KEY TAKEAWAY:

--The technology has the potential to lower claims costs by up to $1,000 per claim and eliminate the historical delay in the traditional accident reporting process, which averages five days from accident to first notice of loss. 

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Too many headlines contain wild hyperbole meant to grab readers’ attention while conveying the enthusiasm of the author. In particular, the word “transformation” has been severely overused and often misplaced, particularly when applied to the auto insurance claims process. This is NOT the case here!

It is our opinion, as experts in auto physical damage claims information technology, that the more sophisticated crash detection as defined here will indeed be transformative to auto claims in multiple ways. 

But first it is critical to understand the relationships among various telematics programs and crash detection technologies.      

Telematics: A Brief History

Telematics, in one iteration or another, has been around since GM introduced its OnStar in-vehicle telematics technology and related safety services. OnStar was initially a dealer-installed device offered in several 1997 Cadillac models. OnStar enabled drivers to connect from their cars with safety advisers in the event of an accident, breakdown or other roadside emergency.

Since then, the convergence of telecommunications and information processing – broadly referred to as telematics – enabled the use of information such as vehicle location, driver behavior, engine performance and vehicle activity. Numerous telematics service providers (TSPs) emerged globally to offer a wide variety of uses across a number of market verticals. In 2002, Octo Telematics was founded in Italy specifically for use cases in the auto insurance industry, originally including fraud, theft and location services.

These early applications required the installation of some type of in-vehicle hardware device (dongles, sensors, windshield tags, etc.). TSP solutions included commercial applications for fleet management, as well as personal lines auto insurance applications including usage-based insurance (UBI) and pay-as-you-drive (PAYD). 

In 2015, a smartphone app-based driver behavior tech company was spun out of Harvard Innovation Labs. Censio was renamed True Motion and was acquired by Cambridge Mobile Telematics (CMT) in 2021. The company’s mission was safer and more affordable driving. CMT has grown to become the world leader in telematics and powers many of the largest insurance telematics programs in the U.S. and globally. 

Consumer adoption within the auto insurance landscape still remains in the low double digits but continues to gain traction as loss costs and premiums continue to rise and consumers seek savings options. Adoption in North America has lagged other global markets for a variety of regulatory and cultural reasons.

More recently, a specific application of telematics – namely crash detection – has emerged as new model smartphones include high-dynamic-range gyroscopes, GPS location, barometers, microphones and advanced motion algorithms that can detect a crash.

See also: How to Reduce Distracted Driving

Accident Detection and False Positives

With the introduction of smartphone accident detection in 2015 by Zendrive, a driver-centric analytics company, variations of crash detection began to emerge, mostly for notifying emergency services, tow trucks and family members. Other applications included the gathering of accident- related data for future use in insurance claims.     

Most recently,  there have been a number of stories about new model smartphones and connected devices with crash detection features alerting early responders to crashes – both real and not.

But beyond these kinds of crash detection, another application is emerging for use specifically in auto insurance accident claims that has the potential to truly transform this process by lowering claims costs by up to $1,000 per claim and eliminating the historical delay in the traditional accident reporting process, which averages five days from accident to first notice of loss.  

Crash Detection and the Auto Insurance Claims Process

Before any insurer would consider deploying a crash detection program, there are two critical technical issues to be overcome: namely, accuracy in detecting real accidents (at speeds below 25 mph) and the elimination of “false positives,” in which sensors misinterpret motion as accidents when it may be something as simple as an accidentally dropped phone, energetic dancing at the Bonnaroo festival or a wild ride on a roller coaster. 

No carrier would want to waste valuable resources and risk annoying their policyholders by contacting them unnecessarily when no accident has occurred. On the other hand, all carriers would find it valuable to be alerted to real crashes in real time. In addition, documented crash details would have great value.      

Right on cue just last month, Sfara, a global telematics technology provider that launched the first mobile phone-based crash detection in 2014, introduced capabilities that solve both of the technical issues.

The distinction between basic crash detection and all-speed, false-positive-free crash detection is critical for effective deployment in an auto insurance claims application.

Low-speed accident detection for claims is more valuable than many may think. Sfara research finds that 70% of crashes occur under 25 mph, as do 48% of crashes involving injuries--and solutions that only capture high-speed accidents miss all of them. 11% of fatalities occur when a vehicle is not moving at all. 

Sfara Crash Detection

Sfara has formed strategic partnerships with Mercedes Benz; Bosch; CCC Intelligent Solutions, the industry’s leading auto insurance physical damage information provider; and Solera eDriving, a global digital driver risk management provider for fleets. These relationships enable insurance companies and fleets that are already integrated with these companies’ solutions to operationalize Sfara’s crash detection results quickly and easily through the simple addition of the Sfara SDK to their flagship smartphone apps. Several top 10 carriers have already begun. Thus, real crash detection becomes available to all policyholders, not just the minority who are enrolled in telematics programs.     

