Tag Archives: telematics

Tomorrow’s Insurance Is Connected

Insurance is, at its core, five things: underwriting and pricing risk, selling and distribution, claims adjudication, servicing and, finally, investment management. Of course, there are hundreds of other skills and important areas, but these are the five central pillars of any insurance company.

Technologies are emerging that enable omnipresent, real-time connectivity between the people and businesses being insured and their insurers, and that is fundamentally changing the business of insurance. Here’s how.

Underwriting: Retrospective to Prospective

Underwriting and pricing is all about data and information at both the macro and micro level. Understanding socio-economic market trends, segmenting and accurately predicting how those may move and change is important. But the most critical data of all is at the individual customer level – the person or business you are about to insure. The more you know about their risk profile, the more accurately you can price their insurance and therefore the more competitive you can afford to be in selling and marketing.

Imagine if an insurer knew virtually everything about the behavior of the insured. Not only where they live but how they live, how they drive, their health and their daily habits. And imagine if the insurer had access to all the historic and predicted natural risk data about where the insured lived and worked and traveled. And imagine if there were computer programs powerful enough to gather, store and use this data to create an accurate and dynamic risk profile of the insured. No need to imagine – those capabilities already exist and are being refined and expanded. The debate over whether ZIP codes or credit scores are a fair and proper proxy for insurance risk will soon be moot, along with all the other retrospective information that has until now informed the underwriting process.

See also: Ready for the Fully Connected Future?

Usage-Based Insurance Evolves to Hyper-Personalized Insurance

A good example of this evolution in insurance is the well-publicized auto insurance product known as usage-based insurance (UBI), which is enabled by telematics – the joining of two sciences, telecommunications and informatics such as computer systems. In its infancy, UBI purported to offer auto insurance discounts based on driving behavior as reported by a device connected to the insured’s vehicle. In fact, these early programs were little more than clever marketing programs and were mostly counter-productive and unprofitable. Adoption rates grew slowly, initially attracting mostly better drivers willing to share their information. But, as smartphones proliferated and became more powerful and capable of reporting more critical driving metrics, these programs have evolved to become effective enablers of accurate risk quantification. In fact, some of today’s more sophisticated reward -based telematics programs are shown to significantly modify driving behavior and reduce risk.    

The initial resistance of consumers to share personal information eroded as they began to embrace other tech-enabled programs such as Google, Facebook, Amazon, Spotify and Uber, which require extensive sharing of personal information for users to participate.  

We are already seeing the expansion of these connected platform ecosystems to include car makers, insurers and supply chain partners and transform the risk, accident and claims management process in terms of speed, cost and customer service. And, early-stage telematics programs have evolved and expanded to pay-per-mile, distracted driving avoidance and – while still early on – crash notification.

The future of connected auto insurance programs is promising as adoption rates increase and accident services enter the mainstream from various directions. One of the more important benefits will be the transformation of today’s reactive claim model into one that self-activates and makes the process easier and more efficient, from initiating a claim and every step through to reconstructing how the accident happened. This model will serve to make current breakthrough technology even more powerful and spontaneous — for example, photo estimating. The possibilities to accelerate the claim life cycle and bolster service represent exciting new value propositions waiting to unfold.

Connected insurance is spreading beyond auto to include other personal lines of coverage such as homeowners, property, life, health, accident and travel and into commercial lines, including property, small business, fleet, ride-sharing, home-sharing and workers compensation. 

Digital Ecosystems: Opportunities Through the Internet of Things 

The Internet of Things (IoT) will transform the world in the near future, and networked devices and sensors will enable this change. According to McKinsey, in 2010 there were 12.5 billion networked devices, and it is estimated that by 2025 that number will exceed 50 billion.

See also: Designing a Digital Insurance Ecosystem

The IoT is becoming a routine aspect of the everyday lives of consumers globally and is transforming business models across all industries. This new digital landscape presents opportunities for insurers: to develop new products (such as parametric insurance), open new distribution channels (such as embedded insurance) and fundamentally reinvent their business and products to include risk prediction and avoidance and real-time assistance and support on a hyper-personalized basis.

Even the investment management function of insurance is changing as carriers form corporate venture capital arms and invest in third-party vehicles that fund and leverage insurtechs and innovative technologies that are not only transforming insurance business operations but are earning outsized returns on investment capital as they exit into public markets.

