Ever since the dawn of the Digital Age some 50 years ago, economists have debated the “productivity paradox.” We all see the incredible, accelerating power of digital technologies and watch them pervade all aspects of our lives, but where are the productivity gains? 

The Industrial Revolution increased productivity so fast and created so much wealth in the 1800s that it transformed the world. Why isn’t what is often called the second industrial revolution (or third or fourth, depending on who’s counting) boosting productivity as effectively? Why has productivity merely been on a steady, unspectacular incline since the early 1970s? 

Some economists say the problem is with the productivity statistics, not with productivity itself. They note that a lot of the gains from digital technologies simply aren’t measurable. Searching on Google lets you learn lots of things you wouldn’t have otherwise known, but how do you measure the increase? Even in a work setting, having the world’s information at your fingertips typically doesn’t mean that you’re producing the same output at lower cost or increasing your output at the same cost – the definitions of improvement used in productivity statistics. You’re maybe producing a better output at the same cost, but economists have a hard time measuring that gain. In fact, some digital technologies show declines in productivity. We no longer buy CDs, so all the work that goes into making the music on them now produces less revenue, even though people are listening to far more music than ever before.

Other economists say we simply need to be patient. It takes years, even decades, before fundamental economic changes can percolate their way through business practices and cause the kind of improvement that we saw in the Industrial Revolution. James Watt’s rethinking of the steam engine in 1776 created the technological breakthrough, but it wasn’t until someone else invented the factory and yet another person invented the limited liability corporation that the power of the engine was fully unleashed – and that wasn’t until roughly 1820. There was, in fact, a brief surge in productivity in the late 1990s, roughly three decades after the start of the Digital Age, and many economists say we can expect more in the future, based on all the technological gains.

I’d note that the disappointment about digital sometimes stems from a simple issue: unrealistic expectations about profitability. Companies will see efficiencies to be gained from digitizing and will predict improved profitability. But they forget that, while they’re becoming more efficient, the other guy is, too – and that those efficiency gains will be competed away. 

That’s all a long way of saying that, while I’m generally an evangelist for technology, I’m cautious about accepting grand claims on how digital technology will transform business in short order. 

So, having chronicled for years how digitization is creating opportunities in insurance, without quite producing the Holy Grail, I was more than a little intrigued when I saw a report from Liberty Mutual that highly digital agencies were growing 70% faster than their less digital rivals. To learn more, I sat down with Tyler Asher, Liberty Mutual’s president, independent agent distribution, for this month’s interview. I hope you find it as enlightening as I did, both on where the opportunities for breakthroughs are, and where they aren’t.

P.S. Here are the six articles I'd like to highlight this month for agents and brokers:

AN AGENT’S GUIDE TO OUTREACH IN 2023

In this new year, agents should branch out of their comfort zones and consider how to improve their efforts to identify and capture new business.

ENDING THE TEDIUM IN INSURANCE

Anyone who has purchased insurance by phone and a series of back-and-forth emails knows how slow and difficult that process can be. But it doesn't have to be that way. 

20 ISSUES TO WATCH IN 2023

While there are certainly more than 20 issues to discuss, here are high-impact matters relating to workers’ comp, healthcare and risk management that need more attention.

7 KEY TRENDS IN 2023

To help industry players orient themselves, compete more effectively and better serve customers in an increasingly volatile world, here are trends to watch for. 

HOW TO RISE ABOVE DISRUPTION IN 2023

Insurers started 2022 in a position of strength and still are in a good spot to drive down costs and increase demand, unless rising claims costs and market volatility continue.

BRANDED COMMUNICATION: A STRATEGIC ENABLER

At a time when few answer a call from an unknown number, insurers can identify themselves as a legitimate caller by displaying logos and a reason for the call on the recipient’s device.

Touchless claims aren’t just the future of the insurance industry – they’re the present. Customers today have shifted from being familiar with doing business online to largely preferring it in many cases, and that ripple effect has been felt and registered by insurance companies globally. But the industry at large has some catching up to do to meet this demand. Recent statistics from Price Waterhouse Coopers indicate that 41% of insurance customers are likely to switch insurance providers due to dissatisfaction with their carrier’s digital capabilities. 

The problem isn’t that insurance companies refuse to update old technology. It’s that technology is only a component of a successful touchless claims implementation. And having the best, latest tools won’t help if you don’t allow processes to evolve and leverage the full capabilities offered. 

My daughter was involved in an automotive insurance claim last year. Because I have some experience working with insurance claims, I offered to help her through the process. My experience with this claim in 2022 was essentially identical to how it would have been handled in 1995. Situations like this aren’t uncommon, but it is worth examining why they’re happening.  

