ITL:

You’ve been a force in software for agents and brokers for some time now. So, I’ll start by asking, generally, what you see as the state of agencies at the moment and where you think they’re headed. Then I’ll poke a bit.

Jason Keck:

One thing I’ve learned is that if you’ve met one agency, you’ve met one agency.  You can’t generalize insurance agents or agencies, and it’s hard to categorize them, as well.

What I have noticed, though, is that larger agencies have institutionalized technology rollout and adoption capabilities. Those agencies are having the most success adopting tools outside of the AMS [agency management system]. In particular with the super-regionals, you have very high-quality, institutionalized adoption. They're very thoughtful and methodical.

As you get into the smaller independent agency channel, it's really a function of the workforce. I don't mean the principals. I mean the actual people with the desks. In some places, you have a whole group of people who are generally younger and more digitally native, and they're very capable with technology. In some places, you don’t. There isn’t a one-size-fits-all answer.

ITL:

If you're running an agency, let’s say an independent agency, how would you think about becoming more efficient?

Keck:

I would first try to understand where my team is spending most of their time, and I’d start by looking at the org structure for the agency. Some agencies are organized by line of business, some by size of business, some by class of business, some by workflow (for instance, new, renewal, service, marketing). Then you have to jump in, searching for where people are spending their time.

Newer agencies are going to be a lot more focused on new business. More established businesses are going to be a lot more focused on renewals.

Once you do the segmentation, you can decide where you’re going to optimize and drive efficiencies. When you figure that out, you ask, what are some of the tools out there to make me better?

ITL:

What are some of the tools out there – other than, Jason’s phone number is…?

Keck:

The payment space is definitely an opportunity. You're seeing a lot of really good adoption there.

But the tools for service are really poor. You have some policy portal and service capabilities, but there’s an opportunity to do a lot better.

The same is true on the commercial rating side. I’m not hearing about anything that’s flying off the shelf. There’s no, “Man, you gotta do this or else.”

ITL:

I'm really curious about service. We publish a lot about it, and the need for improvement seems obvious. Why aren’t the tools better?

Keck:

I haven't seen any good new service technologies in my five years at Broker Buddha. Why? Because CSRs [customer service representatives] are relatively low-cost, and there's a decent amount of mental capacity that has to go into service. Policy changes and endorsements require a lot of hand holding and workflow in the back office. It's hard to build a tool that connects the insured to the broker and to the carrier and facilitates that end-to-end workflow. You don’t just have to build a product for one user group; you have to put together a product that serves three user groups seamlessly and that everybody adopts. That’s really hard.

ITL:

People talk a lot about the need for self-service. It sounds like you're saying self-service may be harder than people think.

Keck:

Some self-service things can be automated, no question. I need to get my policy documents. I need to get my ID card. Tools for those sorts of things are great. But as soon as you head into making a change to your policy, it's harder, right? Who's your policy with? Will there need to be a premium change?

ITL:

Let’s turn to Broker Buddha. What sorts of problems are you guys solving, and where do you think you can go from here?

Keck:

We've been incredibly successful at solving the submission intake problem, particularly around specialty lines. That's our bread and butter, both for new business and renewal. Filling out a PDF sucks whether you’re doing it the first time or having to do it the second time. It's a super, super frustrating experience.

Where are we going from here? The small commercial intake process is an area of white space that nobody's really done a good job of solving for. You're trying to collect information to populate an Acord form. But agents don't know how to complete the form or which questions are necessary to actually get a quote. They don't even know how to explain the questions to their clients! They don't know.

And you also have to populate multiple forms. As an agent, you end up needing to enter the same information on different forms. So, we’ve built a really elegant solution that dynamically loads the forms you need, hides the questions that are irrelevant, defaults answers to the most common responses, uses conditional logic to reveal important questions and generates the PDFs you need when you’re done.  Plus, we integrate eSignature into the experience to tie it all together.   

That's number one. Number two is something that we overlooked early on but that I'm getting really excited about. Most agents are really familiar with quoting in carrier portals, but the portals are really frustrating. There's a material problem around collecting the information needed to enter into a carrier portal because agents don’t know the questions the carrier asks when they’re talking to their customer. This means that when the agent tries to get the quote, they may not have all the information they need. We’re replicating carrier portal questions to support the intake process so the agent never has to go back to the client a second time for more information.

ITL:

Despite all the talk about disintermediation, it’s clear that agents have won. Where do you see them going if you project out a few years?

Keck:

If you look at something like cyber, you see that the macro landscape is having a material impact on insurance products, coverages and pricing. The agent’s role, in many ways, is to understand the changes and to help clients reduce their risk. That's a full-time job, staying up to speed.

What is and isn't covered on these policies becomes very important, and how much you have to pay for specific endorsements makes a big impact. And that's nuanced stuff.

ITL:

That's pretty much what I wanted to hit. Is there anything I didn't ask about that I should have asked about?

Keck:

Change management needs to be a big focus. We started out with a very robust product for small agencies, then moved up-market to larger agencies. What we're doing now is actually stripping down a lot of what we offer so smaller agencies can more easily adopt it. The key is simplicity, which makes change easier, even for less digitally native agencies.

We're still building out all kinds of workflow tools for larger agencies in complex situations.  At the same time, we’re rolling out a simpler solution for smaller agencies that won’t overwhelm them. Solutions have to be turnkey for smaller agencies.

ITL:

Thanks, Jason.

KEY TAKEAWAYS:

--The typical auto insurance model, which has been around for a century, notes the base price of a new vehicle and assumes roughly 20% depreciation each year. But the pandemic has uncoupled that model from reality.

--In recent years, scarcity of vehicles and other issues have resulted in a surge in used car values – sometimes going above their price new, often holding value instead of plunging and generally not depreciating as in “normal” times.

--Every pricing system, every actuarial triangle and any predictive model using the last 20 years or more of historical data is ignorant of this kind of volatility and unprepared to say what should happen next. It's time for insurers to change the way they look at vehicle values. 

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If you were to rent a car, you would expect that a more expensive vehicle would cost you more. You would also expect that, if you damaged that more expensive vehicle, it might cost more to repair. So, you would not be surprised to see a higher-cost insurance option associated with more expensive (and perhaps more powerful or luxurious) versions.

Well, your regular insurance program for your vehicle is not working quite like that – at least not yet.

While the base price of any vehicle can move your insurance rate north, as you add on optional equipment, most current insurance pricing systems don’t take those new features into account. Existing pricing models ignore anything beyond the base price new from an MSRP on the window sticker. Maybe more surprising, that is the last time they think about the value of your car.

Why? Let’s take a step back in time.

The very first auto insurance policy is attributed to Travelers in 1897 for a risk in Ohio. Other auto insurance companies, such as State Farm and USAA, recently celebrated 100-year anniversaries for insuring consumer vehicles. While it’s exciting to see brands across the industry celebrate such a marker, we also just weeks ago saw the very first loss in an annual report in 100 years for one insurance company – something we think can largely be attributed to missing the changing conditions on the value of a used vehicle.

Over the last century of auto insurance, paper policies managed in mailboxes and inbox bins have been increasingly replaced by digital policies on smartphone apps in the cloud, but many legacy processes have not kept up with the times. Two iconic pieces of auto insurance history come to mind – the use of base price new MSRP to set a value in a “set it and forget it” fashion and the use of a one-size-fits-all factor curve for setting a relativity-based insurance value for a vehicle over time (across the nation or within a state).

