For many, the concept of a “smart home” is a futuristic, and perhaps even frivolous, offering where lights shut off automatically once we fall asleep, thermostats are controlled from your phone and security cameras can show you what’s going on in your home from thousands of miles away. However, as I have written in many previous posts, we are only at the start of the Internet of Things (IoT). Significantly more sophisticated devices are already entering the market and soon consumers will see the benefits of both enhanced personal safety and home protection. Forward-thinking insurance companies are not only recognizing the potential for reduction in non-catastrophic loses, they are embracing the potential by filing smart home discounts to create incentives for consumers who use these technologies.
Let’s look at a few of these enabling technologies and their potential for loss reduction/avoidance around the core perils of water, fire and theft:
1) Advanced home security products — The professionally monitored home security market has limited penetration in the U.S. — a significant number of home owners don’t feel the need to have their homes monitored for theft. However, many IoT devices enable basic self-monitoring features as a secondary benefit. From video cameras with 24×7 recording, to controllable door locks, to lights that are triggered on with motion, home owners are now getting home security features included with IoT products that might otherwise be purchased primarily for convenience.
2) Leak detection — Traditionally, these products focus on single points of failure, providing coverage in specific locations, such as below a dishwasher or a hot water tank. While providing a lot of utility relative to their cost, it’s been hard to programmatically prove loss reduction with these devices as the location of the sensor has so much to do with catching the leak. That said, more ambitious forms of leak detectors are entering the market, enabling whole-home monitoring, from flow sensors installed on mains, to lightweight stripping that can be installed in floor boards. Additionally, a series of whole-home shut-off valves are also being introduced into the market. Most of these valves require professional installation; however, they are capable of automatically closing the water main with the slightest detection of a leak or abnormal usage patterns. Water losses may be greatly reduced if a home could automatically respond to a burst pipe or an overflowed toilet.
3) Connected smoke alarms and “listeners” — Fire alarms have saved many lives, but the original design was intended to notify occupants of a fire so they could quickly exit. Unfortunately, if no one is home to hear a smoke alarm, there isn’t much that can be done by way of stopping a fire before a total loss. But the new generation of connected smoke alarms and “listeners” (an add-on that hears an alarm and sends a signal) can message not only the home owner but also a third party who can dispatch emergency crews on a homeowner’s behalf. It’s not hard to imagine how dramatic loss reductions will be when all homes have connected fire safety devices.
An exciting aspect of all of these enhancements is that they are incremental improvements on already approved safety devices, enabling a fast track of the actuarial analysis/regulatory acceptance of additional discounts. But these improvements are just the start…
Connected devices are particularly special because the “intelligence” doesn’t necessarily need to reside on the device itself, but could also live in the cloud, where processing is getting more powerful and less expensive by the day. As such, there is a tremendous amount of innovation in the data analytics space — and here are a few technologies that will almost certainly result in greater loss reduction:
1) Real-time analytics — the more information that can be analyzed in real time, be it from multiple sensors or devices or historical data, the higher the accuracy in early detection of a potential loss situation. For instance, a sharp rise on a temperature sensor might indicate a fire, but it also could be caused from sunlight striking the device. Long-term tracking of that temperature data might quickly indicate what is normal, what is not. Or perhaps a flow sensor might detect a flow of water similar to shower running, but when paired with alarm system that shows the home is unoccupied and the alarm has been in “away” mode for several days could be a clear indication of a burst pipe.
2) Automated response logic — connected devices lend themselves well for automated responses. Homeowners will be able to create steps that are enacted when emergencies are detected. For instance, when a fire alarm rings, the sequence might be something like: a) snap a picture from each camera and take a temperature read from each sensor in the house, b) email/text all of the family that lives there with the data to confirm or override an emergency call, c) if no response within 60 seconds, forward the notifications to a third party for emergency dispatch. Automation combined with human intervention allows for a more accurate and effective response.
3) Predictive analytics — ultimately the best way to lower losses is to prevent problems before they start. This is where heavy processing power is required — as well as buy-in from consumers on the use of their data. Connected homes provide streams of output data and, with it, anticipated performance. Variances in this data might indicate early stages of problems. For instance, a packaged HVAC system might be showing degradation of airflow in the summer, which could mean trouble for gas heating as temperatures drop. It might be in the best interest of the insurance company to ensure performance is restored as the winter comes, prior to the risk of freezing pipes. Additionally, as we are seeing in telematics and auto insurance, you can bet that consumer behaviors will also have the potential to be analyzed, no doubt showing correlation between “safe” homeowners and reduced loss.