A Connected Insurance Industry

The connected insurance industry of the future will still be supported by the same five core pillars, but underwriting and pricing risk, selling and distribution, claims adjudication and servicing and even investment management will look nothing like they did in the last millennium – to the benefit of all stakeholders, including the customer.

Building Telematics Can Mitigate Risk

Commercial general liability insurers traditionally estimate business risk exposure of similar businesses based on variables like floor area and revenue. Advances in cloud computing and artificial intelligence are combining to offer insurers new, better variables to characterize risk.

Insurers generally understand that liability risk correlates to human presence and movement. A hair salon with twice the foot traffic should present twice the slip-and-fall risk. More expensive haircuts may reflect a business customer’s greater ability to pay but probably do not increase slip-and-fall risk. Indeed, risk should correlate linearly with foot traffic unless (1) traffic is so high that conditions become over-crowded and the risk accelerates, or (2) the building falls unoccupied. Measuring foot traffic and occupancy can also confirm that the insured’s description of its business corresponds to its actual business.

Progressive Insurance introduced new attributes to characterize driving behavior when it pioneered automotive telematics in the late 1990s, an early practice of usage-based insurance (UBI). Rather than insure an automobile based simply on the vehicle’s make/model and age and the driver’s sex and age, insurers could introduce newly observable attributes to better model risk:  distance, speed, time of day, etc.

Twenty-five years later, a similar revolution is stirring in building insurance. Advances in cloud computing, artificial intelligence, semiconductors and the internet of things (IoT) make it practical and inexpensive to measure foot traffic and occupancy. Rather than depending on the policyholder to estimate human presence, a process unlikely to deliver numbers that can be compared across businesses, human presence can be measured objectively and continuously. The information will also deliver an actuarial  basis for risk assessment over time.

Risk engineers are eminently capable of characterizing variables like floor surface, lighting and door placement. However, variables like occupancy that change continuously are effectively impossible to characterize during an annual visit.  

These sensors are not your father’s IoT. IoT that measures temperature, lighting, sound intensity, hail stone size or flood level are all first-generation devices that require negligible processing power, either at the edge or in the cloud. The new generation of IoT requires high-performance, low-power, edge computing devices to predict risk, not simply measure what is empirically evident.

Some insurers think of IoT data as the new FICO (consumer credit) scores for businesses. If a hotel’s ballrooms are always below the limit set by the fire marshal, that implies hotel management is willing to play by the rules. If restaurants and bars do not overcrowd their spaces, they are less likely to obstruct exits or understaff operations. Attention to the rules implies lower risk…and that business may be one the insurer will want to retain with lower premiums.

Foot traffic and occupancy data should be of value to the business owner as well as the insurer — if for different reasons. A cafeteria may want to use foot traffic data to plan food preparation to minimize food waste. Office tenants can use occupancy data for space planning: Does the business need more, less or different space in the coming year? A restaurant owner might want to compare receipts to foot traffic and customer dwell time to measure the effectiveness of sales staff. Does a business efficiently use its real estate? How does a company compare with its peers? Are there opportunities to use real estate more efficiently?

It is likely that not all policymakers will welcome a technology that measures occupancy — in the same way not all drivers have welcomed technologies that measure driving behavior. Conversely, businesses that welcome the sensors are likely to self-select as attentive to overcrowding… and reflect a lower risk. And once the sensors are in place, reverse moral hazard suggests that insureds will improve their behavior — justifying a discount offered in exchange for accepting the sensors.

Insurers can gain market share by identifying lower-risk properties and offering discounts. Higher-risk properties will see higher premiums and will either need to work with their insurers to reduce risk or will need to find new insurers — probably one that isn’t employing building telematics technology. The outcome of this trend is that overall commercial general liability (CGL) premiums will decline, in part because high-risk properties will be obliged to work to lower their risk profile.

With risk profile information in hand, property insurance may move to the embedded-insurance model, where insurance is provided by the property owner who is equipped to measure occupancy — and risk — in real time. If your staff is at home during a pandemic, premiums drop contractually. If you double the number of staff in a space, premiums rise. More tenants pay a fair price for CGL insurance, and more tenants are suitably insured.

