Insurance Thought Leadership:

Mark, it’s great to have a chance to catch up a bit.

I saw that Hub International recently took a minority investment that put its valuation at $23 billion. It, Acrisure and some others have been so acquisitive that I’m reminded of a cartoon I saw back in the early 1990s when all of corporate America was in the middle of a takeover binge. The cartoon showed a table of stock prices from the New York Stock Exchange, but there was only one name listed: IBMGEAT&TMicrosoftIntel etc. There were probably 20 more names tacked on.

With that as prelude, what are you seeing in terms of agency consolidation?

Mark Breading:

It's a really dynamic environment and has been for the last number of years, but it's kind of interesting because the number of retail agencies in the U.S. remains relatively constant. There has been all kinds of acquisition activity in the last two years, with about 1,000 agencies acquired each year. Yet, if I look back in history, in 2000, there were 42,000 retail agencies in the U.S. By 2010, the number dipped to 38,000. But by 2022, it's back to 40,000. So, while there were 1,000 agencies acquired every year in the last number of years, more than 1,000 agencies are being launched every year.

Now, to your point about all the aggregators out there, I’ve been blown away by how fast some of them have grown. Some came out of nowhere. There are many stories where, five years ago, a company was valued at $50 million, and now they are valued at $400 million.

On the one hand, these aggregators are snapping up agencies left and right. On the other hand, there's still lots of new activity going on with small agencies. And if you look at the 40,000 to 42,000 that are out there now, most of them are still small. A third of them are still less than $150,000 in revenue – literally a mom and pop around the kitchen table, and that's their living. I think around 60% are less than $500,000 in agency revenue.

There are still lots of small, independent agencies out there, and that makes for an interesting environment.

Insurance Thought Leadership:

I hadn't really thought about all the new agencies sort of filling in for the others that have disappeared because they were acquired.

Does the aggregator model work? In theory, it does, but I certainly have covered some rollups over the years that have not done well.

Mark Breading:

I think we're going to have the answer to that question in the next two or three years. Over the last, say, five years, the aggregators have been very active in acquisitions. In many cases, they let those agencies continue to run independently. But if the aggregators are going to be successful going forward, they have to start to think enterprise, right? How do we optimize our technology, our people management, our partnerships and our relationships?

I can't imagine how they could continue to grow and be successful running hundreds of little agencies.

The aggregators are right at that stage where they need to think about broader platforms and enterprise strategies. Some of them have started to roll up the little brands into the mother brand, but others have left those companies to still just do their own thing.

Insurance Thought Leadership:

That's always the tension. I don't know if I ever sent you a copy, but Chunka Mui and I wrote a book called “Billion Dollar Lessons” that we published in 2008, based on extensive research into 2,500 business failures, and one of the seven major patterns of failure we identified was rollups. They look great for a while, and then, as you say, there comes that point where you either have to start doing something differently or you aren't going to get the value out of the acquisitions. But once you start doing things differently, you can screw up the secret sauce that was making these businesses successful in the first place.

Mark Breading:

There are certainly acquisitions where the aggregators are acquiring agencies of reasonable size, and they're more corporate, so they fit better into the enterprise. But if you're buying a local agency that has 10 employees or 20 employees, and they just serve that local community, it's hard to all of a sudden make that agency part of this big corporate enterprise. If you start telling them, Here's how you have to do business, and we're going to change your brand, it's hard to keep people. They liked working local and for that local agency.

A big challenge for a lot of these aggregators is, How do you retain the talent, keeping not just the producers but the customer service reps and others who are involved in that agency?

Insurance Thought Leadership:

What do you think interest rates will do? It's one thing to be buying up agencies when money is essentially free, but when money is now costing you 6%, or whatever the right number is, that theoretically changes the dynamics some.

Mark Breading:

Yes, it does. We’ve seen that play out a little bit in the insurtech space, but there were still almost 1,000 agency acquisitions last year, and interest rates were higher toward the end of last year than they are now. The pace of acquisitions may slow a little bit, but it seems they’ll continue because the business model requires aggregators to keep buying, at least for a while.

Insurance Thought Leadership:

What other trends are you seeing?

Mark Breading:

I’m seeing a couple of other big trends. One is that the MGA [managing general agency] model is expanding rapidly. There are over 1,000 MGAs in the U.S. now, and we've tracked something like 125 startup insurtech MGAs. In the last few years, we’ve looked at their business models, and about 60% start out as what we have called line-focused or segment-focused. Some might focus only on cyber or

perhaps flood or some other specific peril or say we're just going after the Hispanic segment in the Southwest. As these MGAs grow, of course, they'll either sell or expand.

All these new MGAs are digital natives, so they're investing in tech. If you go back 10 to 20 years, MGAs never wanted to spend a nickel on technology. They relied on their risk expertise in specific areas and on their relationships downstream with independent agencies as well as upstream with underwriting companies. Now they have to be very sophisticated digitally.

The other trend is that there's a lot of activity in new partnerships. Every distributor is trying to figure out how to reach their preferred market segment, so they’re trying to find carriers that want to write the kind of business they want to sell and to leverage the relationships they have with businesses and individuals.

Maybe an agency never worked with an MGA or a wholesaler before, but now they're partnering. Or maybe the agency is expanding their panel of carriers to whom they submit business to add the same capability from the carrier side.

Should they launch their own MGA or work with the wholesalers? Should they do embedded insurance to reach affinity groups?

I see a lot of really interesting activity going on with partnership strategies and new partnerships.

Insurance Thought Leadership:

Have you seen a particularly good example of a partnership?

Mark Breading:

Some are really interesting to watch to see how they develop, such as what Amazon has done with their Marketplace. They are connected with millions of small businesses and are offering professional liability insurance or workers’ comp or whatever via a partnership with Marsh, which is then connected into Hiscox and a number of others. The jury is still out on whether they’ll succeed.

In the workers’ comp space, many are starting to partner with payroll providers, because payroll providers tend to already have a portal into businesses.

Embedded insurance is a whole other dimension, as well.

Insurance Thought Leadership:

The Amazon deal will be fascinating to watch. The potential is huge, just given the reach of Amazon, but, yes, they have to get it right. Operating at their sort of scale, you can go wrong in a big way pretty quickly.

You mention embedded insurance. I have been a big fan but have recently cooled a bit on it because I haven't seen much exciting. What are you seeing?

Mark Breading:

Yeah, I think it's an important trend, but it has been overhyped, for sure.

Part of the issue is that people have different definitions of what they consider embedded insurance Root announced a partnership with NASCAR as an embedded insurance proposition. But it's not. It's just an affinity relationship.

In my view. If you're really talking about embedded insurance, you're talking about the insurance as being almost invisible at the point of service. It's a quick “yes,” “click this” or make a couple of choices and you’ve got insurance, just like travel insurance has always been.

That's starting to happen in personal auto. Obviously, the Teslas of the world are leading, but other OEMs are also doing it. There is still not a huge take up, though. Most personal auto insurance is still sold through agents, despite all the digital options.

