The auto insurance market is in turmoil. Insurers are not only dealing with soaring repair costs and pushback about rising rates but are facing core uncertainties about how quickly electric vehicles will gain share and when autonomous vehicles will really take hold. That last is an existential issue for personal auto insurance, because drivers don't need insurance if they aren't driving; liability will lie with the makers and operators of the autonomous vehicles.

In this kind of tumult, it can be hard to separate the signal from the noise.

I'm here to tell you that Elon Musk's recent promise of a major announcement on robotaxis in August is just noise. 

There are two reasons I can make such a blunt statement: Musk's long history of overpromising on the autonomous capabilities of Teslas and the state of his technology. Let's start with the simple one: his history of overpromising.

When Musk says he'll unveil his robotaxi design on Aug. 8, it's important to step back and look at what else he's said over the (many) years. 

In 2015, he promised Tesla shareholders that cars would be fully autonomous within three years. In January 2016, he doubled down via tweet: "In ~2 years, summon should work anywhere connected by land & not blocked by borders, eg you're in LA and the car is in NY." In other words, by roughly the beginning of 2018, you would be able to tell a car to drive to you in Los Angeles from New York City, and it would do so entirely on its own. In April 2017, during a TED talk, he confirmed that claim: “November or December of this year," he said, "we should be able to go from a parking lot in California to a parking lot in New York, no controls touched at any point during the entire journey.”

2018 came and went without any Teslas crossing the country on their own, but he was back at it in 2019, saying on a podcast: "I think we will be feature complete — full self-driving — this year. Meaning the car will be able to find you in a parking lot, pick you up and take you all the way to your destination without an intervention, this year." He told investors in April that year that "by the middle of next year, we’ll have over a million Tesla cars on the road with full self-driving hardware,” so reliable that the driver “could go to sleep.” He has said that owners of fully autonomous Teslas could just hit a button and make their cars available to others for a fee, so he was basically promising to have a one-million-vehicle fleet of Tesla robotaxis on the road ... by mid-2020.  

You see where this is going. 

Musk has toned down some of his promises in recent years, in the face of regulatory scrutiny and lawsuits by families of people who were killed while their Teslas were in Full Self-Driving mode. But if the old saying is, "Fooled me once, shame on you; fooled me twice, shame on me," then what would you say about people who let Musk fool them repeatedly for a decade? 

You can decide Musk is for real this time on autonomy, if you like. I'll wait for proof.

And his general lack of credibility on the issue is only half the problem. The other is that his technology just doesn't measure up. 

As far back as 2013, when I published a book on driverless cars with Chunka Mui, we argued that Tesla was taking too limited an approach to the technology. It was using radar and cameras to track what was happening around the vehicle but wasn't using lidar (essentially a laser-based form of radar), as Google and others were. The Tesla approach was economical, because radar and cameras were inexpensive while lidar cost tens of thousands of dollars per vehicle. But the benefits of lidar seemed clear--it detects objects that can be hidden from radar and cameras by weather. And Chunka and I argued that lidar costs would follow the same curve that all electronics follow, as described by Moore's law (essentially, that costs drop 50% every two years or so). Sure enough, lidar now costs maybe $1,000 per vehicle, and prices are steadily dropping--but Tesla's AI isn't designed to incorporate information from lidar.

In fact, Tesla has headed in the other direction. In May 2021, Musk announced (against the advice of senior engineers) that he would stop using radar in his self-driving technology. His reasoning was that human drivers just rely on their eyes and their brains, so why did his AI need anything more than cameras? For good measure, he also stopped using sensors that detect objects within inches of a vehicle.

But think about how much trouble you have seeing well enough to drive in a rainstorm or snowstorm or perhaps at night, Wouldn't it be much safer to have inputs from radar and lidar, as well as your eyes (assuming your brain were wired to make instant sense of those inputs, as an AI can be trained to be).

Self-driving technology is really hard. How hard? Even Apple recently gave up after spending $10 billion on an autonomous vehicle project. But Musk is doing himself no favors by limiting the sensors in his vehicles. I'm not sure he ever gets to reliable self-driving of the kind he has been promising if he just uses cameras.

He's also kidding himself if he thinks he can quickly stand up a robotaxi operation. Think of all the intelligence that has to be built into a system that dispatches robotaxis--and that complexity increases by an order of magnitude if, as Musk has discussed, he wants Tesla owners to be able to volunteer their vehicles as robotaxis when not using them. 

And the dispatch system is just the start of the complexities. Who is responsible for cleaning the car when kids are transported back from the beach all covered in sand? And how do you make sure that cleaning gets done before the car is sent to its next passengers? Who is liable if a car is used in a drug deal? Who plugs the car in if it runs out of charge before being returned to its owner? 

I did some consulting for a major company on robotaxis in 2017-18 and can tell you that the list of complexities is extremely long.

Investors in Tesla are going to make whatever decisions they make, but I wanted to be sure that the hype about this robotaxi announcement didn't bleed into anyone's thinking in insurance. Yes, auto insurance is in turmoil, and, yes, autonomous vehicles are an existential threat to personal auto insurance (years from now), but whatever Musk says in August about robotaxis won't even cause a ripple. Ignore it.

Cheers,

Paul 

P.S. As you think about what WILL have an effect on auto insurance, here is a smart piece from two McKinsey partners. 

America’s long-term care crisis warning signs are mounting. The latest red flag is the rising cost of long-term care services across all provider types, with increases up to 10% over the past year, according to the 2023 Genworth Cost of Care Survey. 