Why should these processes be left in the past?

See also: Deteriorating State of Car Insurance

We will save the window sticker story of base price versus total price and the gap between the two for another day. Today, we want to spend a moment exploring active valuation methods versus static and embedded methods for vehicles.

Model risk management disciplinarians may not have gotten around to vehicle valuation for pricing yet – the use of base price new and no further detailed tracking of the asset is deep in tradition and only noticeable in filings and rating algorithms, so hidden in plain sight. The current displacement in valuation trends, however, has completely uncoupled the traditional approach from today’s reality.

Let's explore.

Model Risk Matters - Active vs. Static Methods

One of the more longstanding traditional presumptions since the time before computers were introduced, back when data was manipulated with slide rules and look up tables, is that vehicles always get cheaper with age. That is not a shocking thought, but in recent volatile car valuation times, this embedded thinking has turned into a systemic risk (model risk). Let’s look at a specific case and then the general case.  

The Toyota 2017 Rav4 model year value trend: A specific example in these pandemic era times

Prior to April 2020, the market for a used 2017 Rav4 followed a traditional rule of thumb: straight-line depreciation of about 20% a year. That meant that, in five years, it would have lost 2/3 of its original price. $30k-ish moves to $10k-ish across 60 months. (See the green line in the Rav4 exhibit.)

While other things that consumers insure, like houses, rings, art, etc., all seem to cost more over time – sometimes intrinsically and sometimes due to inflation – the cost for cars normally is presumed to trend downward as they wear out their mechanical function with usage. Nowadays, however, are not normal.

In recent years, scarcity of vehicles and other issues have resulted in a surge in used car values – sometimes going above their price new, often holding value instead of plunging and generally not depreciating as in “normal” times. (See the gray line in the Rav4 exhibit.) Values can also vary from type of vehicle to brand of vehicle and perhaps to the trim level and optional equipment for popular configurations – not a one-size-fits-all situation.

The J.D. Power Used Vehicle Price Index (UVPI), constructed to measure relative market valuation for vehicles less than eight years old (a classic plan for targeting under 100,000 miles on the odometer), indicates that, since the turn of the millennium in the year 2000 until the beginning of the pandemic in 2020, there were relatively “calm seas” in the used car price space.

J.D. Power Used Vehicle Price Index: Trend from January 2000 - April 2023

We observe a notable downturn during the global financial meltdown in late 2008 (and follow-on recession), with a new plateau in pricing slightly higher for post-recession than pre-recession. There were many insurance pricing increases put into effect to adjust to that new plateau of value of vehicles about a decade ago, but otherwise we see a relatively uneventful 20 years of valuation on an indexed basis.

That is until the pandemic.

What we see today indicates that a sea change like never before has hit the shore of used vehicle values. Every pricing system, every actuarial triangle and any predictive model using the last 20 years or more of historical data is ignorant of this kind of volatility and unprepared to say what should happen next.

See also: Buckle Up for Telematics 2.0

It's time for insurers to change the way they look at vehicle values.

Today, it seems every auto insurance company is raising rates across the board on a more frequent basis and in higher amounts than at any time in our lives. Even with the current rising tide, however, we have not seen enough increase to match the change in the most valuable parts of the car fleet, which are up almost double (from the 1-teens to the 2-teens) in the most recent months of the used vehicle price index (UVPI).  

While it is impossible to know what will happen next, it seems the insurance industry can comfortably assume it needs to really pay attention to the value of insured vehicles in a different way than they have so far, to be around for the next 100 years.

This article originally appeared on the J.D. Power site here.

While I've been a proponent of embedded insurance, as have many others, an article published recently should cause some pondering. The article argues that embedding insurance is really just a way to pester customers to buy coverage they don't need.

"You aren't going to take a chance on dinging that rental car, are you?"

"Yes, we just recommended that laptop you're purchasing, but, you know, that model breaks down a lot, so we highly recommend buying a warranty."

"Your trip isn't covered. Are you sure you don't need travel insurance? Are you really sure? Really? We'll give you one more chance...."

The article took me back to the arguments I heard in the early days of mobile phones, in the early to mid-'90s, when carriers talked about how great it would be for, say, coffee shops to know that a customer was walking by and to be able to ping their phones with a coupon for a latte. So many people rejected that idea as nagging, even stalking, that carriers backed off.

I still think embedded insurance, done right, can make the purchasing process more efficient and take out costs while expanding the reach of certain types of insurance, both existing types and potentially new ones. But it's worth looking at the counterarguments, if only to make sure that embedded insurance is, in fact, done right.

Ian Gutterman, founder and CEO of Informed Insurance, makes the argument against embedded insurance in two parts, first laying out why he believes it's bad for consumers and then explaining why he thinks it's even bad for insurers.

He writes:

"Almost every type of insurance being offered as 'embedded' could easily be bought separately. We are not talking about creating new types of insurance for novel risks. It is mostly auto, pet, comp and warranty.

"The main reason they are being repackaged as 'embedded' is because the insurers realized they are bad at selling them on their own. The hope is by using a middleman they can catch you in a weak moment where you might buy pet insurance from the pet store that just sold you the puppy.

"It’s emotional manipulation rather than truly addressing a need."

Gutterman notes that proponents of embedded insurance often argue they're just nudging people toward coverage they need but says, "more often than not, the motivation is what is good for the corporate interests rather than the consumer."

Despite that emphasis on corporate interests, he thinks that embedded insurance is bad for insurers, too, at least in the medium to long term, because it makes their insurance a commodity that can be swapped out for someone else's at any moment. 

Gutterman writes: 

"When you choose to be an embedded insurer, you are... a nameless, faceless entity. The customer doesn’t care who you are. They attribute all the value they perceive from the transaction to the retail brand that you partnered with.... [And] more often than not, the retail partner couldn't care less if another insurer stood in your shoes....

"You don’t have to be a game theory expert to understand how this will end. Distribution partners will demand bigger and bigger pieces of the pie. If you don’t cut them another slice, they will drop you for another partner."

He also warns that embedding the insurance could lead to adverse selection:

"The partner will want to sell your product to every customer since that is incremental fee revenue for them, even the ones with a high likelihood of a claim or willingness to commit fraud. Unless you demand they receive a healthy chunk of their payment as profit-based contingent commissions, they won’t care about your loss ratio."

Gutterman says embedded insurance will only work if it provides three things:

• "Better coverage than available in traditional channels
• Lower price than in alternative channels
• Easier buying process with clear explanation of why it’s a good price and offers better coverage"

That's a pretty daunting set of arguments.

But before you give up hope, I suggest looking at a piece that Chris Bassett, a senior director with Capgemini Invent, published on ITL in January. He says embedded insurance won't fulfill its potential if the coverages being sold are only the sorts of point-of-sale products that Gutterman disparages. But Bassett has high hopes if embedded insurance moves to "point-of-design."

He writes: 

"The opportunity lies in exploring the affinity between the insurance solution and the non-insurance product and how we can build unity in a singular value proposition. Doing so requires introducing insurance at the point-of-design, rather than as a bolt-on at the point-of-sale."