There are areas like warranty and travel, where it's always been. Perhaps embedded insurance makes sense for gig workers and on-demand insurance. But I don't think there's going to be much at all in the whole commercial space, outside of maybe for micro businesses. With business with employees and property and vehicles and liability and so on, I just don't see how you're going to make insurance more invisible. You need advice.

McKinsey had a report a couple of years ago that said that, by 2030, 30% of all insurance is going to be embedded. Perhaps they'll prove me wrong, but I don't think we're going to be there.

Insurance Thought Leadership:

Yeah, 30% sounds like one of those made-up numbers.

Mark Breading:

I'm with you.

Insurance Thought Leadership:

That's really it. That's the sort of overview I was hoping for. Are there any things you're seeing that you think are relevant that I didn't ask you about?

Mark Breading:

The only other thing is that there's a lot of technology activity going on to improve the whole transaction flow between agents and carriers. Everybody is upping their game digitally. A lot of the research we've done has been trying to help people understand: What do agencies want? What are carriers building? And how do we bring them together better so they can everybody’s whole game for the entire ecosystem?

Insurance Thought Leadership:

A worthy goal.

Mark, thanks so much for your time and expertise.

 

About Mark Breading, Senior Partner, ReSource Pro Consulting

Mark Breading is known for his insights on the future of the insurance industry and innovative uses of technology. Mark leverages his background in strategy, marketing, and technology to consult with insurers and technology companies on forward thinking strategies for success in the digital age, where his inventive methodologies, fresh ideas, creative conceptualizations, and ability to incorporate InsurTech and transformational tech in business strategies is unparalleled. His thought leadership in the areas of distribution strategies, InsurTech, transformational technologies, and digital strategies has earned him a ranking as a "Top Global Influencer in InsurTech" by InsurTech News. Mark spent 25 years with IBM, where he co-developed IBM’s Account Based Marketing program and led the global project office to implement ABM across all industry verticals worldwide. Mark was instrumental in the success of Strategy Meets Action from the early startup phase through its acquisition by ReSource Pro in 2020.

Ransomware accounts for a staggering 75% of all cyber insurance claims, a significant jump from 55% in 2016. However, new research from Delinea finds that fewer than half of respondents reported having policies that cover "critical risks," including ransomware, ransom negotiations and ransom payments.

The Ransomware Surge and Its Connection to Cyber Insurance 

With ransomware attacks on the rise, and no signs of slowing, cyber insurance companies have had to evolve quickly. Cyber insurance companies have started considering their own risks and exposure and have raised premiums and increased their cybersecurity requirements before granting coverage. Carriers are looking more closely at how well organizations follow security best practices, such as access control, multi-factor authentication (MFA) and the principle of least privilege. 

Some insurance companies have started pulling back and insuring less or putting more limitations on their policies. For example, many cyber insurers may deny claims due to lack of security controls, acts of war or terrorism, not following compliance procedures and even simple human error – if an incident or ransomware attack is caused or worsened by misconfigurations, insurance companies can argue that it could have been prevented and deny incident claims.

It is extremely important to follow cybersecurity best practices and fully understand your cyber insurance policy to ensure you get the coverage you expect in the event of an attack.  

Understanding Your Cyber Insurance Policy 

It is clear that cyber insurance won’t cover all security incident costs. Many insurance companies will not pay ransomware costs or even help cover all of the costs involved. Oftentimes, organizations must accept the consequences of an attack and, even with insurance, will have to cover the costs to get back on track.

According to Delinea’s research, insurance companies are least likely to cover lost revenue, regulatory fines, legal fees and ransomware payments. Instead, the expenses most often repaid by insurance were the costs associated with data recovery and incident response costs. As ransom attacks become more and more common, insurers will continue to modify their ransomware protection to reduce the level of coverage they offer.

Every insurance policy is different, so it is important to review yours carefully, and often to know exactly what your cyber insurance will and will not pay for and ensure that you are meeting their requirements. 

See also: Does Cyber Insurance Add to Ransomware?

Navigating the Complex Cyber Insurance Landscape 

The evolving landscape of cyber insurance requires careful consideration and preparation, especially when it comes to protecting against prospective ransomware attacks. To secure comprehensive cyber insurance coverage while managing costs, organizations must address the following aspects: 

1. Security Controls: Organizations should implement robust security controls to reduce exposure to ransomware risks. Identity and access controls, password vaults and MFA are must-haves for any organization seeking insurance. These controls can also help minimize potential insurance payouts. 
2. Budget Planning: It is important to allocate a budget for purchasing necessary technical solutions and for hiring skilled workers to meet the higher security standards required by insurance providers. 
3. Risk Assessment: The insurance industry evaluates cyber risk using various models and metrics. Organizations must ensure they understand these metrics and are prepared to demonstrate commitment to cybersecurity risk controls. 
4. Insurance Checklists: Businesses should look into various cyber insurance checklists to ensure they meet the minimum requirements set by insurers. There are also numerous cyber insurance questionnaires available that help businesses have well-informed responses ready for any question insurance companies may ask. 

Cyber insurance should complement a comprehensive cybersecurity program that includes employee training, robust security protocols, regular vulnerability assessments and well-defined incident response plans. With the cyber insurance landscape rapidly changing, and ransomware continuing to rise, it's important to stay informed about evolving insurance policies and industry best practices.

By taking steps to improve your cybersecurity posture and meet your insurance requirements, you can ensure that your organization is well protected and prepared for any adversaries.

The advent of Supply Chain 4.0 marks a transformative shift in the landscape of logistics.

As we stand at the threshold of the Fourth Industrial Revolution, two key technologies - blockchain and artificial intelligence (AI) - are poised to redefine the dynamics of supply chain operations. These digital tools harbor the potential not only to revolutionize the efficiency and transparency of supply chains but also to propel organizations toward unprecedented levels of growth and competitive advantage.

In this article, we delve into the impact of these game-changing technologies on supply chain digitization and how they will shape the future of industry.

What Is Supply Chain 4.0?

Supply Chain 4.0 is the term for the modern, digital era of supply chain management, powered by innovative technologies like blockchain and AI. The "4.0" denotes its place in the “Fourth Industrial Revolution,” following the internet-based advancements of Supply Chain 3.0.

In this new paradigm, supply chains are becoming more efficient, transparent and agile. With the integration of digital technologies, traditional linear supply chains are evolving into dynamic, connected systems. These systems leverage data analytics, automation and machine learning to optimize operations, predict market changes and make strategic decisions. The ultimate goal of Supply Chain 4.0 is to create a fully integrated, automated and transparent supply chain that is resilient to disruptions and capable of self-regulation.

How Are AI and Blockchain Used in Supply Chains?

Artificial intelligence and blockchain have distinctive applications in the realm of supply chain management, each contributing unique capabilities that enhance operational efficiency and transparency.

