A Day to Celebrate: Celent 2017 Model Insurer Winners

A Day to Celebrate:  Celent 2017 Model Insurer Winners

Last April 4, Boston, a city surrounded by history of patriotism and independence, was witness of Celent Innovation and Insight Day (I&I day), an event in which 16 insurers were recognized as Model Insurers for their technological initiatives that, I’m sure, inspired more 280 professionals of the Financial Service industry by the efforts and ideas on how other insurers could implement them within their organizations.

Andrew Rear, chief executive of Munich Re Digital Partners was the Model Insurer keynote speaker. He discussed the role of Insuretech for large insurers and spoke of how these insurers could acquire agility, the pathway that they needed to choose, and more importantly, the risks they had to bear. He also discussed how Financial Services were redefining the way financial products are sold, delivered, and serviced.

No sensible website asks you for your email address anymore. They should know who you are by other means

~Andrew Rear

 

In the afternoon, our analysts participated in a series of debates focusing on the Internet of Things (IoT); Artificial Intelligence (AI); and Blockchain which was lively discussion. In between, Celent presented its Model Insurers for five categories and the Model Insurer of the Year.

Digital and Omnichannel

  • CUNA Mutual Group

The rapid development and launch of a simplified-issue term life insurance product that enables members to apply entirely online, answering only two health questions supported by a completely automated underwriting platform that delivers an instant decision in minutes.

  • Lincoln Financial Group

Lincoln Financial created a digital process to meet customer expectations of doing business, automate underwriting, reduce cycle time, and minimize human touch.

  • New York Life

The New York Life Portal initiative utilized digital connectivity and a ratings engine cloud-based platform to achieve a faster process and empower various actors across the organization.

To learn more of these Model Insurers, please read our report here.

Legacy and Ecosystem Transformation

  • Republic Indemnity

Republic Indemnity’s previous home-grown, legacy policy administration system was implemented in 1994 as a single state, Workers Compensation policy administration system. As the previous system could not issue multi-state policies and with the concern of technology obsolesce, Republic Indemnity looked for a new solution to replace its home-grown, legacy system.

  • ERS

Under new management, the business had to transform itself rapidly and replace 20-year-old technology. It had a major license renewal date in two years and would have been locked in by the vendor to a prohibitively expensive contract. It set about transforming claims first, and then policy with full data migration and scheme rationalization, all while growing the underlying gross written premium

  • Insurance Corporation of British Columbia

At the beginning of 2013, the Insurance Corporation of British Columbia (ICBC) launched the Insurance Sales and Administration System (ISAS) policy transformation program. This was the last project in ICBC’s overall $400 million Transformation Program, which had already successfully replaced legacy claims systems and implemented a new Enterprise Data Warehouse and an enterprise service-oriented architecture.

To learn more of these Model Insurers, please read our report here.

Innovation and Emerging Technologies

  • Suramericana de Seguros S.A.- Wesura

Wesura (Sura) created a peer-to-peer Insurance platform around social networks. It develops private insurance communities so final users can share risk and underwrite people who wants to belong to the private community, the bigger the community the more benefits one can receive.

  • Church Mutual Insurance Company

Church Mutual Insurance Company has partnered with The Hartford Steam Boiler Inspection and Insurance Company (HSB), part of Munich Re, to provide temperature and water sensors connected to a 24/7 monitoring system. This innovative Internet of Things (IoT) technology solution is designed to alert customers to take action before damages and disruptions to their ministries can occur.

  • Markerstudy Insurance

Markerstudy launched VisionTrack in February 2016 to tackle the challenge insurers are facing with rising fraudulent motor claims and to help improve driver behavior.

To learn more of these Model Insurers, please read our report here.

Operational Excellence

  • Aflac

Aflac was in need of some modernizing and is still likely to undergo more change as the industry continues to capitalize on social, mobile, and wearables. In response, the Aflac IT Division implemented an Agile Transformation to its projects and processes to meet the changing needs of the customers.

  • Saxon

Saxon serves the Cayman island community. With a limited pool to hire from or sell product to, Saxon realized that to remain viable in the insurance market, it needed to employ technology to better serve the needs of its customers and grow the business.

  • MassMutual

MassMutual offers a Data Science Development Program (DSDP) in Amherst, MA that trains promising, recent graduates to become well-rounded data scientists over a period of three years. The program combines rigorous academic coursework and practical data science projects for MassMutual — a unique and valuable combination.

To learn more of these Model Insurers, please read our report here.

Data Analytics

  • The Savings Bank Life Insurance Company of Massachusetts

SBLI implemented an advanced risk assessment solution using predictive modeling and data analytics to help reduce cycle times, decrease dropout rates, and eliminate the need to pull fluids and conduct exams, while pricing policies more competitively, placing applicants into appropriate risk classes, and improving customer experience.

  • StarStone Specialty Insurance Company

The initiative is based on the implementation of analytics tools to measure and reduce risk. The solution uses data from internal and external sources. The data may be structured or unstructured. This tool helps underwriters make better decisions.