Clients are already facing the convergence of major trends that pose a potentially devastating dilemma that can compromise their aspiration to age in place and enjoy a happy, healthy retirement. 

The retirement crisis remains a menacing presence. Overall, 80%—or 47 million households— with older adults are financially struggling or at risk of economic insecurity as they age. Recent research also shows a short-sighted attitude regarding long-term care services. While 70% of retirement-age Americans will need continuing care at some point, merely 14% of retirees are very confident they’ll be able to afford it. Lastly, our country’s health is bleak, having the lowest life expectancy among high-income countries.

As the population ages, the threats promises to intensify. Older generations will look to their trusted advisers to weather the storm, providing an opportunity to help heighten clients’ long-term care readiness while bolstering agents’ profitability. 

See also: Using Data Science to End Surprise Billing

Become a Partner in Health 

Today’s rapidly aging society must prompt a paradigm shift within the insurance industry marked by fundamental change in the attitudes of professionals and how they perceive and service their clients.  

The inherent nature of the agent-client relationship has been somewhat fractured amid carrier business directives to increase rates and decrease payouts or claims. This longstanding approach must evolve into one centered on a “Best Alignment of Interests” model that creates a mutually beneficial partnership among carriers, agents and policyholders. 

The critical topic of long-term care is often ignored due to a lack of awareness. One of the most common, and perilous, misconceptions among agents and policyholders is that Medicare covers long-term care. Medicare only covers basic medical needs, and not long-term care services. 

This is a highly underserved market where agents can lend their vital support and promote extended quality of life. Formulate a plan to help clients live the best possible versions of their lives. 

Embrace Innovation for Aging Boomers

The Baby Boomer explosion means professionals will experience a surge in clients who are painfully unprepared, and whose specific needs must be addressed. 

Despite the population’s urgent need, long-term care insurance purchases are declining, with 2022 marking the lowest sales volume in over two decades. This trend is understandable due to heritage issues like inaccurate assumptions, which led to significant rate increases, lack of product innovation, agents and carriers dropping out of the market and overall unfavorable consumer perception of the segment. 

The insurance sector must foster innovation that will ignite behavioral and buying changes and safeguard elderly individuals from financial insecurity during their retirement phase of life. 

Begin with an application overhaul. Innovation can streamline the LTCI application process, which has traditionally involved in-person exams and lengthy procedures that frustrate consumers and result in high rejection rates. Today’s improved risk selection and application processing techniques enable insurance products to provide decisions within an hour, leading to better risk selection and significantly improved consumer experiences.

Innovation is transforming claim handling, making the process more efficient and precise. Automated initial claims routing streamlines the process and swiftly directs claims to the appropriate department or personnel for evaluation and next steps. We must replace legacy systems with automation that saves time and resources, leading to faster response times and reducing the risk of claims getting lost or mishandled.

Additional advancement areas exist in identifying potential policyholders who might require assistance and make future claims for health challenges. Those opportunities require insurers to analyze massive data sets mapped against population health metrics.

See also: Healthcare Inflation's Impact on Auto Insurers

An Ounce of Prevention Brings Big Mutual Benefit

Preventative services play an integral role in protecting and promoting health, yet only 5% of adults 65-plus received these recommended services in 2020. By using data analytics and predictive modeling, insurance carriers can reach out to these individuals, offering assistance, guidance and resources. This preemptive approach can prevent or mitigate problems, helping policyholders maintain better health and quality of life.

There’s a difference between living well into old age and living “well” into old age. Therefore, some insurance carriers are incorporating creative wellness programs into their pre-claim processes. They offer policyholders access to targeted, personalized health and wellness services like fitness programs, nutrition counseling, mental health support and preventive screenings. One example is Assured Allies’ NeverStop, an innovative wellness rewards program that’s built right into your insurance policy. By encouraging healthier lifestyles and early intervention, these insurers reduce the chances of claims arising from preventable health issues while improving the overall customer experience, building stronger and deeper connections.

Small interventions can make a huge impact on health and wellbeing. Falls are the leading cause of injuries for older Americans, with one out of four Americans age 65-plus falling each year. Simply installing a grab bar in a bathtub can decrease fall hazards by 76%. Treating hearing loss may lower the risk of dementia, with hearing aids reducing the rate of cognitive decline in older adults at high risk by almost 50% over three year.

A Critical Wake-up Call 

The inevitable reality facing insurers must be addressed to offset its accompanying, significant cost. We should be encouraged by what we are seeing, as insurtech companies are introducing innovative solutions that can revolutionize the insurance industry and fill the gap in long-term care. These efforts are powered by our social obligation to serve the needs of the growing elderly population, and by the business opportunities they present. The combined force of dynamic solutions and adaptive client service methods can drive the industry successfully into the future. 

Generative artificial intelligence (AI) models are 10,000 times more powerful compared with just five years ago. An increase in power on this scale creates significant opportunities for insurers.

The life insurance industry is at a turning point, with rapid transformation being driven by factors including technological innovation and changing market dynamics. AI, in particular, has the potential to redefine traditional practices and revolutionize the entire value chain, from greatly improving customer services and risk assessments to retention and policy customization.

AI for code – the next big milestone

The use of generative AI for coding for in-house applications is set to be the next big thing in 2024 as the industry realizes just how powerful the latest models have become and insurers find ways to leverage this power. In a recent conversation, a non-executive director in a major U.K. insurance firm revealed that they had already started using generative AI for a coding project to translate all the code from the insurer’s entire legacy box of business into their preferred code to sit more efficiently with their newer main block of business.