The processes insurers use haven’t adapted to the capabilities of the new technology they have adopted. Insurance claims today involve vastly more data than they did decades ago, yet the way that data is being handled and the number of touchpoints in the process haven’t kept up. This leads to a heavier workload for everyone in that chain due to multiple handoffs and slows workflow. Ultimately, customers aren’t served as well as they could have been. 

People are generally resistant to change, and while they may be open to trying new technological solutions, they are hesitant about changing their workflow and established ways of getting things done. This is one of the key roadblocks the industry faces in moving to a truly touchless claims future: New tools are often seen in a narrow focus instead of as part of an integrated system. 

This bolt-on approach rarely solves many problems, and after a while frequently causes more trouble as compatibility issues arise when pieced-together parts don’t play well together. What is needed isn’t necessarily more tech but a perception shift about the way technology should be integrated, not only as individual components working together but also with processes and workflows. When you have seamlessly integrated solutions and make use of their full potential, you’re not only getting the most from your technology investment, you’re also freeing your employees to do what they do best. 

See also: Turkey's Disaster Was Preventable... by Insurers

I see a future, not far off, when a claim can be initiated and begin processing before the claimant gets back home. Imagine you’ve just been in an accident. There’s a QR code on the insurance card you carry in your car that takes you directly to your carrier’s claims portal mobile phone application. You are instantly identified once the code is scanned, and there are no extensive forms to fill out and no typing. Just a few clicks to take photos of your vehicle and any other vehicles involved, capturing damage and license plate information, which is used to retrieve vehicle information. 

From there, the app will activate, managing the claim from start to finish: providing the estimate, arranging for a local body shop to do the work and setting up a vehicle rental. Claims professionals and claimants can communicate through the app, and everything customers need to handle claims is right there on a device that they carry with them every day. 

We’re not there yet, but nothing is stopping us from taking more steps in that direction now. With a slightly different approach to the way technology and processes work together, that could be a reality in just a couple years. The tools are already there, and the customers have made their preference of touchless claims widely known. 

The companies that act today to improve their customers’ digital experiences will see dividends in both customer service and operating expense.

Modernization of core policy admin systems is a foundational piece of a life insurer’s digital transformation journey‒but legacy system replacement introduces data risk and complexity. Join our expert panel on this webinar to find out how taking a Greenfield approach as a first step in a PAS modernization can reduce risk, accelerate innovation and help carriers stay ahead of the digital transformation curve.

Webinar Date: February 22, 2023 at 11AM EST

Register for Webinar

In this webinar, you'll learn:

• How to dramatically increase the speed of product innovation
• How to define digital transformation goals and implement new products in a way that supports achieving those goals
• Tools and techniques to make your greenfield initiative successful

Webinar panelists:

• Alan Dulin, Global Head & Senior Managing Director, Oracle
• David Shively, COO, Equisoft
• Chip Bircher, Analyst, Aite-Novarica Group
• Alec Mendez, Consultant, Equisoft

Can't attend live event?

Register for the live webinar and we'll email you a link to watch the recording shortly after the live event.

Register for Webinar

Sponsored by Equisoft 

It’s a new year for the insurtech industry. While the market has left its nascent stage, it hasn’t reached maturity yet. We are in the midst of what many consider its “2.0” era, where companies have learned what works and what doesn’t, along with new approaches. All this is taking place against the backdrop of the economic downturn and broader challenges that are affecting businesses in every sector. 

Here’s a look at what’s likely ahead. 

Top of mind for many insurtech leaders is consolidation, which is generally consistent with the economic climate companies are navigating. Recessions, rising costs and inflation typically affect funding at a macro level. As that happens, organizations that are not profitable or that rely on funding to survive often look to sell. Others face more drastic measures such as cutting staff or, in the worst cases, are forced to close their doors. Consolidation starts to rise as a result, sparking an uptick in merger and acquisition activity. Larger organizations begin to buy smaller players, or businesses merge. We’re seeing this consolidation now and will likely see it for a while. 

Market consolidation isn’t limited to down cycles. It can be a natural part of an industry’s lifetime, even in relatively positive economic conditions. The shift is ultimately good, in general, regardless. Markets can’t support companies that aren’t profitable or can’t show a clear pathway to profitability. Consolidation cuts the fat and reduces saturation. It typically creates efficiency and opportunity, freeing funding where it is available and enabling top-performing organizations to rise. Those in a position to capitalize can get great deals, merge, make moves and generate other benefits. Amazing businesses are often built in these conditions. Companies that need to be bullish and acquire companies can do so, and companies that are struggling can find a way out. Watch for consolidation in the coming year, and, if considering M&A, now may be the time to start. 

