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Why AI Can Help SMBs' Marketing

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

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Small businesses (SMBs) are a busy bunch. On any given day, they might be fulfilling orders, engaging with customers in-person, managing staff, doing their books — plus dozens of other tasks. Most would relish an opportunity to gain back an extra hour, or save some money.

Luckily, those goals (and others) are attainable thanks to artificial intelligence (AI) and marketing automation. These technologies can help small businesses, including many insurance agencies, work more efficiently, drive more sales and improve the ways they are marketing themselves – without creating more of a headache or a time suck.

We recently published a report at Constant Contact called, Small Business Now: An AI Awakening, that outlines how SMBs like insurance agencies are thinking about AI and automation, and some of the results that early adopters are seeing. With insights from nearly 500 small businesses across the U.S., the study reveals how these technologies can enhance marketing effectiveness and help SMBs save time and money. 

Here are the 10 stats:

  1. Challenge Accepted: 60% of SMBs say their biggest challenge is attracting new customers, while 39% say it’s marketing to their target audience.
  2. Piqued Interest: 74% are interested in using AI or automation in their business, and 55% reported that their interest in using these technologies grew in the first half of 2023.
  3. Off to the Races: 26% are already using AI or automation, and the top use cases are social media (52%), generative content creation (44%) and email marketing (41%).
  4. Proven Success: 91% of the small businesses polled say AI has helped make their businesses more successful.
  5. Reaping the Benefits: 60% of small businesses that currently use AI or automation in their marketing say they have saved time and are working more efficiently.
  6. First Step, Social Media: SMBs say the easiest places to start leveraging AI technology are social media, content creation and analytics.
  7. Financial Gains: 28% of SMBs expect AI and automation to save them at least $5,000 in the next year.
  8. Increasing Efficiency: 33% of small businesses estimate they have saved more than 40 minutes per week on marketing by using AI or automation.
  9. Top Concern: 44% of small businesses noted data security as their top hesitation about using AI.
  10. Value Recognition: The more SMBs use AI, the more they value it. 70% of SMBs would be willing to pay more to access AI and automation. 

See also: To LRO and Beyond: Using Generative AI to Get the Complete Picture for Businesses that Lease Space

So, what do all these stats mean? I’m glad you asked.

AI is here to stay. The small businesses that are currently using tools powered by AI overwhelmingly agree that it is making their businesses more successful. They are working more efficiently, saving money, improving customer experiences and growing quicker.

So, if you’re an SMB that is either starved for more time in your week, or you want to improve the way you engage with your customers without adding extra marketing work to your plate, don’t write off AI as a passing trend. Give it a try, and you might be surprised about the results you see.


Dave Charest

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Dave Charest

Dave Charest is the director of small business success for Constant Contact, a digital marketing and automation platform that has helped millions of small businesses and nonprofits become better marketers.

How Generative AI Changes LRO

Lessor's Risk Only (LRO) insurance carriers are benefiting in four key ways from generative AI.

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Everyone involved in selling, buying and using insurance is experiencing a challenging market. Catastrophic weather, inflation and economic conditions have made it difficult for insurers to pay claims and maintain a profit. Some have pulled out of markets, others have announced they’re not taking on new business and many are raising rates. 

There are new risks everywhere, and Lessor’s Risk Only (LRO) insurance, which provides coverage to building owners from claims from tenants, is no different. It can be challenging – for both businesses and insurers – to understand various risks associated with rental office space. Is there a restaurant renting space on the ground floor of the building? Does the foot traffic from a medical office or store raise issues? Is there a manufacturing firm on the premises?

Insurers can’t write insurance for a business if they don’t have a complete view of the risks associated with a commercial space. In fact, for businesses looking to acquire LRO coverage, a policy could end up being more expensive than it needs to be if an insurer is working from limited information. 

Enter generative AI technology. The technology offers real-time information insurers need to fully understand businesses’ risk profiles. The data not only delivers information on occupant risk factors but can be used to streamline other underwriting processes and identify business opportunities. 

Here are four ways generative AI enables insurers to improve LRO underwriting to grow business: 

1. Better insights and increased accuracy: Many insurers say they don’t always have a good understanding of the businesses occupying a building. For instance, the underwriters might be working from historical data that isn’t always up to date. Or the client might only have limited knowledge of the renters in the building and provide the agent incomplete information. 

Using generative AI and large language model technologies, insurers can get real-time insights into tenant occupancy risks. These technologies use publicly available, structured and unstructured data so insurers are working from the most current information.

Generative AI also enables insurers to continue to get insights on a property during the entire policy term. Renting is fluid and can often have significant turnover. Businesses that occupied a space at the beginning of a policy might change over the course of the coverage period. Insurers can now monitor exposures and decide if the policy needs to be updated based on new risks. 

2. Faster decisions on risks: Spending time researching a business or property to understand its risk profile is not only slow but also wasted time if the entity ends up outside of the insurer’s risk appetite. Generative AI can enable insurance organizations to pre-qualify a prospect’s risk profile in a matter of seconds, with just a business name and address. The insurer can then quickly determine next steps.

See also: Supply Chain 4.0: The Digital Transformation

3. Prospecting opportunities: When insurers use LRO to underwrite a building, they are presented with a list of current occupants. This could identify other potential prospects within that location. For example, an insurer that targets takeout restaurants might be looking at the risk associated with a takeout pizza restaurant in a strip mall. They might learn from the list of occupants that the strip mall also contains a Chinese takeout restaurant and a Mexican takeout restaurant that they currently do not cover. They can pass this information over to their sales team as a new business lead. Additionally, understanding the business exposures of nearby businesses can help insurers identify potential risks and opportunities in their existing portfolio.