As potential examples, he suggests:

• "Connected home solutions with advanced safety and maintenance features built into the property that detect and automatically manage risk (turning off appliances or mains supplies and automatically contacting emergency services)
• Personal vehicles designed to support wellness-focused internal recreational spaces as an extension of a bundled life, health and vehicle insurance package
• Sports equipment (shoes and clothing) with sensors woven into them that monitor performance and health as an extension of a goal-directed training and wellness package that includes personalized life and health insurance risk mitigation and protection, and that connects to a branded community of similar users."

For me, Gutterman describes a scary series of potential land mines, while Bassett lays out a way to start navigating through them. But I encourage you to explore further, both with the full pieces I've linked to here and, perhaps, with some of the other smart pieces on Gutterman's blog.

Cheers,

Paul

KEY TAKEAWAYS:

--The bottleneck is the time it takes to manually review if the presented information is correct. That can take days, leading to delays in policy issuance.

--Software powered by AI, blending multiple layers of technology, can seamlessly conduct identity verification in real time.

--Better verification can help reduce fraud, which cost consumers and businesses more than $300 billion in 2022 just in the U.S., and can help deal with complex compliance requirements.

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Despite the industry's stodgy reputation, insurance is often ahead of the curve, embracing new technologies that improve efficiency, enhance customer experience and increase profitability. Artificial intelligence (AI) and machine learning (ML) have been used to analyze vast amounts of data that help identify patterns, trends and insights that can help insurers better understand risks, predict claims and personalize their services. Blockchain has been used to improve the efficiency of claims processing, reduce fraud and enhance transparency. Mobile apps, such as telematics, and wearables have allowed insurers to collect real-time data on customer behavior and offer personalized pricing and services. Robotic process automation (RPA) and chatbots help automate routine tasks and improve customer service. 

By contrast, the insurance industry has been hamstrung by outdated identity verification practices. Currently, verifying a customer’s identity consumes unnecessary time, labor and capital.

The bottleneck is the time it takes to manually review if the presented information is correct—that can take days, leading to delays in policy issuance and a poor customer experience. Insurance carriers, brokers, regulators and customers can all gain an advantage from a secure and expedited transfer of personal information. 

Existing methods do little to combat the fraud plaguing the insurance industry, which the Coalition Against Insurance Fraud estimates cost businesses and consumers more than $300 billion in 2022. During the same timeframe, the FBI found that fraud was costing the average American family between $400 and $700 a year in premiums. Life insurance topped the list of sectors plagued by fraud—totaling $74.7 billion in lost revenue. Next came Medicare, clocking in at $60 billion, then property & casualty insurance, with $45 billion in lost revenue. 

Despite these discouraging statistics, recent advances in cutting-edge technology show incredible promise for the detection and prevention of insurance fraud. A survey of 100 insurers across a broad spectrum of the industry by the Coalition Against Insurance Fraud found a steady progression in the adoption of detection of claims fraud technology, from 73% in 2014 to 96% in 2021. The same pattern was observed in underwriting or point-of-sale fraud/rate evasion technology, where each year showed an incremental increase in adoption, from 28% in 2014 to 65% in 2021. 

Advanced identity verification technology was the outlier. It was not observed in all previous studies (in 2014, 2016 and 2018), because advanced identity verification technology is new and groundbreaking—pioneered in just the past couple of years. Four in 10 respondents said in the 2022 study said they had adopted such technology.

This software is powered by AI, blending multiple layers of technology to seamlessly conduct identity verification in real time. Anyone who has integrated a next-generation provider of identity verification has seen the benefits in both their onboarding numbers and their operational costs, and the percentage of those employing these solutions is predicted to drastically increase over the next three to five years. 

Modernizing identity verification practices isn’t just about saving time and labor and enhancing the customer experience—it's key from a regulatory compliance angle. The Gramm-Leach-Bliley Act (GLBA) protects the privacy of customer information and requires safeguards to prevent unauthorized access to that information. Enhanced identity verification practices provide a two-way improvement in compliance to GLBA—easier compliance related to data security, as well as secure provisions related to processing customer identity information. The Fair Credit Reporting Act (FCRA) regulates the collection and use of credit information, including collection done in the context of insurance underwriting. Modernized identity verification practices can help insurance companies comply with the FCRA by providing more accurate and complete customer identity information, which can be used to make more informed underwriting decisions.

There is a big price to pay both financially and reputationally when robust measures are not in place. Anthem was fined $16 million for a data breach in 2015 that exposed the personal information of nearly 79 million customers. In the aftermath of the breach, Anthem was criticized for not doing enough to prevent the attack and for not detecting the breach sooner. 

See also: Applying Cyber Lessons to Regulating AI

Britain is raising the bar for fraud prevention regulations by not only penalizing companies found guilty of committing fraud but also the people who fail to adequately prevent it. The Economic Crime and Corporate Transparency Bill, which is in the process of being passed, enables companies to be fined without limit, even if they were not aware of any fraudulent activities taking place within their organization. The proposed legislation is designed to create a culture of aggressive fraud prevention.

The American insurance industry has received plenty of bad publicity during the last decade—users claim the process of getting insurance is time-consuming, confusing and overly bureaucratic. This dissatisfaction starts during the onboarding phase, which requires users to remember unique passwords and lengthy security questions. Biometric technologies like liveness testing and facial matching are a faster alternative to traditional verification methods by enabling customers to verify their identities instantly on a device. Coupling this with document verification to ensure what’s submitted for identity verification purposes has not been forged or tampered, and with address verification—where the individual’s name and address are extracted from the onboarding information and verified against multiple databases—can expedite claims decisions by instantly checking passports and driver's licenses and removing the need for submitting a proof of address document. What was once a tedious and friction-filled onboarding process can become intuitive and user-friendly—boosting brand loyalty and customer satisfaction.

The future of technology adoption in the insurance industry looks bright—by incorporating advances that can help prevent fraud, comply with regulations and enhance the customer experience. Modernizing identity verification practices means ushering in a new age of security and profitability—benefiting customers, regulators and insurance providers alike.

KEY TAKEAWAYS:

--While traditional new business and renewal processes can be time-consuming and result in missed opportunities, AI can quickly generate alternate plan designs.

--During high-load periods, the volume of quotes requiring underwriter review can slow processes. AI can assist by pulling together data, even from previously inaccessible sources like handwritten notes.

--AI-powered chatbots can provide immediate assistance and answers to customer queries, providing a better customer experience. These tools can be trained to learn an insurance company’s products, policies and general “language,” helping customers fully understand their benefits plan.

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Artificial intelligence (AI) has the potential to revolutionize the group insurance industry, particularly during peak business periods, when human resources are stretched thin. 

By streamlining quoting, optimizing resources and automating manual tasks, AI can help increase group insurance sales, boost profitability and improve the customer experience. As a result, 74% of insurance executives plan to increase their investments in AI. Insurers that seize this opportunity early will have a critical advantage. 

In this article, we'll explore the various ways in which group insurance providers can leverage AI to maximize sales and remain competitive. 

Recommending Alternate Plan Designs with AI 

Traditional new business and renewal processes can be time-consuming and result in missed opportunities. It’s helpful for sales and underwriting teams to have data-backed reference points when designing plans for clients. 