AI's role in supply chains is predominantly centered on data analysis and prediction. Advanced machine learning algorithms can process vast quantities of data, deriving insights about market trends, consumer behavior and potential disruptions. This information enables organizations to anticipate demand, optimize inventory and streamline logistics, resulting in improved efficiency and customer satisfaction. Additionally, AI-powered automation can handle repetitive tasks, freeing human resources for more strategic roles.

Blockchain, on the other hand, brings transparency and traceability to supply chains. It creates a decentralized, immutable ledger of all transactions, ensuring that every step in the supply chain is documented and verifiable. This transparency mitigates risks associated with fraud or counterfeiting and enhances accountability among all stakeholders. Furthermore, smart contracts - self-executing contracts with the terms of the agreement directly written into code - can automate transactions, further increasing efficiency and reducing the potential for disputes.

The synergy of AI and blockchain technologies in Supply Chain 4.0 creates a robust, transparent and agile system capable of adapting to the rapidly evolving demands of the digital age.

See also: Growing Risks From Quantum Computing

How Will Supply Chains Benefit From the 4.0 Revolution?

The benefits of Supply Chain 4.0 are manifold and far-reaching. At the core of these advantages is improved efficiency. By leveraging AI and blockchain, organizations can automate manual tasks, reducing human error and streamlining processes. This leads to significant time and cost savings. 

Secondly, these technologies enhance transparency across the supply chain. Blockchain, for instance, offers a secure, immutable ledger of transactions, enabling real-time tracking of goods and ensuring accountability at every step. 

Another key benefit is agility. AI's predictive capabilities allow for timely detection and handling of potential disruptions. It empowers organizations to adapt quickly to market changes and customer demands. Moreover, the integration of digital technologies within the supply chain fosters innovation. It provides a platform for continuously testing, learning and improving strategies, thus driving competitiveness. 

Lastly, Supply Chain 4.0 promotes sustainability by enabling smarter resource allocation, reducing waste and facilitating the implementation of green supply chain practices. For instance, AI can play a pivotal role in improving sustainability by optimizing logistics and distribution routes. Using predictive analytics and machine learning algorithms, AI can analyze complex patterns and trends, taking into account factors such as weather, traffic and fuel consumption. By suggesting the most efficient routes, it helps reduce fuel usage and, consequently, carbon emissions.

Conclusion: Moving Toward a Supply Chain Revolution

In conclusion, Supply Chain 4.0, underpinned by revolutionary technologies like AI and blockchain, holds the promise of a more efficient, transparent and sustainable future. It offers businesses a competitive edge, enabling them to navigate the complexities of the digital era with agility and innovation. As we move forward, businesses need to embrace these digital transformations, harnessing their potential to drive growth, enhance customer satisfaction and contribute to a sustainable future. The revolution is here, and it is reshaping the way we think about and manage supply chains.

Patrick Schmid, PhD, MA, is president of The Institutes RiskStream Collaborative. He previously headed The Institutes’ Enterprise Research Department; served as director of research for the Insurance Research Council (IRC), a division of The Institutes; and worked as an economist for Moody’s Analytics. Schmid has taught economics and finance at Philadelphia colleges and universities.

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Paul Carroll

The last time we talked, you had a couple of use cases, in particular, that were moving along well. To set the stage, would you tell us what the state of play is now.

Pat Schmid

It's been interesting. The consortium has done a very good job of developing an efficient platform, which we call Canopy. This was critical to ensure that costs are reasonable to build and adopt various solutions, which would be done on top of Canopy. Over the past couple of years, we’ve developed the platform to the point where we can build and move forward with a variety of different use cases and a variety of different use case types.

In the past, when we've chatted, we've primarily focused on network-based use cases like Rapid X, the loss data exchange solution for auto insurers. With that application, for small or medium-sized organizations to get the large benefits associated with it, the largest carriers would likely need to be on the network. This, at times, created a kind of chicken-and-egg problem for the consortium, because a similar notion also affects the large players. The benefit of being on the network is based on others joining in, too.

To obtain strategic advice and tackle that challenge, we formed an auto insurance advisory committee that consists of representatives from eight out of the top 10 auto insurance companies. Many of these companies have signed a letter of intent to adopt RAPID X and were, therefore, committed to expanding the network. We are now planning to pilot the Rapid X solution with three companies in the fall; all three are top-15 auto insurance companies. We're keeping the pilot, which will leverage production data, small to move more quickly. We’re very excited because this advisory group has helped us understand that the value of RAPID X may be leveraged in other ways, like displacing various companies’ third-party claims portals. This may make the value to a carrier less dependent on the network adoption of other carriers, which could overcome the chicken-or-egg problem.

We've also been recognizing that what we’re calling linear use cases or partnership use cases can emerge and take off quickly. We recently started a working group that was looking into whether there might be a use case for a parametric trigger using smart contracts on a blockchain for homeowners’ parametric reinsurance. Basically, could the cedant-to-reinsurer parametric contract be automated with blockchain-enabled smart contracts?

As we did that, we were introduced to a technology company called Arbol, which had a contract they were working on with a Florida-based insurance company called Centauri, and they actually leveraged a parametric product during Hurricane Ian and had a $10 million payout. They were looking to automate and put the product on a blockchain platform, so we talked to them about Canopy, and within months this application was built and moved to production. This app is live on Canopy. It actually just won the Insurer Insider Honours “Underwriting Innovation of the Year” award, and RiskStream/Arbol held a summit to start to think about other uses of the application.

Whether it’s the network-based apps or linear/partnership apps, I think we're beginning to see a lot of light at the end of the tunnel within enterprise blockchain use cases in insurance. I think there will be

applications here over the next year or so that will be live and will provide significant operational efficiencies to the industry.

Paul Carroll

For those who aren’t familiar with Rapid X, could you say a bit about how it works and what its benefits are?

Pat Schmid

Sure. It's an auto insurance data exchange solution that allows a carrier’s claims system to exchange information and data, automatically and securely, with another carrier’s claims system. This is done today in less secure ways. To give an example: Let’s say a policyholder with Liberty Mutual calls in with a loss. Liberty will record the first notice of loss within their (let’s say Guidewire) claim system. That Guidewire system can integrate Liberty’s claims system to their Canopy node on our decentralized network of nodes for insurance carriers. Let's say the Liberty Mutual policyholder was in an accident with someone from Allstate. The data from Liberty Mutual’s claims system can be sent from the Liberty node over to the Allstate node in a permissioned and private manner. This node can integrate into Allstate’s claims system, which could be Guidewire, Duck Creek or some other, homegrown claim system. So, by the time the Allstate policyholder calls in, Allstate may already have information on the claim, which will expedite the process on the phone and make for a better customer experience. Our solution also lets their nodes exchange information as they fill in data in their individual claims systems, reducing the back-and-forth between the two companies as they determine liability and so on.

We’re not recording the data on the blockchain itself, by design. The blockchain is simply a state machine for network participants. It’s allowing the system’s state to update and providing access between those two parties to exchange information privately and much more securely than they do today.