Occupancy and foot traffic will not be the last variables to be quietly but accurately measured by Internet of Things sensors. Other attributes that will be able to be measured include the presence of adults versus children; whether persons are running or walking or sitting; the presence of door mats when it has rained.    

As the cost of semiconductors, cloud computing and cellular connectivity continues to decline, sensors will be cheaper to install and manage. At the same time, underwriters and actuaries will be able to accumulate new, invaluable data that more accurately assess risk and reduce the insurance costs of the 75% of customers who, until now, have been subsidizing the other 25% — now that we finally know who’s who.

Past, Present, Future of Telematics, UBI

Insurers have spent the last 20 years exploring the potential of telematics with alternating curiosity, commitment and disillusionment. Last year, 8.2 million U.S. auto policyholders shared their driving data with an insurer, according to the IoT Insurance Observatory, a global think tank.

Insurer participation in the telematics space has been consistent for the past several years, according to annual surveys of insurer CIO members of the Novarica Research Council. Insurers that have deployed telematics generally indicate positive experiences; this includes a majority of larger insurers (more than $1 billion in annual written premium), 63% of which have measured positive ROI from their telematics programs. This is fairly rare for emerging technologies, where insurers are more likely to generally recognize value than formally measure it; the ROI places telematics alongside technologies like machine learning and robotic process automation in terms of the value created for insurers that have deployed it.

Given this activity, it’s useful to example the past, present and future of insurers’ use of telematics in personal auto lines, contextualizing current activity in light of insurers’ past approaches and speculating on future developments based on insurers’ present actions. As the article profiles the stages of telematics adoption, the focus will be on what is changing and why.

The Past (1998-2016)

Insurers in this phase were exploring telematics and the insights it could provide. Progressive’s Snapshot program has been the pioneer in OBD/dongle telematics-backed programs. The company’s journey has motivated other tier-1 insurers to engage with usage-based insurance (UBI). Several other top-10 insurers had introduced similar programs by the end of 2012, at least in some states.

These programs went out of their way to avoid scaring off initial adopters. They offered discounts to opt in and monitored driving behavior only temporarily, and many even didn’t impose surcharges on poor drivers. The value for insurers largely came from self-selection: only good drivers were interested in enrolling. However, insurers that were better able to effectively manage the usage of telematics data for pricing not only obtained better economic results thanks to surcharging the worst risks but were also able to keep an average retention rate above 94%.

The number of policyholders sharing data with an insurer grew to 3 million in 2014 but then leveled off. Insurers’ commitment subsequently vanished, and market sentiment about UBI became pessimistic. After almost 20 years and relevant investments, only about 1.5% of U.S. drivers were sharing telematics data with their insurers.

Number of policies sending data to an insurer by year in the U.S.

The Present (2017-2021)

While many market analysts with a little literacy about telematics data were speculating whether UBI would die before its potential was realized, in 2016 forward-looking insurer Allstate created Arity, a company dedicated to telematics and focused on the usage of the smartphone as a sensor.

Mobile-based data collection has vastly increased the reach of telematics programs by simplifying sign-up. The market has grown at 30% per year in 2019 and 2020. The COVID-19 pandemic has further increased awareness of UBI among the media, agents and customers – especially about pay-per-mile mechanisms – and is likely to support even more robust growth in 2021, as presaged by new mileage-based programs like that from American Family Insurance (MilesMyWay).

At first, it wasn’t clear mobile was a suitable source for telematics data: A leading telematics conference in 2016 included a session titled “Royal Rumble: Dongle vs. Mobile vs. Embedded Data Collection.” But mobile-based solutions have been the growth engine for telematics over the last few years, and quality of OEM data hasn’t yet met expectations. All the new successful approaches rely instead on the sensors present in the phone – sometimes paired with a tag positioned in the vehicle – and monitor the policyholder for the full duration of the coverage, rather than using a dongle for a single initial monitoring period.

See also: From Risk Transfer to Risk Prevention

Continual monitoring has allowed many of the top insurers to expand the way they use telematics data. In recent years, U.S. insurers have:

  • Introduced mechanisms for structured behavioral change– such as cash back earned on each trip – to promote less risky behavior;
  • Leveraged telematics data in claim processes to improve customer experience and increase both efficiency and effectiveness of claims management;
  • Introduced “try before you buy” apps for more accurate pricing at first quote, to attract better risks in each pricing cluster and reduce the premium leakage from bad risks.