Using predictive analytics, insurers can quickly generate alternate plan designs using one of their most valuable assets: their data. 

Here’s how it works: Using an AI recommendation engine, carriers can use their historical sales data to identify the most successful sold plan designs for similar clients. Recommendation engines, like those offered by the Majesco Global IQX Sales & Underwriting Workbench, will fetch data for similar groups (size, geography, industry) and suggest an alternate plan design that can be presented alongside the handpicked plan.  

See also: The Importance of Explainable AI

This acts as a powerful benchmarking tool while circumventing the data limitations in group insurance because it uses the carrier’s own data. 

AI can also be trained to make suggestions for upselling and cross-selling opportunities on optional worksite products, improving the plan member experience while unlocking revenue opportunities. Some factors it might consider to recommend products may include: age, gender, activity level and job role. 

These tools not only help insurers tap valuable existing sources of revenue but also reduce quote turnaround time, providing a better customer experience. 

Optimize Underwriting Resources 

During high-load periods, the volume of quotes requiring underwriter review can slow processes due to an inefficient allocation of human resources.  

Underwriters have varying levels of expertise across different products and quote complexities. Additionally, managers must take their existing workload into account. As a result, quotes might be sitting for days or even weeks before they can be turned around.  

AI can assist underwriting managers in suggesting the most effective distribution of quotes across the underwriting team, taking into account an individual underwriter's current capacity, their expertise and their performance history.  

Additionally, AI can prioritize quotes with the highest chance of closing based on past successes. By identifying these resource efficiencies, insurers can write more business in less time while improving close ratios. 

Automate Manual Tasks, Process RFPs Faster 

The influx of requests for proposal (RFPs) can produce unwanted friction and increase quote turnaround time.  

To assemble a group benefits quote, sales and underwriting teams need to collect and process several key pieces of information from different sources.  

These may include past plan booklets, policy summaries, employee census files, prior claims experience and general client information (industry, size, location).  

Here’s the problem: These data often come in different formats, and they are often not delivered in the form of structured data. In other words, the data cannot be automatically ingested by digital tools. As a result, underwriting teams lose countless hours to rekeying information into their internal systems. 

This Is Where AI Comes in.  

AI systems can extract information from broker emails, attachments and RFP source files using techniques like optical character recognition (OCR) to identify and process unstructured data trapped in PDFs, images, the “back of a napkin,” and other formats.  

Natural language processing (NLP) can be used to train an AI system to read an RFP booklet, learn carrier-specific terms and abbreviations and generate a quote based on the information detected within the source document. These automated processes not only save time but also reduce errors, providing a better customer experience. 

Once the raw data has been captured, it can be converted to structured data in the insurance company’s format and sent directly to their quoting portal or underwriting workbench.  

AI leveraged in this way can drastically cut the time it takes to assemble a group benefits quote, contributes to improved close ratios and fosters better relationships with your distribution partners. 

AI Chatbots to Drive New Revenue Opportunities 

Gone are the days of clunky, frustrating chatbots that pop up when you least want them. The release of ChatGPT in the fall of 2022 showed the true promise of generative AI. 

By using AI-powered chatbots, group insurers can provide immediate assistance and answers to customer queries, providing a better customer experience. These tools can be trained to learn an insurance company’s products, policies and general “language,” helping customers fully understand their benefits plan. 

Chatbots can also be used to identify potential upselling and cross-selling opportunities for voluntary benefits, improving overall sales and profitability. By integrating with health data providers (e.g., Fitbit) and behavioral data tools, this functionality can become even more personalized, tailored to the individual’s unique situation and their goals. 

While agents and brokers can't offer personalized advice to thousands of individual insureds with varying needs and levels of knowledge, technology can. Digital assistants and chatbots can provide valuable guidance to plan members, answering questions, guiding them through the enrollment process and recommending new products and services based on their health and demographic information. 

The Best Digital Assistants  

Sun Life's AI-enabled "digital coach," Ella, encourages plan members to take action on important deadlines, cost-savings and product offerings. Ella's nudges resulted in nearly two million additional interactions from plan members early in the pandemic from January to September 2020. 

Sun Life's investment in virtual coaching paid off. Thanks to Ella's interventions at the right time to the right user, the company experienced an 83% increase in additional coverage purchased compared with the previous year. This success demonstrates the power of digital assistants in providing personalized education and guidance to insurance customers. 

See also: Beyond the Digital Transformation Hype

Embracing the Potential of AI in Group and Voluntary Benefits 

The future of insurance includes AI, which is poised to revolutionize the group insurance industry, providing significant benefits to both insurers and customers.  

By streamlining quoting, optimizing resources, automating manual tasks and improving customer service, insurers can increase group insurance sales, improve profitability and provide a better customer experience.  

KEY TAKEAWAYS:

--Developing AI models with representative and unbiased data leads to increased accuracy and fairness in predicting outcomes and making decisions, resulting in more effective products that meet the needs of a broader set of users.

--But there are challenges, including that data that accurately represents the population and is not biased may not be available.

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Companies often err when it comes to getting feedback on their latest AI. As iterations progress, a team may discover that the algorithms and use cases are enabling misinformation or causing harmful outcomes for customers. At this point, even if the team retracts the product, customers will demand to know why harmful consequences weren’t found through testing before the product was released.

It is a scenario that puts the reputations of both you and your customers at stake.

The following guidance can help you assess where to adjust your product development and design thinking to make ethical AI an enabler of awesome products your customers will trust and love.

The Difference Between Ethical AI and Responsible AI

Although often used interchangeably, "ethical AI" and "responsible AI" are different. Because this post is focused on AI ethics and product development, it’s important to explain the difference between the two terms.

Ethical AI includes the principles and values that direct the creation and use of AI. It underscores that AI systems are developed and implemented in a way that coincides with ethical considerations such as accountability, transparency and impact, with people as the focus. Ethical AI tries to ensure that AI is built and used with justice, even-handedness and deference to human rights.

Responsible AI encompasses the measures and practices you’ve implemented to manage and plan for ethical use, in addition to aspects such as safety, security, accuracy and compliance. These practices include maintaining data quality, creating transparent and explicable AI systems, conducting frequent audits and risk assessments and establishing governance frameworks for AI.

It is important to have a responsible AI approach to ensure that ethical AI principles are effectively put into practice.

See also: The Rise of AI: a Double-Edged Sword

Ethical AI Principles in Product Design and Development

Product teams can maximize the potential of AI and enhance the effectiveness of their products by adhering to ethical AI principles. Ethical AI also promotes innovation in product development.

Here are some examples of where you should be looking in your design and quality checks for AI reviews:

• Developing AI models with representative and unbiased data leads to increased accuracy and fairness in predicting outcomes and making decisions, resulting in more effective products that meet the needs of a broader set of users.
• Incorporating ethical AI practices into the development of AI models increases transparency and explainability, improving user trust and driving more use of products perceived as fair and understandable.
• AI can automate tasks and processes, resulting in increased efficiency and reduced workload for users. But there are implications to consider about what tasks are being optimized and why. Adhering to ethical AI principles, product teams can create AI models that are optimized for reducing mundane tasks so workers can take on higher-value tasks that sustain future growth for themselves and the company.
• Ethical AI principles offer product teams the chance to explore novel opportunities and assess use cases for AI. By crafting AI models that are transparent, explainable and fair, product teams can demonstrate the value of their AI before it affects customers and society.

