KEY TAKEAWAYS:

--An obstacle to writing more small commercial insurance business is the limited data offered by small firms. The effort required to assess the risks does not always match the relatively small policy premiums.

--Enter technology, particularly the advancements in cognitive technologies and modern AI-powered data platforms. These innovations are reshaping small commercial risk assessment by enabling faster, more efficient and accurate underwriting processes.

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Small businesses account for 99.9% of all businesses in the U.S., according to Forbes. Not only is there a large pool of clients, but many are growing. Case in point: Ben & Jerry’s started as a single ice cream shop in Burlington, Vermont. 

Today, it seems no two small businesses are the same. In fact, many—including barber shops, grocery stores and restaurants—are more specialized than ever, as entrepreneurs fill specific market needs. There are restaurants that welcome dogs to dine with their owners, members-only hair salons and bars where patrons can practice ax throwing. Emerging microsegments can be lucrative opportunities for insurers. But targeting them requires fast and accurate ways to assess the risks, as well as a streamlined approach to quoting and binding policies. 

Despite their small size, many small business owners often expect the same attention and expertise large businesses receive. Small business owners want to know the insurer understands their unique risks, and they want to feel confident they have the right protection. 

But the small-business market can be a solid opportunity for insurers because specialization in niche segments can lead to becoming a provider of choice. And the more insurance companies work with businesses in specific sectors, the better they can understand in-appetite risks and nurture profitable business more quickly.

Using technology to address the micro-market

There’s significant opportunity for insurers to write more small commercial insurance business, and technology can play a key role. But one substantial obstacle is the limited data offered by small businesses, making it time-consuming to assess risks effectively. The predicament faced by many insurers and MGAs is that the effort required does not always match the relatively small policy premiums.

Enter technology, particularly the advancements in cognitive technologies and modern AI-powered data platforms. These innovations are reshaping small commercial risk assessment by enabling faster, more efficient and accurate underwriting processes. 

To transform commercial underwriting, insurers and MGAs should evaluate their existing risk assessment methods and explore how using technology for data access can augment their processes. For example, a company may already have an agile system in place to connect with and leverage API-enabled data platforms but needs to adapt workflows. Alternatively, the insurance organization might have a robust underwriting workbench solution in place but require modern technology to gain access to more data for better risk assessment. 

When selecting a data solution to enhance visibility into exposures and risk quality, speed and accuracy are both important. Speed holds particular significance in small commercial insurance, where efficient application response times can outweigh price considerations for agents/brokers and policyholders. By delivering quotes promptly, insurers and their distribution partners can deter business owners from seeking alternatives. 

See also: Emerging Tech in Commercial Lines

While speed is crucial, inaccurate information renders it useless. Emerging AI technologies are gaining popularity for risk evaluation. But these solutions may sometimes finesse answers if reliable sources cannot be located. When considering a generative AI solution, it is imperative to ensure the vendor has established processes to verify data accuracy, such as providing citations for the sources used to develop conclusions.

Additionally, insurers should seek out technology providers willing to collaborate and ensure seamless implementation. It’s best to collaborate with partners who become integral to the team, listen to feedback and adapt the solution to meet specific requirements. Establishing a strong relationship with the provider is another means to ensure accuracy in risk-quality data. Some technology companies even go the extra mile by working closely with underwriting teams, running numerous queries to assure information validity.

The small commercial insurance sector holds immense opportunities for insurers and MGAs. Not only does it offer a sizable client base, but specializing in niche markets can foster expertise, deepen market understanding and align the insurer's risk appetite accordingly. By capitalizing on cognitive technologies, insurance organizations can overcome the challenges of small commercial underwriting, swiftly generate quotes, bind policies and expand business.

KEY TAKEAWAYS:

--Among the other risk trends examined in the latest Allianz report are geopolitical, economic and market volatility and the inflationary environment (ranked #3).

--At the lower end of the risk rankings scale, but not to be underestimated, is the use of new technologies such as AI tools by professional services firms.

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Architects and engineers face greater scrutiny over building and fire safety defects. Financial services professionals may be accused of mismanaging investment funds hurt by inflation. A lawyer’s untrained use of artificial intelligence (AI) tools when preparing client cases could result in an error-ridden brief. The emerging risk landscape for professional services firms is multi-faceted.

A new report from professional indemnity insurer Allianz Global Corporate & Specialty (AGCS) finds that affected professions include management consultants, auditors, accountants, architects, engineers, solicitors and lawyers and media executives, all of whom may be held responsible for losses that arise from a perceived breach of their duties.

Although exposures vary, all these professions face a wide range of civil liability exposures that need to be addressed and mitigated. These could range from accusations of negligence or omissions resulting in harm or damage to the client, to misrepresentation, to failure to identify fraudulent activity, to the unintentional breach of contract, intellectual property rights or confidentiality and regulatory investigations and actions. 

Building safety laws and digital dangers top the heat map

Of the 11 emerging trends in the report, evolving legislation related to building safety and cyber crime, social engineering and data loss are both ranked #1 (very high – a critical impact to operations or loss severity could be expected). 

Although building safety has predominantly been a U.K. issue following the Grenfell Tower fire tragedy in 2017, some impact will be felt globally. In the U.K., extended liability periods for building and fire safety defects could bring new legal claims against manufacturers and suppliers, with a potential domino effect on all specialists in a construction project, such as architects, engineers and design and build contractors, for example.

Cyber-attacks have increased in recent years – and professional services firms are highly exposed due to the proprietary customer data and intellectual property they process or operate with.  For example, cyber mercenaries are increasingly targeting law firms to illegally obtain confidential or protected data that could tip the balance in courtrooms. These "hackers-for-hire" provide technical capabilities and deniability of involvement in the cyber-attack, should it be discovered. 