While more forward-facing than the device enhancements listed in the first section of this article, it’s these enhanced intelligence features that will truly revolutionize loss models. The more advanced the technology becomes, the less dependent the loss prevention becomes on human behaviors.
Imagine a world where the main perils for homeowners insurance carriers such as water, fire and theft are dramatically reduced through the IoT and smart homes. Yes, consumer mistakes/negligence, even moral hazard, will always be an issue, but at some point it’s very possible the home will become smart enough to compensate even for these factors in a substantial way. We are already seeing rapid advancements in these areas in both telematics for auto insurance and wearables for life and health insurance. Similarly with smart homes, these IoT technologies have significant potential to lower losses from non-cat perils.
The insurance industry has been historically slow to embrace technology, lagging behind even the banking sector. This attitude is understandable — the industry relies heavily on historical data, which is generally not available for new technology, and the industry is immensely risk-averse, as even one failure to live up to their commitments could be devastating to an insurer.
Technology is putting pressure on the insurance industry from three sides.
New customer demand
The first is customers, who have grown accustomed to an easy, Facebook-like experience in interacting with large service providers. Current insurance products are far too generalized and one-size-fits-all to appeal to a customer base that is expecting easily individualized products. Technology like usage-based insurance can make a provider significantly more appealing in this respect by making it possible to only pay the premium for risk actually taken; wearables can revolutionize the healthcare insurance market by allowing for truly personalized pricing.
The second source of pressure comes from competitors. Not only will consumers be more likely to give their business to a digital-native insurer, but entire new kinds of exposure are opening that will give a challenger an opportunity to strike. The cybersecurity market is growing everywhere, along with the pressure to contain and manage the risk better, yet traditional insurers are slow to make convincing offers to threatened customers. In addition, the blockchain is making a more decentralized market possible: While insurers could so far count on the immense need for capital as a barrier to entry, the blockchain could finally bring the transparency and reliability needed to make dynamic, small-scale insurance underwriting possible.
Lastly, technology provides new avenues to cut costs in internal processes and pricing products by making available huge sources of data and enabling its more efficient analysis. Insurers currently spend a lot of money on services that aren’t in their core specialty- processing claims, detecting fraud or manually assessing new risk. New algorithms for predicting risk, for example using machine learning, will allow for vast automation of the underwriting process, and managing contracts and identities with the blockchain will reduce the resources needed for fraud detection. New diagnostic technology, like wearables for healthcare or GPS trackers for cars, is bringing a new wealth of data that may balance the lack of historical data that is currently keeping insurers in as-is mode.
With those pressures, however, come a number of important opportunities in three areas: underwriting automation, connected devices and cybersecurity
Automation in the insurance industry can make underwriting both more efficient and more precise, with different lines offering different opportunities for automation.
Insurers are currently using automation primarily to support underwriters and aid in triage, with only a fifth saying their primary objective is to fully automate the process. What kind of automation is possible varies between business lines, but even in the most advanced segment, personal lines, only 42% of insurers say they have “mastered or almost mastered” automation. At the bottom end, life insurance, 80% of insurers say they are struggling or just getting started with automation.
Insurers are focusing on personal lines and small and mid-market commercial to expand their automated underwriting capacities, with more than 40% saying they will increase their spending in each field. However, in line with being late adopters, it is estimated that only 10% of insurers will have an algorithmic business strategy in 2019 that makes use of more advanced techniques like machine learning, which could make automation viable for more involved lines like health.
For most policies in motor, home and life, an underwriter reviews between eight and 15 factors. Current automation systems for life insurance have similarly small data requirements, with around half the systems drilling down into no more than 10 questions, and a third of them asking as many as 60 follow-up questions. Most systems incorporate lab data and prescriptions databases. These amounts of data are small compared with what a sophisticated automated system could use to assess risk.
As a naturally data- and analysis-heavy industry, insurance stands to profit from advances both in the sophistication of automation and in its affordability. As an industry that is also conservative and late to adopt technology, it faces the risk of being outflanked by a less risk-averse challenger that’s willing to bet on automation skills.