Adhering to ethical AI principles during development allows for the creation of AI models that align with core societal values and fulfill business objectives. The effort to improve product accuracy, effectiveness and user-friendliness for all stakeholders within an ethical framework enables product teams to leverage the potential of AI fully.

If it sounds like more stakeholders in the development process, such as user experience, data engineering, risk management and even sales, might be affected by ethical considerations when developing AI, your hunch is correct. Cross-team visibility will become essential to upholding both AI and corporate ethics.

Let’s explore the challenges.

Challenges for Adding Ethical AI Reviews to Products

Incorporating ethical AI principles into product development is essential for responsible and trustworthy AI applications. However, the following challenges and objections might arise during the stages of the process:

• Data that accurately represents the population and is not biased may not be available. Biased data can cause discriminatory and unjust outcomes when AI models perpetuate or amplify existing biases.
• Transparency is key to ethical AI practices, but achieving alignment across teams can be tough. Without designing for interpretability, AI models will lack transparency, which can hinder understanding of decision-making processes when issues arise and time to correct model behavior is critical.
• Likewise, a lack of transparency combined with disagreement on ethical policies can slow development. Early warning signs occur when stakeholders feel ethical principles are an unnecessary layer of planning, not required during objective data-oriented model development.
• AI models can pose challenges in identifying and addressing emergent ethical concerns, especially when product teams have not received effective training on common ethical implications that many models face.
• The absence of authoritative ethical standards for AI and technology use more broadly within companies poses challenges for product teams in determining what practices are considered ethical and responsible. Conversely, this can also be a sign that your organization lacks the diversity of thought or experience to consider ethical policies and safeguards.

The incorporation of ethical AI practices is crucial for responsible and trustworthy AI development. For many of the challenges, AI governance software advancements allow companies to govern, monitor and audit models continuously, providing right-time evidence and documentation that demonstrates AI safety and compliance to various stakeholders.

See also: Beware the Dark Side of AI

Companies That Prioritize Ethical AI Principles

Your AI ethics should be aligned with your corporate ethics, standards and practices. If you have ESG policies, seek alignment between those and your AI. Do not view AI in isolation from broader societal values your organization has or is developing. 

Regulated industries such as banking and insurance are familiar with assessing the performance, robustness and compliance of their algorithms and models against standards and controls. They have been doing it for decades. Rapid innovation and AI have forced these industries to streamline and automate these processes to explain their AI continuously for compliance with industry standards.

Some AI-led insurtechs are going as far as to publicly share their audit process and timing. This is a practice that will become increasingly important to discerning vendors, partners and customers who choose third parties to incorporate human-like AI experiences in their products and want to do it ethically and responsibly.

Customers Decide on Ethics and Trust

Your company and your customers have core business ethics to adhere to and uphold. With proper consideration, your ethics for developing and implementing AI will follow.

By building ethical AI principles into your core product strategy, your company can build immediate trust with end users and customers. Leading ethically with AI also ensures that you are building products that don’t become distrusted or misused or, worse, unsafe tools on a customer’s shelf.

Innovation is at the top of every CEO’s agenda. Yet — despite innovation being a burning priority — why do most innovation initiatives fail to take off?
 
Consider these findings:

54% of innovating companies struggle to bridge the gap between innovation and business strategies.[i]
83% of strategic transformation initiatives fail.[ii]
64% of global executives say a lack of skills is restricting their ability to innovate.  

While most companies want to innovate, only a few carriers know how to innovate systemically. A culture of continuous innovation requires a steady stream of ideas. Ideas you can filter, test, and implement quickly and efficiently.

However, in the real world, innovation is often treated like a project, not a process.

Often the ideas originate from a small group of people — usually senior leaders or the C-suite — and cascade down to the rest of the organization. Many leaders believe their employees will automatically rally behind the idea, do whatever it takes, and push it over the finish line.

But it doesn’t happen that way. Many of these ideas do not get implemented. Employees are either not invested in the idea, do not fully understand its importance, or feel a sense of ownership — and the initiative fails.

Other times, an idea may originate from the frontline. But with a lack of a formal process to solicit feedback, allocate resources, and get stakeholder buy-in, the idea goes nowhere.

“The value of an idea lies in the using of it.” — Thomas Edison

Supercharge innovation with an innovation accelerator

For innovation to succeed, you must bring cross-functional teams together — within and outside the organization — to share their knowledge, experience, and perspectives and approach challenges in new ways.

“Innovation thrives less on individual genius and more on tapping into and maximizing the collective knowledge of the organization.”

Only through a disciplined, repeatable, and collaborative approach can carriers get new ideas to market faster while mitigating delivery and operational risk. An innovation accelerator like OZ Ignite helps you build the proper process to mine, test, and transform your best ideas into innovation initiatives that drive profitable growth.

Three Keys to Innovation Success: Collaboration, Process, Speed

Collaboration: Bring Ideas and Teams Together

Does collaboration fuel innovation? Carriers are asking themselves the same question — and the answer is a resounding yes.  

The top-down approach, where ideas come from senior executives and percolate down, no longer works.

Innovation initiatives — like any change effort —often fail because the outcomes are "not invented here." They’re seen as “one-off ideas” from senior management or “silver bullet solutions” by people with the most influence.

In lieu of a formal process, the bottom-up approach also seldom works because the ideas have little chance of moving up and reaching the right people who can influence decisions. 

Innovation-led growth happens only when it’s embedded into your organizational DNA. That means engaging your workforce across the enterprise — including your customers, distributors, and business partners — creating a dialogue between teams across the insurance ecosystem.

“People support what they help create.” — Ty Bennett, Author of The Power of Influence

Innovation accelerators can help evolve your methodology to collaborative innovation — including methods of obtaining ideas and feedback — with other approaches to projects and development processes to expedite prototypes for review and discussion.

Process: Establish an End-to-End, Repeatable Framework

It feels almost counterintuitive that "ideas" and "structure" should go hand in hand. Most believe innovation is born of a brilliant idea, a momentary stroke of genius. Rather, when successful, it's more likely the outcome of a structured organizational process that your organization develops, cultivates, and embeds over time.

All insurance companies have the knowledge and capabilities to innovate. What they often don’t have is a process to develop these ideas from across the organization into disruptive innovations.

Organizations that do use a structured process — involving several ideation sessions — can (and do) generate ideas faster, test, iterate, and refine them into potential growth initiatives. The payoffs are significant even if only a small percentage of ideas make it through the process.

OZ Ignite recognizes that innovation thrives on order. Not only does the framework manage the entire process from idea to market, but also routinely:

• Collects, shares, routes, screens, evaluates, experiments, incubates, develops, tracks, and reports on your organization's best ideas.
• Brainstorms new ideas to fill a pipeline with customer-centric growth initiatives.
• Integrates brainstorming and design thinking into the iterative prototyping process to fill a pipeline with customer-centric growth initiatives.
• Helps envision your future — whether improving the bottom line through operational excellence, driving profitable topline revenue growth by entering new markets, or leading the industry into new horizons — define it, then design it.