4. Beyond LRO: Insights from generative AI technology can be used across commercial lines business. Better understanding of the risks associated with surrounding businesses enables insurers to more accurately identify if they want to write a particular risk in another line of business. For example, an insurer was evaluating a property for LRO risk and determined that a business in the property was outside its appetite. However, the AI solution identified that the insurer was currently writing commercial policies for three other businesses located in that property. The insurer was able to make adjustments and remove those unwanted risks from their book of business, thereby optimizing their overall portfolio and reducing exposure to potential losses. This highlights the importance of not only identifying new business opportunities but also managing and mitigating risks associated with existing policies based on insights generated by AI technology.

With more current and accurate information, insurers are better able to assess the risks. This means they have more confidence in writing policies and businesses are paying premiums that match their actual risk exposure. With generative AI technologies, insurers can overcome hurdles when underwriting LRO coverage and further use the information to grow their entire commercial book of business.


Chris Schrenk

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Chris Schrenk

Chris Schrenk is chief underwriting officer at NeuralMetrics, a provider of real-time, transparent commercial lines data intelligence for insurance classification and underwriting.

He has extensive experience in commercial insurance and collaborating with leading carriers. His specialization lies in identifying and implementing process improvements that drive automation, enhance underwriting efficiency, improve the accuracy and reduce errors.

'Data as a Product' Strategy

Thinking about your data as a product generates new revenue streams while removing the constraints of data silos. 

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In today’s dynamic risk environment and proliferating data in every walk of life, insurers are struggling to harness the data effectively. To address this data deluge and drive business value, a mindset of thinking of data as a product is a necessity.

This approach requires well-designed strategy to deliver data that consumers want. 

For some companies, the key is internal democratization of data to drive synergy and reduce the inefficiencies that data silos cause. For others, the key is to establish data stewardship and accountability for regulatory and compliance needs and to build fit-for-purpose data products (e.g., pre-fill for underwriters, risk scoring and location Intelligence).

Where to begin?

Data products are built incrementally as a minimum viable product (MVP) that is accessible via application programming interface (API), continually enriched with domain specific data and intelligence, version-controlled and governed in a federated manner. For consumers, the data product shields them from the complexity of identifying, acquiring and processing domain-driven data sources into insights for decision making.

For example, a prospective home buyer has access to data on estimated property value based on criteria such as location, square footage and property type. But many first-time home buyers face financial surprises post-purchase. Auto and home insurance premiums may increase. So may replacement costs when they need repairs. Meanwhile, homeowners may find travel times increasing because of traffic congestion.

Insurers could harness their wealth of data and expose it to customers as a data product for “improving livability.”

See also: Achieving a 'Logical Data Fabric'

How to pursue this domain-driven journey?

To pursue this journey, insurers need to organize data by domains (location, policy, claims etc.) and align their MVP to a defined purpose (e.g., improving livability).  

  • Location is the critical data domain. It breaks down into granular data attributes such as basic information, primary modifiers, secondary modifiers, spatial and hazards. Completeness is a key. 
  • The domain must be mastered via machine-learning-based models for de-duplication, anomalies etc. Enriching the data with external sources enables accuracy and trustworthiness and provides a holistic view of location and risk characteristics.
  • Location intelligence must be based on claims and additional data sets such as aerial imagery, weather, crime and hail and wind risks.
  • Federated governance should be enabled through version controls, domain ownership and cataloguing to allow discovery through meta-data.
  • The data and insights should be published through an API interface. Varied insights can be generated based on the context, such as replacement costs, safety score and protection gaps.
  • Agent apps should leverage large language models and and agent-based modeling framework to enable knowledge management and reasoning capabilities for decision making.

To sustain and make a difference

Learn from failure – Many enterprises embark on modernization journeys as a technology initiative, resulting in limited business adoption and value. The strategy must revolve around business value and adopt an iterative approach, focusing on democratizing value through product features and consumption archetypes.

A data-driven culture focuses on multi-disciplinary data product teams with business stakeholders, domain-driven use cases, a data platform to deliver and democratize access to these data products. The work must be governed and measured by key performance indicators (KPIs) and incorporate consumer feedback.


Prathap Gokul

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Prathap Gokul

Prathap Gokul is head of insurance data and analytics with the data and analytics group in TCS’s banking, financial services and insurance (BFSI) business unit.

He has over 25 years of industry experience in commercial and personal insurance, life and retirement, and corporate functions.

Embedded Insurance Is Made for SMBs

The proliferation of vertical SaaS applications for small and medium-sized firms creates openings for embedded insurance.

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KEY TAKEAWAYS:

--While SMBs have long been seen as a growth opportunity for insurers, the insurance industry simply is not built to distribute products that meet both the needs of SMBs and the objectives of underwriters. Servicing SMB accounts consumes substantial amounts of time for agents and brokers, while the data that underwriters require to make informed pricing decisions on such accounts is lacking.

--But tens of thousands of cloud-based solutions have been developed for specific industries, and insurers can embed offerings in those platforms.

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Embedded insurance is one of the fastest-growing digital distribution methods in property and casualty insurance and is forecast to reach more than $720 billion in gross written premium worldwide by 2030. There is a fundamental reason for this tremendous growth. The embedded channel is an innovative way to reach a segment that has been notoriously challenging to serve through traditional distribution.