See also: Could Auto Accidents Be Reduced by More Than Half?

Insurer Adoption

Crash detection, and its first cousin accident response, are poised to see real traction with auto insurers.

In September, State Farm joined USAA, which incorporated crash detection capabilities into their respective mobile applications a year earlier. In February, Progressive Insurance announced the planned introduction of their app-based accident response service to offer towing and emergency services and to start a claim after an accident. 

Importantly, however, none of these programs have indicated that they can offer service at all speeds.

The Future

Real crash detection, such as that offered by Sfara, is poised for rapid adoption by auto insurers and will literally transform the auto insurance claims process, including first notice of loss (FNOL), which has historically occurred many days after an accident and been labor-intense. Crash detection will enable digital FNOL in real time and can include accident management, triage of roadside services, automated scheduling of vehicle repairs, photo estimating, parts ordering and other use cases not yet envisioned. And because it is low- to no-touch and technology-powered, its cost to carriers will be nominal.  

Crash detection is perfectly aligned with emerging claims process digitization initiatives and will significantly reduce loss costs, thus materially improving combined ratios. It is also well-aligned with the industry’s strategic shift underway in claims strategy from a "repair and replace" to a "predict and prevent" mindset: Crash detection can be the portal through which future advances in vehicle and driver safety can be delivered.

Real-time crash detection and FNOL will help transform the traditional mindset in claims operations to focus on speed of resolution. Equally valuable is the crash data captured with detection, which is instrumental in the claim investigation process. Think of crash detection as an unbiased “witness” gathering all the critical information on speed, direction of travel, point of impact and more.

Auto insurance financial performance is under extreme pressure as costs continue to rise, as vehicle complexity increases, as the workforce is aging out and taking critical expertise with them and as unsustainable, higher insurance premiums are meeting resistance from regulators. Crash detection can deliver significant relief quickly and at low cost.

Policyholders will embrace crash detection once they understand that it is all upside and no downside. Emergency services and accident response will be especially welcome, as will the elimination of irritating phone calls that require repeating accident details to multiple agents. Claims resolution and cycle times, including the return of repaired vehicles, will be materially improved. 

Auto insurance ecosystem partners will see operational benefits and savings through increased real-time, digitally integrated workflow and the elimination of legacy communications and labor intense processes.

See also: Auto Insurance in an Existential Crisis

Call to Action

With the arrival of true crash detection, auto insurers should learn, test, pilot and implement this technology as one of their highest priorities. Their stakeholders and partners will be most appreciative, and their customers will reward them with greater loyalty.  

Crash detection will transform auto claims and become table stakes, and it will be no accident – which is definitely not hyperbole.

The challenges of inflation have significantly impacted our nation, and the insurance industry is no exception. Despite hopeful projections that inflation will be regulated by the end of 2024, the current situation is becoming increasingly expensive for businesses, particularly insurance organizations. Inflation, coupled with supply chain issues, has resulted in a substantial rise in costs, especially in the form of claims spending. Estimates suggest that underlying inflation contributed around 45 to 50% of the total increase in claims spending by the end of 2021, and this trend has persisted through 2022 and into 2023. 

However, it’s not just costs that have been affected; workloads within the insurance industry have also been swelling, leading to higher rates of burnout among employees. This combination of factors poses a significant risk to both the insurance workforce and the financial bottom line of organizations. In order to navigate these challenges, insurers need to effectively combat the rising workloads and costs they are facing—and that’s where automating premium payments can help. 

Read More Here

 

Sponsored by ITL Partner: InvoiceCloud

When a panel of experts recently voted that a gene-editing technique was safe for clinical use, it rang the opening bell for a new era in healthcare. 

The one technique, alone, could have a profound impact on the more than 100,000 Black Americans and 20 million people worldwide who suffer from sickle-cell anemia and who could now be cured, rather than just managing what can be a painful and debilitating condition. 

And that technique is just the first of many research efforts to get out of the lab. Hopes are high that other, related techniques could cure a host of cancers and blood disorders, some forms of blindness, cystic fibrosis, muscular dystrophy, high blood pressure related to LDL cholesterol and much more. 

We're just at the opening bell. It will take many years to fully understand the effectiveness and potential dangers of the sickle-cell treatment, and a lot could still go wrong. It will take decades for the full array of gene-editing treatments to be vetted and rolled out. As a result, the effects on health insurance will be slow to play out. 

Still, the achievement is stunning, and I think it's both worth celebrating for a moment and worth digging into a bit to understand where science can take humanity.  

The sickle-cell technique stems from the work on CRISPR that won the 2020 Nobel Prize in Chemistry for Jennifer Doudna and Emmanuelle Charpentier. CRISPR is a family of DNA sequences that can be used to target and shut off a specific gene in a person's genome that causes disease, such as the one that causes sickle-cell anemia.

More recent research suggests CRISPR can even be used to fix "typos" in the three-billion-letter sequence of the human genome and treat genetic disease.