Speed: Bring Ideas to Market Faster

Fast cycle times are critical in insurance. It means being able to take calculated risks even when huge payoffs aren't guaranteed.

Slow development times — from concept to implementation — can hinder innovation and profitable growth. It’s the number one obstacle to successful innovation and today’s customers won’t wait. If a company can’t organize itself to move faster, it will likely begin to fall behind its competitors.

“There is a correlation between responsiveness and revenue. Two-thirds of customers say that speed is as important as the price.” — Jay Baer

When large teams collaborate — across all departmental and functional areas — to create a shared vision, ideas are brought to market faster. Working together also builds consensus across functional areas, departments, and geographies. At the same time, a structured process helps you get more out of your teams and provides value-added solutions and business decisions that are of higher quality and designed in less time than a more traditional approach. 
With a proven process and methodology, carriers can get months of work done in a fraction of the time.

Now's the time for insurers to act, to accelerate the pace of innovation and transform their best ideas into breakthrough innovations.

Murray Izenwasser, Senior Vice President, Digital Strategy

At OZ, Murray plays a pivotal role in understanding our clients’ businesses and then determining the best strategies and customer experiences to drive their business forward using real-world digital, marketing, and technology tools. Prior to OZ, Murray held senior positions at some of the world’s largest digital agencies, including Razorfish and Sapient, and co-founded and ran a successful digital engagement and technology agency for 7 years.

[i] References: MIT Sloan Management Review Report, 2021
 

[ii] Gartner study

Sponsored by ITL Partner: OZ Digital Consulting

KEY TAKEAWAYS:

--New risks include those stemming from decarbonization, which is leading to new types of cargo, such as electric vehicles and goods powered by potentially highly flammable batteries.

--Hazardous cargos are increasingly transported by larger vessels, which amplify the impact of fires.

--Labeling cargos as dangerous is expensive, so many companies try to circumvent this by labeling fireworks as toys or lithium-ion batteries as computer parts, for example. (Technology increasingly can detect the mislabeling.)

--The Russian invasion of Ukraine has led to a shadow fleet of ships that circumvent sanctions. They tend to be older and to have lower standards for maintenance, creating a hazard.

--The steep decline in shipping rates over the past year could lead more broadly to a decline in budgets for maintenance and risk management.

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Shipping transports around 90% of world trade onboard different vessels, so maritime safety is critical. Improvements have been significant over the past decade, culminating in the sector reporting a record low number of large ships lost over the past year. However, a combination of factors affecting fire risk, continuing and new threats posed by the ripple effects of the Ukraine conflict, decarbonization challenges and economic uncertainty, as well as the rising cost of marine claims, means the sector still has plenty of obstacles to navigate over the next 12 months and beyond, according to the latest Allianz Safety & Shipping Review 2023.

Shipping losses have sunk to the lowest number we have seen in the 12-year history of our annual study, reflecting safety programs, trainings, changes in ship design and regulation. While these results are gratifying, several clouds appear on the horizon. More than a year after Russia’s invasion of Ukraine, the growth of the shadow oil tanker fleet is the latest consequence to challenge shipowners, their crew and insurers. Fire safety and the problem of mis-declaration of hazardous cargo must be fixed if the industry is to benefit from the efficiency of ever-larger vessels. Inflation is pushing up the cost of hull, machinery and cargo claims.

Meanwhile, although the industry’s decarbonization efforts are progressing, this remains by far the sector’s biggest challenge. Economic pressures could put vital investments in companies’ strategies, as well as in other safety initiatives, in jeopardy.

Every year, AGCS analyzes reported shipping losses and casualties (incidents) involving ships of over 100 gross tons. During 2022, 38 total losses of vessels were reported globally, compared with 59 a year earlier. This represents a 65% decline in annual losses over 10 years (from 109 in 2013). Thirty years ago, the global fleet was losing 200-plus vessels a year. 

According to the report, there have been more than 800 total losses over the past decade (807). South China, Indochina, Indonesia and the Philippines maritime region is the global loss hotspot, both over the past year and decade (204 total losses). It accounted for one in five losses in 2022 (10), driven by factors including high levels of trade, congested ports, older fleets and extreme weather. The Arabian Gulf, British Isles and West Mediterranean waters were the second top loss locations (3). Around a quarter of vessels lost in 2022 were cargo (10). Foundered (sunk/submerged) was the main cause of total loss across all vessel types (20), accounting for over 50%. Fire/explosion ranked as the second top cause of loss (8). Vessel collision was third (4).  

While total losses declined over the past year, the number of shipping casualties or incidents reported remained consistent (3,032 in 2022, compared with 3,000 in 2021). The British Isles saw the highest number (679). Machinery damage or failure accounted for close to half of all incidents globally (1,478). There were over 200 fires reported during 2022 (209) – the highest number for a decade, making this the third top cause of incidents globally, up 17% year-on-year. 

See also: Challenges Loom for International Shipping

Hull and cargo fire risks

Several factors are increasing the risk of fires at sea and on land. Decarbonization is leading to new types of cargo being transported on vessels, such as electric vehicles (EVs) and battery-powered goods. Potentially highly flammable lithium-ion (Li-ion) batteries pose a growing risk for container shipping and car carriers. This battery market is expected to grow by over 30% annually over the next decade.

One of the main hazards of Li-ion batteries is "thermal runaway," a rapid self-heating fire that can cause an explosion. The main causes of Li-ion fires are substandard manufacturing or damaged battery cells or devices, over-charging and short-circuiting. Fires in EVs with Li-ion batteries are difficult to extinguish and capable of spontaneously reigniting. Most ships lack the suitable protection, detection and firefighting capabilities to tackle such fires at sea. Attention must focus both on pre-emptive measures and emergency plans to help mitigate this peril such as adequate crew training and access to appropriate firefighting equipment or improving early detection systems. Purpose-built vessels for transporting EVs would be advantageous.

At the same time, hazardous cargos are increasingly transported by larger vessels. Container carrying capacity has doubled in the last 20 years. The 10 largest container operators have more than 400 new vessels on order, and the majority will be larger than the ships they replace. Consequently, the impact of fires is amplified, potentially resulting in more severe losses. Fire is already one of the most frequent causes of total losses across all vessel types, with 64 ships lost in the past five years alone. Meanwhile, AGCS analysis of close to 250,000 marine insurance industry claims shows that fire was also the most expensive cause of loss, accounting for 18% of the value of all claims analyzed.

Industry reporting systems attribute around 25% of serious incidents onboard container ships to mis-declared dangerous goods, such as chemicals, batteries and charcoal, although many believe this number to be higher. Failure to properly declare, document and pack hazardous cargo can contribute to blazes or hamper firefighting efforts. Labeling a cargo as dangerous is more expensive. Therefore, some companies try to circumvent this by labeling fireworks as toys or Li-ion batteries as computer parts, for example. Several large container shipping companies have turned to technology to address this issue, using cargo screening software to detect suspicious bookings and cargo details, while large container operators are imposing penalties. “

Ukraine and oil sanctions: growth of shadow tanker fleet latest safety concern

More than a year after Russia’s invasion of Ukraine, the ripple effects for shipping continue to be felt. The threat of collateral damage on civilian shipping in or around the war risk area remains high and could stem from floating mines for example.