Small and medium-size businesses (SMBs) have long been considered a high-growth market for the insurance industry, not only for the sheer number of such enterprises but also because of the diversity of industries and risk profiles that SMBs represent. Why has profitable growth in this segment been elusive? A big part of the challenge is structural. The insurance industry simply is not built to distribute products that meet both the needs of SMBs and the objectives of underwriters. Servicing SMB accounts consumes substantial amounts of time for agents and brokers, while the data that underwriters require to make informed pricing decisions on such accounts is lacking.

A “one size fits all” approach for SMBs inevitably results in greater risk and missed opportunities for the insurance industry: 40% of SMBs in the U.S. go without insurance, and 75% are materially underinsured. That means many businesses are exposed to loss and financial hardship they otherwise can mitigate, with the proper protection.

Vertical industry environment

A major step in the digital transformation of business operations is the emergence of vertical software-as-a-service (SaaS) platforms. These cloud solutions are industry-specific and designed to meet the service needs of an industry type. With tens of thousands of vertical SaaS platforms, SMBs form a large portion of their user base.

Examples of successful vertical SaaS platforms are: Toast, a point-of-sale and workflow platform designed for restaurants and the food and beverage industry; Procore, a construction management software; and Service Titan, a business platform for commercial service professionals such as plumbers and electricians. In addition, a wide variety of new vertical SaaS platforms is developing, serving industries from architecture to travel, to scrapyards and waste management, according to Bain Capital Ventures.

These platforms serving vertical industries provide an environment that supports the distribution of multiple kinds of embedded services, from digital payments to finance and, naturally, insurance. The nature of vertical SaaS platforms makes integrating third-party products and services an attractive way to enhance the platform’s customer experience – without having to become expert in providing those products and services. As a result, vertical SaaS platforms working with the right embedded partners do not need to develop their own insurance infrastructure to offer compelling coverage to their customers.

See also: 9 Keys for Embedded Insurance

Advantages of embedded insurance

Embedded insurance is a data-led, seamless integration of insurance products. This solution has numerous advantages, including:

  • Enhanced customer service. By embedding insurance in a vertical platform, users gain the convenience of accessing coverage options and can buy policies within the application or platform.
  • Expanded revenue streams. Vertical SaaS platform providers can establish new revenue streams through fees on insurance policies sold through their platforms.
  • Risk mitigation. Insurance coverage helps platform users manage risks and protect their businesses. 
  • Differentiation and competitive advantage. SaaS platforms can stand out from competitors by offering comprehensive insurance solutions that combine data and behavioral intelligence with financial protection.
  • Platform innovation. Offering embedded insurance is a way to encourage innovation in the vertical ecosystem. By identifying industry-specific risks and offering customized coverage, vertical SaaS platform providers can help customers address emerging risk needs.

The critical element in embedded insurance is the technology and data orchestration layer, which gives the vertical SaaS platform access to insurance companies and brokers for product distribution. Data supporting embedded insurance can come from multiple sources, not just the providers of the insurance products. The SaaS platform provider also can leverage its own data on customers to provide relevant, right-sized insurance products.

This makes the insurance purchase much faster and easier, resulting in a direct benefit to customers that also enhances the platform experience. When SaaS platform providers and embedded insurance partners work together to meet SMBs’ needs, all parties win.


Paul Prendergast

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Paul Prendergast

Paul Prendergast is the chief executive officer and co-founder of Kayna, an insurance infrastructure platform that enables embedded insurance.

Kayna provides the technology and data orchestration layer between carriers, brokers and any vertical SaaS platform to distribute products that are directly relevant to policyholders. Founded in 2021, Kayna operates across platforms that serve millions of people and businesses worldwide, ranging from field services, fintech and retail, to personal care and wellness. 

How to Respond at Inflection Points

At inflection points, firms tend to congratulate themselves and keep doing the same things. Wrong answer. 

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KEY TAKEAWAY:

--Whether your actions caused the hockey stick growth or whether you just got lucky, you need a new strategy that takes into account the new reality while giving yourself the space to think about your identity and what activities need to be discontinued.

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I’m fascinated by inflection points within organizations. These are periods of rapid growth or change such as technology startups go through if they manage to find product-market fit. When these companies pitch venture capitalists, they often have a chart showing “hockey stick growth,” which is another way of demonstrating an inflection point.

Line graph with data points X, Y, and Z on a table called Inflection Points

Inflection points are caused because of actions taken by an organization or because of fundamental changes in the world around them. When pandemic restrictions were imposed around the world, Peloton experienced an inflection point in demand for their product. Nothing had radically changed about their product, but a good chunk of the world couldn’t leave their houses. Peloton eventually fell back to earth, unable to sustain their good fortune once restrictions were lifted. 

In this article, I want to touch on the three ideas related to dealing with inflection points and how your organization can be better prepared for a possible future or an existing present. 

You Need a New Strategy

I’m talking to an executive of an organization that is doing really well. They have surpassed all of their growth targets within a couple of years of a five-year strategy. Putting aside the anachronistic nature of five-year strategic plans, it was obvious to me that this organization needed a new strategy altogether. 

If we use the chart above as reference, we can see that this organization formulated their strategy at point X. Their strategy had several assumptions about the future that were no longer true. Continuing on the same plan wouldn’t take into account the plethora of opportunities now available because of the inflection point. It doesn’t matter that there’s three years left, because the plan is no longer rooted to reality.