Claims drivers, which apply across all professions, include phishing and spoofing frauds, third-party supply chain risks, ransomware or malware, a lack of adequate systems or controls or data loss. Not only does a cyber breach present immediate first-party costs and disruption, it can also result in significant regulatory exposures, including action from data protection authorities and considerable fines. Litigation from affected data subjects may follow, including large group claims. Breaches may also lead to client and third-party liability claims, with claimants alleging losses due to business interruption or leaked information. A breach also carries the risk of reputational damage, resulting in stock drops and securities claims. Smaller firms can be more vulnerable as they typically have less sophisticated cyber-security.

See also: Best of Both: Bundling Parametric, Indemnity

Prepare for volatility and unexpected impacts from inflation and new tech

Among the other risk trends examined in the report are geopolitical, economic and market volatility (ranked #3 – moderate impact to operations or loss severity could be expected). The report notes that regulatory exposures can arise for professionals acting for clients who may potentially be caught by a rapidly evolving sanctions regime, while, for construction and design professionals, disruptions to supply chains could bring claims relating to project delays. 

The inflationary environment also ranks as a #3. If inflationary pressures lead to recessionary conditions, there could be a myriad of potential exposures for professionals, including insolvency-related exposures for auditors and insolvency practitioners, lenders’ claims for solicitors and valuers and claims arising from due diligence against lawyers and accountants. Outside of recessionary conditions, financial services professionals may face mismanagement and suitability allegations relating to funds hurt by high inflation.

At the lower end of the risk rankings scale, but not to be underestimated, is the use of new technologies such as AI tools by professional services firms (ranked #4 – minor impact).

While AI has the potential to operate as a risk reducer, as technological solutions evolve rapidly so do the potential claims drivers. These include data privacy or copyright issues, the need to preserve confidentiality when using service providers, risks of errors being repeated in volume work and the level of supervision involved in machine learning tasks.

Professional services firms must continue to properly train and supervise their staff as technology evolves and to ensure the authenticity of work products considering the emergence of tools such as ChatGPT. Ultimately, a lack of awareness of how generative AI works, as well as untrained use, could lead to legal sanctions and civil claims against all types of professionals.  

The full report is available here: Professional Indemnity Insurance Claims 2023.

“Parametric” is a buzzword in insurance today. 

Imagine that you have signed up for travel insurance. Your flight is delayed; instead of your reporting a claim and waiting weeks to be reimbursed, your insurance is connected to an open-data source exposing real-time flight schedules, so it automatically proceeds with the payment with no further formality. 

Same applies for corporate risks when an industrial group signs up for a hail coverage, which payment is based on the size of the hail stones. 

Is the growing buzz about parametric insurance due to its enhanced user experience (UX)? Certainly, but the appeal shouldn’t be restricted to this. 

First things first, let's set the scene with some raw figures:

(source: InsTech)

Buzz is high, but the market is still emerging. It is focused on corporate lines and natural events. 

See also: Best of Both: Bundling Parametric, Indemnity

Closing the protection gap 

Figures show that the main merit of parametric insurance is to provide answers when traditional, indemnity-based insurance demonstrates some limits. 

Parametric insurance is often proposed as a complement to an indemnity-based contract, for instance when terms and conditions exclude certain perils or assign limits or exclusions. Parametric insurance can fill those coverage gaps. 

More substantially, parametric insurance stands for a solution to protect uncovered populations or situations 

There is a continuous flow of announcements about parametric insurance about natural events in developing countries. This involves several sources of innovation:  

--It often consists of micro-insurance for farmers or small business owners who would not have access to insurance otherwise. 

--Specific distribution schemes are at work, through humanitarian/international organizations acting as sponsors, distributors or even financiers to reach fragmented markets. 

--New sources of data fuel the range of parametric products, bringing answers where indemnity-based insurance is unable to do so. 

--Satellites provide weather data used for natural events, but also for performance yield of renewable energy facilities, soil composition to determine drought conditions, 3D imagery to assess water level changes (flood), etc. 

--IoT or sensors help to monitor cargo shipping, navigability of waterways, etc. 

--Credit card transactions can determine business interruption without damage (linked to social unrests, pandemics, weather events). 

--Network transactions make downtime insurable or help with the detection of cyber attacks. 

Not to mention custom indexes built for specific parametric programs.

The list is still open and growing.

On a more general basis, parametric insurance can -- to some extent -- mitigate a lack of insurance capacity.

As a single-peril coverage, parametric insurance provides coverage that is more focused and easier to limit, compared with a comprehensive policy. (Re)insurers may have more appetite under these conditions. 

More importantly, when traditional (re)insurance capacity is shrinking, financial markets may have more appetite for insurance-linked securities (ILS) as a way to diversify their portfolio (in terms of geography or financial markets cycles). In some way, parametric insurance stands for a continued evolution initiated by Cat bonds in the '90s. 

Risk management or corporate finance? 

Parametric insurance offers another advantage that opens up wider prospects: speed of payment. 

In traditional insurance, a catastrophic event requires long filing procedures, the involvement of adjusters to determine conditions, assess losses, etc. It can take months (if not years in case of litigation), whereas parametric insurance claims triggering payment in a matter of weeks. This means much more than UX! 

Most small and medium-sized businesses don’t have cash reserves or business continuity plans to withstand catastrophic events impairing their activity. A swift payment can represent a matter of survival. Enough to justify the cost of parametric insurance. 

The same rationale applies to larger organizations, at a wider scale. A catastrophic event that is quickly compensated doesn't draw on cash reserves or require negotiating a credit facility. Parametric insurance turns out to be a tool to protect equity and reduce performance volatility. A key point for large listed companies! 

Add to this that when parametric insurance is transferred through ILS, it tends to move the insurance cursor from risk management to corporate finance, from risk manager to CFO! 

