Tag Archives: connected car

Connected Car Data: Moving Past the Hype

It is still early in the evolution of collecting and using mobile data from drivers and their vehicles, but many large industries with huge stakes in the outcome are participating and paying close attention.

The Current Conundrum: Many Contestants, Few Prizes

Formed in 1995 as a collaboration between GM, Electronic Data Systems and Hughes Electronics, OnStar was almost certainly the grandfather of the connected car. In 2002, Progressive insurance and General Motors Acceptance Co. partnered to introduce the first usage-based insurance (UBI) program in the U.S. Using GPS and cellular phone tracking capabilities, the Snapshot program offered discounts to low-mileage drivers on the program. What followed – and continues to evolve exponentially – was an explosion of business models, technologies and programs for use in the insurance and commercial fleet industries, with applications ranging from underwriting, claims and fraud to accident management, driver safety and behavioral modification.

While the earlier and still prevalent telematics programs rely on a small communications device connected to the vehicle on-board diagnostic (OBD) port, the proliferation of smartphones has enabled the elimination of these device costs and provided more convenient mobile solutions. In addition, car makers have begun installing software and communications in new-model vehicles, which further simplifies the user experience and expands program capabilities, integrating them into dashboard screen interfaces. By 2020, more than 90% of new cars will transmit telematics data, according to the Auto Care Association. More recently, intermediary technology providers known as telematics service providers (TSPs) have emerged to offer consumers and insurance carriers turnkey connected car programs, and several industry information providers have introduced telematics data exchanges (TDEs), which consolidate drive and vehicle data from a variety of car makers and provide insurers with uniform, normalized data.

This connected car evolution from OBD to embedded to mobile to hybrid is enabling more than just new insurance products; it is transforming the business of auto insurance. Automotive original equipment manufacturers (OEMs), insurers, TSPs, telcos and information providers all seek to monetize the exploding streams of connected car data – but no universal or dominant models have emerged as yet.

Secret to Success: Partnerships

The emergence of insurtechs, with their innovative application of new technologies to solve age-old insurance challenges, along with the implied threat of those solutions to traditional insurers has dramatically changed the way insurance executives think about partnerships. Today, strategic technology-centered partnerships are enabling insurers to transform their core processes and expand into more markets than ever before. In fact, many of the largest carriers have formed or joined dedicated insurtech venture capital funds and accelerators, whose portfolios potentially represent a double win, financially and in process improvement.

In the area of the Internet of Things, of which connected car is a major subset, inter-industry partnerships and alliances are critical – indeed mandatory – for success. Even one-time competitors are seen to collaborate where both parties do better together than separately.

Partnerships between ecosystem participants are inevitable, and desirable – with each segment leveraging its core strengths and expertise in support of mutual business objectives and their common customers. In the case of connected cars, those are the owners, drivers and passengers as well as the policyholders.

See also: 5 Steps to a Connected Car Strategy  

Aligning Interests by Focus on the Common Customer

By focusing on the common customer, each participating segment partner can “win,” defined as achieving their primary strategic objectives. In the case of auto insurers, winning means improving and strengthening the customer experience and relationship while improving underwriting and operating results. For car makers, winning means lowering the total cost of ownership for car buyers – a fundamental strategic objective that has recently emerged – and reinforcing brand loyalty with car buyers and owners. Furthermore, lowering total cost of ownership is a strategic objective that auto insurers embrace, as well.

For intermediaries such as TSPs and TDEs, winning means adding significant value to existing relationships with insurance company clients and adding new customer segments and product revenue streams to their businesses while lifting and reinforcing brand recognition across all segments.

And let’s not forget one more important reality – every connected car program, regardless of the participants, requires acceptance by the same common customer.

Solving the “Many to Many” Challenge

With the increase of advanced driver-assistance systems (ADAS), connected cars and the emergence of autonomous vehicles, data experts, along with OEMs, insurers, brokers and agents, are joining forces to bundle whole-life vehicle costs together to offer new mobility solutions such as car subscriptions, car sharing and other short-term vehicle use models to appeal to changing consumer needs.

The challenge presented by this proliferation lies in the wide range of devices and the variations in hardware and software technologies that are broadcasting data in non-standard structures. This lack of uniformity presents what LexisNexis Risk Solutions calls the “many-to-many” challenge. The torrent of inconsistent data from disparate data sources presents numerous serious impediments to consumer program portability and driver scoring calculations and will eventually impede market confidence and growth of these programs.