On top of this foundation, we’ve started to add capabilities. One that's really interesting was brought to us independently by two top-five personal auto insurers. Most of the top insurance companies in personal auto have third-party portals that can provide data to other companies, so employees don’t have to handle lots of calls. The challenge is advertising to their competitors whether they have a third-party claims portal and where to go. There’s really no benefit for a company maintaining their own third-party portal. So these two companies suggested creating an industry “universal portal” so even small companies that don’t have a third-party portal and that aren’t on the Rapid X network can use it and help make the whole industry more efficient. This will likely leverage RAPID X as a back end and allow RAPID X participants to engage (with a much smaller data set) with those not yet on the network.

We’re also looking into adding an auto insurance fraud detection solution. While RiskStream is known for blockchain, our sweet spot is where multiple parties are involved in an issue. We can use any appropriate technology to solve those multiparty business process challenges. For detecting fraud from double-dipping, enterprise blockchain may not be the best tool because generally you need to pool the data to detect it. The industry is, for good reason, concerned about pooling data because of security and privacy issues. But technology can let the industry pool data confidentially (using what’s known as confidential computing).

Imagine this confidential computing platform to be a black box that no one owns, including RiskStream. No one can get the data from within it. But it's part of the RAPID X network, and Rapid X can start to feed it (with tiny bits of private, secure information) after each exchange between two RAPID X users. To continue with the example I used before, when Liberty Mutual and Allstate resolve that claim using Rapid X, it feeds a little bit of data into this confidential computing platform. Then, imagine CSAA comes to the table with a claim with Nationwide later. They can query the confidential computing platform to see, for instance, if that exact VIN has been involved in another incident with another insurer on the network recently. None of the parties will have access to the data, but they can query it to obtain a warning of double-dipping fraud.

Paul Carroll

I can imagine all kinds of benefits. Is there any way to quantify them in terms of time saved? Money saved? Something else?

Pat Schmid

We conducted a study on this, but at that time it was based on various assumptions. With the pilot, we’ll be using production data, so we’ll have real information on the ROI in a couple of months.

Paul Carroll

What did you find in the earlier analysis? I know it's not as complete as the pilot will be.

Pat Schmid

Our previous report on Rapid X ranged between $62 million and $173 million in savings industrywide.

In the Liberty Mutual/Allstate example I was sharing before, the first benefit would be that Allstate would reduce the amount of time needed to transmit information from the policyholder to their system of record. The second benefit is that the effort exerted in data exchange would be reduced. In our working group, among a large number of carriers, we were shocked to learn that the average claim requires five points of contact back and forth. These are all manual, normally conducted by phone or electronic communication, then often keyed into the respective claims system. That’s very inefficient and may not be maximizing privacy and security. The third benefit is the reduced reliance on external vendors that charge carriers for the data used in claims prefill. The fourth benefit is that Rapid X has a simple liability feature that allows carriers to notify one another when liability is determined in certain cases. Finally, there is a reduction in overall cycle time, which will lead to a better customer experience on both sides.

Our members think there's vast potential here and see possibilities for extension to a suite of surrounding products, including fraud detection, broader liability determination, subrogation and salvage. The big question is: Can The Institutes and RiskStream get the industry participants to work together? We're showing through our advisory groups, our pilots and our working groups that we can, and that has been a challenge for other enterprise blockchain initiatives. That's the big step. Once companies start to move to production, we think we will cross the chasm, so to speak. This will lead to a snowball effect. So we're close, but we have a little more work to do.

Paul Carroll

You have an awful lot of the big players, and the small players tend to follow the big players. And correct me if I’m wrong, but I don’t see any competitive reason for companies not to work together on Rapid X. There might be logistical issues, but I don’t see a business reason not to do it.

Pat Schmid

I agree. And the nice thing for a lot of these larger insurers is that they're operating across different lines of insurance, and we have other solutions that can be beneficial to them in other areas. We have use cases in surety bonds, for example. We're also going to be starting up a working group in commercial property and recently launched a lab in inland marine. We have several use cases in the life and annuities market. So, industry players like Nationwide or Cincinnati Financial, for example, that operate in all of the above, have benefits in supporting our initiative because theoretically they're going to want these efficiency gains for surety bonds, but they’re also going to want it for commercial property, and they're going to want it for life and annuities.

On that note, surety is actually our largest initiative, by far. It's global in scope. We've been working with five international surety associations: the International Credit Insurance & Surety Association (ICISA), the Canadian Surety Association, the National Association of Surety Bond Producers, the Surety & Fidelity Association of America and the Panamerican Surety Association. At the outset, these entities supported the effort to create a surety network. Since then, we’ve worked with the industry on two use cases. The surety industry is riddled with complexity and paper because of all the disparate parties: You have the obligee, the surety, the agent, the principal, all involved in verification. So there’s a variety of parties involved in a manual, paper-based process that could be digitized. Thus far, we’ve created an application for a power of attorney document that is created as an NFT [non-fungible token] and digitally verified across the various parties. Since then, we've more moved to the bond itself, again creating an NFT to track delivery and verification.

Now we’re working with large core system providers such as BondPro, Surety2000, Tinubu and Xenex to integrate various systems to the nodes. This will help as we’re now moving to engage obligees. The work has received a lot of attention in the surety space. I wouldn’t have predicted that sector would be so supportive of technology solutions, but enterprise blockchain has been of deep interest to them. I think the key reason is multiparty business process challenges. That’s the sweet spot for enterprise blockchain.

Paul Carroll

If we talk in a year or two, what do you think will be the headlines for blockchain? It sounds like Rapid X is a big one. Surety bonds would be a big one. What else?

Pat Schmid

I see Rapid X moving to production and starting to provide business benefit. Those additional features will likely start to be leveraged, as well – the fraud detection and universal portal, for example. Others may, too, such as assistance with subrogation and increased efficiency in the title transfer process in salvage.

I do think the surety bonds initiative will move to production here over the next year to year and a half in power of attorney verification and bond delivery/verification and probably start to move forward in some other areas, as well.

We'll start to see progress in other sectors, especially life and annuities. The lead there is what we are calling the Mortality Monitor, which allows network participants to securely and privately share certain data on a deceased party in a permissioned manner, provided another network participant also has the deceased as a policyholder. If the industry can find ways for the carrier to learn of the death quicker, the beneficiary reward process is also going to be expedited, which is going to benefit everyone.

I think payments is also ripe for change. As you’ve seen with the use cases I’ve mentioned, a lot of focus has been on data exchange and verification within claims and underwriting, but it’s likely payments use cases will come to light in the next few years. I think these will move very quickly when the time is right.

Finally, I anticipate that insurtechs with innovative solutions will get involved and that partnership use cases can move very quickly, as Arbol did. We have the technology platform today, and we have the business network of all these large carriers, brokers and reinsurers, so if you bring a good idea to the table it can move really quickly to production and provide business benefit.

