prevents insurers from using gender for pricing within Europe.  Since its implementation, there has been an increased interest in telematics across the region as insurers look to use the data generated to predict driving behaviour).
When I reflect on this further, the insurer’s stance makes perfect sense to me. For years, established players have relied on their scale and the history captured within their systems to provide them with a competitive edge.  All of the time that market rules of engagement remain unchanged, the insurer is better off prioritising investment towards making use of the data it already has, rather than place a big bet on a risky source of new data or a new data led propositions for unproven markets. However, in maintaining a capability to search for and then experiment with these new sources of data, this insurer has enabled themselves to be better placed to respond when the threat finally occurs.  This is a fast follower strategy (or ‘Fast Second’ to use a phrase coined by Constantinos C. Markides in his book of the same name).  For incumbent players in service industries, this strategy can often prove to be highly successful as a response to a disruptive play by a new entrant. Perhaps today more than in recent history, it could be argued that new entrants and small agile competitors using alternative sources of data to gain a competitive advantage are becoming a real threat to established insurers.  We have seen early examples within the industry already, such as with the Climate Corporation’s entry into the crop insurance market (and then its subsequent acquisition by Monsanto for an eye watering ~$1B earlier this month), the positioning of personal health apps to assist in managing risk for health insurance, and the growth of telematics for ‘pay how you drive’ insurance models. Once these new non-traditional data sources and data-led propositions start to gain real market traction, the key to success for industry incumbents may not lie in being first but instead in first being aware followed by being the fastest to execute.

New Year, New Tools to Service Insurance Customers

New Year, New Tools to Service Insurance Customers
For those interested in how new data techniques and availability are changing business models, I can recommend the article Smarter Information, Smarter Consumers in the latest edition of Harvard Business Review. http://hbr.org/2013/01/smarter-information-smarter-consumers/ar/1 The central premise is that legislation in the U.S. and U.K. now requires government agencies to make public data available and consumable in electronic form. This enables new techniques that leverage this information and provides increased value by making the purchasing process more intelligent. The authors offer their concept of “Choice Engines” – on line tools that guide consumers to make better purchasing decisions more efficiently using public information. At some point in the future, they also predict that private data will be added to the mix and allow the engines to work at a personal, individual level. Most of the use cases are consumer product-oriented, but as this blog has described previously, customer service expectations in other industries will influence insurance purchasing. The person who benefits because their cell phone company suggests ways to lower her bill (the authors’ example) will also want the same service from her insurance agent/company. Consumers and businesses will expect to be contacted by their agent/insurer when their risk profile changes. For example, if an addition is added to a house, insureds will expect that their insurance will be monitoring building permits and will want to be contacted proactively so their insurance can be adjusted appropriately. Two questions specifically related to insurance deal with timing and distribution models. Which insurance company will be the first to employ a choice engine for its insureds and prospects? Can an insurer with a mediocre data infrastructure and skill base compete with those which invest early and heavily in data techniques? Will independent agents embrace choice engines as an enabler, or reject them as a threat to their value proposition? Would an insurer be willing to offer such a tool to a distribution force that they don’t control? There is no question that managing risk will move from a point-in-time (usually renewal) event to a more continuous process. What is to be seen is which company changes the insurance purchasing model and transforms the buying process by using a tool like a choice engine.