When looking at exactly how these technologies can improve our day-to-day work, the writing of computer code is a prime example of a core application of AI. For example, an AI coding system can help generate and test code, as well as assist in the debug process, which many developers struggle with. AI can also significantly help to improve documentation and adherence to coding best practice.

AI technologies can also facilitate code translation, such as transforming an Excel macro file into an open-source code like Python or R, with the endgame of fitting such applications into a better-governed process. There are many other applications of generative AI that can help the insurance industry, such as report drafting, checking the consistency of reports in large groups or compliance with group or professional standards and process automation that requires collation and large numbers of documents to be inspected.

Insurance firms are also undertaking competitions internally to see who can come up with the best generative AI use case, such as feeding generative AI an insurer’s complete collection of training and underwriting manuals to create an expert bot. This approach also benefits from avoiding the risk of any external interaction, which is sensible for insurers in 2024 that are considering how best to use generative AI, while a better understanding and a level of control are still being established.

See also: Balancing AI and the Future of Insurance

AI regulation on the rise

The opportunities of AI do not come without risks, which means implementing AI must be approached with care. As AI becomes progressively more integrated into insurance industry practices, regulatory oversight is also on the rise. This means insurers need to make sure that their AI practices comply with relevant regulations. 

With such a heavy reliance on data, protecting data privacy and maintaining ethical standards are crucial. For this reason, insurers will need to comply with data protection regulations and handle personal or sensitive data ethically when using AI.

There is also the risk of bias unfairness. AI models can unintentionally learn and produce biases presented in the training data, leading to unfair outcomes. As a result, a continuous monitoring for bias is essential, alongside a commitment  for transparency and fairness in their AI applications.

A key question for regulators will be the extent to which their focus is on the internal use of AI by an insurer, as opposed to concentrating on the company’s actual outputs generated by AI. With the main focus of regulators to date having been on the outputs (for instance, whether premiums are fair and non-discriminatory), the hope shared by many insurers is that this approach will persist.

A further problem arises with transparency. All model users, stakeholders and regulators ideally require their models to be transparent. But this is not possible with generative AI, which is typically based around neural networks with a hundred or more labyrinthine layers, each containing thousands of nodes (in effect, robotic neurons). So how can we learn to cope without transparency? Alternative criteria will need to be defined to allow use while retaining confidence in that use. 

See also: Cautionary Tales on AI

The AI takeover - redefining insurance

All too often, the insurance industry approaches risk from a one-sided perspective, only seeing the negative. While this is a natural human instinct and typical of chief risk officers concerned with everything that could possibly go wrong, real-world risks tend to be two-tailed. That is to say, insurers also need to think about the commercial risks of being slow to harness the powers that generative AI offers and hence being left behind.

Looking ahead, the insurance industry is likely to accelerate the pace at which AI and human expertise are integrated. Insurers that invest in the necessary resources and capabilities to ensure the benefits of AI are effectively harnessed, while being mindful of its limitations and potential challenges, will be best equipped to thrive in this new era of insurance innovation.

Generative AI will be profoundly transformative and far more so than analytics and machine learning were predicted to be 10 years ago. Until very recently, industry leaders were skeptical as to how such tools could safely help their business. Given the record speed at which these tools are evolving, coupled with an increasing awareness of the technology’s scope and transformative potential, we should be flipping the default question from "show me how generative AI can help in this part of the value chain" to "explain to me why you’re not using generative AI here." 

In 2024, the landscape of healthcare underwent a profound transformation, marking it as the Year of Digital Health & Wellness. The widespread adoption of telehealth, catalyzed by the COVID-19 pandemic, reshaped the way medical services were delivered across the U.S. 

Prior to the pandemic, telehealth usage was relatively low, with approximately 5 million users nationwide. However, as the need for remote healthcare grew, so did the use of telehealth services, skyrocketing to over 53 million participants among Medicare recipients alone. Now, in 2024, 91% of health systems report having a telehealth program. 

It wasn't just the aging population that embraced telehealth. Even workers' compensation agencies, which previously provided minimal coverage for telehealth services, experienced a significant shift. Before COVID-19, only about 1.2% of all medical bills covered by workers' compensation included telehealth services. However, at the peak of the pandemic in April 2020, this figure surged to approximately 8.8%, indicating a rapid adaptation to remote healthcare solutions. Although the use of telehealth services has since stabilized, it still remains significantly higher than pre-pandemic levels, hovering around 4%.

This unprecedented surge in telehealth usage serves as a critical foundation for the transition toward Digital Health & Wellness. The widespread acceptance and integration of telehealth into mainstream healthcare delivery systems have demonstrated its efficacy and value in providing accessible, convenient and efficient medical care.

See also: Data Science Is Transforming Public Health

In today's rapidly evolving healthcare landscape, Digital Health & Wellness has emerged as a pivotal force, encompassing the integration of information and technologies to manage health risk and promote wellness. This concept represents the convergence of healthcare and technology, aiming to enhance delivery methods and improve patient outcomes. Often used interchangeably with terms like telehealth, mHealth, eHealth and health informatics, Digital Health & Wellness has gained prominence, particularly in the wake of the pandemic.