Parametric insurance is no silver bullet

Parametric is simple to explain, but designing a hail coverage, as per our above example, is not simple: 

It requires high-quality data (available, accurate, real-time), possibly certified by a third party… 

…and some work to define the actuarial link between the trigger and the loss incurred, through risk modeling and analysis of same events history. 

Basically, a poorly calibrated parametric product can lead to: 

--the trigger being reached and payout released, but no significant damage for the insured; 

--the trigger not being reached, but the insured suffered a loss. 

Parametric insurance is meant to avoid complex claims processes, adjudication costs, etc. If, in the end, adjusters or lawyers have to be involved to mitigate such cases, parametric insurance would lose part of its upside. 

In that sense, beyond its apparent simplicity, parametric insurance still requires significant education. 

What about price: Is parametric insurance cheaper? It is difficult to compare a single-peril parametric coverage cost against a comprehensive policy. Because parametric is often used to fill gaps from traditional insurance, it stands for an additional cost for sure… yet with upside. 

Finally, the parametric alternative doesn’t change a basic insurance rule: If there is no risk appetite from carriers, there is no capacity; if there is no capacity, there is no insurance, parametric or not. As simple as that!  

The primary way to mitigate this, especially for Cat events, is to ensure a proper mutualization of the portfolio. This is why pooling is increasingly used, sponsored by supranational organizations to provide more legitimacy. 

See also: Parametric Insurance: Is It the Future?

The second mitigation is about finding alternative sources of capacity to cover primary carriers. Parametric insurance can be boosted by the appetite from financial markets for high risk/high yield in a low-interest-rate environment. With increasing interest rates, will financial markets demonstrate the same appetite for ILS-shaped parametric products?

So, what is ahead of us? My views on the drivers for parametric insurance to gain traction: 

It is a data game. The development of new data sources allows parametric insurance to expand, especially beyond natural events. Parametric could become mainstream when it thrives for mainstream perils. The question is, how attractive can parametric be against indemnity insurance? The UX advantage is granted, price advantage remains to be demonstrated. The unbundling of coverage against comprehensive policy will be the next challenge. 

Along with it, it is an actuarial/data science game. When current models are not applicable, new ones have to be invented. Risk modeling innovation aims both at keeping indemnity-based insurance relevant, and at using parametric as a sustainable way to transfer Cat risks. 

It is a capacity game. As long as parametric insurance deals with high-severity perils, reinsurance will drive the market: It dictates conditions to the primary carriers and defines the ultimate protection of insureds through retrocession or ILS. The main question is about frequency: If frequency adds to severity (re climate change), there will definitely be a capacity issue. 

It is a regulatory game. Regulation is there to protect the insureds, but when regulation impairs insurers trying to adjust their terms to market conditions, it produces a shortage in capacity. Another question is the bias introduced by the different regulatory frameworks between reinsurance and ILS on one hand and primary insurance on the other. It is not certain that this asymmetry is beneficial to the protection of insureds.

KEY TAKEAWAY:

--If an existing brand does not represent the true value an agency has to offer, a rebrand could be in order. But it should never be a spur-of-the-moment decision, should be allowed enough time to take shape, should draw on ideas from the whole team and should be continually monitored based on key customer metrics.

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When you first thought about opening an insurance agency, you likely visualized a name and maybe a logo as part of the business's identity. From the beginning, you considered how your business would be perceived by consumers, how they would interact with it and how it would contribute to your reputation. Whether consciously or not, you were thinking about your agency brand. 

Over the years, an agency’s brand evolves with its service offerings and the world around it. Today, 70% of purchase decisions are based on emotion, according to a study by Gallup, so branding that consumers like and relate to emotionally can be a revenue generator. There will come a time when the original brand no longer serves the agency or evokes consumer emotions, and decision makers will consider rebranding to bring new life to the business and realign themselves to fit their client’s needs. 

Should you rebrand? 

An effective rebrand at the right time can encourage loyalty with existing clients and growth with new ones. Conversely, a rushed, incohesive rebrand can damage the agency’s current book of business and opportunity with new markets or, at best, result in a waste of time. 

Take Brinks Home Security’s rebrand to Broadview Security after they were acquired by Broadview in 2009. After failing to consider the long-term brand standing of the Brink’s name, the company lost a large portion of their base clientele. In response, they reinstated the Brink’s name two years later.

Taking a calculated risk that still considers existing clientele is important. 

While it is impossible to put a time stamp on when to rebrand, agents should be paying attention to the value their agency brings to the industry. If their existing brand does not represent the true value an agency has to offer, a rebrand could be in order.

Our organization, SIAA, for example, is no longer the organization we were a few years ago because independent agents require a different suite of support than they did when we began 25 years ago. As such, we have chosen to undergo a rebrand that better highlights our offerings for the modern independent insurance agent.   

See also: Is Your Agency Ready for Automation?

Take your time

A rebrand should never be a spur-of-the-moment decision. Once the risks have been considered, independent agencies should allot a minimum of six to 12 months to complete the process. If it were to be done in six months, it would require full-time attention. The key is not to rush. Rebranding will require many pivots, and allowing time for these small, detail-oriented tweaks is essential.

Allowing enough time to go through the rebrand process will also let agents better analyze what is working and what is not in the business. A rebrand is not the time to throw everything away and start over. 

Agency owners should ensure the business leads with what they do well and consistently. They should consider the agency’s core values and mission statement as well as their agency data, including lead conversions, sales numbers or client retention rates. This data can illuminate what is working with the brand and what needs to be changed. Existing clients stay with their agency for a reaso,n and management would do well to identify those facets of the business and find better ways to spotlight them in the rebrand. 