2023 will also likely see less investment funding in insurtech. Signs of change began last year, with potential impact to continue in the next 12 months. This will in part play a role in further market consolidation, though funding won't completely stop. It will just become more focused and selective. VCs are looking to deploy investments more carefully, with an eye on organizations that can win the game of insurance, versus the moonshot risks and high valuations of the past. Successful companies with a track record can gain during this stage, as investors become more selective on where dollars are deployed and attention turns to companies that have insurance fundamentals and established paths to profitability. 

See also: 20 Issues to Watch in 2023

Technology is always at the forefront of insurtech. However, it’s getting increasing attention among legacy insurance companies, which will likely drive a bigger focus on technology in the market this year. It will play a role in helping companies do more with less, reduce inefficiencies, streamline processes and create capital. We’ll likely see this also drive consolidation in the category as bigger insurance companies opt to buy insurtechs in niche markets instead of building innovation in-house. Smaller insurance and insurtech businesses will also do the same where they can, either merging or acquiring to gain technology assets. It’s not likely that there will be large, sweeping disruption or change that will uproot the whole industry. But we will see highly specialized insurance companies continue to leverage technology and do really well. 

The coming year will likely present a lot of opportunities for big carriers to buy whatever they’re interested in. Larger companies are well-capitalized and tend to remain relatively recession-proof, with a lot of resources to deploy. They will be scrutinizing insurtechs and taking a hard look at their core business and fundamentals and their odds of achieving profitability in the coming years. The days when insurtechs could rely on outside capital and hitting milestones to get to the next funding round are gone. Business this year will be about hitting target milestones to be self-sustaining or finding other ways to make money. Highly specialized insurtechs that stay focused on their market niches will likely do well and will gain the most interest and attention from investors as well as large carriers looking for acquisitions.

Over the past half decade, several organizations in the workers’ compensation industry have promoted their business by saying they apply artificial intelligence, or AI. I looked at their offerings a few years ago. I found that what they meant by AI was worthy of consideration. However, AI today means computational power dramatically more effective than what was then promoted. AI has the potential in 2023 to dramatically raise the quality of claims handling and underwriting, to name two functions in workers’ compensation. 

One might say that a breakthrough has just taken place that makes AI work in the way we’ve implicitly expected for a long time, and until now have not experienced.

In late 2022, OpenAI released for free public use a system called ChatGPT, heralding a new generation of what will be widely used AI products.  As of the end of January 2023, some 100 million persons are estimated to have used it, making it the most rapid large-scale launch of a consumer product in history.

ChatGPT is the first sign of a quickly emerging AI generation. It is very easy to use. Responding to a request posed in conversational English, it writes plans, analyzes your writing, fixes computer software, writes a poem. I compare it to driving a car without any knowledge of how the engine operates. It is much more insightful and efficient in many instances than Google search.

I tested it out posting many workers comp-related requests. Some responses were vapid, but most ranged from useful to very insightful. With more preparation, the system has great promise as a practical tool. Claims staffs can use this generation of AI to more accurately predict claims outcomes and to select interventions, such as case management or subrogation reviews. Underwriting staff can better price premiums.

We’ll get into some scenarios in a moment. I want now to provide a very basic (albeit somewhat rough) introduction to machine learning using large language models, which is at the heart of ChatGPT.

Machine learning using large language models does not use what we might normally call algorithms-based or logical thinking to predict. It will confidently predict that the word “you” usually comes after “thank,” not because it knows the meaning of words and grammar. Its prediction process is so complex that it can’t be explained or audited by the user.

Consider how to predict the second to last elements in “The quick brown fox jumped over the lazy [word] [punctuation].” 

The computer, without any intrinsic, original knowledge of what a word is, or word meaning, or grammar, will produce a numerical score for each element relative to the probability of each element coming before or after each of the others. Hence the three elements in “the” will have a relatively high predictive score to precede “quick.” And “jumped” will have a lower predictive score to follow “fox.” That is because the elements that precede "quick" are easier to predict than the elements that follow "fox."

The computer has been trained by inspecting many millions of texts, one at a time, converting letters and punctuation into numbers. For each string of numbers, the computer will recalibrate scores for each number relative to its probability of coming before or after each other number. It is searching eventually for strings of words followed by a period. It will assign a very high probability, with a great deal of confidence, that the missing word is “dog,” much more likely than it is “cat” and far more likely than it is “cloud.” 