Because CRISPR is altering body chemistry at such a basic level, researchers are proceeding cautiously, initially focusing on conditions such as sickle cell where a single gene defect has been identified as the cause and where editing the gene should have no side effects. 

Even with sickle cell, the work has a very long way to go. The panel of experts who have found the treatment safe for clinical use have only seen it tried on 44 patients, and just 30 have been followed for at least 16 months. No side effects have been recorded, but, as this article in the New York Times explains, snippets of genetic material created by CRISPR could conceivably bind to an unintended part of someone's genome and turn off the wrong gene.

The treatment is rough on patients. The Times says: "Patients first have eight weeks of blood transfusions followed by a treatment to release bone marrow stem cells into their bloodstream. The stem cells are then removed and sent to the companies to be treated. Next, patients receive intense chemotherapy to clear their marrows for the treated cells. The treated cells are infused back into the patients, but they have to remain in the hospital for at least a month while the new cells grow and repopulate their marrows."

The treatment is also very expensive -- likely to cost millions of dollars per patient. But the healthcare system in the U.S., alone, spends $3 billion a year treating sickle cell, and gene-editing offers a full-on cure, so Medicare and private insurers have indicated that they'll cover the treatment. 

To me, the milestone here is that we now have the prospect of actually curing chronic diseases like sickle cell, many cancers, hypertension and more, not just managing them. 

And capabilities will only accelerate from here, largely because AI lets researchers sort through exponentially more possibilities than unassisted humans can as they wrestle with the mind-boggling complexities of human biology. Already, AI has let researchers understand how hundreds of thousands of proteins fold themselves, which determines a lot about how they interact with other proteins and with any drugs; previously, just determining the shape of a single protein required a chemical process that took more than a year and cost in the six figures.   

As you keep reading about the great prospects for generative AI -- and they are great -- realize that other strains of AI are at work, too, and some are helping usher in a new, gene-editing era in healthcare that will benefit millions and millions of people.

Cheers,

Paul

As inflation and increasing global risk push up the cost of coverage, a powerful tool has gained traction in recent years: partial or total self-funding of workers' compensation.

While companies assume more risk, they get significantly more control over coverage, claims management and associated costs. The result is often highly cost-effective.

For example, when OneDigital client Wheeler Health, a healthcare and human services provider, was grappling with an increase in its workers’ compensation premiums, the answer came in the form of a partially self-funded plan. This program did two things for Wheeler Health: It helped manage the financial burden (workers' compensation expenses had soared to nearly $1 million for a $25 million payroll) and gave the client a more active role in claims management. 

The plan leveraged an A+ national insurance carrier without the need for unconventional claims-handling methods or a third-party administrator and offered a smooth transition – claims reporting continued as usual to the insurance carrier, with fixed monthly premiums. The fixed-rate premium increased less than 2% annually.

Savings have run into the millions of dollars over the past decade. Had Wheeler remained on their fully insured plan, their annual workers’ compensation costs would hover around $1.8 million to $2 million. 

Partially self-funded workers' compensation programs offer greater financial control and cash management by allowing companies to only pay for actual, incurred claim expenses, reducing the need for fully valued traditional insurance premiums. This approach fosters a stronger safety culture, as companies see precisely where their premium dollars are going and become more invested in preventing workplace accidents and injuries to minimize claims and costs.

By tailoring their self-funded plans, companies can align workers' compensation strategies with industry-specific needs and risk profiles, optimizing coverage and cost-effectiveness. This transformative model can also greatly enhance employee well-being and productivity and overall organizational resilience.

See also: Case Study on Using AI in Workers' Comp

Why Don’t All Groups Take Advantage?

While the financial benefits of well-designed partial or fully self-funded workers' compensation plans are extraordinary, they aren't that common. Some possible reasons are a general lack of understanding and limited product knowledge. Quite frankly, it’s also less profitable for insurance companies when clients move to this type of plan. 

But, as you can see, the benefits can be substantial.

Employers with a substantial payroll, a strong commitment to workplace safety and a desire to reduce workers' compensation expenses should consider this option. 

Data-driven decision-making has long been the goal of P&C commercial lines carriers. There has never been a shortage of data within a carrier’s own walls, and decades ago some sought to create a competitive advantage through the use of predictive models. However, it was a considerable challenge to amass and normalize enough structured data to train a model. The handoffs to run and use a model were manual. And keeping the model current—by retraining it with newer data—ran into the same challenges.

Despite these early hurdles, carriers saw the value of using models to evaluate risks and identify the new business submissions in the queue with a higher probability of winning. Risk analysis models eliminated discretion in comparing exposures with target account guidelines. Predictive reserving models avoided being solely reliant on each claims adjuster’s experience to recognize the losses that looked simple at intake but carried all the hallmarks of a complex and costly claim.