Additional use cases like these allow insurers to build more robust UBI business cases, creating value on insurance profit and loss. This, in turn, allows insurers to create more attractive value propositions for customers: The more value created, the more there is to share with policyholders in the form of discounts, rewards and cash back. These incentives in turn attract new customers, driving further adoption.

Forward-looking insurers investing in these innovations today are progressively building the set of competencies necessary for mastering the usage of telematics data in the insurance business. This will not only create faster-growing and more profitable UBI portfolios but also address the transition to future mobility, as suggested by the story of Avail, the car-sharing service created by Allstate.

A large portion of the market hasn’t reached this level of maturity, however. Underwriting is still the most common area where insurers use telematics, although a few are beginning to explore other areas.

Many insurers are still watching the space, especially midsize insurers, which have engaged with telematics at roughly a third the rate of their larger counterparts. The percent of insurers deploying or piloting telematics has been roughly unchanged since 2018. (Insurers that are already participating, many of which have measured positive ROI, are continuing to innovate.)

Insurers whose internal technology environments are still mid-transformation may have a harder time supporting value-added telematics features; for these insurers, the value proposition for telematics as a whole is less clear. In particular, insurers need substantial data capabilities to manage UBI data at scale and innovation capabilities to transform the way business has been done for decades. As insurers continue to improve their data capabilities, and as more and more consumers adopt telematics, insurers that aren’t yet in the space may have more ability and more reasons to enter it.

The Future (2022-2030)

An insightful postcard from the future has been delivered by Tom Wilson, Allstate CEO, in a recent Bank of America Securities virtual conference: “If you’re not leaning into telematics, you’re not going to be in business for very long, at least on a profitable basis.”

We believe that in 10 years it will be the norm in the U.S. personal auto market:

  • For customers to download their insurer’s app on their phone to be insured. This app will continuously use the smartphone’s sensors to deliver a superior customer experience regardless of what product a customer chooses: pay-per-use, telematics-based renewal pricing or a policy with a traditional rating based only on traditional variables such as age, credit score, etc. This telematics app will have more than 40% daily active users, as some international insurers have already demonstrated. These interaction frequencies are not far from social media.
  • Telematics will prevent risks, both by real-time warnings in risky situations and by driver improvement via rewards for safe driving. Some international insurers have already put these into practice and created a reduction of their expected losses. Insurers will create an overall benefit to society by making drivers safer.
  • Claims touchpoints will be enhanced by the usage of telematics data and a virtuous collaboration between humans and AI. Policyholders will enjoy more accurate and efficient processes, from FNOL when accidents are detected, to claim triage, to adjudication and repair and payment. Customers are already demanding this, as shown by a 2019 customer survey conducted jointly by Cambridge Mobile Telematics and the IoT Insurance Observatory.
  • Customers will use their insurers’ apps to select among personalized offers of telematics-based services and additional contextualized risk-transfer solutions.

See also: Personalized Policies, Offered via Telematics

Forward-looking insurers are already preparing for this kind of scenario. This will in turn require transforming processes to most effectively use telematics data. It may not be enough to simply have a UBI product: The technology itself has a cost, and value-sharing (e.g., through discounts), can start at 10%. Insurers will need to use telematics data effectively to generate a return on this investment.

Insurers will have to educate both externally and internally: Not only will they need to communicate the benefits of telematics to potential customers, they’ll need each internal functional area to have a basic literacy about telematics. We expect that the next 10 years will see a tremendous degree of innovation and adoption, so telematics and the value-sharing it enables will be necessary to compete at the leading edge. This in turn should create a sense of urgency: Although simple telematics products can be replicated quickly, effectively leveraging telematics data to generate profitability can take years of iteration and concerted effort across organizations, and capability gaps will require years to be closed. After 20 years of experimentation in the U.S. personal auto market, telematics is ready to take flight.

From Risk Transfer to Risk Prevention

Recent developments in technology and the corresponding availability of data can improve risk prevention. A key driver is the Internet of Things (IoT), the growing network of connected devices ranging from consumer wearables to industrial control systems.

According to a recent report by Kaspersky, 61% of enterprises already use IoT applications. So, nearly two-thirds of insurers’ corporate customers can potentially integrate IoT data into insurance services. And a recent study by Aviva revealed that the number of internet-enabled devices in the average U.K. home has increased by 26% in the last three years to over 10.