ChatGPT describes itself in these words: A model which is exposed to vast amounts of data and learns to predict and respond with “human-like text with a high level of coherence and relevance.” It is trained to handle tasks such as language translation and computer code writing. It can be fine-tuned to perform on limited data sets for claims or underwriting.

See also: The Key to 'Augmented Intelligence' 

Consider the adjuster with a new workers’ compensation claim involving multiple bodily trauma. AI of this generation will predict ultimate claim cost – that doesn’t sound very impressive. But it will also advise the adjuster what additional information will improve the prediction. And, it will predict which medical treatment and what treatment will lower the cost, and by how much. 

For the underwriter, AI predicts ultimate costs of all claims and advises on what information and what interventions (such as loss control and experience rating/deductibles) will improve prediction and will increase profits for the insurer. 

Is this what we want? The answer is yes, with caveats. What if AI enables decisions that might conflict with ethics and public policy? For instance, it might predict that a combination of experience rating, high deductibles and no loss control may yield more injuries but higher insurer profits than a program of aggressive loss control.  

And, how concerned should we be about not being able to track the computations, generating lessons on how to peel a boiled egg and the probability of medical fraud? As in the example of predicting “dog,” the computer operates at an unbelievable level of complexity. It cannot tell you the meaning of dog, or trauma, or subrogation, or high deductible, except to predict that a set of numbers compose what we humans call words, which we humans give meaning, such as “dog” as an animal rather than as the verb for giving chase. One can say that the computer is very useful and unaccountable.

Industry organizations such as large insurers, the National Council on Compensation Insurance, the Workers Compensation Research Institute and medical reimbursement services may be the first ones to bite into the apple. And none too soon for all others to grasp the potential of this new generation of AI.

The COVID-19 pandemic was a catalyst for technological change across the insurance industry, especially within personal lines. Customers demanded virtual and digital interactions, so insurers responded by accelerating the development and investments in transformational technologies. Although it may not be accurate to classify our current era as post-pandemic, insurers have adjusted their plans to match the needs of society today.

In SMA’s newest report, "Transformational Technologies in P&C Personal Lines: Insurers' Progress in 2022 and Future Predictions," annual research findings are revealed that track insurers' plans and progress in transformational technologies. Thirteen transformational technologies have been identified that are revolutionizing personal lines and are explored in the report, which offers insights into insurers' progression, with each based on impact and activity.

One area that has progressed by leaps and bounds is new user interaction (UI) technologies. These technologies, which include messaging and collaboration platforms, business texting, chatbots, real-time video chats, personalized interactive video and voice, have the most impact and activity in personal lines today. About eight in 10 insurers in the segment have active plans in the category, while a quarter already have new UI tech in production. This is not surprising, as insurers rushed to improve digital interaction capabilities during the pandemic. Furthermore, personal lines executives see the potential for new UI tech to transform core business areas, primarily policy servicing and claims. This is consistent with the continuing emphasis on improving the customer experience and the evolving demands of customers.

See also: Personal Lines Channel Strategies

Machine learning (ML) is also a critical area for insurers to track, especially because the technology is working with other AI and becoming embedded in many vendor solutions. Nearly all personal lines insurers see significant promise for ML in underwriting, and 61% see transformation potential in claims. However, there is a rise in the percentage of insurers interested in ML but need more funding. SMA’s observation is that this is primarily among Tier 3 and 4 insurers, particularly those with less than $500 million in premiums.

As we move through 2023, we will see some effects of the pandemic continue, such as workforce dynamics and evolving risk exposures, in addition to newer challenges, including the uncertain global economy and political volatility. Carriers must carefully consider the strategic use of transformational technologies while weighing the priorities for investment amid a changing business environment.

Today’s insurers use big data from myriad sources to underwrite more accurately, price risk and create incentives for risk reduction. From telematics that tracks driving behavior to social media that creates a digital footprint that could offer unprecedented insights, new sources of data are now capable of producing highly individualized profiles of customer risk.

Insurers are increasingly using artificial intelligence (AI) and machine learning to manage manual, low-complexity workflows, dramatically increasing operational efficiency. Also behind the rise of AI-powered insurance is the ability to predict with greater accuracy losses and the behavior of customers. Some insurers say it also gives them more opportunity to influence behavior and even prevent claims from happening.

Yet, is there a risk that this new way of doing things could actually create unfairness and even undermine the risk-pooling model that is fundamental to the industry, making it impossible for some people to find cover? After all, AI is not an agnostic technology and so can be used in ways that reinforce its creators’ biases. As a result, insurers need to be especially sensitive to ensure they develop and use AI and machine learning ethically and manage their customers’ data with watertight controls.