Paul Carroll

The whole effort sounds so much more robust than when we talked last. Is there anything else you want to highlight that I haven't thought to ask about?

Pat Schmid

The only other thing I’d mention is RiskStream is here to help the industry on multiparty business processes. While enterprise blockchain has been and will remain our focus, a lot of attention has recently been on AI, and our members have asked about multiparty usages of this technology and whether RiskStream could potentially work on related solutions. Again, our focus is enterprise blockchain, but if the industry has an example where there’s a multiparty use of AI, there may be an opportunity RiskStream could look into. To better understand this, RiskStream is preparing an educational series on multiparty AI usage in insurance in the winter. Stay tuned for more on that.

Paul Carroll

This was great, Pat, as always. Thanks.

FROM THE EDITOR  When cryptocurrencies crashed last year, the many I-told-you-so's tended to dismiss not only the currencies but also the underlying technology: blockchain. Not so fast. As you'll see in this month's interview, with Patrick Schmid, president of the RiskStream Collaborative, blockchain keeps moving forward and is very close to entering production with at least a couple of applications than can make the industry operate more efficiently.  In particular, RiskStream's Rapid X, which lets insurers share information on auto accidents, is about to start a pilot that will use production data. Among other things, that pilot will let RiskStream generate real data about the savings in time and money that come when insurers can stop playing phone/email tag and can collaborate via blockchain on filling out the claims documentation.  RiskStream has also made great progress in an area where it didn't expect to find nearly so much interest: surety bonds. Working with five major industry groups, RiskStream has developed applications that greatly simplify all the document handling that goes into powers of attorney and into the delivery and verification of the bonds themselves. The collaborative, which, like ITL, is an affiliate of The Institutes, continues to broaden adoption of its Mortality Monitor. The application allows network participants to share data on a deceased party with another network participant that also has the deceased as a policyholder. The goal is to speed the processing of benefits. Progress on blockchain has been slower than I, at least, expected. I knew there would be technical issues and figured it would take time to line up industry support for a radically new technology. But I underestimated the extent of the chicken-and-egg problem -- you don't get the full benefits of a blockchain application until all the major players are on the network, but the major players aren't inclined to join the network until they see the potential for real benefits.  The good news is that RiskStream has pulled together support from just about all the major auto insurers and, while earlier in the process on surety bonds, has major backing there, too. And the history of what's known as network effects (or Metcalfe's Law) shows that when a technology reaches the tipping point, adoption comes very quickly. So, no breakthrough for blockchain yet, but stay tuned. We're getting there. Cheers, Paul P.S. In addition to the interview with Pat, you might want to read this piece in Risk & Insurance, a sister publication of ours, that provides a thorough survey of the blockchain landscape. In this month's FOCUS on Blockchain, Pat Schmid, president of the RiskStream Collaborative, highlights the significant strides being made in adopting enterprise blockchain solutions. He discusses the successful development and potential impact of the "Rapid X" data exchange solution, shedding light on how it enhances efficiency in claims processing. Read the Full Interview "Whether it’s the network-based apps or linear/partnership apps, I think we're beginning to see a lot of light at the end of the tunnel within enterprise blockchain use cases in insurance. I think there will be applications here over the next year or so that will be live and will provide significant operational efficienciesy benefits to the industry. " — Pat Schmid Read the Full Interview READ MORE Can Blockchain Transform Insurance? Insurers are looking to harness the power of blockchain to infuse processes with the three T's: trustworthiness, transparency and tamper-resistance. Read More Blockchain’s Future in Surety Industry Bond execution still involves antiquated technology like typewriters and fax machines. It’s time to catch up, including with blockchain. Read More Top 10 P&C Insurance Technology Trends These technology trends will reshape the way insurance companies operate, interact with customers and mitigate risks. Read More How Blockchain Enhances Reliability, Speed Let's take a look at three options for how blockchain is transforming insurance and improving insurance services. Read More Is Blockchain Still on Track? With B3i declaring bankruptcy, will blockchain/DLT (distributed ledger technologies) ever reach the point of disrupting the industry for the better?   Read More Why Digital Titling Is Transformational Digital vehicle titling is revolutionizing auto insurance, offering same-day service and cost savings. West Virginia is setting the example. Read More FEATURED THOUGHT LEADERS Faheem Shakeel Lisa Trymbiski Abhishek Peter Alexandr Khomich Chak Kolli Bill Keogh

Did you hear that sound? It could be opportunity knocking. Despite the slowdown in merger and acquisition activity in the first part of 2023, the climate for growth in the insurance sector is promising, now and into 2024. The chance to grow or sell a business can present itself quickly, so it’s wise to be prepared. How can you be ready when opportunity comes knocking? 

Outlook for M&A in insurance

The early-year turmoil in the banking industry, due in part to rapid acceleration in interest rates since March 2022, had a cooling effect on M&A activity in the first half of 2023. Many signs, however, point to a potentially better atmosphere for deal-making. The long-predicted recession still has not occurred, inflation is cooling and mortgage interest rates have declined. In the insurance sector, deals continue to be made, even in this challenging environment. PwC describes insurance M&A activity as resilient despite macroeconomic headwinds and predicts insurance deal activity to remain very active through the remainder of the year. 

See also: Combating Healthcare Insurance Fraud

How to be ready when opportunity knocks

If expanding or selling your agency is in your future, it makes sense to prepare yourself and your business so you can act quickly if the right opportunity arises. Here are five key steps that will help you to be ready.

1. Review and reflect on what your business needs. Do you have strong producers and enough of them? Are your technology tools – and the staff who manage them – up to date? Is there an area of service you’d like to expand into but haven’t had the capacity or talent pool to handle? Having a wish list of attributes to look for, including staff with specific skill sets, will make it easier to recognize a good acquisition target.

2. Be conscious of your company culture and values. Insurance is relationship-based, so working with people who share your company’s ethics and approach to business is vital. Whether you want to acquire or sell, finding the complementary fit for current and future employees will lead to a more successful transition. 

3. Have your house in order. Nothing can sink a deal faster than incomplete or inaccurate financial records or problems with regulatory compliance. Lenders like to say, “Run your business every day as if you’re going to sell it.” Make sure that all records are up to date and complete, and that you’re in full compliance with all industry regulations. It will save time, money and headaches in the long run.

4. Maintain a strong cash position. In insurance deals, the majority of the valuation in a deal is cash flow, rather than physical assets. If you’re a seller, being able to demonstrate a strong and predictable cash flow makes your business an inviting target for acquisition. If you’re looking to buy, being in a liquid position can help facilitate a deal quickly.

5. Stay in close contact with your lender. It’s never too early to let your lender know you are looking for opportunities to buy or sell, even if you don’t have a specific deal identified. Your lender can help you get a general deal structure in place so you can respond quickly when a potential acquisition target becomes available. Setting up a structure also reduces the chance of surprises arising that could derail the deal.

