Customer journey mapping for a CIO

Customer journey mapping for a CIO

If you’re like most CIOs, your firm has embarked on the latest craze – customer journey mapping.  I’ve blogged about this before.  It’s a terrific exercise – intended to identify how customers engage with your firm through every type of interaction – personal, machine, or paper.  Most are focused on optimizing the interactions between the policyholder and the insurer; some include optimization of the agent experience, and some are starting to look at expanding the experience to look at how to embed the insurance experience in non-insurance aspects of an insureds life.  (See FIGO for a great example).

Some firms have hired third party consultants to help with this exercise; some have even put a new position in place – a Customer Experience Officer – someone who looks across the traditional siloes of underwriting, claims and finance to craft a holistic experience. 

As carriers go through this exercise, demands are being placed on the IT team. Here’s a few ways you may be asked to participate:

  • Data and reporting– Part of understanding the customer journey is tracking it.  Understanding where the biggest interaction points are, and where the biggest pain points are is the first step in improving the experience. You may be asked to install tracking software on the website (if it’s not already there).  Third party data and AI may play into new segmentation schemes as teams are looking at new ways of doing dynamic segmentation (See my report on this topic)  You may be asked to add new reporting or analytics tools as the team looks at using predictive modeling to identify next best action. And you’ll be asked to measure the progress of the new journeys through new reports and new metrics such as a customer friction factor.
  • Workflow and Task Automation – Much of customer journey mapping is figuring out how to operationalize the new journey.  Once the customer experience has been defined, the hard part is to deliver on it.  If you are reliant on people to deliver a consistent experience, you leave yourself open to error.  Your team may need to spend much more time defining business rules and implementing workflows to deliver the experience. If you are one of the insurers that has not yet automated this, you may need to consider adding some additional technology.  (This has actually been one of the major drivers of core system replacement).
  • Customer Communication – Insurers are looking at eliminating the jargon and simplifying the message. This may mean redoing forms or creating new forms.  That’s not a huge deal.  But where we see more effort is finding new ways of communicating with customers.  Text, mobile applications and video are all growing ways of communication.   Here’s a great example of automated video communication to deliver a personal touch with no people involved.  Push communications, text or phone messages letting the claimant know their check has been issued, for example, can reduce calls to the call center while improving customer satisfaction
  • Omni-channel access – Smartphones are on track to bypass desktop computers as the number one way to access websites.   You’ll need to make the website mobile-friendly.  But you also may need to put in a call center – especially for those insurers who are looking at adding a direct or semi-direct channel. 
  • Cool stuff – As insurers start going down this path and get more comfortable being creative, they often look to add more ‘cool stuff’.  Gamification is one of the newer areas – using game techniques to drive engagement and to drive behaviors.  Drones are reducing the need for scheduling inspections.  Video chat for first notice of loss can reduce fraud and improve satisfaction.  There are many tools – and many InsureTech startups playing in this space. One last area that can be kind of cool – the user interface.  If you don’t have formal skills in this area, definitely use an outside consulting firm to help with this. UI design is fairly complex and makes a huge difference in the customer experience.  All of this cool stuff requires integration. One note, while the partners out there likely all have open APIs,  your team may end up spending more time than anticipated making sure your own systems can integrate and send data and service calls back and forth.
  • An agile organization –  As insurers become more skilled at understanding how to tweak and enhance the customer journey, speed becomes even more important.  Creating an innovative, agile organization  is a critical aspect of delivering quickly.  If you haven’t chatted with Mike Fitzgerald on innovation, or Colleen Risk on shifting to an agile development process, now might be the time.

In a highly fragmented industry with excess capital and declining rates, insurers are looking to building a solid customer experience to drive growth and retention.  Journey mapping is one of the tools being used.  Time to step into the fray and get involved. 