I worked with another organization that was also experiencing an inflection point. The difference was this organization knew they needed a new strategy. In a short time, they realized they needed to be stricter about their criteria for expansion and not risk overextending themselves.

When management teams face inflection points, there’s a tendency to keep doing the same things. After all, isn’t that what created the inflection in the first place?

Yes and no. It is possible that past actions directly contributed to the inflection. Think about Apple and the popularity of products like AirPods, which depended on the success of the iPhone. It is also possible that conditions in the world changed without your input. Think about airlines and the massive rebound of leisure travel that occurred after the pandemic.

Regardless of the cause of the inflection point, an organization needs to reevaluate their strategy and ensure that it still makes sense for where they want to go.

What Does Your Organization Need to Be?

There are many strategic frameworks out there, but I contend that inflection points require organizations to answer one important question. 

What does your organization need to reach point Z in the chart above?

Think about what kind of organization is needed to successfully operate in the future and then determine what decisions are congruent with that identity.

When Uber started, it faced all kinds of legal challenges. They approached the battles with a war mindset, willing to fight in every city and country around the world. There’s no denying that this identity helped them break into a monopolistic industry that had rejected technology. At some point, Uber went from underdog to established player, but it didn’t change its identity. It took the public exit of the founder and CEO for Uber to shed its hostile culture. 

See also: Cyber Insurance at Inflection Point

What needs to be discontinued?

Continual growth, especially in an inflection point, requires equally aggressive discontinuation of certain activities, products and markets.

Sears successfully moved through multiple inflections by decreasing the focus on activities that had made them highly successful in the past. While Sears made their name with their catalog and shipping products by railroad, they eventually replaced all of that with retail stores. They noticed the demographic and cultural changes—migration to urban centers, the rise of the car and the increase in consumer spending after WWII—and successfully discontinued the model that made them successful. But they failed to discontinue their stores and move to ecommerce (like Amazon). 

As you rethink your strategy, you should have a clear plan for how you will get out of specific products or markets. They may be highly profitable or politically important but the consideration has to be whether these activities will fit in your new future. Be wary of activities that consume a disproportionate amount of time and resources. 

Conclusion

Inflection points are a good problem to have, but they can quickly turn into just problems. Regardless of what caused them, organizations need a new strategy that takes into account the new reality while giving them the space to think about their identity and what activities need to be discontinued. You can ride inflections to new heights, but doing so requires careful thinking on how to survive at higher altitudes.


Ruben Ugarte

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Ruben Ugarte

Ruben Ugarte helps insurance organizations, teams and individuals make exponentially superior decisions.

He has done this across five continents, in three languages, and his ideas have helped hundreds of thousands of people. 

 

Under the Hood: Unlocking the Hidden Value in Insurance Data

Discover the secrets to P&C insurance success in the data-driven age.

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In a world where “Data is everything, and everything is data,” carriers need to leverage data better than ever before.

Every day, a staggering 2.5 quintillion bytes of data are being generated, collected, and harnessed worldwide. And 90 percent of this data, according to Forbes, has materialized in just the past two years. Meanwhile, the global insurance data market is experiencing rapid growth and is expected to reach $30 million by 2028. *

Within this data are hidden customer insights and business opportunities. But for this data to be valuable, you must be able to find the data you want when you need it. Then, turn this data into information and information into action.

But that's becoming increasingly harder due to the sheer volume and nature of data. Different kinds of data — transactional data from core business systems and the data collected through other sources (imagery, sensors, warning systems, telematics) — can be scattered throughout a business, making it challenging to marshal in a concerted way. So, while data is everywhere, the question is how do we bring it all together? How do we analyze and extract insights at scale to improve decision-making, create efficiencies, and provide better customer experiences?

In this e-book, we explore the unique data challenges P&C carriers face, how they can harness the data they have, share and leverage information internally and externally, and integrate insights into every step of the decision-making lifecycle — ultimately, optimizing efficiency, offering a better customer experience, and turning this unexcavated data into a goldmine of opportunities.

Read Now

 

Sponsored by ITL Partner: OZ Digital Consulting


ITL Partner: OZ Digital Consulting

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ITL Partner: OZ Digital Consulting

OZ is a global digital technology consultancy and software delivery and development partner founded to enable business acceleration by leveraging modern technologies I.e., Artificial Intelligence, Machine Learning, Data Analytics, Business Intelligence, Micro Services, Cloud, RPA & Intelligent Automation, Web 2.0/3.0, Azure, AWS, and many more.   

Our certified consultants bring a diverse array of backgrounds and skill sets to the table, leveraging the latest outcome-driven technologies and methodologies to address the unique, constantly evolving challenges modern businesses face. We accomplish this by supporting the digital innovation goals of our clients, keeping them ahead of the competition, optimizing profitable growth, and strategically aligning business outcomes with the technologies that drive them – all underpinned by decades of mission-critical experience and a shared culture of continuous modernization. OZ will work side by side with you to fully leverage our relationships with the world’s leading technology companies so you can reap the benefits of best-in-class implementation, integration, and automation—making the most of your technology investments and powering next-gen innovation.

Why Can't People Think Straight?

Analysis of the 49ers' loss to the Browns on Sunday provides a perfect example of a cognitive blind spot that hinders innovation.  