See also: Why AI Is a Game Changer

An Inside Look at AI in Commercial Lines Carriers

Resource Pro Insights’ newly released research, “Artificial Intelligence in P&C Commercial Lines: Carrier Plans, Perceptions and Potential for High-Value Use Cases,” offers a comprehensive look at AI within commercial lines carriers today.

We include robotics process automation (RPA) in our AI research. While not everyone considers this an AI technology, RPA has proven itself to be an effective, adjacent-to-AI solution for carriers to automate repetitive actions. Our research reveals that RPA is well-embedded within commercial lines, with most carriers being in the investment phase of planning, piloting or running in production.

AI solutions are helping commercial lines carriers realize new value across the insurance lifecycle, with even more potential in the future. For example, conversational AI allows insurance carriers to offer self-service and personalized product education, enhancing customer experience. The value of RPA for billing is on the rise, to achieve both precision and speed in producing invoices and booking receivables, functions that can span multiple, disconnected systems. Advances in voice systems that include multilingual natural language processing are removing friction in policy servicing interactions. Image recognition and computer vision are giving carriers the ability to expand the scope and geographic reach of their loss prevention services.  

Machine learning in the insurance industry plays a key role in helping carriers make data-driven decisions. More than 75% of carriers have plans or pilots or will be using it in production this year. The power of machine learning is amplified by the growing market of third-party data available to train and refresh models. Within underwriting and risk management, these third-party sources enable carriers to automatically augment risk profiles and verify submitted data -- for example, SIC/NAICS codes. Machine learning can score each risk, apply more refined straight-through-processing rules and triage underwriting referrals based on a model prediction of those most likely to bind.

The value carriers believe AI can offer in the commercial lines submission process is noticeably higher this year than last. New business applications and policy change requests contain unstructured and structured data in a seemingly infinite array of formats. Machine learning is able to normalize submission data and validate or augment using third-party sources. What could have taken days can now occur in minutes.

Commercial carriers also see value in using AI for predictive claim reserving, an area claims organizations have been modeling for years. The earliest efforts by carriers had their data scientists creating models that were manually run after each new claim was registered. Now there are solutions with models based on both internal and external data. Some not only automate predictive reserving for each new claim but also run throughout the life of a claim, triggered by changes to the loss information.

The expected value of AI for commercial claims fraud monitoring and detection is lower than last year, but still high overall. Carriers appreciate that AI can automate a more thorough approach to continuously monitor open claim files for potential fraud. Many available external data sources play an essential role in offering carriers a nationwide lens on the bad actors and other warning signs.

Learn more about the current state of AI for property and casualty commercial lines carriers by reading our new research report, “Artificial Intelligence in P&C Commercial Lines: Carrier Plans, Perceptions and Potential for High-Value Use Cases.” 

Quick question: What’s the most important thing you can do to ensure a successful 2024 for your agency?

The answer: Finish out 2023 as strongly as possible.

After all, you can’t set a course for a prosperous future without knowing where you’ve been. And chances are, if you weathered the hard market and all its many challenges this year, you will carry plenty of momentum into the next year and beyond.

How can you plot a course for growth? Let’s review a few key considerations of annual agency planning and reveal a few tips that agents can use to drive their efficiency and profitability.

Where (and When) to Begin

If you haven’t yet started your 2024 agency planning, you should do so as soon as possible. The first step is to calculate your anticipated year-end results.. 

If your analysis reveals you might end 2023 short of your financial goals, you can still take steps to close the gap. Look to capture any potential revenue. Consider whether you could hit a quarterly incentive target or accomplish a business goal that could trigger additional guaranteed payments.

Additionally, look at your profit-sharing agreements. Is there a lock-in for achieving a specific sales target or a certain number of policies that you can still attain? Or can you start placing business with a carrier now so you can boost your profit-sharing potential and even lower your loss ratio? Another wise idea: See if you can reduce reserves on some of your larger claims to improve your year-end payout potential. Remember, the stronger you finish out 2023, the bigger head start you’ll have on driving 2024 results.

See also: 5 Must-Haves in Agency Management Systems

Five Must-Haves for Planning Success

Once you have your year-end ’23 plan set, it’s time to dive into 2024 planning. Consider the following five essential elements:

1. Know your carriers’ expectations. Before setting your own agency goals, you need to know what your carrier partners plan to accomplish in the coming year. Some carriers are looking to grow in 2024, but others are taking a different approach in response to the hard market. If your key objective is agency growth but your five most trusted carrier partners aren’t in growth mode, you’ll have to adjust your goals to match what’s feasible for your agency.

2. Decide what you’ll do differently. This can be the most difficult part of annual planning. It’s always tempting to keep doing things the way they’ve always been done, especially if those things have led to agency success in the past. But at its core, today’s market is much different than the one we’ve experienced for the past decade. That means you’ll need to make some changes to remain competitive and profitable.

3. Set clear goals—and put them in writing. Do you plan to grow in personal lines in 2024, or are you targeting a new class of commercial lines business? No matter which goals you choose to pursue, make sure to write them down and share them with your team to get full buy-in. 