Insurers can use the newly available data from IoT applications to reduce risks for customers, whether directly – through real-time risk mitigation solutions – or indirectly, by promoting safe behaviors over a longer period.

Prevention services are not new in the insurance industry; for years, insurers have provided consumers with loss prevention advice, and risk-engineering teams advise businesses in commercial lines. Ways to prevent risk, however, are changing. IoT allows risks to be better managed. This can be seen as the very essence of the evolution from pure risk transfer to a “prescribe and prevent” scenario.

See also: The Human Risks in Insurer/Broker M&A

Real-time risk mitigation

Real-time risk mitigation results from the direct use of IoT technology and can either consist of:

  • Automated actions by IoT actuators that affect the risky situation without any human intervention, like autonomous driving systems in cars, or
  • A warning to trigger some kind of human intervention, such as a water leakage alert that activates an emergency repair service.

These risk mitigation actions can be triggered by the detection of three different situations:

  1. Missed safety tasks, such as scheduled inspection or equipment that needs preventive maintenance, or a diabetic patient who has left insulin at home or missed a check of blood sugar level.
  2. A risky situation, such as a frozen pipe; a cold storage door that has been left open; spilled liquids on a supermarket floor; workers without adequate equipment in the workplace; unsafe lifting by an employee; a distracted driver.
  3. The consequences of an event that has already happened, such as a water leak; an unsafe worksite; an injury; or the failure of a patient to adhere to a treatment. A mitigation action is then initiated by the IoT system.

Real-time risk prevention is most mature in commercial lines, driven by the loss control culture present in commercial insurance. Field inspections by engineering teams are well-established, and enhancing this work with new technologies seems like a natural step.

A few personal auto insurers around the world have integrated real-time warnings in their telematics programs. This live feedback – from line departure warnings to alerts about coming risky intersections – influences driving behavior and allows insurers to reduce expected losses.

Water leakage sensors are one of the most cited preventive services in home insurance. However, as of today, insurers have struggled to introduce approaches that generate substantial demand and a sustainable business case. Finding a sustainable business case in the smart home insurance market is challenging, but innovations should make homeowners the ultimate winners.

Figure 1: Leveraging IoT data for multiple use cases

Source: IoT Insurance Observatory & The Geneva Association

Bundling risk prevention with other customer services, such as security, has been the most successful approach to date. The sustainable business case is built on a bundle of different services – some sold after the purchase – and on the reduced churn rates built through customer engagement.

Life and health is the least mature field for real-time risk mitigation services. There have been many insurance pilots over the past few years around early detection, care optimization and medication adherence, but only a few examples have scaled to market level. Reasons for the slow adoption include: 

  • Health costs in most countries are not fully covered by insurers but by a public health system. 
  • Entering into the medical device space would mean entering into the medical regulatory field. 
  • Medical advice comes with significant responsibility and requires deep and specialist knowledge.
  • Execution at scale needs insurers to deal with many different medical service providers. 

Real-time risk prevention services and approaches to them are very heterogeneous. The only common denominator is that all successful services are based on a multi-year journey. 

Promoting less risky behavior

The second way to prevent risk is to encourage less risky behavior. Insurers have a role to play in creating a positive safety culture and raising awareness in society.

We can distill a three-pillar concept from the successful examples: 

  • Pillar one: Create awareness of the current risk level
  • Pillar two: Suggest a change in behavior
  • Pillar three: Offer incentives for changes in behavior

The sustainable adoption of safer habits for the benefit of all stakeholders can only happen when all three pillars are successfully implemented. 

The first two pillars are closely linked and depend on feedback to customers. Awareness of the current level of risk leads to the question: What change will make the activity safer? Before changing our behavior, we need to be aware of our current behavior.

Raising awareness of risky behavior and identifying ways to change it are not enough. There is a need to encourage people to instigate real and sustainable changes in their behavior through rewards.

The customer’s perception of the value of the rewards, their cultural context and frequency and the intersection with behavioral economics are all integral. Changes in human behavior are also instinctive; A combination of behavioral economics and gamification to engage individuals is therefore needed to help to drive behavioral change.

The most mature business line is life and health. Fully individualized suggestions and challenges are provided to customers based on the number of steps registered by their mobile phone or physical activity data from wearables.