Oil sanctions have also resulted in Russia and its allies creating a shadow tanker fleet to transport and sell its oil. Estimates of its size vary – as many as 600 vessels. The shadow fleet is more likely to be made up of older ships, operating under flags of convenience with lower maintenance standards. The increase in their number is a worrying development, threatening the world fleet and the environment. A major incident can cause loss of life as well as uninsured damage or pollution. In May 2023, an uninsured, unladen 1997-built tanker, Pablo, exploded in Southeast Asia, reportedly killing crew. 

Decarbonization: the sector’s biggest challenge

Shipping contributes around 3% of global greenhouse gas (GHG) emissions annually and is committed to tough targets to cut these. The pace and progress of its efforts are influenced by technological developments, adoption of energy-efficient fuels, regulation and market forces. Shipping companies and cargo operators are already switching to vessels powered by liquefied natural gas and are using and testing alternative fuels such as biofuels, methanol, ammonia and hydrogen, as well as solar and battery-powered all-electric vessels, wind-assisted propulsion systems, more efficient propellers and bulbous bow designs.

Shifting away from carbon-based shipping will involve a demanding period of change and significant investment of about $1.4 trillion. A mix of fuels is likely to exist for the next five to 10 years, posing challenges for shipowners, operators and ports. From a loss perspective, the industry has not yet seen any major claims from alternative technologies or fuels. However, as these are introduced at scale, more issues may surface.

Economic pressures back on the radar

Following the post-pandemic boom in container shipping, economic and geopolitical uncertainty and falling demand have hit freight rates. The cost of shipping a container between Asia and the U.S. or Europe in April 2023 was more than 80% lower than a year earlier. The question is whether this decline, together with the prospect of an economic downturn, will affect maintenance and risk management budgets. Prior downturns have affected these, leading to losses and an uptick in machinery damage incidents. 

See also: Shipping Industry Safety Keeps Improving

Factors affecting the cost of claims

Increased commodity prices, higher labor costs and supply chain disruption have had a significant impact on marine insurance claims, in particular hull and machinery. The price of steel, a key cost driver in hull claims, increased sharply post-pandemic, as did prices for spare parts. A typical propeller or machinery claim now costs around two times more than pre-pandemic. Shortages and delays in obtaining replacement parts have also led to longer stays in repair yards, while labor shortages have also increased costs. This comes on top of the increased expense of dealing with large vessels, which face higher costs for repairs, salvage and towing. The post-pandemic boom in container shipping has also been affected. Cargo values have risen with the increase in the price of goods and raw materials.

KEY TAKEAWAYS:

--Insurance is expanding into so many new areas, which represent opportunities to bring in diverse talent. We shouldn't just focus on making "core" parts of insurance more diverse.

--When we think about the user experience, we shouldn't just focus on serving our diverse customers. We must serve our diverse employees, too.

--Technology can help, but only if it is stewarded properly. There needs to be a diverse group of individuals at the helm. You do not know bias you cannot see.

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According to McKinsey, at the entry level of the pipeline, insurance is more diverse than the average of other industries. We’ve done great work, but the diversity across the industry is not keeping pace with the diversity of the customer base. In fact, diversity decreases as the level increases, meaning the most senior levels within the insurance industry still lack diversity.

I recently spoke at Duck Creek Technologies’ Formation conference and spent an incredible amount of time with customers, partners and analysts discussing how we can build and support the diverse insurance industry we crave. We crave it because we know it serves all people with speed, intelligence and transparency and delivers better business outcomes.

Here are a handful of ways the insurance industry can be diverse by design — and build a future where people and technology work hand in hand to deliver humanized experiences that reflect the individuals whom insurance serves. 

Look beyond “core” insurance functions for diversification.

The insurance ecosystem is growing in terms of breadth of offerings and depth of functionality. The insurance value chain is extending across new functions. Insurance buyers are expanding across more generations and backgrounds than ever. These changes open doors for talent to positively influence our industry at different stages of the insurance lifecycle. 

I started my career as an attorney, focused on insurance, regulation and compliance. This led me to become a subject matter expert working alongside software development teams that build insurance products. While this is a somewhat unconventional path, it has proven viable in insurance technology, and non-traditional paths are becoming more of a norm because they dissolve the traditional barriers to entry. And the insurance ecosystem is growing, with contributors from cloud technology to payments processors, mobile app development and telematics having a more significant influence on insurance. Mine is the type of path others can — and should — follow.

Cybersecurity is another opportunity for the insurance industry to fill talent needs and benefit from diverse perspectives from women or underrepresented groups in STEM. Cybersecurity in 2023 isn’t just about executing risk mitigation functions. It is about educating, communicating, collaborating, networking and strategizing — all functions that lend themselves well to talent diversification. With IT and tech talent shortages looming, there is opportunity aplenty.

See also: How Diversity Can Stoke Innovation

Focus on the user experiences of workers within insurance, too.

Two common mistakes occur when people hear the words "user experience": 1) People default to thinking only about the end user of a product/solution, and 2) people conflate user experience with the customer experience and use them interchangeably. Suppose we are to promote diversity within the insurance industry, from product ideation to fulfilling a policy or claim. In that case, there are a broader set of user experiences to consider across the entire ecosystem. These include building, servicing, marketing and implementing solutions, and many more experiences that may need to be considered.

Here's a concrete example. We have a range of people using our solutions, including the purchasing customers, the configurators (who implement and personalize suites) and the varying individuals who work at insurance companies. There is no single user experience. Every interaction along the way is diverse, so that diversity must be reflected in how we design our technology experiences. All groups of individuals think differently, have various levels of technological acumen and have varying thought patterns and analytical processes. Building in support of these experiences starts with diversification of thought.

To ensure that insurance is an appealing and rewarding profession that diverse groups want to enter, we must make it accessible. Building the right experiences along every touchpoint in the insurance value chain is a crucial step in this evolution. We must know – and represent – the personas for which we are building.

Data shows that customers demand empathy and human experiences.

Insureds currently run the risk of dropping the ball. Yes, insurers are coming out of challenging times, but here are two numbers that should be improved AND, more importantly, at present, that represent missed opportunities for insurers — in terms of dollars and reputation.

According to our survey of over 2,000 insureds around the globe, 45%, on average, didn’t hear from their insurer over the course of a year, which is up from 34% in 2022. Furthermore, after purchasing coverage, when interacting with their insurance provider, 44% said they preferred to speak to a human, an increase of nine percentage points. So, we both demand more touchpoints (digital and physical) and demand human interaction. As much as technology is critical to insurance functionality, service and profitability, insurance is a people business.

We must diversify to better represent the people we serve. Diversity gives insurers, agents and other key insurance functions an advantage to flex empathetic muscles. Insureds who can see themselves represented within an insurer, who feel their insurer knows them or who can have their varying emotional needs met during times of despair will have a stronger brand affinity. There is an opportunity at the insurance industry's doorstep to win consumer hearts, minds and dollars.

Use technology to your advantage, but steward its use correctly.

Technology is an irreplaceable cog in advancing the insurance industry. It is our answer to supporting, empowering and elevating talent. Technology can simplify the complexity of insurance by finding new ways to automate, apply visualization and maximize reuse. Technology — and regulatory and inflation headwinds — will bring about rethinking insurance processes. As found in the survey referenced earlier, there will be an increased reliance on technology AND people in our industry’s future.