The pandemic highlighted the necessity for healthtech solutions and the convenience of receiving medical care from the comfort of one's home. This shift in patient preferences, coupled with advancements in technology, has paved the way for a transformation in healthcare delivery. With the global healthcare market projected to grow by 5.4% annually from 2022 to 2028, there exists a vast and expanding market for Digital Health & Wellness solutions. 

Even the regulatory environment has become more favorable, with the Biden administration prioritizing healthcare innovation as a cornerstone of its agenda.

One focus will be on musculoskeletal conditions (MSK).  MSK conditions, which encompass a range of disorders affecting the muscles, bones, joints and connective tissues, represent a significant portion of healthcare expenditures in the U.S. According to data from the Centers for Disease Control and Prevention (CDC), MSK conditions rank among the leading causes of disability and chronic pain in the U.S. 

The scope of the issue is staggering, with an estimated 1.71 billion people worldwide grappling with musculoskeletal conditions, and a notable 30% of individuals over the age of 45 affected by some form of MSK issue. These conditions often coexist with other health-related issues, compounding their impact on overall wellbeing. MSK conditions account for billions of dollars in healthcare spending annually, underscoring the urgency of effective intervention strategies.

See also: How Digital Health, Insurtech Are Adapting

The surge in virtual wellness tools, particularly in the domain of digital physical therapy, offers a promising avenue for addressing MSK concerns. These innovative solutions leverage technology to deliver accessible, personalized and effective care to individuals managing MSK conditions. By providing remote access to expert guidance, monitoring and rehabilitation exercises, digital physical therapy platforms empower patients to take an active role in managing their MSK health. 

The challenge lies in bridging the gap between traditional healthcare models and innovative digital solutions, ensuring that individuals receive comprehensive and integrated care for their MSK wellness needs. This necessitates a holistic approach that encompasses not only symptom management but also prevention, early intervention and continuing support. 

As we navigate the complexities of MSK wellness in the digital age, collaboration between healthcare providers, technology developers, insurers and policymakers is paramount. By harnessing the power of advanced technology, data analytics and patient-centered design, we are paving the way for a future where MSK conditions are effectively managed, healthcare costs are reduced and population health is optimized.

In the rapidly evolving landscape of Digital Health & Wellness, insurance companies are adapting to meet the changing needs of consumers. Recognizing the importance of preventive care and holistic wellbeing, insurance providers have introduced in 2024 additional reimbursement codes and expanded coverage for annual wellness visits. In a significant development, Medicare Advantage programs are now extending coverage to include Digital Health & Wellness memberships, acknowledging the vital role of technology in enhancing healthcare access and outcomes. 

Also, 2024 marks a turning point in the approach to employee wellness, with a sharp uptick in workplace programs focusing on digital solutions. From large corporations to small businesses, there's a concerted effort to prioritize employee health and overall wellbeing. 

At the forefront of this transformation are technological innovations that empower individuals to take control of their health. Digital health platforms, wearable devices and AI-driven solutions are revolutionizing wellness programs, offering personalized insights and actionable data to users. By shifting the focus from reactive healthcare to preventive measures, these technologies are reshaping the healthcare landscape and driving a fundamental change in how we approach wellbeing.

These developments underscore the immense potential for Digital Health & Wellness to revolutionize healthcare delivery and improve patient outcomes. By leveraging new technologies and focusing on wellness, the healthcare industry has a unique opportunity to address longstanding challenges and usher in a new era of patient-centric care. 

As we look to 2024 and beyond, Digital Health & Wellness is poised to play a central role in shaping the future of healthcare, driving innovation and improving access to quality care for all. So, yes, all indications mark 2024 to be the innovative year for health.

In recent years, contact centers charged with managing customer experience (CX) have undergone a transformation. Specifically, customer service agents, with calm voices and readiness to assist, are getting a boost from artificial intelligence (AI). 

When done right, contact centers deploy AI to augment agent capabilities and automate and streamline workloads. However, as the world experiences an increase in natural disasters, insurance claims are on the rise at a time when agents are reaching a breaking point.

I am a firm believer that human agents are essential. I’m also pragmatic and even optimistic that – powered by AI – human agents can receive the support to make their jobs more manageable, which will help reduce contact center churn while improving customer engagements. Here are three trends that will make a difference in how AI plays out in the insurance sector in 2024.

1. The Ascendance of Specialized "Closed AI" in Business and Insurance

In the realm of business applications, viewing AI as a broad category rather than a singular entity offers a more nuanced perspective. Various AI technologies are finding their niches across different business functions, with certain tasks benefiting from AI's capabilities, while others might inadvertently complicate processes by attempting to integrate AI where it's not needed. A notable trend emerging, particularly within contact centers and extending into the insurance industry, is the rise of specialized "closed AI" applications.

These closed AI systems are designed to perform specific functions. The contact center can include tasks like customer conversation transcription, summarization and sentiment analysis without the need for extensive training and integration into business systems. On the flip side, you've got "open AI" options that really need agency to mesh well with your business's inner workings and require resources, expertise and data to train the AI models. Closed AI is pretty much ready to go with only some minor configuration, offers more control and can be ideal for tasks like automating repetitive work around handling claims, such as summarization or follow-up actions.

See also: 5 Ways Generative AI Will Transform Claims

2. Keeping the Human in the Middle

The importance of maintaining a human-centric approach in AI deployments will increasingly resonate throughout 2024, especially within the insurance sector. During a series of AI-focused seminars across various U.S. cities in September 2022, the discussion centered on the use of AI in contact centers, underscoring the heightened risks and costs tied to autonomous chatbots as opposed to those that augment the skills of human agents.