Insurers have for more than 25 years used primitive systems to fully automate small-scale risk in simple lines (for example, travel insurance), or to aid their underwriters by more effectively triaging requests and directing them to the underwriter that’s best suited for them, or to do some preliminary analysis. These systems generally rely on simple rules and are seen as supporting underwriters. As automation products become easier and cheaper to implement, and new decentralized technologies like blockchain make small-scale underwriting more transparent and available, we can expect their share to increase incrementally.
More importantly, insurers are also facing a new wealth of data both for historical risk research and for better assessment of new risk that could fundamentally change the way risk is priced. However, traditional systems are not equipped to deal with these amounts of data, and few insurers are ready to implement the machine learning technology that would be. The problem is that modern machine-learning can produce results but cannot generally explain them. Policy underwriters are naturally skeptical of underwriting risk based on a technology that provides no justification for a pricing beyond the rigor of its setup and the vastness of the data it has been trained on. However, insurers already use fundamentally similar systems for assessing their underwriters’ competence—if a junior underwriter repeatedly prices a risk outside of the usual range the same way a more senior underwriter would, the junior underwriter will be allowed to price those risks without supervision. If insurers can learn to trust this approach with technology, too, they will embrace machine learning.
Underwriting automation will become a significant field of innovation around both reducing staffing and coping with the new amounts of data, with each business line requiring its proper automation technology. As risk assessment algorithms become more reliable and executives more confident in them, they will be able to make low-level underwriting both cheaper and more consistent. As new sources of data for risk analysis become available, insurers will have to use machine learning algorithms to be able to make sense of the vast amounts of data.
Connected devices in insurance describes the network of smartphones, wearables, home diagnostics and other internet-connected devices that form one of the fastest growing spaces within insurtech. This stands to make available a new wealth of data for insurers to handle better pricing and encouragement of risk-decreasing customer behavior.
Wearables and Diagnostics
87.7 million U.S. adults, or about 38%, are expected to be using a wearable device in 2019, a growth mainly fueled by smartwatches and wristbands. VCs invested around $3 billion in IoT startups worldwide in 2015, and 38 million European and North American households are expected to have a smart thermostat in 2018, with two-thirds of those lying in North America. Nearly two-thirds of consumers already own or plan to purchase an in-home IoT device in the next five years.
Only 3% of insurers are already making use of wearable devices, and less than a fourth are developing a strategy for them, even though 60% of insurance executives believe that wearable technologies will be adopted broadly by the industry.
Telematics in cars allow insurers to track driving patterns of their customers. The advent of cheap GPS devices has made this technology ready for widespread adoption with usage-based insurance (UBI) and dynamically adjusted premiums. More than 15% of the U.K. car insurance market is usage-based, and Progressive alone has more than 4 million UBI customers in the U.K. In the U.S., there are around 5 million UBI policies in effect, and approximately 70% of all auto insurance carriers in the U.S. are expected to use UBI by 2020, with more than 26% of all motor policies being usage-based. Usage-based programs on average lead to a 57% decrease in total claims cost.
Health insurance tech startups raised more than $1.2 billion in venture funding in 2015, more than twice as much as in 2014, and making up almost half of the $2.6 billion in venture funding that was raised by insurance tech startups overall. Insurers themselves have committed more than $1 billion to investments in startups, and many of them have established their own in-house venture capital funds to exploit IoT and ready themselves for new markets.
58% percent of smartphone users in the U.S. have downloaded a health-related app, and around 41% have more than five health-related apps, generating data that insurance providers could use to fine-tune their individual premium pricing and encourage low-risk customer behavior. The first insurance company to offer discounts to customers using technology aids for better living was John Hancock in 2015. Other companies in the U.S. and elsewhere have since followed suit, offering as much as a 15% premium discount.
The number of connected devices is projected to grow by 35% each year over the coming years. This creates a new wealth of data, which insurers see as important but do not know how to tackle. To understand how insurers can approach the issue, we must look at the health insurance industry, which is at the forefront of integrating wearable tech and makes up for about half of all insurance tech investment.
Most of the efforts to integrate technology by insurers are simple and mainly designed as promotions, like awarding credits for a number of steps taken: this is a far cry from what big data could do for adaptive premium pricing based on comprehensive health data for each customer. The problem is likely a skepticism toward new technology for which no historical experience is available.