The team knows best 

Your team will be your strongest asset in a rebrand. From making preliminary decisions to communicating the final product, agency staff will often have the best insight on perceptions of brand among clients, on areas that can be improved and on legacy aspects to maintain. Agency owners should ensure their team feels welcome to offer ideas and feedback. This way, management can alleviate some of their workload, and the staff will be familiar with the vision when it comes time to reintroduce the agency. 

Plan for the follow-through

When the rebrand has been built out on paper and an agency is ready to implement their changes, it will require a commitment from staff to ensure consistency. Agents should be prepared to enforce their new brand guidelines and practices by listening to their staff. Management should monitor how they are interacting with clients or prospects and stay present in email chains and other communications to confirm their approach aligns with the new brand vision. Any identified branding gaps should be addressed with staff to ensure they understand the goal of evolving the brand. 

It is crucial that independent agencies know how they are going to measure the success of their rebrand. Agencies should consider data such as lead conversions or client retention rates. Management should track these numbers throughout the rebranding process to have a tangible idea of how the new brand is performing. When the new brand is first launched, agencies might see a small decrease in these numbers before they begin to grow. This is normal, but agencies should remain diligent in monitoring progress.

See also: Incumbents Can Score an Alley-Oop! 

Tap into your resources 

While a time-consuming process, rebrands need not be excessively expensive. Organizations like SIAA can be a great resource for guidance throughout a rebrand. While SIAA does not offer formal resources for rebrands, we can help connect our members with resources such as Logotournament.com or freelance professionals to assist with various parts of the rebrand process such as content creation and graphic design. Agencies also should consider consulting their network for additional resources or rebrand insights they may have from their own experience. 

Rebranding can be a daunting task for any business. Independent agencies might find it difficult to imagine making the time to undergo a rebrand that will bring more value to the industry and their clientele. However, rebranding is a natural and integral part of owning any business, especially one with longevity.

Consider taking a moment to imagine how your agency might benefit from a reintroduction to the world and the new opportunities a rebrand could present.

"The best loss is the one that never happens."

That, to me, is the most compelling line from the interview I conducted recently with Pete Miller, CEO of The Institutes. The Institutes (with which ITL is affiliated) has for some months now been arguing that insurers should take all the data that they're gathering on potential hazards in commercial buildings, homes, cars, etc. and spin it forward. Rather than view data analysis as a historical exercise for pricing risks, then indemnify customers for losses, Pete says — and I wholeheartedly agree — that there is a major opportunity for insurers to use sensor data to spot wiring problems before they lead to fires, to detect a leak before it can do any damage, to warn workers that they're risking injury before they get hurt.

Insurers will pay fewer claims. They will also avoid all the costs of processing the claims that don't happen. They will have the opportunity to sell all sorts of new products and services that minimize risk. Meanwhile, insurers will not only spare customers from paying a deductible but will let them skip all the hassle that comes with recovering from a fire, leak, etc.

Talk about fulfilling the insurance industry's noble purpose. Talk about creating loyal customers.

If you want to dig deeply into "predict and prevent," I encourage you to check out the podcasts Pete has been conducting with insurtechs such as Whisker Labs and Betterview, with executives from insurers such as Chubb and brokers such as Marsh McLennan, with insurance commissioners and with customers. (If, like me, you're more a reader than a listener, you can find the transcripts for each of the six podcasts on the same page.)

In the meantime, here is the interview I did with Pete, which, in my not so humble opinion, is a great summary of the opportunity that predict and prevent presents:

ITL:

The predict and prevent theme really resonates with me. How did the idea take shape, and how did it become a major theme for The Institutes?

Pete Miller:

The idea came from an awareness of emerging technologies that can really help to do more effective and, in fact, more-real-time risk mitigation.

If you think about it, the best loss is the one that never happens. And there's a huge amount of data, including real-time data from IoT sensors, as well as a vast increase in the tools that are available to process and make sense of the data. If you start to combine all that, then there's an opportunity for real-time, improved data analytics for resiliency.

As a result, we can make people's lives better and safer and easier. We can use analytics to predict what's going to happen and stop problems before they start.

ITL:

What are some of the best examples of predict and prevent that you've come across since you started focusing on this theme?

Pete Miller:

Whisker Labs has a device called a Ting that is really, really cool. You just plug it into a wall socket, and it monitors for electrical hazards both in your wiring and the electrical devices you're using and alerts you before a fire can start. State Farm is deploying Ting to its customers [at no cost to them].

There's also a device that people in a warehouse can wear. It learns your body for the first few minutes. If you’re taller, you do some things differently than if you’re shorter, for instance. After that initial phase, if you're doing something like leaning over too far and are risking injury, the device goes, "No, don't do that."

How cool is that? You prevent injuries that could have someone walking around in all kinds of pain for a lifetime.

Others are looking at ways to head off damage from wildfire.

It's all been really interesting.

ITL:

You have lots of senior insurance executives on The Institutes board and talk to others all the time. What has their  reaction been to predict and prevent?

Pete Miller:

I can't talk about actual deliberations within our board, but I can say that there's a very broad recognition that this is the right thing to do. The theme really resonates. It's just too logical, and if the insurance industry doesn’t do this then somebody else will. There's so much benefit to be had.

Insurance companies understand that a predict and prevent approach cuts their losses. They don't just have fewer claims but also avoid all the expenses associated with loss adjustment. The loss never happened.

Policyholders are happy because you're telling them you can detect problems and prevent losses.

Regulators see this as a great opportunity, too.

ITL:

I imagine that there are also ways to take the data being gathered and feed it back into building codes, insurance contracts or other instruments that will change behavior.

Pete Miller:

There are a variety of ways, some of which is dual-purpose. Chubb, for instance, is working with a real estate company that has a bunch of office buildings, and they put water sensors in them. The sensors provide real-time alerts if there is a water leak or flooding, and a valve can shut off the water automatically. The sensors also generate data that can be provided to builders or property managers or those who write the building codes and that will help head off similar problems down the road.