Even with ChatGPT shaking things up in the AI world, experts agree on the importance of keeping a human touch in AI-driven interactions. This is especially true in insurance, where a personal touch in customer service really matters.

This doesn't just cut down on risks and costs—it also makes customers happier and agents more effective—all by using AI as a helping hand versus a replacement.

Initial experiences with AI-driven chatbots have, at times, led to consumer dissatisfaction. While newer language models have improved at understanding user intents, the challenge of programming these systems with sufficient guardrails to act autonomously without causing user frustration remains.

By keeping human agents engaged with the help of AI, insurance companies can make the best of both worlds: AI's smarts plus the personal touch only humans can provide, making every customer interaction smoother and more enjoyable.

3. Market Challenges for Specialized Chatbot Providers in the Insurance Domain

The landscape for specialized chatbot providers, once distinguished by the sophistication of their AI solutions, is becoming increasingly competitive. These providers are no longer only competing against each other but are also up against major tech giants equipped with advanced large language model (LLM) capabilities.

Furthermore, as AI technology becomes more accessible and standardized, the value offered by these specialized chatbot services is diminishing. Many are finding it necessary to pivot, serving more as gateways to the broader LLM frameworks developed by industry leaders such as Amazon, Google, Microsoft, OpenAI and Hugging Face.

As AI becomes more common, it's putting a great deal of financial pressure on these companies; making it tough to stand out in a market that's starting to prefer all-in-one customer engagement solutions instead of just AI features on their own.

See also: Balancing AI and the Future of Insurance

In Insurance, Personalized and Efficient Customer Service Is Key

In 2024, the trend toward embracing specialized closed AI applications will accelerate as it removes the speedbumps to implementation, particularly within the insurance sector, where such technologies can streamline operations and enhance customer interactions. At Upstream Works, we're focusing on augmenting the capabilities of human agents with AI. It's all about blending tech smarts with a personal touch, which is key in the insurance world, where top-notch, personalized and efficient customer care is key to satisfaction and loyalty.

We're standing at an exciting juncture where road safety, auto insurance and technology converge. AI isn't just an added feature; it's transforming the very fabric of mobility and insurance. It allows us to reimagine risk assessment to be granular and precise by tapping into vast amounts of real-time data from vehicles using telematics and computer vision. 

Insurance is no longer a one-size-fits-all proposition; it's personalized. Data on driving habits, distances traveled and even the time of day now determines insurance premiums. This not only encourages safer driving but also provides a tangible route to transparent and accurate risk assessment, for fairer underwriting. 

We’re not just assessing risk in hindsight but foreseeing and mitigating it. For starters, Advanced Driver Assistance Systems, or ADAS, and computer vision are going beyond warning drivers of impending collisions and are preventing them. These systems are building up to fully autonomous driving.

See also: How Geospatial Data Lowers Traffic Risk

Driving Force Behind Safer Roads

Computer vision as a technology is capable of mechanically "seeing" and understanding the details of visual information. Using in-car cameras that provide real-time alerts for driver distraction and potential collisions, these integrated features direct safer driving practices. Imagine significantly reducing human error, which accounts for over 90% of traffic accidents. That's what AI brings to the table. 

AI-powered telematics devices contribute to road safety by monitoring driver behavior, vehicle performance and environmental factors in real time. By analyzing this data, AI can predict potential hazards and provide warnings to drivers. These insights can be used for coaching drivers toward safer driving habits, reducing the likelihood of accidents.

ADAS improves both driving experience and safety by using sophisticated sensors and cameras to assist drivers. Features such as automatic braking, lane-keeping assistance and adaptive cruise control help mitigate human errors, providing a buffer against accidents. ADAS can take immediate action in critical situations faster than a human might react, thus averting potential collisions.

AI telematics, computer vision and ADAS together deliver complementary benefits for reducing road incidents and creating a comprehensive safety net. While computer vision and telematics focuses on monitoring, analyzing and improving driver behavior over time, ADAS provides immediate interventions to prevent accidents. 

Tailoring Risk to Real Behavior

Analyzing vast and real-time vehicular data sets provides a comprehensive profile of driving behavior, driver history and usage patterns, to deliver fair and accurate risk assessment. AI algorithms trained on millions of use cases can detect patterns for fraud detection, analyze data to forecast future events and assess the likelihood of various outcomes. AI helps build personalized, accurate and tailor-made insurance products that can integrate seamlessly with existing solutions and deliver an enhanced customer experience.

AI has also been a game-changer in streamlining claims processing. Consider a scenario where, instead of waiting for an appraiser or adjuster, a driver can simply take images of their damaged vehicle after an accident. These images are then processed by AI, which not only appraises the damage but also verifies the nature of the claim. This translates to faster response times, quicker settlements, fraud reduction and enhanced accuracy—all leading to a swift, safe and fair settlement experience.

Data-Driven Safety 

AI is not just a technological leap but also a collective stride toward a wider socio-economic impact. With safer drivers on the road, we can hope for reduced accidents, lesser claims and reduced pressures on healthcare systems. Beyond the fiscal implications, there's an intrinsic human value in potentially saving lives and in the peace of mind brought about by a safer environment.

Telematics and computer vision, in today’s mobility ecosystem, are key drivers of this change. The rapid adoption of connected vehicles—be it EVs or hybrids—is not just transforming the automotive world but also propelling AI and insurance industries forward.