How ethical is AI?

AI has become an integral part of the day-to-day operations across most industries and can be credited with condensing vast amounts of data into something more usable. But as companies come under greater public scrutiny for how algorithms are influencing corporate behavior, the question of how to ethically apply machine learning and AI is top of mind for insurance leaders.

It’s important to remember that AI doesn’t really reason; Algorithms have no ethics; they are just simply algorithms. So, instead of asking how ethical a firm’s AI is, we should be asking how far ethics is taken into account by the people who design the AI, feed it data and put it to use making decisions.

For privacy issues, organizations are required to adhere to GDPR regulation, the European legal framework for how to handle personal data. At this moment, however, there is nothing similar in place to grapple with the raft of ethical challenges presented by this rapid rate of AI innovation. The EU AI Act, first proposed in 2021 and expected to pass in 2024, is understood to be the world’s first international regulation for AI. So, although various pieces of legislation are being prepared, grey areas still remain with companies having to rely on high-level guidelines that could leave significant room for interpretation. Therefore, for the time being at least, responsibility primarily rests with companies, organizations and society to ensure AI is used ethically. Insurers will need to think through their entire data ecosystem to achieve comprehensive AI governance, including the insurtech vendors with whom they partner.

With machine learning continuing to generate significant additional value across insurance, the value of applying a clear ethical framework should be considered an essential component to successful adoption and value extraction. In addition to transparency, key components in WTW’s own ethical framework, for example, include accountability and fairness -- understanding, measuring and the mitigation of bias – of the models and systems in how they operate in practice, in addition to how they are built, and technical excellence to ensure models and systems are reliable and safe providing privacy and security by design.

See also: 3 Steps to Demystify Artificial Intelligence

Transparency

While insurers were already on a digital journey and innovating products prior to COVID-19, the pandemic has certainly fast-tracked some of these transformations. Besides the more recent factors of rising uncertainty in global markets and high inflation, evolving customer demands have been applying tremendous pressure on the industry to transform at speed. 

To respond to customers’ expectations for speed and convenience, with products and services tailored to them, and experiences equivalent to those elsewhere in life and online, insurers are having to innovate faster with AI technology increasingly becoming a must-have component and function to augment their risk management activities. The increasing use of AI in making decisions that affect our daily lives will also require a level of transparency that is explainable to employees and customers.

Given the immense volumes and diverse sources of data, the real value of AI and machine learning is best achieved when making intelligent decisions at scale without human intervention. Yet, this capability once achieved gives rise to the perception of a "black box," where most of the business personnel do not fully understand why or how a certain action was taken by the predictive model. This is because, as companies leverage data more heavily and the types of analyses and models they build become more complex, a model becomes harder to understand. This, in turn, is driving an increasing demand for the "explainability" of models and an easier way to access and understand models, including from a regulator’s point of view.

Transparent AI can help organizations to explain individual decisions of their AI models to employees and customers. With the GDPR ruling that recently came into force, there is also regulatory pressure to give customers insight into how their data is being used. If a bank uses an AI model to assess whether a customer can get a loan and the loan is denied, the customer will want to know why that decision was made. That means the bank must have a thorough understanding of how their AI model reaches a decision, and to be able to explain this in clear language.

Realizing the potential of AI 

Opportunities for more sophisticated pricing and immediate P&L impact have never been better. Pursuing pricing sophistication can enable transformative shifts toward advanced analytics, automation, new data sources and the ability to rapidly react to changing market environments.

External data can help insurers better understand risks they’re underwriting. With a complete picture of driver and vehicle, motor insurers can better assess risk and detect fraud. By feeding external data into analytical models, they can quote more accurately and attract desirable risk profiles at the right price point. Investment in AI can also enable an insurer to further enhance the customer experience throughout the policy lifecycle -- from streamlining at the time of quote to processing claims more quickly.

The demand for transparent and responsible AI is of course part of a broader debate about company ethics. What are an insurer’s core values, how do these relate to its technological and data capabilities and what governance frameworks and processes do they have in place to keep up with them? Ultimately, for AI to have the most impact, it needs to have public trust

While it's generally accepted that being digital is a good thing—even an essential thing since the onset of the pandemic—for agents and brokers, it's hard to quantify just how great the benefits are. So, it caught our eye when a study reported that highly digital agencies are growing far faster than ones that are laggards in the digital transition and offered specific reasons for the difference. To dig deeper, ITL sat down with Tyler Asher, president, independent agent distribution at Liberty Mutual Insurance, which conducted the research.