When creating goals, be specific. Spell out exactly what success will look like; for example, increasing policies per client or adding a certain number of new clients. Include distinct goals for staff, such as the number of quotes or client retention calls you expect them to achieve. 

4. Build out your marketing strategy. Your goals will shape your 2024 marketing initiatives. Be sure to measure all marketing—including metrics you collect in your CRM and social media management tools—so you can double-down on the best-performing tactics and channels. 

5. Seek outside help as needed. If you’re a member of an independent agent alliance, you can access expert assistance with agency planning. For example, at SIAA, our master agencies provide guidance to their local member agencies about how to write the types of business carriers are seeking the most. We also offer access to local agency growth coaches who have incentives to help our agents grow and succeed.

Five Tips to Achieve More in 2024

While there are no guarantees, these five tips can help you choose the best path forward for your agency:

1. Evaluate your agency’s value proposition. Make sure it still resonates with your clients. Agencies that once differentiated themselves based on price may find it difficult to succeed in the current hard market.

2. Choose technology wisely. When weighing tech investments, choose solutions that will help you improve efficiency, eliminate duplicate work and enhance the customer experience. These can include anything from marketing automation platforms and payment processing solutions to new websites, video proposal tools and agency mobile apps. Consider that clients today seek support beyond typical office hours and explore whether virtual assistants or service centers can help you increase your hours of operation without adding to agency headcount. 

3. Educate whenever possible. On a recent SIAA panel call, experts from several large agencies agreed that education is one of their biggest challenges. Customers need to understand the reasons behind their policy increases. Successful agents will take time to explain the nuances, such as how inflation and rising replacement expenses have affected policy costs. 

4. Consider setting parameters around re-shopping. It’s harder to find lower-cost policies in a hard market. Accordingly, agencies that once re-shopped policies with every renewal may want to consider setting more specific criteria, such as only re-shopping business that has increased by 15% to 20% depending on market conditions.

5. Keep on prospecting. Once you identify a prospect, treat them like a client. Include them in your newsletters and promotions, and invite them to follow your social media channels so you can increase your odds of turning them into a customer.

See also: The Key to Agency Management Systems

Plan Confidently for the Future

To ensure success, involve all agency stakeholders in your planning process. Make your plan a living, breathing document that you can update throughout the year. And build in individual goals for agency staff members so you can hold them accountable. With this approach, you’ll develop a solid strategy that will propel your agency forward.

The business world is in a near-constant state of flux. With technological innovation and shifts in perspective, business and the working world are always changing and are incredibly competitive. As a result, employees who adopt practices of lifelong learning are often best prepared for the myriad changes within their careers. 

Learning should continue throughout a professional career. By creating a culture around continued education and rewarding the lifelong learners in your organization, employers can help their teams remain as cutting-edge and experienced as possible, allowing both the organization and its employees to reap maximum benefits in an ever-evolving landscape.

The necessity of lifelong learning 

Today’s leaders and HR professionals are seeking to hire for attitude and personality and train for skills. They know finding a good culture fit may be far more important and indicative of an employee that will be easier to retain than seeking one with the “perfect” skillset. 

Amid issues with retention and employee satisfaction that fueled the Great Resignation, companies that offer continued education are likely to fare better long term. A recent survey showed that 94% of employees would stay with their current employer if that employer invested in their lifelong learning.

Agents, risk management professionals, adjusters and other employees must always be aware of changes within the insurance industry, law and regulations to stay competitive in their roles. Staying on top of market trends within the insurance industry can vary by type of insurance or by state, making targeting continuous education all the more important. 

Adapting to change 

Each industry will introduce new necessary skills that employees will have to learn if they intend on growing within their careers. With this in mind, organizational leaders must serve as models, providing relevant learning opportunities for their team members and growth-orientated mentorships. In addition, team members must be aware of the benefits of lifelong learning and have a clear picture of what taking advantage of learning opportunities means for their long-term career outlook.

See also: The Key for Agents: Lifelong Learning

Innovation and creativity 

Providing lifelong learning opportunities for employees can also boost inter-organizational creativity and expand perspectives. With more creativity and innovation coming from the various team members, organizations can grow, develop cutting-edge products and services and engage with expanded markets. 

It may seem like there is little to no room for creativity within an industry such as insurance or risk management, but that outlook could be short-sighted. When problems pop up within the insurance industry — such as rising insurance premiums in Florida or California — the educated and creative minds will be the problem-solvers. 

The more teams are engaged with and involved in creative organizational growth, the better the job satisfaction, productivity and overall retention will be. 

Leadership development 

One primary reason to cultivate a lifelong learning culture is to develop future organizational leadership. Today’s leaders won’t be around forever, so it will be up to the next generation to continue the mission and goals of the organization. 