This connectivity enables the collection of vast data sets, to create personalized and efficient insurance solutions. This data-rich environment will further encourage safer driving behaviors, aligning insurance premiums with real-time driving patterns and engendering a culture steeped in responsible driving and road safety.

See also: Auto Claims and Collision Repair: The Great Reset

The Future With AI at the Wheel

As we stride confidently into the future, a robust, forward-thinking regulatory framework is essential to navigate these complexities, ensuring AI technologies not only push the boundaries of what's possible but do so responsibly and transparently. AI systems often rely on vast amounts of data to function effectively. Compliance with data protection and privacy to safeguard users' data will enable greater acceptance and adoption of AI technologies.

The future holds a connected sphere where cars communicate seamlessly. Business innovation will then center on vehicle identity, in-car payments and diverse in-vehicle services that will reshape the insurance business models, while promising a safe, more secure and sustainable future for mobility.

One of the things I have always loved about working in insurance is that it is hardly ever boring. It’s an industry that offers you the space to learn and grow, and taking advantage of this opportunity is not just to your benefit, but to the consumer's, as well. This is especially true when it comes to how emerging technologies can help you more accurately predict a policyholder’s risk profile and set rates accordingly. A perfect example is geospatial technology (GIS). 

With the climate changing, severe weather occurrences are leading to increased levels of risk for insurers across the country (with some regions affected more than others). GIS allows for more accurate risk assessment, going even deeper than ZIP code level.

Climate change and insurance

In 2023, Florida, Texas and Louisiana experienced the most hurricanes, and these severe weather occurrences inevitably led to insurance losses. According to Rate Retriever’s Quarterly Rates Update, these three states were – unsurprisingly – also among the most expensive for car insurance in 2023.

Instances of severe weather such as hurricanes, tropical storms and tornadoes have been increasing, and premiums (specifically in coastal regions and the Midwestern part of the country) have been skyrocketing as a result.

To remain competitive with the rates we are offering while still protecting ourselves, we need to analyze risk more closely than ever before. GIS can help us do just that through the use of highly specific maps.

See also: How Technology Is Changing Fraud Detection

What is GIS?

In the simplest terms, GIS is the process of understanding severe weather risks through precise mapping. This technology allows for the insurer to analyze and identify certain hazards or catastrophic risks associated with a certain region with incredibly tight precision. This basically allows you to take territorial rating assessments one step further, getting down to a level so incremental it can split one street in half and predict a different level of risk for each side.

We are all familiar with the old way of territorial rating: the tedium of inputting every ZIP code in a particular region or state into an Excel file and going through each line item to assign a specific rating. GIS flips this process on its head by allowing you to scatter plot all your policy locations on an actual map and analyze the risk exposure much more tightly.

This technology also helps you to assess risk in a more real-time manner and work to prevent fraud by not allowing new business quotes to come through your system while a catastrophic event (such as the wildfires that ravaged Texas back in February) is taking place. This makes it much more difficult for individuals in a particular area to game the system by getting insurance only when they know severe weather is coming and they’re likely to have a loss.

The benefit to the consumer

The key benefits that GIS offers to insurance professionals are fairly simple: 

• The ability to more narrowly predict risk level by region can help you save money on claim payouts 
• This technology can help prevent fraud by exposing potential insureds who are only getting insurance because they know severe weather is coming
• It simplifies the process of territorial rating by being able to visually analyze different regions on a map

There are plus sides of this technology for consumers, as well. By adopting GIS technology, you have the ability to warn your clients of potential losses before they happen so they can act. 

While there is nothing you can do to prevent the hurricane from coming, you can keep your clients in the loop on how the hurricane may affect them. With this information, clients can make necessary arrangements to protect their assets and perhaps avoid having to file a claim altogether. 

The information you provide to clients introduces an additional benefit for you as an insurer: an increase in client loyalty. If the insured trusts that you have their best interest at heart, they have more incentive to remain a client. 

See also: Convergence and the Insurance Ecosystem

The potential of GIS

The possibilities for how GIS can be implemented and utilized are vast. When you’re looking at a GIS map and you’re able to understand where the impacts of severe weather are felt most strongly you have the power to almost see into the future and predict these occurrences before they happen. This allows you a level of protection that has never been possible before.

Artificial intelligence and machine learning technologies also come into play here, enabling you to add the likelihood of an event like a hurricane or a tornado into your modeling service so you can try to understand how these events might affect losses. This likely means that as GIS becomes the industry standard for territory rating, AI and ML technology will become more prevalent right alongside of it.

This kind of technological advancement has the potential to affect your business all the way across the board. It introduces opportunities for automation and deep analytics in underwriting, risk management, claims, business reliance and several other areas. 

Autofill is my friend. I just wish insurance came closer to the experience I have when buying other products.

That issue turned out to be key to the conversation I had this month with Jeff Heine, chief revenue officer at Novidea, an insurance management platform, about the friction that can be eliminated in the process for purchasing insurance.

“Instead of making people enter information in every system multiple times,” he said, “why not flip the dynamic and use the information that’s out there? …  We’ve surrounded the broker with all kinds of information, so have them draw on that information and just ask the policyholder to confirm the answers to questions.”

Heine, who described his suggestion as an inversion of the submission process, expanded on the idea to propose a “container” for information. Once the customer, working with an agent or broker, assembles the information needed to write a policy on, say, a property, it can be enriched with information about comparable properties that provide context on the level of the risk. With data on risks becoming more granular, the carrier and broker can share with the insured not just what the level of risk is but why the level is what it is and what the insured can do to reduce the risk (and lower premiums).