ITL:

To me, the tipping point for predict and prevent has always depended on being able to make a strong economic argument. If you retrofit a house to install sensors and a valve that can automatically shut off the water when there’s a leak, that costs you maybe $700 or $800, and you have to install a lot of those valves to prevent a single loss. How close do you think we are to a tipping point?

Pete Miller:

In round numbers, the cost to set up and monitor those sensors that Chubb installed is less than $5,000. A single water loss? $100,000, on average. So, for that client, the math is easy.

Whisker Labs says its Ting device can prevent 75% to 80% of house fires, and the cost of a device is minuscule.

Those economics are coming into line. It's starting to make sense. And the costs are always coming down.

Companies are also viewing predict and prevent as a value-add in terms of customer satisfaction. Customers think, "I have an older home, and my insurance company is giving me a device that protects me and my family." That's worth something.

ITL:

I saw in your podcast interview with the founder of Whisker Labs that he also talked about how devices like his Ting get smarter as more get deployed. You can see, in his case, that a certain fluctuation in the flow of electricity in a building that didn’t initially seem significant actually shows a risk of fire.

How do regulators deal with this new approach? Do insurers just graft it onto the existing insurance model? Or does there have to be a more fundamental change?

Pete Miller:

That's a very good question.

Insurers understand that this is a cultural shift, and, frankly, there's some resistance. Some people say, "Well, that's not insurance." But the people I've talked to say, "Well, now we're kind of thinking we're risk managers." Insurers will certainly always indemnify clients for losses, but if we think in terms of risk managers then there's a whole series of broader products and services we can offer.

There are other risks that can be mitigated, too, beyond fire and water. Cyber, for one. Insurers can help clients reduce those risks and eliminate a lot of losses. On the commercial side, there are lots of additional property risks that insurers could help reduce. More can be done with telematics in cars.

And I keep going back to the selling point: You, the insurer, proactively stopped something bad from happening.

You didn't just save me my deductible. I don’t want to have to do a bunch of stuff to recover after a loss. If I own a business, I don’t want to have down time.

It's the same reason I go to the dentist, right? Because I don't want all my teeth pulled.

You asked about regulators. Every regulator I talk to says this is awesome. They look at predict and prevent from a consumer point of view, and they say, "You just saved the consumer a lot of heartache."

ITL:

Words to live by.

And it sounds like the opportunities will only grow from here.

Thanks, Pete.

 

Cheers,

Paul

 

For this month’s ITL Focus, on operational efficiency, ITL Editor-in-Chief talked with an old friend and colleague, Jamie Yoder. Jaime is the president and general manager for Sapiens North America, which provides software tools that help insurers transform their businesses.

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ITL:

My mantra for a long time has been, “Let’s burn all the fax machines.” But I know you take a broader view when you think about how insurance companies can operate more efficiently.

Jamie Yoder:

I go back to the Digital Darwinism paper I published with ITL on the principles of a bionic organization. Too often, companies do little pilot projects to try to operate better rather than systematically understanding how to improve the speed and efficacy of decisions that happen across an organization.

The nice thing about ChatGPT is that it’s put in everybody's minds, “Oh, wow, we could use AI everywhere.” Not that we weren't attacking inefficiency across the board already, but now the ability to take a systematic approach has become obvious.

ITL:

The issue went from difficult to obvious, almost overnight.

Yoder:

I guess that's always the case. Then people get disillusioned, and we revert a bit, but then we find all the real opportunities.

If you step back a bit and look at the full potential of digital and all the advances it’s enabled, those innovations are in the capture, consumption, interpretation and use of data in new and exciting ways. And those new sources and new techniques allow for transformation in three key ways. You can change the way you engage, with customers and others. You can change the way the work is done. And you can change the way your organization changes.

In a bionic organization, the issue isn’t whether the machine or the people do the work. It’s about how they work together to improve the speed and efficacy of every decision and about how you keep improving over time.

When I look at generative AI, I like the notion of it as a copilot. With every task, it can almost be like having somebody there helping you. This is low-hanging fruit. The AI allows you to do the tasks you do every day, but much better and much more readily.

We have a product called Decision that allows you to visualize and manage complex business logic. Building those models can take a lot of manual effort. A simple use case for generative AI – one we’ve already done—is to describe for it what you want as your model and what the logic is, and to have it grab the eligibility rules for a mortgage or a claim or something else. You’ll have to test the model the AI gives you to make sure the logic is sound, but you can deploy it almost instantly.

You can produce an answer engine for agents dealing with customers.

You can use the AI to gather all kinds of different information and at least provide some guidance to augment what you're thinking, in any role from underwriting and marketing to legal, finance and management.

ITL:

I love the idea of AI as a copilot. I’ve described generative AI as providing rough drafts for us humans to finish. How do you make sure a generative AI doesn’t have the “hallucinations” that have sometimes embarrassed users very publicly?

Yoder:

You’re not using the AI to fully automate. You're just using it to sift through an awful lot of things to provide you the basis for a decision.

We used to look at underwriting in the commercial space and say, Wouldn’t it be great if every underwriter was actually a team that included a data scientist? Now, you can have an AI poring through all the information that’s available and winnowing it down. You aren’t just using the AI for efficiency. You’re uncovering information that you wouldn’t have gotten otherwise and making better decisions.

Think of the junior underwriter who gets binders full of information and has to sort through it all, and mostly is just trying to figure out what has been done with similar situations in the past. Now, the AI can do all that sifting and comparing and make sure that junior underwriter doesn’t miss something.

Marketing is another good example. The AI can create a nice outline based on your inputs, which is enough to trigger good ideas and to help ensure you don’t miss any angles. You’re not going to create something and post it automatically, but the AI can get you started, and we humans are good at sculpting once there’s something to work on.