The Race to Find the Next Insurance Credit Score (or How, Maybe, to Reinvent P/C Insurance Pricing)

The Race to Find the Next Insurance Credit Score (or How, Maybe, to Reinvent P/C Insurance Pricing)

What is an insurance credit score? Basically it is a set of algorithms applied to data from credit reports which provide guidance for pricing and underwriting personal lines insurance. Although it has been a source of political and regulatory controversy over the years, the use of insurance credit scores is now widespread.

Much of the controversy has been over possible disparate impacts on various societal groups. But a root cause of the controversy has been the non-intuitive relationship between a given person’s use or misuse of credit on the one hand—and that person’s probability of incurring insured losses on the other hand. It just doesn’t seem to make much sense. But statistically there are correlations, which in general have passed regulatory review.

Insurance credit score controversies now ancient history (i.e. were settled before most millennials graduated from high school).

But suddenly something interesting is happening.

The race is on to find the next insurance credit score—and the winners (if there are winners) will gain a pricing (and underwriting) edge.

There are only two requirements to enter in this race.

  1. You have to forget about all the kinds of data and information that insurers have been using to price and underwrite risks.
  2. You have to use your digital imagination to find some new data and models which provide the same or better lift as the old data and models which you have just thrown out the window. (Lift is the increase in the ability of a new pricing model to distinguish between good and bad risks when compared to an existing pricing model.)

So what kind of new data might a digital imagination look at?

  • For personal auto, connected cars will provide a rich data set to mine. How about whether a car is serviced at the manufacturer’s suggested intervals (correlated with whether the car is serviced by a dealer or by an independent repair shop)? Or the use of a mobile phone while the car is in motion (correlated with time of day, precipitation, and whether satellite radio is also playing)? Or use of headlights during daylight hours (correlated with the frequency of manually shifting gears in a vehicle with an automatic transmission).
  • For homeowners insurance, connected homes could supply all types of new data. For example, whether Alexa (or other IPA) controls the home’s HVAC systems, correlated with setting security alarms before 11 pm). Or, electricity and gas consumption, correlated with use of video streaming services on week nights. Or the number and type of connected appliances, correlated with the number of functioning smoke, CO, and moisture detectors.
  • For commercial liability insurance, telematics and IoT will be the key data sources. Does a business with 10 or more commercial vehicles use both fleet management and telematics solutions? What mobile payment options are offered (correlated with dynamic pricing capabilities)? The business’ use of social media and messaging apps, correlated with the degree of supply chain digitization.

Of course obtaining a lot of this data will require permission from policyholders—and even with permission these methods may raise social or political issues. But premium discount and loss control incentives for telematics programs have proven effective. And for better or worse, Scott McNealy got it right in 1999.

The Great AI Wars

The Great AI Wars

Last week saw one of the last big players make their position in machine learning and AI clearer at Apple's WWDC event with the launch of their machine learning options. These days you're not a credible large cloud provider if you don't provide some interesting APIs around machine learning and AI with the likes of Google, IBM, Amazon, Microsoft (Azure), and Alibaba (Aliyun) to name but a few. Apple's discussion focuses on being able to embed these technologies on the device with the Apps rather than perhaps the building of the models and the execution – much less focus on pushing data into the cloud.

The war I speak of in the title however, is not some dystopian future where humanity fights for survival but rather the current war over talent that enables the use of these technologies. Insurers going through digital transformations and looking deeply at their analytics are finding they are competing with ever more unlikely companies for talent including rising InsurTech firms as observed in previous blogs. The good news is that basic machine learning capability and training is increasingly available as the democratisation of machine learning continues apace – in fact if you look at Apple's documentation this discusses the ease downloading and converting models and integrating them to Apps rather than the nuances of various training algorithms.

Machine learning isn't new to insurance with coverage in our predictive analytics reports courtesy of Nicolas Michellod and case studies. It is clear however that these tools and techniques are increasingly being embedded into solutions throughout the insurance eco-system and beyond – and they are raising customer expectations. A discussion on what this means for core systems is given in my recent report here, as well as a discussion on what this means for new front end opportunities with the rise of chat bots in our discussion on conversational systems and a broader discussion on the differences in designing intelligent systems versus programmed ones is discussed in designing the aware machine.