“The insured is becoming more of the risk manager,” Heine said.

Crucially, the container is portable in Heine’s view of the future. The insured can take it with them even if they move to a different carrier; they don’t need to start from scratch in providing information on whatever is being insured. Although Heine and I didn’t talk about passing that container on to the next owner of a property, that would be possible. You’d have to redact the information about the owner, but all the information on the property could be sent along, saving the new owner the friction that comes with having to look up the age of a roof and a host of other details.

I’m sold. I think you’ll find the conversation interesting, too.

Cheers,

Paul

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Paul Carroll

I wonder, first, if you would describe what you see as the main points of friction between carriers and agents and brokers?

Jeff Heine

Let's look at commercial insurance. There's a lot of data and documents that are passed back and forth between the broker and the carrier and, downstream, the reinsurer. One mature prospect we have literally says it still emails spreadsheets. Think about the loss of time just in structuring the risk to get it to market. And did we capture all the data? What about midterm adjustments? Can you keep the data current? That's been a consistent point of friction. 

The friction makes getting the right coverage incredibly difficult. When I recently bought some insurance for a condo, I went with the agent who did the best job of using external data to suggest the right coverage for me. The friction extends all the way through claims, opportunities with loss prevention and so on. 

Paul Carroll

I always try to think of analogies, and, in this case, the process of applying for insurance reminds me of applying to colleges back in my day. It’s all so manual, and a lot may differ from carrier to carrier, from agent to agent. I wonder why the process can’t be more like the universal application that so many colleges use now. My kids used the universal form, applied to maybe 15 schools, and went to Cal and Yale, while I applied to three and went to Michigan State. Just sayin’.

Jeff Heine

Absolutely. In my recent experience, one agent asked for all kinds of basic information and had me take some photos, while another basically just asked for the address and came back with more complete information. 

A lot of times, there will be midterm adjustments, but they won’t be captured into the AMS [agency management system], so they won’t show up in the renewal. That’s frustrating for the customer.

Paul Carroll

What are other points of friction?

Jeff Heine

Carriers not only want to know as much as possible about the risk but also want to enrich the data based on information about similar properties. Carriers also need broad access to the data, not just in silos. That’s where LLMs [large language models, used in generative AI] have a real opportunity.

We did a survey on the state of digital transformation in insurance, and we learned that about three out of four insurance organizations have a plan in place to make significant changes to their tech stack in the next year. That’s because it's costing them too much money and doesn’t give carriers the data they need to properly price the risk or serve the needs of the account.

Paul Carroll

An old colleague of mine, working at a claims-related insurtech, said his goal was to make the claim the boss of the process. Rather than have a person be the boss, sorting through emails and trying to keep track of all the data that needs to be gathered and all the people who need to be pinged, the claim would use AI to pull everything together. Jeff, I need this information. Michelle, I need this information. Jeff, I’m still waiting for that information. That sort of thing.  

Jeff Heine

Rather than have the broker asking questions of the policyholder, a better way is: We’ve surrounded the broker with all kinds of information, so have them draw on that information and just ask the policyholder to confirm the answers to questions.

We'll call it a container. Instead of making people enter information in every system multiple times, why not flip the dynamic and use the information that’s out there, enrich it and start to look at the actual exposure at the front porch before it even hits the carrier? 

Think about the cost to the carrier just to decline a submission and how much they could save. 

Paul Carroll

I hear you on, Can you confirm this? Autofill is my friend.

We’ve started to get into solutions, but I'll explicitly ask that question: What can be done in the short term and then what can be done in the long term to reduce the friction?

Jeff Heine

Some of it is just about modernizing. There are still so many different legacy applications out there that don't provide a formal view for the customer. Then there are technologies that sit on top of the legacy systems—and I mean systems, plural. Our research shows that insurance organizations are using at least five-plus different tech systems. And it's not just policy admins; it's how you rate/quote/bind; it’s the CRM [customer relationship management] system. So we have to modernize, however that's done.

We also have to have modern applications, like a customer insurance portal, so you can interact with customers in the way they want to be met, in the way they’re used to. I think that need is acknowledged. It's just a really tough shift. 

But again, I’d stress the need to invert the submission process. Don’t just have the broker gather data. Start by using other technologies that can not only get the data you need but enrich it. You take care of the insurance opportunity while making yourself easier to do business with. 

I know there are folks out there doing this. There's actually quite a bit of money spent on the whole submission process by the carriers.

Paul Carroll

That's great. Is there anything I didn't ask about that I should have asked about when it comes to friction?

Jeff Heine

I’d just come back to this idea of a container. Let’s think of the insured having all their information where it's a bit portable, and give them a bit more power over their transactions. You know, where I, as the customer, am not having to rekey information all the time. I know a bit more about my risk. 

Smarter consumers are actually looking for ways to manage their exposure themselves, and I think that the container idea empowers them a bit with the portability of their data.

Paul Carroll

I like that. That certainly has been the push for a long time in healthcare, to give people full access to their records and to make them portable. We’re a long way from getting there, but I think that’s the right direction to move in.

Jeff Heine

In some markets, like Florida and California, insurance has become much more difficult to obtain, but Firewise designations, for instance, are helping people prepare their homes to make them more insurable. That's an example of that container, if you will. People are getting information and having to take responsibility. The actual insured will be more of a steward of what they do in that container.