Learning opportunities that are built within the organization will instill confidence in people with natural leadership abilities, allowing them to rise to the occasion. When structuring lifelong learning initiatives, organizations need to give space for promotions and reward individuals who take full advantage. 

See also: Opportunity Now and in 2024

Practical strategies 

Lifelong learning initiatives can become part of a company’s core when practical strategies are applied and made a priority. Companies should home in on the skills that are imperative for team members to learn to grow within the company and keep the company on the cutting edge. 

This strategy must include having a finger on the pulse of the industry changes and innovations, so leadership knows what skills their team members need to have to stay competitive. Organizations should also encourage collaboration within the learning environment, as teams that learn together often grow and innovate more effectively. In addition, companies should create space within the organization to learn on the job, so continuing education opportunities can be accomplished along with day-to-day productivity. 

With lifelong learning woven within the fabric of the company makeup, team members and leadership can work together toward innovative growth. 

Paul Carroll

To start out, how are agents and brokers responding to digital distribution platforms?

Jonathan Hendrickson

Agents and brokers are responding positively to digital distribution platforms -- the platforms are a source of enablement for our brokers who use them. Within Gallagher, two examples of who uses them are the inside sales brokers in small markets and the wholesale brokers working with E&S carriers. Both are benefiting from them. Gallagher uses platforms to make it easier for clients and save our team's time in working with multiple markets.

Paul Carroll

Can you say a little bit about how that works? Early on, everybody was talking about disintermediation. Now people seem to realize that agents and brokers have a real role, How does that hybrid work, between the digital and the person?

Jonathan Hendrickson

There are quite a number of insurtechs that are working to enable brokers, and we partner with those types of companies.

One type of enabling platform is a SEMCI, which is a single-entry, multiple-carrier interface. A SEMCI allows brokers or clients to put information into a system that can yield several quotes and options for clients. It is an enabler of the end-to-end process for a client and makes it smoother.

Paul Carroll

That's helpful. What about customer preferences? What are they showing that they like and don't like? And does it vary by type of client, line of coverage or anything else?

Jonathan Hendrickson

Preferences vary by type and size of client. Clients are more comfortable making digital purchases in personal lines than in commercial lines. That's been true for a while. In commercial lines, clients largely want to talk with an agent or broker before completing a purchase, even for small commercial purchases. The market research we’ve seen estimates that small commercial market purchases are made at single digits in terms of percent of premium (coverage) that is purchased fully digitally.

Most clients begin their search online with education and research, even if they don't make a purchase. Often, they end up working with someone who can help answer questions. Some clients like to correspond with text, so Gallagher is working on developing more of those kinds of capabilities to meet the client where they want to be.

Paul Carroll

Having covered technology for a while, I’ve found that there's sort of a flow. Technology starts one place and then flows in a direction for a long time. So, for example. Defense Department work in the

1960s and 1970s flowed out into consumer channels. Now, technology seems to be flowing in the other direction. My hypothesis on digitization and insurance has been that it would really start in the personal lines, then maybe move into small business as it moves up into large commercial. Does that sound right?

Jonathan Hendrickson

From what we've seen so far, the movement to fully digital purchases beyond personal lines has been pretty slow. And there's some value to moving at a slower pace. Insurance is in the business of de-risking things for other industries. When you have a bedrock that you can build upon, that's very helpful and a great foundation.

Paul Carroll

What about generative AI? How much is that being used? And how much do you think it can be used in the next year or two?

Jonathan Hendrickson

Overall, we believe that use cases in generative AI are still in the early innings. But it shows great promise. Gallagher has been running a number of proof of concepts to understand the capabilities of generative AI, and we expect we're going to be able to leverage it to help enable a number of areas, including our client, sales and service teams. We are encouraged about how these capabilities will help and support them.

Paul Carroll

Can you share a use case or two?

Jonathan Hendrickson

Gallagher started using generative AI for language translation, and so far it has been terrific. Prior to generative AI, we’d work with other organizations who would help with the different languages. For example, if you work in Quebec, you need to translate to French Canadian. In one of the really early wins, we found that generative AI language translation can give us a better starting draft.

We're doing other things, as well, including seeing how it can glean information from documents to better prepare other documents. A lot of work has been done determining how we help provide information faster for those who are going to be providing advice to clients.

Paul Carroll

That’s interesting. While with the Wall Street Journal, I lived in Brussels and then in Mexico City. So I've struggled with both French and Spanish. An AI translator would have been nice.

More broadly, how are agents and brokers leveraging technology to streamline and enhance their own internal processes?

Jonathan Hendrickson

Gallagher is working to leverage technology to streamline and enhance our business processes. We're using single-entry, multiple-carrier interface platforms to save time providing quotes to clients. We're also leveraging technology to provide a renewal process that is more digital, which saves time for both our clients and our service teams. We are also combining data with technology platforms to help provide advice through benchmarking and analytics. Creating more digital self-service options for clients while leveraging technology to help increase efficiencies are just a few of the ways that we're using these new capabilities.