While AI is a battleground for the big players for insurers it is becoming an increasingly accessible source of new approaches and automation – both an opportunity to better serve customers as well as cut costs. The ease with which machine learning and AI can be embedded into simple applications now will only increase adoption and there are small things any insurer can do. Of course if you want to go much deeper, as pointed out in this Harvard Business Review article, if your company isn't good at analytics, it's not ready for AI. I disagree a little with the authors perhaps, we're in a world where anyone can do something – one can just download and convert a model and incorporate it into our systems as pitched by Apple.

For those looking to go further, the good news is there are many vendors that can help, and many partners too of all shapes and sizes. I'm happy to say the InsurTech investments in the industry are only increasing this number and the opportunities for applied AI in insurance. Further, there are many conferences discussing both analytics and the rise of AI – if you're attending or looking for them do get in touch, I or my colleagues would love to discuss.

Reflections from the Digital Insurance Agenda, Amsterdam

Reflections from the Digital Insurance Agenda, Amsterdam

Earlier this month Craig Beattie and I ventured off to Amsterdam to attend the Digital Insurance Agenda (DIA), where we also delivered a keynote. This was the event’s second year and, within just 12 months, it has grown significantly to around 850 people – attracting insurers, innovative technology players (from both the establishment and budding entrepreneurs), and investors from across Europe and beyond. The format is a sprightly mix of keynote presentations, panels, and live demonstrations. And, like last year, it was another great mix of people and ideas, each focused on driving change in customer engagement across the industry through technology.

(Venue: Gashouder at the Westergasfabriek. An impressive venue – with Celent on stage somewhere up there at the front :-))

Key take-aways for me were:

  • Distribution and front-end engagement remains a strong area of focus for innovation. However, unlike recent history where investment has been heavily channelled into mobile or touch-enabled browser experiences, the presence of chat and other app-less modes of interaction were strongly evidenced throughout most of the live demos. This has been a hot trend over the last 12 months, and where Celent has explored both insurer and consumer attitudes towards it (see Celent report: Applying Conversational Commerce to Insurance: Aligning IT to the Machine World). Given the issues that many insurers have had with trying to encourage customers to download their apps and engage with them through them, it’s not hard to see why 'smart chat' is being pursued so aggressively.
     
  • Heavier focus on the use of data for risk profiling and the application of emerging AI techniques (beyond chat use-cases). Personally, I find it incredible just how low the entry barriers have become for experimenting with data and AI. The perfect storm of huge compute power via the cloud, open-source and pay-per-use models for advanced technology enables those with relatively modest means and a great idea to get started. For me, this continues to be one of the most interesting areas in our industry for mining value. It’s also an area that insurers still find a challenge (see Celent report: Tackling the Big Data Challenges in Global Insurance: Differences Across Continents and Use Cases).
     
  • Celent has been tracking the development of innovation partnerships across the industry for a number of years (see Celent report: Insurer-Startup Partnerships: How to Maximize Insurtech Investments). At DIA, it was easy to see this in action. The vast majority of firms presenting were not a direct threat to the industry at large, but instead were exemplars of better ways of doing things through the use of smart technology. It’s not hard to envision that a few of the firms demonstrating at DIA will walk straight into pilots following the event.

The event was closed with a keynote from Scott Walcheck of Trov. Scott shared openly some of the progress that they have been making – which, to me, feels impressive. For example, they now have ~60-70 engineers working on the team and claim to be growing revenue by ~44% month-on-month (albeit from a starting position of zero).

Out of all of the insurtech start-up activity globally, there are just a handful of firms (in my opinion) who have the potential to really shake things up – and Trov is one of these.  They now have the capital, the engineering capacity and the partnerships to do some truly incredible things – if they choose to.