Paul Carroll

I see carriers not just getting more granular about how they're evaluating the risk but then communicating back to the homeowner. I owned a home in Lake Tahoe for a number of years back when my kids were younger and were ski racers, and I got sort of vague feedback in those days about, well, you need to have brush cleared away from the house for this distance to reduce the risk from wildfire. That was sort of helpful, but these days carriers are starting to be more specific. They don’t just say, your risk is X. They say, your risk is X because of these factors. If you change the landscaping, if you upgrade the roof, if you do something else, then your risk score will improve by this much. 

Jeff Heine

You make more of your own choices. And that’s going to force the agency and broker market to think and behave a bit differently, because the insured is becoming more of the risk manager.

Paul Carroll

This is great, Jeff. Thanks.

About Jeff Heine

Jeff Heine serves as chief revenue officer at Novidea, responsible for driving global revenue and other revenue-focused functions to achieve the company’s business objectives. He brings 20 years of property and casualty (P&C) insurance industry expertise. Most recently, he served as CRO at Betterview, a remote property intelligence platform that turns data into actionable insights for P&C insurance carriers. The company was acquired by Nearmap, one of the world’s largest location intelligence and aerial imagery solutions providers, in December 2023. Before that, Heine was CRO at Groundspeed Analytics, an AI-powered ingestion and data solution for the commercial P&C industry, which Insurance Quantified acquired in June 2023. Heine has other related experience, including Guidewire Software, Adsensa (now Coupa Software) and CCC Information Services. He holds a BS from Bradley University in Illinois.

With an unprecedented "super-cycle" of elections in 2024, almost half the world’s populations will go to the polls before the year is out. According to a new report from Allianz Commercial, security is a concern in many territories, not only from the threat of localized unrest but because of the wider-reaching consequences of electoral outcomes on foreign policy, trade relations and supply chains.

The headline election will be in the U.S. in November, when a narrow result could inflame existing tensions. The European Parliament elections in June could also deepen divisions, if radical-right parties gain votes and seats. As unrest can now spread more quickly and widely, thanks in part to social media, financial costs from such events for companies and insurers are mounting. Economic and insured losses from just seven civil unrest incidents in recent years cost approximately US$13 billion. With the threat of terrorism also on the rise, and the prospect of greater disruption from environmental activists, businesses will face even more challenges in the next few years and will need to anticipate as well as mitigate evolving risks with robust business continuity planning.

So many elections in one year raise concerns about the fueling of polarization, with tensions potentially playing out in heightened civil unrest. Polarization and unrest within societies are fueled by fear. They undermine trust in institutions and challenge people’s sense of a common purpose built on shared values. We also expect to see increased unrest around environmental issues in the future, not only from activists but from those who are pushing back against government climate mitigation policies.

See also: 20 Issues to Watch in 2024

All eyes on elections in the U.S. and the E.U.

The U.S. presidential election in November is likely to be a close call, with the outcome depending on results in a handful of states. A recent poll shows that more than one third of Americans believe President Biden’s election in 2020 was not legitimate. [Editor's note: No evidence supports their belief.] Widespread disaffection among voters could be exploited by misinformation created by artificial intelligence and spread via social media. Deep fakes, disinformation and repurposed imagery, as well as customized messaging, could galvanize unrest or influence small but potentially decisive parts of electorates.

Many commentators have predicted that European Union elections in June could see a number of states politically shift to the right, with the potential for populist or far-right parties to gain votes and seats, building on a trend seen in 2023. Any success for these parties across Europe could result in growing opposition to E.U. environmental, immigration and human rights policies.

The impacts of a political shift to the right and subsequent policy changes endure long after a political party’s term in office. They fundamentally change societies and public attitudes and make the next electoral shift to the center or left seem drastic, creating the potential for schisms and potentially violent responses from those who feel underrepresented by a regime change.

Environmental activism and terrorism threat expected to rise

Between 2022 and 2023, environmental activism incidents increased by around 120%. An impactful example was the arson attack on an electricity pylon in Germany by a left-wing extremist group. This suspended production at a local Tesla plant in March 2024, leading to economic losses estimated in the hundreds of millions of euros, according to reports. In addition to high-profile protests, a trend toward using more targeted tactics, such as focusing on individuals or politicians, is evident. There is a chance that more environmental protests could escalate from acts of nuisance into larger criminal acts.

The number of deaths from terrorism increased 22% in 2023, and is now at its highest level since 2017, although the number of incidents fell. The major terror attack in Moscow in March is a timely reminder that the risk of politically or religiously motivated terrorism is back on the global agenda, and that the losses can be catastrophic. The primary driver of Islamist terrorism is the radicalization of home-grown perpetrators, which is currently being fueled by the Israel-Hamas war and is leading to an increased risk in the U.S. and Europe. However, government foreign policy is also a big driver of risk, as the Moscow attack proves.

See also: Top Global Business Risks in 2024

Multinational companies show increasing demand for political violence insurance

Political violence can affect businesses in many ways. Those in the immediate vicinity of unrest can suffer material damage to property or assets and business interruption losses, while indirect damage can be inflicted on companies in the form of loss of attraction or denial of access to their premises. 

Businesses need to protect their people and property with forward planning, such as ensuring safe and robust business continuity planning is in place in the event of an incident, increasing security and reducing and relocating inventory if likely to be affected by an event. Using scenario planning and tracking risks in areas key to their operations can raise businesses’ awareness of where political violence and civil unrest risks may be intensifying. Companies should also review whether their insurance policy covers the impact of risks such as strikes, riots and civil commotion.