  • Meteo Protect

Although a broker, Meteo Protect gives clients a means to evaluate how climate variability contributes to their companies’ results by analyzing the relationship between each business activity and the weather. It couples this with a platform to price and underwrite fully customized index-based weather insurance, for any business anywhere in the world.

To learn more of these Model Insurers, please read our report here.

CSE, Model Insurer of the Year

In 2017, CSE has been awarded Model Insurer of the Year for its aspiration to achieve “the best product in the industry.” This meant they had to overcome legacy thinking and practices to re-think all the features including coverage, pricing, rules, process, and communications To do so, they sought inputs from customers and analyzed the market using two common analyses: 5 Cs and SWOT. From this point on, CSE assembled and adapted its core system.

To learn more of the Model Insurers of the Year, please read our report here.

The quality of the submissions this year is a clear indication the industry is turning a corner and embracing transformation, digital initiatives, innovation and valuing data analytics.  It is inspiring to see the positive results the insurers have achieved and a pleasure to recognize them as Model Insurers for their best practices in insurance technology.

How about your company? As you read this, are you thinking of an initiative in your company that should be recognized? We are always looking for good examples of the use of technology in insurance. Stay tuned for more information regarding 2018 Model Insurer nominations.

Why Not a Bot? Adjuster Bots for Connected Cars

Why Not a Bot? Adjuster Bots for Connected Cars

We’re not quite there yet. But there is a path to get there—probably in only a few years.

We’re already at the point where fender bender claims can be estimated with a set of smart phone photos (offered by esurance and many other carriers)

But what more serious accidents which involve damage to a car’s mechanical systems? 

Here is one element of an Adjuster Bot solution: electonic control units, ECUs. For years, automobiles have been manufactured with dozens ECUs which control, monitor, and diagnose a broad away of systems within the vehicle, including its engine, power train, brakes, steering, airbags, electronic stability control. Information from ECUs can be accessed from vehicle’s On-board Diagnostic Port (OBD-II). The primary purpose of the OBD-II is to enable maintenance and repair of the various systems. (Telematics devices–aka dongles–plugged into the OBD-II port have been the primary method to gather and transmit telematics data to insurers.)

A second critical piece of the puzzle falls into place: communication. Automobile manufacturers are racing towards creating connected cars—typically using 3G or even 4G LTE cellular modems.

So this is what an automobile Adjuster Bot ecosystem would look like:

  • A cellular modem which tells the Adjuster Bot that an accident has occurred
    • And transmits data from ECUs describing the functional/non-functional status of major car systems
  • The AI-powered Adjuster Bot which, through deep learning, identifies the probability of repairing or replacing components within those systems; and which:
    • Alerts police and/or medical assistance as warranted (e.g. if airbags deployed)
    • Queries repair estimation and total loss systems
    • Integrates with the insurer’s Direct Repair Program
    • Creates an initial estimate of cost and time to repair
    • Presents a customized video to the driver, describing:
      • Arrival of tow trucks, transportation to a rental car facility, the split of insurer and policyholders financial responsibility; links to download a claimant app

Next up: Adjuster Bots for Connected Homes

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.

Conversation systems and insurance — one experience

Conversation systems and insurance — one experience

To start with full disclosure, I am a huge fan of the Amazon Echo. We have them throughout the house, and have automated our home so Alexa can control most light switches, ceiling fans and more. We play music through them, ask for the weather, schedule appointments, and more.

All my kids are believers from our 5 year-olds on up. It’s fun to hear one of my five year-olds ask Alexa to play the song YMCA and then burst into full song, including the dance. My one personal recommendation. If you have an Echo and children, turn off voice purchases. I found out the hard way.

So I thought I would check out how Alexa does with insurance. My plan is to try all the skills and leverage them into a report. I may even have to purchase one of Google’s new Google Home devices just to compare them in this use case.

So I spent considerable time this morning trying to get an auto quote. Let’s just say the outcome was that I gave up. I won’t name the insurer, as I am sure that their Alexa skill works well in other areas such as information sharing and likely works for others to get a quote, but it sure did not for me. I do want to give credit to the insurer, as they are out on the bleeding edge doing these quotes.

First it asked me my birth year. It heard 1916. That’s not when I was born, but that’s what it heard. I tried to correct it, using the instructions it had provided, but no dice. I gave up and started over, only to be born in 1916 again. This time it was so stuck I had to unplug the Echo. I was surprised, as Alexa’s voice recognition amazes me.

I’m old, but I’m not 101 years old.

I finally made it through on the third try with very careful enunciation. Made it through my wife’s birth year and the fact we’re both married (apparently being married to each other wasn’t important).

Got to the question on what body style. I tried convertible, since, well, it is a convertible. That wasn’t an option. Since the app had prompted 2 door car as an example, I tried it. Um, no. That’s not supported. That seemed odd, but I tried car. Apparently car is OK.

Made it through miles driven a year.

Go to age of the car. My car is a little older, but no antique. However, apparently 12 years old is fatal, as the app crashed with “Sorry I am having trouble accessing your skill right now”.