If you’re intending to sell, especially as part of an internal succession plan, you may need to hold some of the debt. Lenders can help put together the bones of a deal that can be fleshed out over time as your plans become more definite. The length of time a deal takes is almost always up to the borrower and how quickly they respond to requests for information and documentation. Communication is critical.

While market forces – unemployment, inflation, the possibility of recession and interest rates – are always uncertain, opportunities for growth are always available. The temporary slowdown in M&A deals of the past several months means there is capital out there waiting to be deployed.

Whether you’re looking to buy, sell or facilitate succession, following management best practices and staying in close communication with your lending partner will help you meet opportunity when it comes knocking.

Whether the sport is football, soccer, basketball or even eSports, all have one thing in common — they require insurance. 

While policies for participants need to be considered separately from the policies for the teams and the leagues, in the end, nearly every aspect of sport is insurable. Some policies are straightforward. Some policies are unique to sports. And some policies are becoming harder to find. 

Business of Sports 

While the on-field activities get most of the attention, an army of professionals works behind the scenes to conduct the business of sports. All of those business tasks must be insured as they would be for any other business. 

These policies begin with the team’s general liability and umbrella policies. These cover the team if someone gets hurt on team property, at a game or during an event.

One high-profile case came up earlier this year when a New England Patriots fan died in the stands after getting punched by an opposing team’s fan.  

It looks like the initial autopsy is showing that the punch was not what caused the death. But say it did. In a case like this, it is easy to imagine the stadium being on the hook for a lawsuit. Lawyers would almost certainly claim that the venue didn’t provide enough security or oversight, or that one of the people involved in the fight was overserved alcohol. 

The general liability policy would likely pay up to defend the case and potentially pay any eventual settlement or judgment. 

The front office also has to buy the other policies any other business would, such as health insurance for the coaches and business staff, (but typically not the players). The same goes for workers' compensation. 

Teams and venues also carry property insurance in case something like a hurricane rips the roof of a stadium. 

And in that case, the team’s business interruption insurance would kick in and help the team relocate and help them find another venue to play in while the home venue is being repaired. Insurance might also cover the inevitable loss of income between what could be earned at a home stadium and the adopted home. 

Post-COVID, these business interruption policies typically have exclusions for infectious diseases. 

Players' Health Insurance

On the players' side, the health insurance policies tend to be collectively bargained, so the players have a separate policy from the rest of the organization. Every player in the league would have the same health insurance, and when they change teams, they stay under the same program.

Workers’ compensation is also complicated for players. Because they are technically working when they are playing, there needs to be a policy in case they are injured on the job. There are very few workers’ compensation policies willing to take on the risk of player injury, meaning, in most leagues, the policy is negotiated and purchased leaguewide. 

Players’ Salary Insurance 

One of the policies that is perhaps unique to sports centers on players’ salaries. 

Each league approaches these policies differently based on their collective bargaining agreements. 

For example, in the NBA and NHL, player contracts are guaranteed. If a player sustains a career-ending injury a week after signing a 10-year contract, the player is still paid a full salary for the duration of the contract.

In these cases, teams can get disability policies for players. They come with big deductibles and really only cover the team in the event of a season- or career-ending injury. They are also expensive, so teams don’t insure everyone on their payroll — just the top players. 

The NFL is a little different because their collective bargaining agreement lets teams cut players before the end of their contract. Many contracts have a certain portion guaranteed, but outside of that, if a team cuts someone a year into a five-year contract, the remaining four years don’t have to be paid out.

Subsequently, not many NFL teams insure contracts outside of unusually large guarantees or signing bonuses. 

Specialized Disability Insurance

When it comes to specialized cases, there are disability policies covering an athlete’s dominant arm or legs, for example. 

These policies are typically custom-written by large insurance syndicates.  

The cost and availability for these specialized policies really depend on the athlete, their income, their sport and any pre-existing conditions and inherent risks they face, said Mark Di Perno, president of Sportunderwriters.com. 

Players can also protect themselves from off-field injuries through so-called 24-hour disability policies. These would protect the athlete if they were injured outside a sporting event, such as during a ski trip. 

In sports such as the NFL, individual athletes often purchase policies to protect themselves in case they are hurt and their team cuts them rather than paying out the remainder of their contract. 

Women-Focused Coverage

Women playing professional sports face a unique set of challenges, which at least one insurer has developed a policy to address. 

Willis Towers Watson has introduced their women in sports coverage, which evolved from the existing professional sports policies but was tailored to meet the demands and needs of women. 

These policies offer additional benefits, including for pregnancy complications that stem from an accident due to training or playing, as well as a post-partum benefit to aid the player in returning to their profession, said Tiffany Peña Santos, senior associate, accident and health broker for WTW. 

The women-focused plans also include mental health support, including post- and pre-natal depression, and a benefit that helps women retrain in another field of work if they have a career-ending injury. 

The polices even offer assistance with childcare expenses. 

“We can’t forget the fact that there is a large pay gap in the sports industry,” Peña Santos said. “Elite male footballers, for example, would be unlikely to have childcare bursary included in their insurance policies, whereas elite female footballers may need this to get back on the pitch.”

2024 and beyond

The hottest issue facing sports insurance right now seems to be head injuries. 

There have been thousands of lawsuits filed regarding concussions and traumatic brain injuries in nearly every contact sport. 

In the highest-profile case to date, the NFL settled a class action lawsuit for more than $1 billion in 2013, which many in the industry believe marks more of a harbinger of things to come than it does the end of an issue. 

Subsequently, many insurers are either not quoting policies or they are including a traumatic brain injury exclusion or coverage limitation. 

There are still a handful of policies available with exposure to head injuries, but many experts have wondered out loud whether the industry can sustain the long tail of claims coming from these costly payouts. And without insurance for head injuries, many wonder what the future for contact sports could hold.

KEY TAKEAWAYS:

--Generative AI can improve auto insurers' claims processes, optimize customer interactions and recommend plan changes. 

--Some companies are slow to adopt because of inaccuracies and bias issues, privacy challenges, intellectual property concerns and heightened regulatory scrutiny.

--Like any new technology, generative AI needs effective guardrails. Once the right procedures are in place, it can provide value across the customer lifecycle for auto insurance companies.  

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As an insurance professional, you’ve likely watched the rise of generative AI. But has your employer taken advantage of generative AI yet? If not, maybe they should be.

Although auto insurance professionals have used AI for decades — particularly in the form of machine learning and predictive modeling — generative AI is a new frontier. By creating original content using patterns from existing data sources, generative AI tools like ChatGPT and Bard offer endless applications for auto insurance professionals. Used effectively, generative AI tools can help auto insurers create highly personalized programs that cater to customers’ unique needs, building stronger relationships and increasing efficiency in the handling of common tasks.

But as with other emerging technology solutions, adoption of generative AI isn’t a linear path. 