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I come from a long line of people who scream at the TV when our Steelers are playing. My Dad taught my siblings and me well, and I've done my fatherly duty by passing the passion along to my two daughters. When the younger one was watching a Steelers game in college, a fellow student knocked on her door, said he'd heard a lot of yelling and wanted to be sure "you guys are all okay." My daughter was watching the game by herself.

I'm proud of you, Clare.

As you might imagine, I can be a tad critical of what the announcers say. But I was especially struck by the analysis by the TV pundits following the Cleveland Browns' upset of the San Francisco 49ers on Sunday. 

The pundits praised the Browns and denigrated the 49ers as though the outcome had never been in doubt. But, but, but... the 49ers had a 41-yard field goal attempt with six seconds to go that would have won the game, and NFL kickers are about 85% successful from that distance. The Browns didn't just need a coin flip to win the game; they needed the equivalent of calling a coin flip right three times in a row. 

Yet, given how the human mind works, everything about the game was viewed by the pundits based on the fact that the 49ers' kick leaked slightly outside the right goalpost. Had that kick been a yard or so to the left, the pundits would have had a completely different interpretation -- those gritty 49ers, etc.

I don't mean to trash TV football pundits -- well, maybe a few of them... but not more than half... two-thirds at the most -- but wanted to point to the faulty analysis of the game because it demonstrates a serious cognitive bias that's baked into us humans. 

It's called survivor bias, and it's a real threat to innovation. 

As much as it hurts me to be kind to the Browns (Pittsburghers call them "the Brownies"), their defense was awesome, and they mostly outplayed the 49ers. The win also makes for a great story. The Browns were without their injured $230 million quarterback Deshaun Watson and instead started a journeyman who had been in the XFL four years ago. Yet the Browns beat a team that was generally considered to be the best in the league.

After the game, the TV pundits could only sing the praises of the Browns. For instance, former Dallas head coach Jason Garrett said on "Football Night in America": “The guys on the defensive line for Cleveland were owning the line of scrimmage.... [49er quarterback Brock Purdy] certainly came down to Earth today. Struggled with the conditions, a lot of balls were slipping out of his hands, he wasn’t accurate…he just didn’t play as we’ve seen him play to this point.”

Everything he said is true, but neither he nor any of the other analysts said anything about how lucky the Browns had to be to win the game. Even before the field goal attempt by the 49ers that gave them an 85% chance of winning, the Browns benefited from a phantom unnecessary roughness penalty on what would be their final drive of the game (a clear error demonstrated by exhaustive replay analysis). Rather than face fourth-and-10 against a ferocious defense, the Browns picked up 15 yards and a first down, on their way to the field goal that provided the 19-17 margin of victory.

Just imagine how the take on Purdy would have differed if the 49ers had made the field goal. All his struggles would have been noted, but the narrative would have been about how the second-year quarterback, the last pick in the 2022 draft, had survived a brutal challenge from the Cleveland defense. He had marched the 49ers 52 yards down the field with time running out and had set up a field goal that kept his team undefeated. Why, he might be the new Tom Brady.

Purdy for MVP! Purdy for President!

There is certainly some smart analysis in football. (Looking at you, Ryan Clark and Bill Barnwell.) And that kind of analysis needs to be brought to insurance and innovation.

Barnwell actually accomplishes a lot based on just a single, simple adjustment to win-loss records. Rather than decide that some teams have a talent for winning close games, he believes that games decided by seven points or less are essentially coin flips. So, all a team's close wins become half-wins for analytical purposes, as do close losses. Based on that adjustment, he predicted, for instance, that the Minnesota Vikings would tumble from their 13-4 record last season, because they were 9-0 in close games. Sure enough, the Vikings began this season 1-4. (Barnwell also predicted that my Steelers will have their first losing season in Mike Tomlin's 17 years as head coach, but he can be wrong sometimes... I hope.)

The problem for corporate innovation efforts is that they are typically evaluated based simply on a win-loss record, without a Bill Barnwell on ESPN explaining the sorts of other issues that should be incorporated into the analysis.

Venture capital firms are built on the idea that nine out of 10 startups fail. You just have to be sure that the one success is so big that it covers for the others. In corporations, though, the people who keep moving up the corporate ladder are the ones with the unbroken string of wins, so the strivers don't want a one-in-10 chance of major success. They want a 10-in-10 chance of success, even if that success is small.

That's why, I believe, telematics adoption in cars is still so low even though its potential has been apparent for decades -- I, personally, first wrote about the technology almost 25 years ago -- and even though Progressive introduced its Snapshot capability 15 years ago. This need for guaranteed success is why take-up of the IoT has been so cautious, why companies are being so careful about the switch from the traditional "repair and replace" approach in insurance to a "predict & prevent" model, why so many companies are talking about the potential for generative AI but so few in insurance are actually exploring it in any significant way. 

Guarantees of small successes don't lead to breakthroughs.

The survivor bias is hard to shake, though. The first time I encountered it was in a great book on risk that talked about a ship full of Romans who were caught in a storm that was about to sink them but who prayed to the gods and survived. No one ever heard from the Romans who prayed to the gods and drowned, so how could anyone dispute the claims that the gods saved that one ship?

A very smart friend of mine once wrote a book about self-made billionaires and reported that they tended to be single-minded and made big bets. Great, but what about all the folks who were single-minded, made big bets and lost those bets? You could do a book about the benefits of buying lottery tickets if you just interview the winners.