How this data is managed and converted from raw driving data into reliable rateable factors for use by auto insurers is crucial in determining how OEMs and insurers will collaborate to support the future of connected car programs for consumers within both insurance and auto industries.

The solution that presents itself is a central hub that is capable of ingesting, cleansing and contextualizing driving data regardless of data source to resolve the many-to-many problem. With access to the entire insurance market for both insurers and OEMs, the potential exists to ultimately transform the mobility-insurance market into one connected ecosystem to the benefit of all participants – including consumers.

Telematics Data Exchanges to the Rescue

As connected car programs continue to evolve, the challenge insurers will increasingly face is that the number of sources and collection methods for telematics data will continue to grow as programs evolve and all of the resulting data will need to be standardized. Telematics data exchanges, such as the LexisNexis Telematics Exchange, are able to help insurers and OEMs navigate evolving technology by providing them with normalized data and advanced insights that are most relevant in growing their business.

To succeed, these telematics data exchanges will have to be developed and managed by trusted, well-established information providers that already do business with a majority of insurers, that have a deep understanding of the automotive industry, that have sophisticated and powerful data processing assets and that have a culture of innovation as well as a corporate commitment to data privacy and security. When you consider all of these qualifications, there are really only small handful of companies that qualify.

See also: Advanced Telematics and AI  

Telematics data exchange providers enable insurers, auto manufacturers and drivers to benefit from the evolution of UBI programs. These platforms provide insurers with driver scores through a single point of entry and leverage existing system integrations, regardless of each customer’s data collection preference. They also enable OEMs to collect and seamlessly integrate vehicle data into insurers’ existing UBI programs. In addition, auto manufacturers can gain valuable insights, improve return on investment (ROI) and access data analytics expertise that provides them speed to market to provide value-added products and services to their customers. OEMs will also have a practical opportunity to encourage safe driving and enhance customer ownership experiences.

Everyone Wins

In summary, professional management of connected car data and the wide variety of telematics solutions will enable consumers to confidently share their driving scores across a range of carriers and maximize the benefits of participation in current and future programs.

In addition, it will allow the claims process to evolve from its current state to instant crash notification, touchless claims and eventually to claims mitigation. Telematics data exchanges will help to build customers’ loyalty to their chosen carrier and OEM brands. Additionally, a telematics exchange will enable participants to innovate and quickly execute by providing the vital ingredients and processes required to fast-track transformation at scale and deliver real value to customers. Successful telematics exchanges will bring together OEMs and insurers for the benefit of consumers in their seamless digital lives.

The authors wrote this article in the run-up to the Connected Claims USA Summit in Chicago, where both spoke this week. 

5 Steps to a Connected Car Strategy

We are awash in data, and as modern life becomes increasingly connected it is going to quickly turn into an avalanche. Analysis of driving behavior is already challenging the fundamentals of insurance pricing, and that is just the tip of the proverbial iceberg.

The questions that the industry needs to answer today are both simple and complicated:

  • How do we take full advantage of all the data and related insights?
  • Why haven’t we reached the scale in market that has been predicted?
  • What have been the challenges?

See also: Cybersecurity Holes in Connected Cars  

In my view, there are five fundamental steps that need to be studied and addressed for an organization to take full advantage of the myriad opportunities that have been created by this era of connectivity.

  1. Capture and store individual driving data: Of course, it all starts with the capture of data — that’s fundamental. While data makes up less than 20% of the entire effort, if you begin with high-quality components, the opportunity for success is limitless. Well-sourced data provides a foundation to better understand your customers and how you can help. Using that level of meaningful data, you can better price your products, deepen engagement with consumers and improve both your economics and your customers’ overall satisfaction with the claims process. In today’s ecosystem, there is both high-quality, granular data as well as the ability to tap into the many data sources that exist.
  2. Predict individual driver risk and future losses: We are in the business of insurance. We are responsible for both understanding and predicting the behaviors that cause accidents as well as the expected costs of loss that are incurred. This is no small task. It requires models that leverage telematics data and loss data. This kind of meaningful data must be sourced from the same time period, so our models can identify the driving behaviors that are causing those accidents, as well as the costs of each incident.
  3. Streamline rating and program operations: Your rating and program operations need to be refined, streamlined and optimized for a different environment — this is a new era. You must know when and why there are issues with your customers and address them appropriately and quickly. These programs must be properly managed. You need to clearly and consistently communicate with your agents, stakeholders and partners, as well as your consumers, especially as your program grows.
  4. Optimize driver safety and improve driving experiences: The feedback from long-term, trusted partners as well as from your customers can offer early indications that provide the guidance needed to create or expand a successful new service. To make each driver safer, while improving the driving experience, you must learn and respond to what the consumer data is telling you, specifically the trends of value that provide real insight. Dig in and leverage consumer research, listen to the customer — specifically what they like and don’t like – and, above all, pay attention to the user interface. Whether that’s the expansion of a new offering or deep-sixing a new product capability, you need to be willing to change and adapt your vision to the qualitative and quantitative feedback.
  5. Uncover deeper insights: This isn’t just about pricing; as an industry we are barely scratching the surface of this massive opportunity. It’s important to look for opportunities that will move this effort beyond pricing. Analyze the data itself, as well as the feedback from your customers, to anticipate what the customer is going to want in the future and how the data can optimize your business. Use the data to transform your claims process, provide incentives for better driver behavior and identify fraud before it happens. This kind of approach will lead to more of your customers appreciating and valuing your brand approach.