ITL:

I'm intrigued by your report that agencies that are highly digitized are growing 70% faster than those that aren't. I thought I'd start there and ask you to tell me a little bit about the report and how you arrived at that number.

Tyler Asher:

Digital isn't a new phenomenon in the independent agency space, but the trend has accelerated, certainly during COVID. We've been keen to understand where customer expectations changed, how agents adapted and whether they have sustained the adjustments. And we have been tracking these sorts of things over time. This research had 700 independent agents respond, and we found that highly digital agencies grew 70% faster than their less digital counterparts.

A set of digital capabilities stood out as being most highly correlated to growth. For instance, how agents think about digitization across the entire value stream from sales, to service, to continuing customer communications, things like online chat, things like digital marketing, things like the ability for customers to get a quote online.

ITL:

If I'm a slow-growing agency at this point, what would be the two or three things you might point me to that would maybe move me toward the better end of the spectrum?

Asher:

An agency needs to start out by making sure it can be found, through a good digital storefront, and being active on social media and thinking about SEO [search engine optimization]. Some more advanced agencies take digital marketing to the next level, doing paid advertising or paid search. But even just the fundamentals of having a good, modern, clean website that's mobile-friendly, one that comes up in the local results so you can be found, is really important. As prospective customers are looking for, "Who am I going to do business with?"—agents need to be putting their best foot forward.

The next step is thinking through online quoting. We believe insurance is fundamentally a relationship business, and agents differentiate themselves from any other channel through the breadth of their offering and the custom-tailored advice they provide. The online quoting experience can be something as simple as having a button or form where you collect information from the client digitally, so you can quickly follow up and make sure you’re meeting their full needs.

After handling the top-of-the-funnel stuff, you need to get into all aspects of the customer lifecycle. Can you handle their transactional needs—paying a bill, getting policy documents or ID cards, making a simple change to a policy, finding contact information, etc.? How do you digitally enable all that so you can take the transactional burden off an agency's staff and let them focus on driving long-term loyalty?

You also have to let the customer choose how they want to interact with you. It's more typical today that transactions are done asynchronously. It's no longer, "come into the office and sign these documents." It's, "are you available via email or via chat?" Many agents are also developing long-term relationships by sending out a regular email newsletter, for example. There are a lot of digital aspects to managing the customer relationship.

ITL:

I think customer service is key. What role should the carriers play?

Asher:

It's incumbent upon carriers to continue to invest in their digital capability so they can enable agents to make sure the easy stuff really is easy, so customers can handle simple transactions anytime, anywhere. From an agency standpoint, they have to make sure they're taking full advantage of what the carriers are offering, whether that's self-service on a website or through the mobile app. The more that agents have leaned into those digital capabilities, the better they do. Independent agents need to provide the same experience that customers are getting from other industries.

ITL:

I'm seeing some companies offer technology that helps agents organize their days, based on AI that suggests phone calls, meetings, sales opportunities and so on. Are you seeing that much, and how effective do you think that sort of technology can be?

Asher:

We're very familiar with that premise, and it’s a growing trend. We're a data-rich industry. So, there are lots of opportunities to deploy data to predict how best to meet customer needs, both in terms of sales and service.

ITL:

While there's been loads of talk over the years about how insurance agents will get disintermediated, agents have not only survived but thrived. In fact, it seems to me that carriers are competing hard these days for the love and affection of agents. Am I right about that?

Asher:

That is absolutely true. We've actually seen an increase in carriers entering the independent agency space. You've had some strategic pivots by national carriers like Nationwide and traditionally captive carriers like Allstate. I think there's more interest in the independent agency system than there's ever been.

ITL:

One last question. I've studied enough statistics over the years to have had the difference between correlation and causation beaten into my head. How much do you think your report shows that becoming increasingly digital causes better results, and how much do you think you found a correlation? In other words, might those agencies that are already prospering be more likely to go digital, rather than having the digitizing drive the prosperity?

Asher:

I think you're spot on. Actually, before my current gig, I used to run data analytics for Safeco, so the correlation-causation question is near and dear to my heart, too.

I think there's an imperfect answer. It's hard for us to say, "Hey, if you take this digital step, here's the exact result you're going to get." But we can say, "Here are the best-performing agents, and here’s what they're doing." And there is evidence of causation, that an actual tactic is having an impact. When we look at customers who engage with us in digital channels for things like self-service, we see a higher Net Promoter Score with those customers. We see higher retention with those customers. So, we know we’re meeting customers’ and driving real business results. That's demonstrable to agents.

ITL:

Terrific. Thanks so much, Tyler.