We all fall victim to the sense that rich people must be smart. How else did they become so successful? But I've interviewed more billionaires than I can count and... hmmm. Lots are very impressive, but plenty just aren't. And I've interviewed loads of people who didn't make it big who struck me as much smarter than most of the billionaires -- such as the fellow who invented the iPad (but before the technology was quite ready) and launched an early form of eBay (but took ownership of the goods being auctioned, rather than just facilitating the exchange between private parties).

The survivor bias has even reared its head in academic research and has required corrective action. Papers on, say, the potential for new drugs get published when they find a statistically significant benefit, which generally means at least 95% likelihood. But research that doesn't find the desired result tends to not be published. Non-results are boring. So those reading the academic research see the survivors -- the studies that are 19 out of 20 certain of a positive link -- but not the potentially many other studies that found no link.

Government sponsors are increasingly requiring that all research be published, whether or not it produced an exciting result. And that sort of discipline needs to be brought to business.

Yes, those who have a sterling record of success might well be CEO material. But how big were their successes? Did they take any actual risks? What about the noble failures, the people who did take big risks and failed through no fault of their own? 

If we can get away from the survivor bias that people who succeed must be winners and can focus on rewarding noble efforts, we'll be much less cautious and more innovative as an industry.

Go, Steelers.

Paul

P.S. If you must know, my pet peeve with TV football analysts is their years-long claim that a receiver catching a 50-yard pass by outleaping a defender grabbed the ball "at its highest point." Paying even the slightest attention to physics, it's obvious that the ball reached its highest point when it was halfway to the receiver -- 25 yards or so upfield. At that point, the ball was 40 feet or more above the ground. While NFL players are exceptionally impressive athletes, no, it isn't possible for someone to catch a ball at its highest point, 40 feet or more in the air.

After years of my yelling at the TV, most announcers have changed their terminology and say a receiver "high-pointed" the ball when he makes a leaping catch on a long pass over a defender. That terminology doesn't make a lot of sense, but at least it's an improvement over grabbing "at the highest point."

Next, we'll get announcers to stop talking about "negative yardage" when they mean a loss and "positive yardage" when they mean a gain.

Here's hoping.

Go, Steelers. 

Redefining Insurance: Embracing AI, Data, and Innovation Beyond Policies

In this Future of Risk Forecast, Jim Jones shares his view of how technology is transforming insurance, and how he prepares students to succeed in this new landscape.

Jim Jones The Future of Risk Forecast

 

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Jim Jones is the Executive Director of the Katie School of Insurance and Risk Management at Illinois State University. The Katie School supports over 500 students majoring in risk management and insurance, actuarial science, and other majors who are interested in careers in insurance. He works with Katie School staff, the Dean of the College of Business, industry executives, departments chairs, and faculty in helping to develop talent for industry. Jones is Chair of the CPCU Society Ethics Committee.


Insurance Thought Leadership:

What technology now in the market do you believe will have the biggest transformative impact on insurance and risk management in the next 5 years?

Jim Jones:

All of the technologies that are helpful in predicting and preventing losses. The industry will need to distinguish itself by providing value for customers in doing more than just providing insurance policies. This could be smart IoT for homes, wearables to reduce worker injuries, or AI to help insureds better identify loss trends.

Insurance Thought Leadership:

What do you see as the biggest obstacles to insurance innovation, and how would you recommend overcoming them?

Jones:

Status quo bias is always the biggest obstacle. Past success has always been the greatest impediment to future innovation. Regulatory rigidity also is a real challenge to innovation, but can be overcome to some extent through regulatory sandboxes and the use of synthetic data to predict how innovations will impact customers.

Insurance Thought Leadership:

What is an area (or areas) that you believe remains untapped/unfulfilled/overlooked for the promise of innovation in insurance?

Jones:

The creation of a database of curated data that can be used by AI. Industry and regulators will be more comfortable with the AI recommendations if they know the data is accurate and valid.

Insurance Thought Leadership:

How do you believe AI will transform insurance and/or risk management?

Jones:

AI will transform every aspect of insurance, claims, underwriting, and distribution. I think professionals in the future will have limited careers if they do not understand how to leverage AI in their jobs.

Insurance Thought Leadership:

Have your programs changed or expanded to prepare tomorrow’s insurance and risk management professionals for working in new ways with technology and data?

Jones:

Yes, we have workshops and student research with real world clients in order for them to keep up to speed with changing technology and risk landscape.

Insurance Thought Leadership:

Has the wider application of technology in insurance changed how students view opportunities in the insurance industry?

Jones:

Once they see the opportunities, we have a much more diverse pool of talent interested in insurance. Insurance already has so much data and that is appealing to students who want to work with and analyze data. Other technology oriented students see the opportunity for technology in insurance related to AI and to cybersecurity.


Insurance Thought Leadership

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Insurance Thought Leadership

Insurance Thought Leadership (ITL) delivers engaging, informative articles from our global network of thought leaders and decision makers. Their insights are transforming the insurance and risk management marketplace through knowledge sharing, big ideas on a wide variety of topics, and lessons learned through real-life applications of innovative technology.

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Cybersecurity Turns Attention to IoT

While the focus has been on IT infrastructure, insurers and clients are realizing the IoT creates the biggest attack surface for hackers.

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The nature of business risk has changed dramatically as cybersecurity attacks increase in volume, velocity and effectiveness. Data breaches have emerged as a new category of threat that can have catastrophic effects on a business of any size, and the growth of massive botnet armies controlled by threat actors signals that the attackers are becoming more powerful.