Or think about contracts. Most contract clauses are repeated, so if you have a large language model that’s built off all the contracts you’ve ever done, you can have it do an awful lot of the work on new contracts you’re writing.

ITL:

A great thing is that it sounds like people can do things in the short term, not just in the long term, that can generate efficiencies while building long-term momentum.

Yoder:

In that Digital Darwinism piece, we say you shouldn’t just use AI to look at the stars. You should also use it to pick up the trash. I'll be quite excited to see how generative AI picks up the trash, because there can be a lot of quick wins.

Just train your AI on all the proposals you’ve ever done. 70% of the questions you’re asked are always the same, so the AI can provide the answer, leaving it to a human to provide unique spin as appropriate.

Have the AI look at your submissions and ask it, How have we responded to all the similar submissions we’ve received in the past?

ITL:

A quick digression: People talk a lot about large language models. It seems to me there's also potential for what I think of as small large language models: You train the model on all the data that’s out there on the internet but then bring it inside your company and only give it access to your data, your procedures, etc. Do you see the same thing?

Yoder:

Absolutely. You go wide initially and then give the model deep domain expertise.

ITL:

Glad I’m not hallucinating. What comes after the easy wins, after the picking up of the trash?

Yoder:

Companies need to operationalize the information from the AI within their process flow. Decision modeling is a huge part of what we do, so we look not just at how to ingest all that information but how to augment the intelligence in that human-machine pairing.

Then, of course, we’re going beyond how to do the work and looking at all the below-the-waterline stuff, about how you change the way you change. There’s a huge advantage in development, in testing, in documentation and so on if you can create an environment that lets you continually improve.

As we help insurance companies transform, I keep looking at those three levels: how you engage, how you do the work and how you improve. That last one is key. You can’t just do projects. You have to create an environment that lets you get better and better all the time. You need an operating model that is built to continuously evolve.

You don’t want machine learning. You want a learning machine.

ITL:

A great idea to end on. Thanks, Jamie.

FROM THE EDITOR  Jamie Yoder, the president and general manager of Sapiens North America, jokes that driverless vehicles are no big deal. The Amish had them decades ago, he says. A farmer would get drunk and fall asleep on the bench at the front of his cart, and his horse would eventually start trotting and take him home. Jamie would know. Even though he now runs the North America operations of a major provider of software products and tools and has made a career out of digital technology, he grew up in an Amish community. I've heard that joke a few times because I've known Jamie since 1996, when we met via Diamond Technology Partners, where we were partners. I've heard a few other stories, too, because Jamie has been my go-to on lots of insurance-related subjects as he became the insurance practice leader at PwC (which bought Diamond in 2010) and then the president at Snapsheet, an insurtech that has been an innovator in claims management, even before taking on his senior role at Sapiens. But I've not heard from Jamie -- or anyone else -- as broad and crisp a description of the opportunities that ChatGPT and other generative AI models present for insurers as what Jamie said in this month's interview. He doesn't stop with the opportunities for operational efficiencies, either, even though that is the topic for this month's ITL Focus. He lays out a whole host of very specific opportunities but also sets them within a broader framework that can lead to a long-term competitive advantage.  The key, Jamie says, is to not just change but to change how you change. That's even more important than having a horse that knows the way home. I hope you'll check out this month's interview. Cheers, Paul   For this month’s ITL Focus, on operational efficiency, ITL Editor-in-Chief talked with an old friend and colleague, Jamie Yoder. Jaime is the president and general manager for Sapiens North America, which provides software tools that help insurers transform their businesses. Read the Full Interview "When I look at generative AI, I like the notion of it as a copilot. With every task, it can almost be like having somebody there helping you. This is low-hanging fruit. The AI allows you to do the tasks you do every day, but much better and much more readily."  — Jamie Yoder Read the Full Interview READ MORE A New Year's Resolution for Procurement Let's behave less like the secret police in a totalitarian state and procure in a more empathetic, flexible, open, friendly and fair way. Read More The End of Globalization? Following many decades where globalization ruled, corporations will be reversing their globalization efforts for at least the next decade and likely far longer. Read More Why Automation Is So Important Agencies, brokers and carriers spend an inordinate amount of time and money on back-end processes that detract from core objectives. Read More Power to the People Operational intelligence uses AI to create measurable insights into how work is being done and allows for new ways to work and get paid. Read More 5 Key Challenges Where RPA Shines Automation has already been widely accepted by the banking and financial industries. It is high time for insurers to adopt RPA. Read More Branded Communication: A Strategic Enabler At a time when few answer a call from an unknown number, insurers can identify themselves as a legitimate caller by displaying logos and a reason for the call on the recipient’s device. Read More FEATURED THOUGHT LEADERS Robin Merttens Paul Carroll Allister Yu Tom Bobrowski Uday Birajdar Joshua Ayres

KEY TAKEAWAYS:

--When implemented strategically, instant payments yield back-office efficiencies and delighted customers. However, poor implementation can have the opposite effect, resulting in siloed internal systems, repetitive remediation efforts and confused, frustrated customers.

--To ensure the success of your instant payments initiative, you must focus on delivering a seamless experience for users, providing them with as many payment options as you can and (this is the hardest part) integrating your back-end systems and processes with payors.

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As a consumer, you enjoy the convenience of instant payments in various aspects of your life, from splitting the bill with friends using Venmo to receiving direct deposits for your salary. But as an insurance professional, the idea of instantaneous payouts, claims checks and other transactions has been a long time coming. 

Instant payments in insurance are finally gaining traction—and for good reason. In 2022, 20% of all claims payouts were made through an instant payment system, and it’s easy to see how they offer benefits to both customers and insurers. Customers benefit from increased convenience and faster receipt of claims payouts. Insurers enjoy advantages such as reduced payment fraud rates, increased customer satisfaction and decreased manual efforts involved in tasks such as accounting reconciliation and mailing paper checks. 