About Tyler Asher

Tyler Asher is President of Independent Agent Distribution at Liberty Mutual Insurance, heading up the combined $18.8B Liberty Mutual, Safeco and State Auto independent agent distribution organization.

He played a pivotal role in Liberty Mutual’s acquisition of State Auto in 2022 and now leads a unified field team of associates committed to providing the support and resources the organization’s nearly 32,000 appointed agencies need to grow profitably. He is deeply dedicated to building a culture of advocacy that keeps agents at the center, which has earned the company recognition as champion of the independent agent for five consecutive years, according to the annual Channel Harvest agent voices survey. Under Tyler’s leadership, Liberty Mutual has risen to the number two carrier within the IA channel.

A speaker, mentor and industry advocate, Tyler has devoted his 20+ year career to working with independent agents and advancing the IA channel.

The death toll in the earthquake in Turkey is staggering -- more than 37,000 people are known to have died, as I write this, and the UN says the actual total  could be twice that. But the number who died didn't need to be nearly so high, even though the earthquake and its aftershocks were massive. Tens of thousands of people should still be walking this Earth -- shaken up but very much alive. 

The blame falls squarely on contractors who constructed shoddy buildings and on all those who falsely sold companies and individuals on the earthquake-resistant qualities of the spaces they were buying or renting. Blame also belongs to those government officials who failed to spot and publicize the problems that caused entire blocks to collapse even though buildings were supposedly built to modern standards in an area known to be vulnerable to earthquakes. 

But I do think insurers can help prevent future disasters. It won't be easy. It will require finding a way to share the industry's evaluation of risks in ways that go beyond the narrow confines of a policy and that range beyond the one-year time frame of the normal insurance contract. But it's worth a try. 

I've had occasion to think about earthquakes and building standards ever since I was searching for a new office as the bureau chief in Mexico City for the Wall Street Journal in 1994. Memories were still fresh from the 1985 earthquake that had collapsed buildings throughout the city and killed at least 5,000 (the official count) and probably more like 10,000 people. So, I wasn't just trying to find more space as I hoped to consolidate Dow Jones operations in Mexico but was looking for resilience in the face of earthquakes, and I got quite an education on just how much force buildings could be constructed to withstand. 

My problem as a buyer boiled down to two issues: information and incentives. And those two issues not only confront other buyers as they think about where to locate in earthquake zones but create hurdles for the broader, societal desire to keep earthquakes from causing billions of dollars of damage and killing tens of thousands of people.

The information issue was simple: Others had it, and I didn't. Those who constructed the buildings I visited certainly knew what standards they had or hadn't met. Government inspectors did, too. But I was operating at a severe information disadvantage. I could look at the brochures I was presented and maybe dig into government reports, but I still wasn't going to really know just how a building would perform once the shockwaves of a major quake starting rolling through the drained lakebed that Mexico City is built on.

The agents for those builders also didn't have any incentive to be open with me about the resilience of an office. They just wanted to make a sale. I'm not saying there were necessarily dishonest. I'm merely acknowledging the realities of capitalism. They had every reason to gloss over any imperfections, just as the builders had incentives to keep costs as low as possible during construction. 

Government inspectors also didn't have incentives that lined up very well with mine or with those of society writ large. They produce their reports for decision makers in the bureaucracy, not for the public, so they use obscure language and don't even have a very good way of informing the public about the relative safety of buildings. And -- let's be frank -- inspectors aren't always as pure as the driven snow in a political culture like Mexico's in the mid-1990s. Bribes were known to happen. 

Here's where insurers come in. They have both the right information and the right incentives. They can not only help an individual like me circa 1994 but can also educate a whole populace about risks in ways that could greatly limit the devastation from future earthquakes. 

As I said, it won't be easy. Yes, underwriters have all the data they need on the general risk of an area such as Mexico City or on the recently devastated area along the Turkish-Syrian border, where three tectonic plates come together. Insurers also have accurate data on all the buildings whose owners or renters they underwrite. And insurers have reason to want to help clients avoid losses, especially as we move more toward a "predict and prevent" model and away from the traditional "repair and replace" approach to insurance. 

The biggest problem is that the decision to rent or buy tends to happen before insurance enters the equation. In addition, the cost of insurance is typically reflected in one-year increments, as policies come up for renewal. 

But what if insurers in Turkey had warned prospective occupants a decade ago that certain buildings weren't, in fact, built to modern standards for withstanding earthquakes, despite what the owners' agents claimed? What if insurers had also said that risks (and premiums) would increase each year because pressure continually builds where tectonic plates cross, until an earthquake releases that tension? What if the insurers had put a hefty price tag on those increasing risks, showing prospective occupants that they wouldn't save nearly as much as they'd hoped by moving into a building constructed to a sub-par standard? And what if those insurance conversations had happened before the lease or mortgage was signed, rather than afterward?