The concerns about potential inaccuracies and imaginative limitations in using these tools are causing decision-makers at auto insurance companies to hesitate to fully embrace the technology.

Ultimately, ChatGPT is like a driver-assisted autonomous vehicle. It requires a driver willing to invest in its possibilities of efficiency and personalization, unafraid to sit at the forefront of technology innovation. At the same time, however, these tools also require a driver who is prepared to assess outputs and intervene when necessary — a human at the wheel of a new technology always performs better than the technology on its own. 

Why generative AI is worth your effort: Optimizing the customer lifecycle 

So far, auto insurance companies have only scratched the surface of generative AI’s potential. Even industry leaders that have already started using generative AI can benefit from being more open-minded and creative about how they can use technology to improve future operations. 

For example, generative AI tools can create automation and back office efficiencies by summarizing and synthesizing common insurance content and data. You can use these capabilities to speed up marketing content delivery, code generation, training and other documentation resources.

However, generative AI’s true power lies in its ability to deliver value to your customers — helping improve your customer experience, as well as your acquisition and retention metrics. 

When you layer generative AI into your customer interactions, you can: 

1. Improve claims processes: Generative AI can streamline your customer claims process by extracting and categorizing information from claim documents and other data sources, such as driving data before and after a crash. While this process might require customized generative AI models, the investment can be worthwhile because of the volumes of unstructured claims data insurance adjusters must manually organize. Beyond organizing this claim information more quickly and effectively, you can also use generative AI to personalize messages based on the claims information customers provide. This is a win-win: The technology improves the customer experience, reduces the claims adjudication cycle time and enhances your brand reputation.
2. Optimize customer service interactions: By combining a generative AI virtual assistant with insights about your drivers, you enable more personalized, efficient customer interactions. For example, a generative AI chatbot can automate contact center interactions based on information about your customers’ needs, driving behavior and coverage, providing customers with relevant, personalized answers and information — and saving you time. 
3. Recommend plan coverages: Coverage selection can be an overwhelming experience for auto insurance shoppers. Generative AI helps you analyze customer information and driving data to generate personalized insurance policy recommendations and accelerate the selling process with increased bind rates. The result? You simplify shopping experiences and allow consumers to pay for what they need, using generative AI to personalize suggestions with a customer’s unique needs, lifestyle and risk profile at the center.

While these are three prominent use cases, there are many more applications of generative AI, including risk assessment, fraud detection, trend prediction and modeling. 

What’s preventing auto insurance companies from fully embracing generative AI? 

If generative AI boasts these benefits for auto insurers, why has industry adoption been slow?

Risk aversion, regulatory issues, competing priorities and the novelty of generative AI have all prevented auto insurance companies from incorporating generative AI solutions in their marketing, claims and sales efforts. For starters, a lack of understanding among decision-makers and an absence of in-house generative AI expertise may prevent many businesses from taking advantage of the technology. 

And like many other white-collar workers, auto insurer employees may worry about losing their jobs to automation. As a result, they may hesitate to rely on generative AI solutions. It’s important to remember that generative AI tools are still nascent technology. So, it’s understandable that auto insurance employees are risk averse toward the technology and haven’t yet taken advantage of it in their work. At the same time, it’s important to remember that AI can augment an employee’s tasks without fully replacing their entire position — these technologies need a human at the wheel. 

Leadership teams at auto insurance companies must be prepared to address the concerns that have arisen around the use of generative AI tools. Although one in six Americans have used generative AI, most view AI unfavorably, leading to the distrust of tools like ChatGPT. Some of the skepticism about generative AI in insurance is justified because it can introduce biases, inaccuracies ,and security risks. Commonly cited risks include:

• Inaccuracy, ethics and bias issues: Generative AI models are only as accurate as the data they’ve been trained on and some can “hallucinate” inaccurate information. Left unchecked, generative AI models may reference and even propagate offensive and controversial content. As state legislatures move to ban the use of credit-based scoring algorithms and auto insurers work to combat bias in the quoting process, decision-makers at auto insurance companies will need to remain vigilant about this tendency when bringing on generative AI solutions, offering clear guidelines and best practices to employees. 
• Privacy, security and confidentiality challenges: Your generative AI technology vendor may store user data after intake, which can lead to hacks, leaked information or personal details accidentally being made public. This presents a risk to auto insurance companies that hold sensitive personal data about drivers.
• Intellectual property concerns: Generative AI tools may produce computer code and other work not protectable by your existing IP rights, such as copyrights and patents. 
• Heightened regulatory scrutiny: As more auto insurance companies take advantage of AI, the NAIC is monitoring its usage and considering regulations. 

These risks may sound overwhelming at first. However, delaying adoption can increase distrust and cause businesses to fall further behind. Companies that shy away from generative AI tools now might trail competitors using these tools to reduce expenses and improve customer experiences. So it’s best for leadership teams at auto insurance companies to focus on adapting to these tools now by investing in reskilling and retraining while setting up the right guardrails and security measures.

Take full advantage of AI with a governance strategy

To address generative AI concerns and take advantage of its benefits, your organization can start small with clear guardrails and then adopt and mature a governance strategy. From there, you can monitor regulatory changes, collect employee and customer feedback and use any early learnings to inform and shape your strategy over time. 

Regardless of your strategy, human involvement and oversight are critical as your organization adopts generative AI. Your teams should carefully review inputs and outputs for accuracy, fairness and bias. You’re more likely to generate usable results from a generative AI tool if the input is accurate — like real driving data — or if your data is peer-validated. While it might be easier said than done given the potential scope of inputs and outputs found across insurance spaces, it’s worth the effort.

Likewise, when consumers know exactly how and when their data is being used and how it benefits them, carriers can more effectively use data to create personalized auto insurance programs. Transparency around data usage and human involvement in generative AI benefits everyone involved. 

The takeaway: Like any new technology, generative AI needs effective guardrails. Once the right procedures are in place, it can provide value across the customer lifecycle for auto insurance companies. 

With these wheels, generative AI gets you where you want to go

Your imagination is the limit when it comes to generative AI, which can be both an opportunity and a hindrance. 

If your business opts to invest in generative AI, you have the power to define how to responsibly use generative AI tools to improve experiences for your customers, provide increased business value and offer more efficient processes to employees. But the process starts with making sure you have the right inputs, like accurate and timely driving data, and ensuring you have guardrails in place.

Dream big and make sure a driver is always behind the wheel of your generative AI technology.

While Scott Van Pelt opens his version of "SportsCenter" on ESPN with "The Best Thing I Saw Today," I can't limit myself to just one thing here. I've seen a whole bunch of smart things over the past week that I'd like to share as a sort of grab bag. 

Several relate to AI -- even though we all feel like we're inundated with news about the field. The one that could be most important for insurance concerns what may be a breakthrough in how we forecast major storms -- three models based on a new approach were extremely accurate in forecasting the path of Hurricane Lee in mid-September, beginning when the storm was thousands of miles from North America. 