Paul Carroll

To talk about Gallagher more broadly, how are you focusing on technology and innovation? And are there particular Insurtech sectors that are looking interesting to you?

Jonathan Hendrickson

Two of the top categories for Gallagher are digital enablement and data and analytics, including AI. Another area of importance involves evolving risk management solutions. It's an area we like to keep an eye on, if for no other purpose than just to be a good adviser to clients who are looking to leverage these kinds of solutions.

Paul Carroll

At The Institutes, we've begun a real focus on “Predict & Prevent.” Is that the kind of thing you're trying to do with clients? Or could you just tell me a little bit about what some of those risk management opportunities are?

Jonathan Hendrickson

Gallagher prides itself on staying on top of what's happening in the marketplace, even if it's not a service that we're offering to a client. It is important for us to be educated about trends so we can do a better job handling and advising about risk management.

“Predict & Prevent” is one of the services that we have been working on with clients. As an example, there are wearable devices to help employees with ergonomics and are designed to prevent injury. When you have people whose workdays involve a lot of movement, the devices can help them identify high-risk postures. If a device detects a high-risk posture, it gives them a little haptic buzz, and with the right kind of training and reinforcement, movements that can lead to injury can actually be minimized. Additionally, the behavior change can reduce uncomfortableness that diminishes employee production. So you can make the work environment better for people, and they don't have injuries that cost the company money.

Other technologies coupled with safety systems at workplaces that identify high-risk behaviors help employers know who needs additional coaching. All of this is designed to help people, which is ultimately a terrific outcome.

Paul Carroll

I love the themes you're talking about.

Jonathan Hendrickson

Besides the wearables, a lot of groups are trying to get out in front of water damage, which we know is a huge category of loss, with leak detection. And we’re seeing increasing interest from clients who are considering adopting some of those types of solutions.

Paul Carroll

It has always struck me that while rates are going up all over the place, they're coming down consistently in workers’ comp, which suggests that workers’ comp may be leading the way in terms of reducing risks.

This has been great. But is there anything I didn't ask about that I should have asked about?

Jonathan Hendrickson

I really liked the questions and topics we discussed today. These are the kinds of questions being asked, and here at Gallagher we are trying to work through solutions. Today's conversation seemed like a very natural extension of some of what the industry is trying to focus on and move toward.

Paul Carroll

Okay, perfect. I really appreciate your taking the time.

 

About Jonathan Hendrickson

Jonathan Hendrickson is the VP, Head of Insurtech Development for Gallagher. Prior to joining Gallagher in 2018, Jonathan was the Head of Global Strategy for Aon Hewitt and led partnerships for Insurtech and Analytics across Aon. Prior to Aon, Jonathan worked at McKinsey & Company where he served clients in both health and P&C insurance. Jonathan began his career working in technology with Cap Gemini Ernst & Young. Jonathan has his M.B.A. from The University of Chicago Booth School of Business and his B.S. and B.A from the University of Southern California, all degrees with honors.

Platforms have repeatedly provided the groundwork for surges in technological process over the 35 years I've been writing about innovation. MS-DOS wasn't just an operating system. It provided a platform in the 1980s and 1990s that became the home for all sorts of what were originally discrete little programs (clocks, calculators, etc.) and then for far more powerful programs (word processors, spreadsheets, browsers and so on). Google didn't just provide a search engine. It provided a platform for commerce, for maps and for a host of services that we use to navigate the internet. Amazon has become a platform for all kinds of products and sellers and even for businesses wanting to host their IT operations in the cloud.

With all that history, I've been keeping an eye on the platforms that are developing for distributing insurance, and a long series of conversations at InsureTech Connect in Las Vegas at the beginning of the month showed me that there's been a lot of progress. To get a handle on just what's been happening over the past year or so, I sat down with Jonathan Hendrickson, vice president and head of insurtech development at Gallagher, for this month's interview. 

He said agents and brokers who use digital distribution platforms are taking to them because they're more convenient. For instance, he said a SEMCI -- which stands for single-entry, multiple carrier interface -- lets brokers or clients put information into a system that can yield several quotes and options. 

Hendrickson noted that, in commercial lines, clients want to talk with an agent or broker before completing a purchase. That's true even in small commercial, where he said the percentage of purchases that are fully digital is still in the single digits. 

"There's some value to moving at a slower pace," he said. "Insurance is in the business of de-risking things for other industries. When you have a bedrock that you can build upon, that's very helpful and a great foundation." 

What about generative AI (the question of the day and maybe week, month and year)?

He says Gallagher has been experimenting and found, for instance, that generative AI can do a very helpful first draft of a translation into another language. 

"We're doing other things, as well," Hendrickson said, "including seeing how it can glean information from documents to better prepare other documents. A lot of work has been done determining how we help provide information faster for those who are going to be providing advice to clients." 