I also found it interesting to hear that they have started to evolve their business model into three focus areas, being: (1) Trov as a direct brand; (2) White-labelled Trov; and (3) Insurance-as-a-service, where they will rent their platform to partners – plus with an aspiration to evolve it into auto, home and other lines.  Given Celent’s focus on technology research across the industry, this last model-type is of keen interest. Trov’s engineering capacity is already a similar size to (and in some cases larger than) many mid-to-small insurance carriers. It is also larger than some of the traditional independent solution technology providers out there. Could they be the next big technology player on the scene in addition to their existing branded business?  Only time will tell, but it is clear they are already demonstrating how insurtech represents a new way of delivering insurance product development.

For more commentary on DIA, see Craig Beattie’s Moments on Twitter.  Also, keep checking the DIA website as they will shortly release some of the videos from the event.

Closing the deal with e-signature

Closing the deal with e-signature

E-signature has become such a part of my life that I am surprised when I am asked to provide a wet signature. I sign for credit card purchases, deliveries and legal documents, even my tax returns (!), using a click or a digital signature pad. But, if I want to change my beneficiary for my life insurance, I have to download a .pdf, sign the document with a pen, and mail it to the insurer. Insurance has been a slow adopter of e-signature. However, as the process of buying life insurance and receiving post-issue service is becoming increasingly more digitized, insurers are working to remove paper from everyday processes.

The adoption of e-applications, web portals, and mobile technology is helping to drive the change, but it is my belief that it is primarily driven by customer expectations set by other industries offering easy-to-use digital processes. Consumers expect companies to be easy to do business with and will choose the company they purchase goods or services from based on the ease of use. E-signatures provide a way to offer a digital experience that is easy to use, fast, and secure.

In our new report, Putting a Lock on Straight Through Processing, my colleague Karen Monks and I profile 11 providers of e-signature technology for insurance. This is the final report in a series that began last year.  During the year, we looked extensively at new business acquisition and the technologies that power it. We wrote reports on solution providers for illustrations, e-application, and new business and underwriting in addition to e-signature. Along with the vendor reports, the series included two benchmarking reports and a report in which insurers compared their level of automation to Celent's automation capability matrix to determine if they are minimally, moderately, or highly automated.  

With the increased emphasis on cycle time and cost, e-signature is being increasingly being adopted as a way to check the box on making processes fast, flexible, and efficient. E-signature software frequently integrates with other solutions to support new business acquisition as well as post-sale service.

The ability to collect an electronic signature for a new application at the time of sale providing the legal authorization to obtain underwriting requirements and evidence from third party providers has enabled straight-through processing and the ability to provide a decision to the applicant within minutes, instead of weeks.

Common e-signature use cases for life insurance:

  • New policy application
  • Disclosure delivery
  • Agent licensing and appointment
  • E-delivery of policies
  • Beneficiary change and other policy servicing
  • Premium payments

Life insurers that investigate e-signatures will be pleasantly surprised by how quickly and relatively inexpensively e-signature can be implemented as well as how easily and securely a paper signature process can be automated. I am a big fan, as I’m sure you are, of less paper and more automation!

 

A cautionary tale of legacy technology or how to avoid a major meltdown in your organization

A cautionary tale of legacy technology or how to avoid a major meltdown in your organization

Were any of you flying Delta from April 5 to April 9?  If so, this story will be no surprise to you.  For the rest of you, you may remember it was spring break and terrible weather pounded Atlanta. The severe weather caused a five–day meltdown across Delta’s flight network and over 4,000 flights were cancelled. During those five days, Delta struggled mightily with two basic functions of its business – flying airplanes and accommodating passengers. The weather is, of course, out of Delta’s control, but the response and the ensuing chaos was amplified by something insurers understand all too well — the lack of modern technology. 

According to a Wall Street Journal article, the root of the problem was a telephone busy signal. An internal investigation found the biggest problem was that Delta’s 13,000 pilots and 20,000 flight attendants calling in for a new assignment couldn’t get through to the people in Atlanta who were rebuilding the airline schedule. Computers told gate agents rescheduled crews would be there, but the flights would end up canceled for lack of a crew member who was lost in Delta’s communication fiasco and unaware of the assignment.