As the Washington Post reported, "The models are orders of magnitude faster and cheaper to operate than conventional, government-run weather models. While AI models don’t yet provide all the capabilities needed for operational forecasting, their emergence portends a potential sea change in how weather forecasts are made."

Let's have a look. 

The new models take me back to the late 1980s and into the 1990s, when "expert systems" were the cutting edge in AI. The basic idea was that you find an expert and build a system around that person's (or those persons') expertise. You ask or observe how that stock trader, or plant operator or whomever made decisions in as many circumstances as you could imagine, then build software that would make those same decisions in those same circumstances. The problem was that you could never imagine all the circumstances or draw all the expertise out of the person, who often had developed gut instincts over time that they'd act on in, say, a stock market crash but that they wouldn't know how to articulate ahead of time. So the limits of so-called rules-based systems became clear.

The breakthrough came when computing power became so plentiful that AIs could be turned loose to simulate a nearly unlimited set of possibilities and to see what responses were optimal. This simulation approach is what has led, for instance, to the AIs that have defeated the world's best Go players. The initial AI was a bit of a hybrid -- it built on a base of human expertise. That was then surpassed by an AI that was simply given the rules of the game and learned by playing billions of games against itself. That, in turn, has now been surpassed by an AI that started without even being given the rules as it started its simulations.

Go players talk with reverence about Move 37 in game two of a series that an AI, AlphaGo, played against Lee Sedol, a top-ranked player, in a series that the AI won 4-1. The AI's move went against all the precepts of Go that have been taught for centuries but, analysis now shows, was brilliant.

The switch from expert systems to endless simulations and machine learning is, very roughly speaking, the change that may be beginning with weather forecasting for major storms.

At the moment, the two main approaches -- one developed in Europe, one in the U.S. -- operate based on data and knowledge that has been collected and developed over decades and that has been turned into extremely elaborate models. A supercomputer needs perhaps an hour (and a lot of electricity) to conduct trillions of calculations and turn those formulas into a forecast about the path and intensity of a hurricane.

The new models -- produced by Google, Microsoft, Nvidia, Huawei and a number of startups -- start with the extensive data on weather conditions that are collected for the supercomputer-based models but ignore all the formulas that the supercomputers then use to generate forecasts. The new models are built on deep analysis of decades of prior weather data and, based on the patterns discerned, can produce a forecast on a desktop computer in a minute, or even seconds.

In the case of Hurricane Lee, the new models accurately predicted on Sept. 10 that it would make landfall in Nova Scotia six days later and were ahead of the established models in suggesting that the hurricane might travel close enough to Cape Cod to produce severe weather. 

The hope is that the speed and low cost of operating the new models will also allow for what are called ensemble forecasts. The new models could be used to generate a whole series of forecasts based on slight variations in the weather data it's fed -- which can be imprecise -- and generate a range of forecasts that would provide a more robust look at how a storm might behave. 

"Ensemble forecasts from conventional models can miss extreme events, such as excessive rainfall or heat, because they are limited to about 50 simulations due to the time and cost of generating them," the Washington Post article said. "AI could enable the generation of much larger ensembles in as little as a few minutes, potentially leading to more useful forecasts and risk assessments for emergency managers, the general public and numerous industries.

"'Our hypothesis is we can easily now scale up with AI models to thousands or tens of thousands of ensemble members,' Anima Anandkumar, senior director of AI Research at Nvidia, said in an interview."

Given the normal trajectory of technology, I can imagine this new sort of model moving from hurricanes to other sorts of severe storms, including tornados and derechos, which have historically been less predictable. In time, I could even imagine these models being used to warn of the sorts of severe thunderstorms that dumped 25 inches of rain on Ft. Lauderdale in April and that hit the New York City area with as much as 10 inches of rain last week. This sort of severe storm is a relatively new phenomenon, apparently related to high temperatures in nearby ocean waters, but AI could well recognize the signs that what looks like a routine thunderstorm could actually last for many hours.

One storm obviously doesn't prove anything about the new models, but they're off to a good start, and AI tends to improve rapidly once it gets its arms -- brain? -- around something. Any improvement in forecasting does, of course, increase the odds that people can protect themselves and their property, assisted by their insurers.

That explanation took longer than I expected, but let's still get to the other smart things that caught my eye in the past week:

--The clearest example I've yet seen of ROI from generative AI, from an interview in Fortune with Erik Brynjolfsson: 

"In a study that colleagues and I conducted, a company with a call center did a phased rollout of a large language model—generative AI—that gave suggestions to some of the workers [as they responded to callers], but not to others. So we got a kind of controlled experiment. The people who had access to the technology were dramatically more productive. It was about 14% on average, but the least experienced workers were about 35% more productive within just a couple of months: a big, big change.... Customer satisfaction dramatically improved.... The employees seemed happy. They were less likely to quit—much less turnover."

--A smart framework for thinking about investments in generative AI, from my longtime friend and colleague Tim Andrews. He says we are still in the Institutional phase of his i3 model, characterized "by the need to go to large institutions for access." Next will come the Individual phase, when "the technology is affordable but not cheap and generally requires some expertise to install and maintain it." Finally, there will be the Invisible stage, where "the technology disappears from view and becomes embedded in just about everything possible....Interest in the technology itself wanes, except when broken or missing....  A lost internet connection is painful because of the interruption of a video call or streaming movie, not because of the underlying internet technology." 

--A mind-boggling stat on the homeowners' insurance crisis, suggesting that we have a long way to go before it's resolved:

"First Street estimates that 39 million U.S. homes are insured at artificially suppressed prices compared with the risk they actually face."

--Five myths about customer loyalty, from Jon Picoult, one of my go-to's on the topic, including:

"Myth #1: Satisfied customers are loyal customers.

"Satisfied customers defect all the time. In a widely cited customer experience study, Gartner found that 20% of customers who said they were satisfied with a particular company also said that they planned to shift their business to another provider. This is why customer satisfaction is really a one-way ticket to the business graveyard. To cultivate true, long-term loyalty, businesses must do more than just satisfy customers – they need to impress them, thereby cultivating the repurchase and referral behavior that is the lifeblood of any thriving company."

Cheers,

Paul

 

 

 

In today’s business landscape, time saved is money saved. Insurance companies must carefully evaluate time-consuming areas where automation can be most effectively implemented. One crucial aspect that demands attention is the billing and payment experience, as it represents one of the few touchpoints insurers have with their customers.

The adoption of paperless billing has gained popularity as a convenient and reliable way to receive communication. By digitizing bill delivery, insurance carriers can save costs associated with printing and mailing, as well as minimize time spent on manual tasks like envelope stuffing. Additionally, this shift towards digital processes contributes to reducing an organization’s environmental impact.

By leveraging these cost-effective measures, insurers can improve efficiency and optimize their financial performance. To estimate potential savings, utilize the Paperless Estimated Savings Calculator, which helps determine the cost benefits of having more policyholders receive their bills online.

Calculate Your Savings

 

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