Platforms tend to take shape slowly -- then suddenly grab hold. DOS, for instance, was in the market for nine years before the version introduced in 1990 really captured the market. We're not at MS-DOS 3.0 yet in insurance, but, if you dig into the interview, you'll see there's an awful lot going on.

Cheers,
Paul

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60% of small businesses, including insurance agencies, that use AI or automation say their marketing is working more efficiently.

Chief information officers, chief digital officers and others running digital innovation initiatives usually have to scrounge around for every bit of funding they can find. Not so with generative AI.

It has caught the public imagination so quickly that the world of innovation funding has flipped upside-down. 

Every board knows it needs something intelligent to say about a generative AI strategy, which means every CEO knows they need something intelligent to say about a generative AI strategy. Those CEOs are turning to the in-house digital innovators and saying: "Help me figure out something intelligent to say about a generative AI strategy."

So every CIO, CDO, etc. finds themselves with money being thrown at them so they can set up a slush fund and experiment to help define a strategy -- or at least a placeholder that buys time for a strategy to be developed.  

The CEO of an AI vendor I spoke with at last week's InsureTech Connect in Las Vegas said his sales cycle with major carriers used to be 12 months, or even 18, but the demand for generative AI is so feverish that he now may go from initial contact to contract in four to six weeks. He says one prospect saw a demo and asked for a contract on his way out the door. 

Now, throwing money at a problem in hopes of finding a strategy tends not to end well. But while no one I met at ITC -- or anywhere else, for that matter -- has a clear answer about how generative AI will play out, some do have smart advice on how to get starting on working out what that future could look like. 

In its simplest form, that advice amounts to: Dig in and play around. That doesn't mean just as a company; that means as individuals. There are endless possibilities -- and pitfalls -- associated with generative AI, and there's no time like the present to start acquainting yourself with them.

Put in a more rigorous way, "dig in and play around" means "think big, start small, learn fast," which has been my mantra for the nearly 30 years that I've been writing about corporate innovation. My frequent co-author Chunka Mui describes our approach in detail in this piece from May, "Six Words to Focus Your AI Innovation Strategy," about how to approach generative AI. 

On the theory that nobody is as smart as everybody -- the founding principle for Insurance Thought Leadership -- it likely will also be useful to find fellow experimenters with whom you can share experiences as you learn both what does and what doesn't work. Along those lines, a longtime colleague, John Sviokla, already knows a ton about generative AI, as he showed in this interview I did with him recently, but through his recently formed GAI Insights group is convening lots of other smart people to share their learnings.

My personal approach when dealing with something as big and daunting as generative AI is to try to make it real by looking for examples. I get the basic theory and see the potential, but I've also seen people gloss over a lot of problems with a lot of technologies over the years, so I look for tangible results to guide me.

At ITC, I found a few new ones. Some were modest -- having the AI listen to a phone call for a claim and fill out a first notice of loss, then figure out where to place it in the queue, based on an assessment of the severity of the accident. Some were more intricate and potentially important. For instance, I was shown a live underwriting assessment of a restaurant in the Washington, DC, where the generative AI found a mechanical bull (because of a picture on the website) and a deep fryer (based on the menu). Those are the sorts of things that a thorough underwriter would have found, but having the AI find them in seconds, rather than minutes or tens of minutes, could help insurers with a tricky problem: making sure the intensity of the underwriting effort is justified by the potential size of the business.

Recent conversations, such as this one with Megan Pilcher, the insurance go-to-market leader at IntellectAI, for this month's ITL Focus also show that we're making progress in identifying opportunities. For instance, she says:

"When an underwriter prioritizes their work, documenting the accounts they did not write is a less than desirable task. We can start using AI to do that documentation and provide a summary. When the risk comes back the following year and a different underwriter picks it up, they can get a rundown." 

And: 

"With today’s manual processes, someone only pulls [loss run] information if a decision has been made that at least they want to quote the risk. But would there be value in doing it at the beginning of the process, extracting loss information on risks that you would have weeded out? What could your actuaries do with that data? Could their predictive modeling be different if we were able to provide them loss data on every submission that comes to the door?... You start thinking about getting into a particular class of business, or a particular line of business, and you wonder, how many submissions would you get? What would the losses be? How would you need to price it? Now you have historical data to use for evaluation."

So, yes, my takeaway from ITC was that nobody has figured out what comes next for generative AI. But there at least are some ways to figure out how to figure out what that future could look like.

For me, that means: "think big, start small, learn fast," a la Chunka's piece; convene as many smart fellow experimenters as possible, a la John; and surface as many solid examples as you can, a la Megan and others.

Cheers,

Paul

P.S. As long as I'm highlighting smart pieces we've published recently at Insurance Thought Leadership, here's one more. I always enjoy the quarterly conversations I have with Dr. Michel Leonard, the chief economist at the Insurance Information Institute, and his latest economic forecast is especially interesting. He says the Fed may be signaling that it could keep raising interest rates into 2025, which would have major implications for the economy and, thus, for the insurance industry.