I have to confess, my first thought when I read this article was to wonder how on earth a major company like Delta can be so lacking in modern technology. My next thought was wow, this is true for the insurance industry as well. While life insurance companies don’t have the challenges of rescheduling thousands of flights, a negative change in the stock market can create thousands of customer calls. And when a major catastrophe occurs, property casualty insurers can also be inundated by phone calls.

Delta’s response was to double the size of the crew-tracking team, dramatically increase the number of phone lines by June; and hope to have a system which will be able to send crews information about their trips electronically by August.

Rather than relying on hope, following are suggestions for insurers so that they can avoid the type of meltdown experienced by Delta:

  • Self-service portals or apps where customers can check their balances, make changes to their policies, and communicate with their insurer.
  • Chatbots that can provide answers to questions without human interaction.
  • Text messages to keep insureds informed.
  • Webchat to allow communication via the website.
  • Omni-channel support to allow seamless switching between devices.

We can’t control the weather or the stock market.  Unexpected events will happen.  But, how an insurer responds to them can have a significant impact on the customer experience and the customer long term relationship with the insurer.  In a hyper-competitive market, customer experience is a key differentiator.

If you are interested in building a better customer experience, here is a report you may find interesting, Standing Out in a Bland World: Global Life Insurance Customer Service Strategies.

The Death of Processes and the Birth of High Frequency Underwriting

The Death of Processes and the Birth of High Frequency Underwriting

Let’s consider a car insurance market where all new contracts go through online aggregators. Let’s assume all the car’s information (vehicle brand, type, category, plate number, etc.) and potential insured data (driver’s name, age, address, historical claims, etc.) is standardized, packaged to include all relevant information needed by an insurer to price a motor insurance risk, and instantaneously electronically transferred to an aggregator as soon as the car is purchased (payment triggers the packaged data transfer, quoting, binding, and contract sealing). With today’s technology and connectivity, this quote and bind process can be done in less than a second.

In insurance, a process is a series of tasks to turn raw data into valuable information to make a business decision. In other words, a process requires time between its inception and its end and almost always human intervention. Indeed, today’s quote and bind process captures relevant data about a car and a driver through a questionnaire. Then insurers need to evaluate the risk involved and price it before a quote is given and potentially accepted by the driver. Even though many digital interfaces can be offered to perform the whole process, the potential customer still has to respond to a set of questions and click on a button to accept a proposal. In our extreme digital example, all the tasks are reduced to a minimum of time and fully automated; the driver doesn’t even have to fill in a questionnaire since all relevant data is packaged, transmitted, analysed, and sealed into a new car insurance contract in less than a second as soon as the car purchase is triggered. Can we still call it a process when there is an instantaneous business decision (underwriting and pricing) made and an outcome (contract sealed) produced, and this without human intervention? Well, I think with extreme digital, processes as we know and define them today are dead.

The next question is: How can insurers differentiate in a world where customer engagement is nonexistent? One might think that it would be price. Actually, it is speed. Indeed, I think that the ability to match a specific demand faster than competitors will allow an insurer to win the deal. To do so, they’ll need to support what I call high frequency underwriting in order to have their quote matched with the demand side within milliseconds (faster than competitors’ quotes). Indeed, for the same price, the fastest proposition will win the deal.

Now, let’s get back to my initial assumption: all new contracts go through online aggregators. Let’s consider an aggregator owned by an insurance player. If this insurer can get time advantage versus other insurers feeding its aggregator, it will be able to adapt its quote to optimize its margin using competitors’ information and leverage the speed advantage, even though it is about milliseconds.

This scenario is not unrealistic, because high-frequency trading is about milliseconds. So, who knows, maybe one day we will see insurers not thinking much about processes, but focusing more on speed.

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