Cyber defenses have evolved in tandem, producing increasingly sophisticated solutions for the vast scale of threats organizations encounter as an inevitable result of leveraging the networking and computing infrastructure they need to compete in the modern business environment. Naturally, insurers began to develop processes and structure to serve their traditional role in guarding against this risk, but that development hasn’t proceeded smoothly. 

In recent years, to comprehend the scale of their liability compared with the policyholders’ ability to protect themselves, insurers implemented standards and policy exclusions that require organizations to do far more to secure their attack surface than ever before. If they can’t, these organizations face severe threats on two fronts: the inability to effectively guard against first-order threats to their system as well as the inability to take advantage of the appropriate financial tools to limit the resulting damage.

While these threats present a short-term challenge for many companies, they also reveal an opportunity for the medium and long term. Organizations that build a safe and insurable cybersecurity posture will be better positioned for growth than companies that choose not to invest in those tools and processes. Even if the organization chooses to self-insure, having insurance-worthy cyber hygiene measures in place can reduce potential damage.

Many organizations recognize the need to improve their security: According to market research firm Market.US, the global cloud security market is valued at $20.54 billion in 2023 and is projected to grow to nearly $150 billion by 2032.

Most of the focus is on IT infrastructure. But for many organizations today, the most efficient way to build a safe and insurable cybersecurity posture is to focus on IoT (internet of things) security.

See also: A New Approach to Cyber ​​Resilience

Why IoT?

IoT devices function differently than traditional IT computer systems. IoT devices have agents placed on them (the typical way IT systems are patched) and, until recently, could only be updated manually. Most organizations with IoT systems benefit by using them at scale – think of factory systems, transportation and logistics and automation systems that can physically exist anywhere (not just in datacenters). The devices must work as a team.

Naturally, this volume and sprawl makes manual updates prohibitively burdensome. As a result, more organizations than not are left with vulnerable, unpatched, out-of-date firmware on thousands of network-connected devices. This dynamic also produces a suboptimal organizational dynamic: Because devices need to be maintained manually on-site, they often fall under the authority of on-site teams rather than IT security experts. As a result, IoT networks generate the largest unsecured attack surface for most organizations. Any responsible approach to business risk will involve securing it. 

Why now?

In recent years, there have been high-profile disputes between insurers and their policyholders who filed claims on data breaches and other cybersecurity incidents, and it’s clear that insurers are recalibrating their approach to cyber risk. They are implementing far stricter requirements to qualify for coverage, and an organization effectively must accept the insurer's security requirements as mandates.

The best way for organizations to approach this shifting climate is to work with their insurer so there is a two-way flow of information and the terms of the policy can be customized to the specific business. This helps the insurer understand both the technical and business realities, and through that collaboration, organizations will gain insight into how regulations will develop over time. At the same time, organizations themselves must evolve and take a leadership role when securing their own systems to minimize their cyber insurance premiums.

See also: Cyber Insurance at Inflection Point

How to build a safe and insurable cybersecurity posture

An efficient ecosystem of asset and application discovery tools that leverage automation has delivered IT security teams the capacity to find threats faster than ever. However, because of their distinct technical properties, IoT networks have remained largely untouched by these advancements. At best, teams have been able to mitigate threats (e.g. through port blocking), but to move to true remediation requires a focus on both automation and scale.   

Organizations, first of all, must take advantage of the latest technology to secure their most vulnerable attack surfaces. For most organizations, this is IoT networks. Specifically, this means deploying agentless solutions that can support all types of IoT devices while managing the relationship among all devices and apps, along with their interaction with the broader network. IoT systems must be visible, operational and secure – no longer simply functional.  

Organizations must also change how they approach resolving potential threats, which for IoT are increasing in both volume and velocity. Until now, the focus for most security teams has been on mitigation, or limiting the damage after an attack. In the best case, teams limit the potential for an attacker to use a particular vulnerability. In other words, security limits the potential damage but does not eliminate the threat.

This approach, while eminently understandable considering the scale of modern threat environments, is outdated. Organizations now have the tools to remediate the threat and bring systems back to full operational status. 

Pairing discovery solutions with remediation solutions is an indispensable step toward establishing the cybersecurity posture necessary to do business efficiently and profitably in the modern threat environment. Naturally, companies should prioritize their most vulnerable attack surfaces – in many cases, IoT systems.

As recent CISA directives have shown, along with high-profile breaches from IoT entry points, visibility and security of IoT devices in tandem with all cloud assets must be a top priority for all businesses.

Organizations should develop collaborative relationships with their insurers to ensure that their underwriters have the appropriate level of knowledge and understanding of the landscape as well as how it evolves in real time. At the same time, they must accelerate investments in automation to bring all potential weak points, especially IoT, up to a standard of capability and resiliency that all stakeholders from the boardroom to insurers to the security team itself can feel confident about.

In this way, organizations that take advantage of the latest security technologies, especially as they relate to IoT, will be poised to grow unencumbered by the weight of unsecure, invisible networks accumulating risk as time goes on. 


Bud Broomhead

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Bud Broomhead

Bud Broomhead is the CEO of Viakoo, a leader in IoT device remediation.

He is a serial entrepreneur who has led successful software and storage companies for more than two decades. He has experience delivering computational and storage platforms to the physical security space for over seven years, with an emphasis on infrastructure solutions for video surveillance.