Emerging technologies such as AI, ML, automation and more will assist the world (and the world of insurance). But with the use of advanced technology comes a responsibility to study it, understand it and apply it in a way that is beneficial for all. And the only way to recognize this is to have a diverse group of individuals at the helm. You do not know bias you cannot see. You need to know personas to understand how individuals engage with or react to technology.

Our industry cannot afford to miss this generational chance to capitalize on assistive technologies. We must understand, represent and build insurance for the people who need it, how they want it and when they want it. More than 140 million millennials and Gen Zers populate the U.S., with approximately half the country now under 40 years old. We need to steward technology responsibly.

See also: Industry Still Lags on Diversity

Bonus: Rising tides lift all boats, so look intrinsically to do your part.

I don’t recall from whom or where this quote originated, but it’s worth sharing nonetheless: Words without actions are meaningless, but actions without words are confusing. Over the past few years, the insurance industry has been right to engage in dialogue around diversity – from diversifying products to its workforce and more. The stage is set for action. 

One of the best pieces of advice I can give to any organization that affects the insurance ecosystem is to make sure you do what you can to move the needle. Here are a few quick examples to inspire action on diversity:

• Establish employee resource groups (ERGs) for women and diverse populations, and think and act more globally.
• Where appropriate, leverage councils (such as DE&I or employee experience) as agenda setters.
• Host in-person or virtual events where connection, culture and community are the focal point.
• Identify a data-based hiring strategy that seeks to increase talent pools with diverse slates of candidates.

At the end of the day, we must try to break down barriers and show a commitment to embracing the insurance industry we desire. Accountability, innovation and growth will follow.

To check in on the prospects for the Internet of Things, Editor-in-Chief Paul Carroll chatted with Dave Wechsler, the insurtech lead investor with the $2 billion venture fund operated by OMERS, the pension fund of Ontario. Dave, an old friend of ITL’s, has a long history with the IoT and telematics, including as the vice president for growth initiatives at Hippo and as the leader of IoT business initiatives at Comcast.

ITL:

To set the stage, how are you thinking in general about IoT these days and about what it can do for insurance?

Dave Wechsler:

To me, it's about collecting data and using the data in real time to prevent loss. You’re driving too fast. You're not locking your door. You've got a smoke alarm battery that's dead. We gather real-time data and then coach around it, explaining to the customer why this is important. Ultimately, we underwrite against the data. Good behavior should be rewarded, and bad behavior should be penalized.

I don't necessarily think the consumer should be burdened and have to buy a lot of devices. I do think the insurer can drive a lot of technology into the business, home or auto to improve results. The economics don't really work today, but they’ll keep getting better and better.

I have a history here. I built one of the first wireless thermostats in 2000 and had thousands of Nest-like thermostats across the U.S. and Canada. They were $5,000 apiece. Now, you can go buy one that's far superior for $59. As IoT technology gets adopted, the price points will drop, and it will be very valuable for insurers.

ITL:

I'm interested in the economic argument, and you’re actually in the middle of my introduction to it. A few years ago, I had a long conversation with Notion about its water leak sensors – and you were part of the team that ran the acquisition of Notion while you were at Comcast. If you could riff a bit on the economics, that’d be great.

Wechsler:

If you could be assured that dropping one water sensor puck below your washing machine would catch all of the water leaks in your home, you’d remove the non-CAT water risk, and the economics would work. But, inevitably, that’s not how it goes, right? You get the five-puck pack from your insurer, you drop the five pucks and the place that you didn’t drop the puck is inevitably where you have a leak. If you have a whole home water shutoff, you’re going to catch more problems, but that runs you maybe $700 or $800 installed, and you’ll have a harder time justifying the expense.

Unless the customer is sticky. If the customer stays with you for 10 years, maybe because of the leak detection, then there is a very good return. But you have to balance those people against the guy who only stayed for a year or two, and you spent $800 on him.

I would argue probably that none of the products work today as an aftermarket standalone purchase on a pure dollar-to-dollar basis. So, how do you make the IoT work broadly? You probably need a new business model. Why don't we provide water loss avoidance as a service?

The carrier wouldn’t have to worry about how many devices are in the home or what they are. We'll just run a book for you, and you won't have water losses. We'll charge you per house per year. If we decide to have 100 technicians outside a house every day, that’s our business. Same if we want to gamble on a house, maybe because it’s new construction, and not put sensors in there. That could be a really innovative business model.

ITL:

We've talked a lot about water. Are there other areas that you see as having big potential?

Wechsler:

Sensors for fire are getting less expensive and may get to the point where there’s a crossover, where you can make an economic argument for installing after-market products. But I'm not sure that that is the right model because there's still a lot of user risk. I still think you probably need a new business model to get big scale going.

Lots of IoT companies see the potential. They just don’t have enough capital.

ITL:

How quickly do you think we could get to scale?

Wechsler:

I don't want to make this sound futuristic, because the technology all works today. The price point is still just a little high, and there are regulatory issues. For instance, privacy constraints may mean the carrier can only test a sensor once a year, for underwriting, and not monitor it in real time.

ITL:

I think real time is the key. If you send me a report about my driving and coach me that I did something dangerous two weeks earlier, that’s not a lot of help. But if you warn me that I’m about to cross black ice, because someone else swerved on it a minute earlier, that makes all the difference in the world.

Wechsler:

I can't wait for continuous underwriting. I can't wait for real-time data.

And there doesn’t have to be any crazy engineering any more. Sensors may get fooled initially. A whole home water shutoff valve might get nervous about the rate of flow because someone flushes the toilet after they’ve turned the shower on, but sensors figure things out, and monitoring water flow, humidity, wiring and heat is pretty straightforward. 

ITL:

Have you ever heard the name Stu Ungar? He was one of the best poker players of all time but famously careless with money. He paid his water bill in Las Vegas with cash—when he had it—and a friend finally noticed that he seemed to be carrying quite a wad. He asked Ungar what his water bill was each month. “About $3,000,” Ungar said. The friend said, “Stu, you have a leak. A big leak.”

Talk about needing a leak sensor.

Wechsler:

And the issue wasn’t just his water bill. The leak was probably doing structural damage to the house, too.

ITL:

One last thing, while I have you: Are there any other trends that are getting you excited?

Wechsler:

There are lots of new entrants in commercial auto, and they’re all starting with cameras in the cab, which will end a lot of the “he said, she said” litigation related to accidents and make the whole process smoother.

More broadly, think back to when telematics first came out, 20-plus years ago. The concept of consumers engaging with insurers was crazy. No way. Nobody’s ever going to do it. Well, a year and a half ago, I was in Florida with my dad, who was 79 at the time, and he said, “Hey, man, I just got this amazing thing from Geico. It saved me 400 bucks.” I asked what it was. “I downloaded an app, and it scores my driving,” he said. He’s a really safe driver, so he saved a lot of money, and now he’s all in on using the app.

Eventually, this flips from a reward to a penalty, right? Safe drivers don’t just pay less; unsafe drivers pay more, as they should. If you’re worried about technology penalizing you, then you’re probably admitting you have risk factors.

This, to me, is what technology is about—how risk is underwritten.

ITL:

Thanks, Dave. I’m always smarter after we talk.