Providing instant payouts is also increasingly necessary for insurance providers to maintain their competitiveness, especially with the emergence of Gen Z in the policy pool. To meet the expectations of tech-first consumers, insurance companies must prioritize and invest in an instant, seamless payout experience.

Instant payments are the future

While the Automated Clearing House network (ACH) has served as the go-to method for electronic payments, it involves a delay of three to five working days. Although an improvement over mailing paper checks, it ultimately falls short of a real-time experience. 

With instant payments, on the other hand, the recipient receives their claim seconds after it’s been sent. The future of payments is undoubtedly heading toward instant transactions, as evidenced by the support of prominent institutions such as the Federal Reserve, which is investing in advancing instant payment solutions. In fact, the Federal Reserve plans to launch its own instant payment platform, FedNow, in 2023.

There will soon be three forms of instant payments available (excluding peer-to-peer apps). In addition to the soon-to-be-released FedNow, they are the Clearing House Real Time Payment network (RTP), which has been processing payments since 2017, and push-to-card payouts, which instantly transfer funds to cardholders' existing payment cards.

With instant payments accessible to the vast majority of consumers, insurers that have not yet adopted ACH can leapfrog from paper checks to instant payment. For those that have already adopted ACH, instant payments are still worth considering. Faster receipt of claims instills confidence and reduces uncertainty in recipients, creating a seamless, satisfying experience for policyholders.

See also: Ready for Era of Real-Time Payments?

Three things to consider

When implemented strategically, instant payments yield back-office efficiencies and delighted customers. However, poor implementation can have the opposite effect, resulting in siloed internal systems, repetitive remediation efforts and confused, frustrated customers. To ensure the success of your instant payments initiative, prioritize the following practices:

1. Focus on the user experience

The digital world is littered with failed websites, applications and services. No matter how innovative and valuable your application may be, if the service has a cumbersome user experience, customers will quickly abandon it. 

That’s why it’s important to make the digital payout experience as intuitive and seamless as possible. For example, customers shouldn’t have to leave your app to enroll in digital payments or re-enroll every time they have a claim. Minimize the number of steps and redirections involved, and keep everything embedded within your app. 

2. Provide policyholders with a choice

Your digital payouts should accommodate all three types of instant payments: RTP, FedNow and push-to-card. Additionally, consider integrating popular peer-to-peer (P2P) apps such as Zelle and Venmo to reach a wider range of consumers. Customers should have the freedom to choose their preferred instant payment method. Your user experience needs to keep these enrollment processes embedded within your app.

Fear of fraud is a common concern when it comes to digital payment transformation. Surprisingly, digital push payments actually experience lower rates of fraud compared with paper checks because the receiver's identity has already been verified through digital channels. Physical checks, on the other hand, are susceptible to uncontrollable external circumstances such as mail theft and misdelivery.

3. Integration with back-office processes

In addition to delivering a top-notch experience for customers, you need to provide back-end integrations for payors. Integration of systems and processes is a key requirement to fully realize the benefits of digital transformation. By doing so, you simplify workflows for insurers and employees, reduce the risk of manual errors and minimize time-consuming remediation efforts.

Transforming back-office processes and integrating instant payments with existing systems is the most time-consuming aspect of adopting instant payments. However, investing time and effort into this integration is necessary to establish a solid foundation for your payment processes.

While insurers can build out their own instant payment capabilities, proceed with caution. Honestly consider the costs and expertise to: a) maintain instant payment processes, b) handle exception cases and processing issues and c) stay up to date on evolving payments technology and make necessary upgrades. Keeping up with these demands within a homegrown system is more expensive, difficult and time-consuming than outsourcing these efforts to payments specialists. 

See also: 5 Trends to Ride in 2023

Future-proof your business with instant payouts

With the proliferation of instant payment options, insurance providers have a pivotal opportunity to revolutionize their operations and deliver a competitive customer experience. The growing emphasis on instant payments by prominent payment players underscores the significance and relevance of this transformative payment method in the financial space. 

By embracing instant claims payouts, you can unlock benefits such as enhanced internal operations and reduced fraud rates while further future-proofing your business.

Data, data everywhere. Data has gone from scarce to superabundant, but actual information remains elusive. Turning data into information, and information into action is the goal. For carriers, this brings huge benefits — but comes with big challenges.

All this data is scattered across systems, applications, and devices — and is not available in a unified, accurate, relevant, or secure view. Combining all of these data sources is not enough: you will still have to transform this raw data into actionable insights – a formidable task.

But first the question you need to ask: is the data you have the data you want?

Not All Data Is Good Data

In the insurance industry, the accuracy of data is paramount. The efficiency of the claims process is contingent upon the adjuster's ability to verify a claim, which is based on having accurate data. The foundation of claims automation is also accurate data, both structured data from the system and unstructured data from the filing to determine the appropriate course of action for each claim. The automation system continually reassesses its previous decisions as new information is added. Attempting this process with inconsistent or "dirty" data can lead to erroneous decisions and a subpar customer experience.

In many instances, data is not synchronized, leading adjusters to prioritize claim outcomes over data quality when managing high caseloads. Similarly, insurance underwriters depend on accurate data for risk assessment, which can influence premiums, policy terms, and profitability. Unfortunately, many insurers are grappling with inaccurate underwriting data, necessitating requests for additional information from agents and customers, leading to both longer decisions and lost business.

For instance, when underwriting and pricing property insurance, carriers often rely on the insured or their agent to provide Construction, Occupancy, Protection, and Exposure (COPE) details about the property. These details enable the insurer to evaluate the potential loss associated with the property and price it accordingly. However, the insured may not always provide accurate information, leading to policy underpricing and increased losses. Utilizing third-party data is not always a solution due to its high cost, and carriers must strike a balance between data quality and turnaround time.