Unlocking the Power of Digital Payments

Agencies can take the fear out of digitizing payments through C.A.R.D., which stands for Collect, Apply, Reconcile and Disburse.

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Paper checks are a thing of the past. This was a shift many industries were starting to see prior to 2020, but the switch to digital payments really picked up speed during the pandemic when many consumers saw exchanging cash and checks as an unsafe option. According to McKinsey, nine in 10 people have begun using a form of digital payment since the start of the pandemic. 

Businesses have been forced to adapt. Insurance, unfortunately, was slow to join the digital payment revolution. Despite the high operational overhead that comes with collecting check payments, the pain of change and lack of core functionality and integration with accounting systems inhibit many agencies. Sometimes, the roadblock to adoption is simply not understanding how the technology works.

Fortunately, there’s an easy way to take the fear out of digital payments: C.A.R.D., which stands for Collect, Apply, Reconcile and Disburse. Using this framework to break down the collection process can help agents better understand what happens at each stage of the payment journey and feel more comfortable going digital.

Collect: Improve customer experience with more choices

The “Collect” phase covers the invoicing and billing portion of the payment process, focusing on the channel, payment choice and communication notifications. This part of the payment cycle delivers a better customer experience by offering choices and simple experiences, something consumers have come to expect in today’s online world. 

For example, insureds can pay their premiums through various channels, such as custom payment links, portals or unique payment pages, all of which allow insureds to pay much more quickly than they could when writing and mailing a paper check. Using these types of payment channels also cuts back on data input, reducing the risk of errors that come with manual entry while also keeping the data secure and only visible to those with permission to see it. Additionally, insureds are given a choice of payment methods that include ACH and major credit cards, many of which offer next-day funding – a win for both agents and customers! 

A digital payments solution also provides multiple communication channels between an agent and their insureds. Payment prompts and copies of receipts can be sent through emails or SMS text messages, creating a digital paper trail. 

See also: First Steps to Digital Payments Processes

Apply: Reduce errors with automatic credits to debits

After a client makes a payment, it must be credited appropriately. It can either be left on the client’s account or added to a specific policy or invoice. This is where “Apply” comes in. When using a digital payments solution, agents still have the option to manually apply these credits, or the solution can auto-apply those credits to debits.

Not only does automating the crediting process save agency staff time, but it significantly reduces the risk of errors, while improving security and compliance. Handling paper checks risks exposing client payment details such as bank account numbers and personal identification information. Using a digital payments solution allows the agency to create unique security and user permissions for its staff, ensuring they only have visibility to the accounts and payments pertinent to their role. Agencies and customers alike can take comfort in knowing sensitive information is safe and secure. 

An additional benefit of automating the “Apply” stage of the payment process is digitizing account activity. When payments are made online, account activities can be synced and tracked, making it easier to complete the audits needed to meet compliance requirements. 

Reconcile: Improve accuracy and reduce costs with auto-matching transactions

Once a payment is applied, the “Reconcile” stage begins. This is where an agency trues up the cash balances, payment deposits and management system receipts. Automating the reconciliation process creates an opportunity to auto-match and highlight payment transactions with general ledger receipts.

Automating this step is often the highest-value part of adopting digital payments for most agencies. It reduces the operational overhead needed to manually match transactions, eliminating low-value tasks and allowing staff to focus on new and renewal business servicing. It also improves accuracy because manual reconciliation allows for a large margin of human error that is removed when using a digital payments solution.

Disburse: Solve administrative hurdles when sending to carriers

The last stage in the digital payments journey is “Disburse,” which is where the payments are sent to the appropriate parties – typically carriers. This step may seem simple enough, but there are often obstacles when it comes to handling this step manually. Using a digital payments solution can solve administrative challenges such as storing carrier payment details more easily on files, initiating payments to appropriate entities and automating direct bill sweeps.

See also: Enhancing Claims Via Digital Payouts

A Few Things to Keep in Mind

Once an agency decides to take the plunge into digital payments, there are a few things to consider when choosing which solution is best, including:

  • Product Integration: Make sure the solution integrates natively with any existing management systems, customer portals and websites. This allows data to flow between the systems to automate the payments process.
  • Payment Choice: Agents should look into factors such as transaction volume limits, whether ACH and major credit cards are accepted, if next-day funding is allowed and if checkout pages allow insureds to choose partial payments and which invoices to pay.
  • Security and Compliance: For any payments solution to be valuable, it needs to be secure and comply with all PCI and NACHA regulatory guidelines. It should also have tokenized data, configurable security settings and capabilities to manage multi-branch/region security differences.
  • Reporting: To increase staff efficiency, agencies should consider a solution that provides real-time visibility on all payment transactions, sends real-time notifications to multiple designees, allows you to create customizable reports for actionable data and can intuitively offer insights and analytics into digital payments trends.

Starting the Digital Payments Journey
Collecting premiums shouldn’t be the hardest thing an agent does. But as with any technology update, moving to digital payments may feel overwhelming. Understanding how they work, the benefits of implementing and what to look for when choosing a solution will help agents move forward with confidence.


Chase Petrey

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Chase Petrey

Chase Petrey is the president of applied pay at Applied Systems.

He has a diverse career in the enterprise software industry, bringing with him fintech, software as a service (SaaS), and analytics skills.

Petrey also serves as president of the Salt Lake City Chapter at Silicon Slopes, a nonprofit organization that exists to empower Utah's tech community to learn, connect and serve to make entrepreneurship open and accessible to all.