See also: Why Connected Cars Are So Vulnerable  

We have spent a tremendous amount of time and resources trying to anticipate exactly how much this industry will really be disrupted. We can no longer rely on our old-school approaches or the reliable case studies we were taught in business school. I urge everyone to not just consider how this industry might change at the macro level. This isn’t black and white – this requires a nuanced quantitative and qualitative approach. I believe that almost all our processes will be disrupted, fueled by greater connectivity and changes in consumer mobility. It is time to get to work.

How to Reinvent P&C Pricing

The answer to P&C pricing may lie in the insurance credit score. That is basically a set of algorithms applied to data from credit reports that provide guidance for pricing and underwriting personal lines insurance. Although the score 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 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. The correlation just doesn’t seem to make much sense. But statistically there are correlations, which in general have passed regulatory review.

See also: Credit Reports Are Just the Beginning  

Insurance credit score controversies are 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 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 that provide the same or better lift as the old data and models that 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 with 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 similar device) controls the home’s HVAC systems, correlated with setting security alarms before 11 p.m. Or, electricity and gas consumption, correlated with use of video streaming services on weeknights. Or, the number and type of connected appliances, correlated with the number of functioning smoke, carbon monoxide 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)? What are the business’ use of social media and messaging apps, correlated with the degree of supply chain digitization?

See also: Why Credit Monitoring Isn’t Enough  

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 when he was asked about privacy and said, Nope, you don’t have any.

The Insurance Model in 2035?

On June 1, there was a high-level conference organized by the alumni of the three most prestigious business schools in France, HEC, ESSEC and ESCP Europe, whose title was “How to run an insurance company in the context of digital, societal and regulatory transformation?” The most burning issues were addressed with depth and perspective, including issues relating to the impact of digital revolution, the clash of generations and the new playground imposed by Solvency 2 on insurance.

The three major French insurers, AXA, Allianz and Generali, compete to operate as quickly as possible while the digital transformation of their business lines and organizations face an environment of increased uncertainty and threats from the emergence of new competitors—GAFA (Google, Apple, Facebook and Amazon) or startups—which have mastered the art of customer relationship.

Should we fear Google or an insurtech?

According to many insurers, GAFA may be strong competitors for insurance companies. Indeed, they have undeniably strong assets: a market capitalization among the highest, expertise not only in customer experience but also in algorithms and data and a very high level of agility. What would be similar to Google – the first advertising agency of the Internet – in a rich yet complex industry like insurance, which is highly regulated and whose confidence is only acquired after many years and millions of dollars of investment?

See also: 8 Exemplars of Insurtech Innovation  

The insurtech? Besides Oscar and Lemonade, which are true insurers, the vast majority of insurtechs are brokers that cannot work without an insurer’s support. And even if some startups succeeded, it would take time, and they would not be independent for quite some time.

Where is the real threat? In 2035, we might see a world with little risk

As we know, the heart of the insurer’s business is risk management. However, technological innovations will likely reduce risk levels significantly.

According to a KPMG report on autonomous cars, there could be as much as an 80% reduction in car accident frequency by 2040 if auto and safety trends continue. Another example suggests a scenario where the personal auto insurance sector could shrink to 40% of its current size.

According to Ray Kurzweil, director of engineering at Google and futurist, we will reach a point around 2029 when medical technologies will add a year to people’s life expectancies. Some believe that the adoption of these innovations will be hindered by people’s refusal to allow invasion of privacy. However, another could argue that, who would hesitate to provide more personal data, such as DNA, if that person was guaranteed, in exchange, an additional 20 years of life?