Three Steps to Getting Data You Can Use

Step 1: Data validation and cleansing

You have all the customer data. But do you have the right data validation tools to check for errors and inconsistencies?

With these tools, you can flag any data that doesn't match your requirements. Once you identify errors and inconsistencies, the next step is to clean up the data.

The process involves removing or correcting data to meet well-defined standards. Though time-consuming, it's critical and best done with cross-functional teams and stakeholders. For quality data, you need the support of the front line and everyone responsible for the data.

Step 2: Data integration and analysis

Once the data has been collected, validated, and cleaned, it is ready to be integrated into your systems for analysis. This analysis can provide invaluable insights into customer behavior and risk. However, Property and Casualty (P&C) carriers often rely on legacy systems that are not equipped for data integration. These systems may require additional capabilities to exchange data with modern systems, and integrating this siloed data with newer technologies may necessitate complex transformation. Data integration is more than just combining data sources; it is about generating meaningful insights through advanced analytics capabilities, data modeling, predictive analytics, and machine learning.

Step 3: Data quality management

Data quality management is a continuous process that involves auditing, profiling, and cleaning your data to ensure its accuracy. Regular check-ins with the teams responsible for collecting and maintaining the data (such as CRM and data entry teams) and the stakeholders who use it (such as underwriters, claim adjusters, actuaries, and data scientists) are essential to maintain data quality.

Poor data quality can have detrimental effects on business operations. By integrating your applications and sources and streamlining your processes, you can enhance customer service, mitigate risk, and unlock new revenue streams. This optimization of data management is not merely a technical necessity but a strategic imperative for the insurance industry. Bad data is bad for business.

Murray Izenwasser, Senior Vice President, Digital Strategy

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

 

 

Sponsored by ITL Partner: OZ Digital Consulting

Ever since the U.S. Supreme Court handed down a decision last week that bars affirmative action in college admissions, I've been waiting for the other shoes to drop. And they are starting to. Many are wondering, in particular, not just about what happens to talented kids of color as they apply to elite universities but about the effects on diversity, equity and inclusion (DEI) programs at corporations.

I don't expect the effects will be major in the short term, but the win at the Supreme Court will surely embolden those arguing that race can no longer be a factor in decisions about hiring and promoting and will lead to all sorts of legal challenges. So, companies should keep a weather eye out to make sure that their DEI programs stay within the changing boundaries of the law. 

The issue is especially important in the insurance industry, which -- to its credit -- has been attentive to DEI. 

An essay in the New Yorker lays out the issues facing all proponents of diversity: 

"Opponents of affirmative action have been filing lawsuits for a very long time. For them, this decision will represent anything but a satisfying end to the struggle. Instead, they will see it as an invitation from the Supreme Court—one to be accepted quickly, before the court’s membership changes—to look for other places where the majority’s way of defining color blindness does not prevail." 

An op-ed in the Wall Street Journal over the long weekend framed the issues for corporations in an essay carrying the headline, "Is Your Company's DEI Program Lawful?" Written by a conservative lawyer, the piece says corporations should read the Supreme Court's decision carefully "because it will likely end up applying to them. Many companies have pushed racial preferences and quotas under the guise of “diversity, equity and inclusion” policies that run contrary to the justices’ warning against choosing 'winners and losers based on the color of their skin.'"

He writes that companies make themselves especially vulnerable to challenge if they publish numerical benchmarks and specified percentage goals based on race. The author also suggests that employers can reduce their exposure if they take into account the "twin commands" cited in the SCOTUS decision:  “that race may never be used as a ‘negative’ and that it may not operate as a stereotype.” 

"The former command," the op-ed says, "calls into serious question the use of race as a 'plus factor' in hiring and promotion.... The latter command calls for a searching analysis of the genuine goals of workplace diversity. [The Supreme Court decision] rejected the broad and amorphous justifications for racial preferences advanced by Harvard and [the University of North Carolina], such as that these policies broaden knowledge, foster innovation and enhance empathy. Companies that base their DEI policies on similar grounds should... reformulate them in a way that is, in the words of the majority opinion, 'sufficiently coherent for purposes of strict scrutiny.'"

An essay in the New York Times takes a somewhat more optimistic view of the decision's likely effect on businesses, saying, "As a legal matter, the Supreme Court’s rejection of race-conscious admissions in higher education does not in itself impede employers from pursuing diversity in the workplace." But the author quickly adds that "many experts argue that as a practical matter, the ruling will discourage corporations from putting in place ambitious diversity policies in hiring and promotion — or prompt them to rein in existing policies — by encouraging lawsuits under the existing legal standard."

The author says there will be particular pressure on "leadership acceleration programs or internship programs that are open only to members of underrepresented minority groups," which he says "were already on questionable legal ground."

For my part, I think the insurance industry has two clear business purposes that justify a continued emphasis on DEI. We serve such a diverse set of customers that, of course, we need a diverse set of people at all levels making decisions about how best to serve those customers. We're also facing the departure via retirement of so many people that we have to tap into talent pools that we've previously neglected, including racial minorities.

I also think smart lawyers will find plenty of work-arounds for companies that feel a moral obligation to DEI because of the centuries of discrimination against minorities. Even in his opinion saying colleges couldn't use race as a consideration for admissions, Chief Justice John Roberts wrote that colleges could take into account life experiences -- and many kids of color have had the sorts of experiences that produce the dramatic personal essays that can catch the eye of an admissions officer. Colleges can also still take into account factors such as poverty that can favor racial minorities. 

So, all is not lost, by any means, for proponents of DEI. But everything did just get trickier.

Hope all my American friends had a great Fourth of July. I hope all the rest of you did, too, of course, even if you weren't eating hamburgers and hot dogs and watching fireworks.

Cheers,

Paul