In personal auto telematics, customers often receive a detailed analysis of their driving style via a dashboard in a mobile app. Many insurers also automatically display tips for improving the driving score, or introduce contests on specific issues – so-called leaderboards. 

See also: Despite COVID, Tech Investment Continues

In commercial lines, IoT data is being used to enhance the activities of the loss control teams and to provide periodic safety insights to risk managers and supervisors of the insured companies.

The real-life case studies on promoting safer behavior afforded the following key findings:

  • The reward system needs to be set up to reinforce positive behavior. The reachability of the reward is key. 
  • There are cultural aspects to incentives. It is important to find compelling benefits and rewards that engage target customers. What works in one country does not necessarily work in another. The rewards must be explicit and tangible. For example, monthly cashback on fuel costs is effective, but a free weekly coffee also materially influences behavior.  
  • Frequency is key. A yearly premium discount is not enough. Positive engagement must be nurtured on a short-term basis. This mechanism gives people a reason to come back to the platform. 

Enablers of prevention services

The integration of technology into prevention services greatly increases complexity. As a result, the enablers for success are the effective business transformation, cultural change and understanding of the corresponding financial management rather than the technology itself.

Figure 2: Complexity of the financial management of IoT-driven prevention services

Source: The Geneva Association

We identified the following as the main success factors:

  • C-level commitment
  • Development of vision and strategy
  • Development of culture and capabilities
  • An effective value-sharing scheme with the customer
  • Management of new and complex financials

Several new elements need to be considered in the financial management of this new paradigm, such as service fees, partner contributions, self-selection effects and net IoT costs, which are harder to integrate into the economics of traditional insurance products.

The full report from which this article is derived is available here.

The Key to the Future of Mobility

For the past few decades, mobility innovation has trended in one direction: empowering the individual consumer. Google Maps and GPS have made navigation simple and paper maps obsolete, while rideshare apps offer options that traditional taxi services could not. Autonomous vehicles aren’t yet commonplace on the street, but experiments have logged millions of crashless miles. We’re living through the greatest change in general mobility since the invention of the jet engine. 

Insurance has a traditionalist reputation; insurers often reassure customers by advertising that they’ve been in business for several decades or even for whole centuries. The industry’s emphasis on past practice and proven traditions is admirable and necessary. But so is innovation, and we see insurers from every corner of the globe excited to build smart new products and programs based on new technologies. 

Telematics, the practice of analyzing mobility data for special insights, can help solve some of insurance’s oldest problems. Conventional actuarial models struggled to differentiate between individuals and types. If twin brothers live at the same address, work jobs with comparable salaries and share the same red sports car, they’re going to look equally high-risk to an insurer. One brother may be a thrill-happy daredevil, while the other shuns speeding and is conscientious about his turn signals, but the insurance company has few ways to recognize this. The responsible brother and the irresponsible one will pay the same fees despite their wildly different risk profiles. Telematics can make a huge difference here – it personalizes an insurance policy to each driver, providing the most equitable way to price premiums possible.

This is good for drivers, because it encourages good driving, and for insurers, because they’re much better able to predict costly car crashes. 

See also: How Tactile Sensors Can Help in Auto

The uses for telematics in insurance are obvious, and dozens of companies have partnered with telematics providers or founded in-house telematics operations. The customer’s phone is the central infrastructure element for telematics, but much remains to be built.

First, there’s the matter of what you might call social or trust infrastructure: Although most of us transmit huge amounts of data to Apple, Google and Facebook every day, potential telematics customers need to know that they are not being spied on. Explaining why telematics doesn’t compromise privacy is essential.

Second, telematics needs to be as simple and unobtrusive as possible. If a driver must open an app every time they step into a car, that’s an issue.

Finally, customers must be able to easily track the benefits of their participation. If, for example, a customer learns that their adherence to speed limits has earned them a 10% reduction in their premium, they’ll feel persuaded they’ve made the right choice. 

The insurance industry is evolving, but it doesn’t do it as noisily or quickly as the tech, automotive or mobility industries. We can see the changes happening, and the infrastructure necessary for the transformation grows firmer every day. As the insurance market becomes ever more competitive, telematics and related innovations offer the prospect of a more efficient industry that works better for everyone, giving insurance consumers better choice, service and prices.