Connected homes that are bristling with sensors inside and out and that also populate smart cities of tomorrow, could contribute to a decline in claims by 43% by the year 2025, according to McKinsey.

Whether for life or P&C, over the next 20 years the risk level will significantly decrease, which will result in a drastic reduction in the value of the insurance market.

The twilight of insurers?

Can we therefore announce the end of the insurance industry? Certainly not. However, the share of insurance and the income of insurers could drop significantly. To maintain the same level of business will require finding new sources of profit.

From insurers to “preventers”

Indeed, the insurer of tomorrow will be one that will transform its business model around prevention and become a prevention specialist. The decrease in risk will become a major challenge that will require considerable investments in people, infrastructure and technology. New prevention services charged on a subscription basis will likely be the new source of margin for insurers. One can imagine that the new standard of performance for the new model of “Prevention as a Service” will be the ratio of prevention fees to insurance premiums. Then, we will see the complete reversal of the traditional business model.

See also: Insurtech: One More Sign of Renaissance

The question that then arises is: Should a manager of an insurance company not make the leap and skip the step of digital processing in an insurance context to strive for refocusing its business model around prevention?

Connected Vehicles Can Improve Claims

Personal auto insurers have traditionally been more reactive than proactive in a slowly changing industry. However, that approach may no longer be adequate as vehicle technology accelerates at a pace the insurance industry is unaccustomed to embracing.

To date, the focus of personal auto insurers has been on the underwriting impact of driver-assisted technologies that can self-park, maintain their lane and even force the vehicle to stop to avoid collisions. Insurers are continually fine-tuning their underwriting algorithms to align with such decreasing risks. However, insurers need to broaden their scope and move beyond tweaking rates. Let’s face the truth: Automobile claim processing relies on antiquated theories and techniques that are costly and inefficient and can produce faulty outcomes.

See also: Telematics: Because Accidents Happen  

Up until the 1980s, adjusters actually went out to the accident location to canvass the scene, interview witnesses, measure skid marks and look for obstructions to vision — all for the purpose of making a sound and well-researched liability decision. To cut costs, insurers eliminated scene investigations and relied almost solely on driver statements and physical damage to determine liability. The process works fine in a clear liability situation like when a stopped vehicle is rear-ended. But it doesn’t work so well in a multiple-car pile-up or an accident at an intersection. How often do we hear from the driver statements like, “He came out of nowhere,” or, “I thought I had the green light,” or, simply, “I don’t remember”? These same individuals have a vested interest in being found free of fault, in fear of adding points to their driving record and seeing increased rates. How do we expect desk-bound adjusters to make the right decision with facts and circumstances such as these? Liability adjusters futilely spend an inordinate amount of time searching for clues, hoping to uncover the truth when faced with conflicting stories or facts.

Today, there are cameras everywhere and telematics available on almost every vehicle. The University of Michigan’s MCity is testing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications that will soon be prevalent in our environment. Just as autonomous vehicles are using these cameras and sensors to alter the vehicle’s behavior, the V2V/V2I images and data can record the facts associated with the accident. This data can be consolidated to confirm and recreate the scene leading up to an accident.

Information that adjusters rely upon will suddenly become objective, rather than subjective or tainted by guesstimates. For example, in an accident where a pedestrian darts out from between parked cars and is hit by a moving vehicle, the data will answer many questions. (How fast were you traveling? At what point did you apply the brakes? Did you try to swerve to avoid him? Were any vehicles or vegetation blocking your vision?) Without a witness, this type of accident is difficult to assess today, and the task is even harder to assess when the pedestrian is a child. Utilizing V2V and V2I data to validate the accident facts can make the process much less painful and much more equitable for all involved, especially for anguished parents who may not have seen their child dart into the street.

See also: Predictive Analytics, Text Mining, And Drug-Impaired Driving In Automobile Accidents  

While not everyone wants to share their day-to-day driving data with their insurers, insurers could offer customer discounts or deductible waivers for sharing the last several minutes of data leading up to the impact. This may be more palatable to many conscientious consumers, who see this option as effectively protecting them from the potential of being falsely accused of liability.

Data is ubiquitous, waiting to be harvested and used to improve liability decision making. It’s time for insurers to initiate interactions with auto manufacturers and transportation infrastructure suppliers to create industry standards for sharing V2V, V2I and telematics data that can result in dramatic, positive changes in how claims are handled and negligence is determined. Insurers all want to make accurate liability decisions and consumers deserve a fair outcome. We finally have the tools available to ensure just that.