The other major industry using connected devices is car insurance. Here discounts are given to customers who drive less and more safely than others, and the benefits so far have been clear: a 57% reduction in claims. It remains to be seen how much of this reduction will turn out be a temporary Hawthorne effect, but it is sizable enough to pique interest everywhere. The major problem is that so far insurers do not penalize worse-than-average drivers, and it is unclear to what extent customer will accept self-tracking as mandatory or de facto mandatory by pricing. The same issues will also have to be faced by other insurance industries moving to integrate IoT.
Insurers agree that the Internet of Things and wearables will play a major role for the industry but have so far only used them in often-gimmicky promotional efforts, hindered by the fact that they cannot penalize customers for risk-increasing behavior. The health insurance market is the main point of investment for insurance tech, but the rise of smart devices everywhere makes innovation possible in all parts of life. The first insurer to overcome the regulatory hurdles and offer truly adaptive and responsive insurance that is not limited to one or two factors but embraces big data will have a strong first-mover advantage.
The cyber insurance market grows each year both in size and import but is insufficiently understood and served by insurance providers, who so far have few technological options to contain, predict and address cyber risk.
Risk levels and market size
Estimates for the yearly cost of cybercrime vary from €330 billion to €506 billion. The cost will increase as businesses and their supply chains become more digitally integrated. In the past three years, the average economic impact of cybercrime per organization in the U.S. has risen from $11.6 million to $15.4 million. The biggest share of this impact comes from the cost of business disruption. The global market for cyber insurance is estimated to rise to $20 billion in premiums by 2025.
Customer awareness and adoption
Businesses are insufficiently insured and informed around cyber risk. Around 40% of Fortune 500 businesses currently have insurance against cyber incidents, but generally not enough to cover their full exposure. In the U.S., 24% of all business have some form of cyber insurance. 48% of enterprise customers say they lack the necessary understanding of the complexity of cyber risks to better prepare against them.
Available products and expertise
Of the 10 largest insurers, only five offer standalone cyber coverage. While 90% of all insurance underwriters offer cyber insurance as an add-on to other products, more than 50% do not have any dedicated underwriters for cyber risk and rely on underwriters for other lines. Consequently, 70% of insurance brokers claim there is little to no clarity about what is covered in cyber products.
Cyber insurance is a major challenge for insurers as there is little historical data to inform the correct insurance pricing, and there is great variation from year to year in the kind of cyber attacks and damages that businesses face most. Technological solutions to better protect against cyber threats or at least contain the risk are unsatisfying. As a consequence, the traditionally conservative, risk-averse and technologically skeptical insurers are failing to live up to their role as protectors of businesses against new, existentially threatening cyber risks.
While adapting rapidly, the strength of protection against cyber crime is unlikely to proportionally increase with the strength of the attacks, so defenses against cyber attacks are usually about one generation behind, with new types of attacks emerging each year. Businesses and their supply chain are digitally integrating to an ever larger extent, so both the target size and sophistication of cyber attacks will lead to rising risk and damage from cyber incidents, creating more exposure for businesses everywhere.
These businesses are by and large aware of this threat but find themselves insufficiently informed about how to protect themselves because insurers fail to provide the much-needed expertise. The damage to different developed countries’ GDP from cyber crime ranges from 0.5% to 1.5%. As this share increases, we can expect regulatory pressure, which already represents a big liability risk for cyber incidents, to lead to an even higher demand for comprehensive cyber insurance.
At the moment, insurers are still unsure about how to best underwrite cyber risk and often go the safe route of not offering dedicated cyber products at all, or only offering very limited products. As cyber insurance becomes more of a business necessity, insurers that cannot provide expertise on it will seem unreliable and unfit to support a business and see their market share suffer in other lines as well, and hence this area becomes an important space for further investment.
Cyber risk is a major, growing risk to insurance providers, including banks, and businesses looking for insurance, both because of liability exposure and the threat of business interruption that could run into substantial unplanned-for costs. Even though awareness is increasing among business leaders, insurers are struggling with offering the right products with relevant features and pricing because of their lack of experience. An insurer that knows how and is willing to underwrite this new type of risk will quickly capture a sizable market share. There is a level playing field for insurers and new players as there is no historical data available for both — agility and willingness to use new sources of data could be a competitive edge for new insurtech players.
You can find the full report from which this article is excerpted here.