How many occupants would have been dissuaded (and lived)? How many builders would have retrofitted offices or at least adhered to high standards in future construction?

I saw such broad conversations about cost have an impact in the personal computer industry in the late 1980s and through the 1990s. Many budget brands lost credibility when consultants began rating the total cost of ownership over the lifetime of a PC, and buyers could see what they'd likely spend on maintenance, software that wasn't included in the base model, etc. These days, makers of electric vehicles are changing the conversation along similar lines. Yes, EVs cost more up front than those with internal combustion engines (even with government incentives, in many cases), but they require much less maintenance and, of course, don't require gasoline. 

So, while I realize a lot has to happen between my noodling on earthquakes and broad societal impact, I'm hoping that we can change the timing and nature of conversations about insurance and blunt at least some of the effects of earthquakes in years to come.

Cheers,

Paul 

Looking back at 2022, insurance providers mostly had a quiet year that ended in turmoil. The $132 billion in insured losses from natural catastrophes in 2022 was 57% above the 21st century average. On the other hand, health insurance claims related to COVID-19 tapered off, and there were fewer storms affecting P&C policies. Life insurance payouts occurred less frequently, as well, following the record highs of the pandemic. 

But 2022 was an intense year for insurance providers. Hurricane Ian devastated Florida in September, and, at $65 billion insured losses and counting, it was the costliest natural disaster of the year. The year’s relative quietness also meant demands for most lines of coverage were lower, and consumers, rather than buying policies, cautiously waited for economic conditions to unfold. Inflation and recessionary fears cooled interest in life insurance products, lowered investment income and contributed to increased prices when paying claims. Supply chain issues even hurt the insurance industry; building materials, car parts and everything in between are much more expensive, and insurers are covering that cost directly. Life insurers were able to manage more of these pressures than most; they have flexibility to match premiums to market conditions and take advantage of rising interest rates. 

What does this mean for insurers in the year ahead? Luckily, they started 2022 in a position of strength, and still are in a good spot to drive down costs and increase demand, unless rising claims costs and market volatility continue. 

Leverage technology to adapt for disruptions

Insurance, like all industries, is dealing with a tough labor market. Investing in people to keep them trained and equipped to handle all necessary processes can be a lot, but it’s crucial. Insurance companies also need to find ways to do more with even fewer people. The best way to do so is to augment employees with automation. Automation can eliminate mundane and time-consuming tasks to create a more rewarding workplace. As insurance companies step into the future, this will be key.

As a side effect of insurance work, many insurers have more data than they know what to do with. They need to capitalize on their analytics in more ways than one. Data analytics should drive investment decisions, product development and pricing and help with fraud detection. With deep analysis of data, insurers can manage uncertainty and better model predictions and strategies. Data analytics can allow insurers to be prepared to answer “What if?” to figure out what’s coming. Assumptions, instinct and Excel models aren’t enough. 

Moreover, insurers have to anticipate disruption to their models and to the world economy and prepare for it. Uncertainty is rampant, and so are cybersecurity threats, geopolitical tensions, changes to tax law globally, compliance burdens and rising competition from insurtechs. Insurers have to adapt much more quickly than before, and automation and using the data they’re generating will allow them to be nimble and anticipate market pressures before they become issues. With good data and augmented workforces, insurers can be more resilient and agile to face coming challenges. 

See also: Risk Barometer for 2023

Create a better customer experience

In 2023, insurers will have to balance improving their internal processes and improving their customer experience. Consumers are demanding simpler processes to buy and use insurance, and traditional insurance companies are often left in the dust by digital-first companies that aren’t hindered by legacy systems or traditional ways of doing business. To stay relevant, insurance companies will need to adopt digital capabilities to stay apace with nascent competitors. By doing so, they can help customers much more quickly when disaster strikes and reach their policyholders effectively on their own terms. If the customer journey isn’t fully mapped out, it won’t have technology in place to communicate with policyholders when they need assistance quickly. On top of that, customers are expecting insurers to be socially and environmentally conscious, not just paying lip service to their causes, with true ESG strategies. Insurers that are aggressive about ESG can differentiate themselves in the market for both consumers and for employees.  

These fundamentals of adopting new technologies, using data effectively, augmenting workforces, simplifying customers’ experience and fully integrating ESG strategies need to be instituted if insurers are going to stay competitive in 2023.