OK, odd, but wireless sometimes blips, so no problem. Started over for the fourth time.

Worked my way through all the questions, enunciating very, very carefully and got to age of my car.

Yep. Crashed again.

At that point, I gave up and decided to write a blog instead.

Or I could have played a game of Jeopardy with Alexa.

CES 2017: JUST HOW SMART IS AI GOING TO MAKE CONNECTED CARS AND CONNECTED HOMES?

CES 2017: JUST HOW SMART IS AI GOING TO MAKE CONNECTED CARS AND CONNECTED HOMES?
Walking the exhibit halls and attending sessions at the mammoth Consumer Electronics Show, it was easy to identify the dominant theme: AI-enabled Intelligent Personal Assistants (IPAs).
  • Manufacturers and suppliers of connected cars and homes are betting big on IPAs: overwhelmingly favoring Amazon Alexa.
  • Impressionistically, Google Assistant, Siri, Cortana and others trailed some distance behind.
Natural language commands, queries and responses provide a vastly more intuitive UX. And these capabilities in turn make owning and using a connected home or car much more attractive. But there is a deeper potential benefit for the connected car and connected home sellers: developing context-rich data and information about the connected home occupants and the connected car drivers and passengers. This data and information include:
  • Who is in the house, what rooms they occupy—or who is in the car, going to which destinations
  • And what they want to do or see or learn or buy or communicate at what times and locations
Mining this data will enable vendors to anticipate (and sometimes create) more demand for their goods and services. (In a sense, this is the third or fourth generation version of Google’s ad placement algorithms based on a person’s search queries.) Here’s what this means for home and auto insurers:
  • As the value propositions of connected cars and homes increase, so does the imperative for insurers to enter those ecosystems through alliances and standalone offers
  • The IPA-generated data may provide predictive value for pricing and underwriting
  • IPAs are a potential distribution channel (responding to queries and even anticipating the needs of very safety- and budget- conscious consumers)
A note on terminology: the concept of “Intelligent Personal Assistants” is fairly new and evolving quickly. Other related terms are conversational commerce, chatbots, voice control, among others.

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 Evolving Role of Architects

The Evolving Role of Architects

In the last couple of weeks I’ve had the great opportunity to spend time with IT architects of various sorts both inside and outside of the insurance industry. The discussions have been illuminating and offer different visions and futures both for technology that supports insurers and for the future of the architecture function in insurers.

One of the main events that allowed for this conversation was a round table held in London with architects from insurers. The main topics were the relevance of microservices style architectures to insurance, the role of the architects in AI and InsurTech and the future role of architects at insurers. Another event that offered an interesting contrast was the inaugural London Software Architecture Conference which I'll call SACon below (Twitter feed).

Microservices

I won't fully define microservices here but briefly it’s an approach to delivering software where each service is built as it’s own application which can be scaled independently from other services.

Microservices as a way of delivering software was the default approach at the SACon. There were sessions where architects sharing stories about why sometimes you had to work with a monolith or even making the case for not having the services in discrete applications. Meanwhile at the round table the monolith was the default still with the case being made for microservices in some parts of the architecture.

There are use cases where microservices make a great deal of sense, particularly in already distributed systems where a great deal of data is being streamed between applications. Here the infrastructure of microservices and the libraries supporting the reactive manifesto such as Hysterix and Rx* (e.g. RxJava) and indeed one insurer related their use of microservices to support IoT. Others discussed using this style of approach and the tooling surrounding these architectures to launch new products and increase change throughput but in all cases these were far from replacing the core architecture.

For now microservices is not the default for insurer software but is certainly a tool in the box. An observation or two from SACon from those looking to adopt: First it doesn’t solve the question of how big a service or a component is, something architects need to discuss and refine and; Second, microservices needs a great deal of automation to make work, a topic covered in our DevOps report to be published shortly.

Architects and AI

I have a background with training and experience both in computer science, AI and machine learning. One thing that I noticed going to the analytics conferences where AI is discussed is the absence of IT representation – plenty of actuaries, MI/BI folks, marketing folks – was this a place for architects?

Most insurers present at the round table had activity within the organisation for AI. For the most part only data architects are involved in this discussion – AI being distinct from business and applications architecture for now. It’s my opinion that AI components will form part of the wider applications architecture in the future, with AI components being as common place as programmed ones.

Architects and InsurTech

Here is an area where architects can more immediately contribute in a meaningful way both in reviewing opportunities and unique capabilities from InsurTech firms and in discussing integration where acquisition rather than investment is the goal.

The challenge here of course is the age old challenge for architects – to have a seat in the discussion the architect function needs to demonstrate the value it can bring and it’s internal expertise.

Finally, one amusing discussion I had was with a few architects from startups. As I discussed legacy systems they also related seeing legacy systems in their organisations – albeit the legacy systems were 2 or 4 years old rather than 20 or 40 years old. The intriguing thing here was the reasons for them becoming legacy were the same as insurers – availability of skills, supportability and responsiveness to changing demands. It may hearten architects at insurers that start ups aren’t immune to legacy issues!

 

 

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.