In-house legal software is blending cutting-edge technology with legal expertise to solve complex challenges.

The legal focus has shifted over the years, from intellectual property protection and contract drafting to data privacy, cybersecurity and fintech regulations. Risk management methods need to adapt to these changes, and our focus needs to shift from mere mitigation to strategic anticipation and navigation.

While traditional risk management methods remain relevant for issues like operational or financial risks, the legal dimension requires a more preemptive and tailored approach — and modern legal software offers solutions that are not just reactive but anticipatory.

Key Developments in Legal Software

The landscape of legal technology has undergone a seismic shift, particularly in the last year. This transformation can be attributed to several key developments that have elevated legal software from a mere tool to an indispensable asset for risk management.

• Generative AI has become a cornerstone of modern legal technology. It goes beyond mere automation, from automating routine administrative tasks to sophisticated data and trend analysis. AI reduces the risk of human error by automating labor-intensive processes such as contract management. This allows legal professionals to focus their expertise on more complex, high-stakes tasks, effectively shifting the paradigm from reactive to proactive risk management.
• Modern knowledge management (KM) software aggregates information from various departments into a single, searchable database. This collective expertise not only enhances the firm's capabilities but also provides a robust foundation for risk assessment and mitigation strategies. Leveraging the aggregated data requires serious software muscle power.
• As mergers become more frequent, specialized technologies have emerged to manage the intricate and time-consuming process of data management during these mergers.
• Enterprise risk management has expanded its horizons to include not just financial governance but also security, IT, third-party relationships and governance, risk and compliance (GRC) procedures. Modern legal software is increasingly becoming part of a broader technology stack that manages a diverse array of risks. 
• The technological revolution in the legal sector has given rise to new roles such as legal technologists, legal process analysts and legal data scientists. Traditional law firms are finding their existing structures increasingly obsolete and are having to redefine their services and integrate technological capabilities.

See also: Cybersecurity Standards for Insureds Are a Must

The Power of In-house Legal Software in Risk Management

Traditional risk management tools often rely on manual inputs, static databases and lengthy processes. In contrast, in-house legal software offers automation, real-time data analysis and adaptive algorithms. 

By leveraging AI and machine learning capabilities, in-house legal software can identify risks, categorize them based on severity and relevance and propose tailored mitigation strategies. 

What does this mean for legal teams? Quicker response times, better overview of potential threats and more time to focus on strategic decision-making rather than sifting through data.

Imagine a global corporation with complex contractual obligations spanning numerous jurisdictions. Staying compliant and tracking liabilities would be time-consuming and prone to error. However, with advanced in-house legal software, not only could they maintain real-time oversight, but they could also receive alerts for potential compliance breaches and devise a proper response.

Or imagine a startup navigating the intricate web of intellectual property rights. It could use legal software to automatically scan for potential infringements of intellectual property, ensuring the startup remains on solid legal ground as it grows. 

Leveraging In-house Legal Software for Insurance

The integration of in-house legal software in the complex ecosystem of insurance serves as a potent catalyst for savings and precision in many different tasks:

• It transforms insurance policy reviews: Historically, insurance policy reviews have been exhaustive, requiring meticulous examination of documents and terms. Today, companies can use legal software to automatically scan policies and flag discrepancies, outdated terms or potential compliance issues. This leads to quicker reviews and assurance of policy accuracy.
• It enhances compliance policies: By constantly updating their database with the latest regulations, modern legal solutions ensure that insurers remain compliant at all times. They can alert teams of impending regulatory changes, enabling them to adapt in advance.
• It revolutionizes contract management: Legal software aids in organizing, tracking and analyzing different contracts. Automation can identify unfavorable terms, potential areas of dispute or clauses that are misaligned with a company's standard practices.
• It elevates insurance transactions: Compared with traditional methods, in-house legal software enhances the efficiency and reliability of insurance transactions. From automated underwriting processes to real-time claims assessments, these tools cut down the duration of transaction cycles and minimize human error.

Legal automation saves time and money and leads to more accuracy in all of your processes.

Overcoming Implementation Challenges

Adopting new tech solutions inevitably comes with a specific set of challenges.

A common obstacle is our innate resistance to change. There are many approaches to change management. What we have seen work best are workshops and case studies that illustrate the tangible benefits of the new system — with an emphasis on how these tools can complement, rather than replace, existing expertise. 

Other common issues come in the form of integration issues and data security concerns. Both can be addressed by working closely with your IT department to vet and choose a reliable legal software vendor that offers the right security certificates and a modular solution that can be tailored to fit within existing frameworks.

Getting past all of those obstacles sets you on the path to success. But you need to be able to measure that success to continue on the same path. 

This is why you need to establish clear metrics from the outset, such as response times to risks, reduction in compliance breaches or efficiency gains in legal processes. Remember to take your baseline numbers before you start implementing new workflows and digital solutions so you can calculate potential improvements. 

See also: 3 Practical Uses for AI in Risk Management

Parting thoughts

The symbiosis of risk management and innovative in-house legal software opens up a new dimension: the ability to "future-proof" our businesses. However, this only comes as a consequence of the shift in our perspective — from seeing risk as a threat to be avoided, to viewing it as a challenge that can be turned into an advantage.

After all, in an age of unpredictability, the best defense is a strategic offense.

When it comes to integrity, money and shame seem to be the motivators that matter for people and businesses. With enough greed or fear, lapses in behavior and judgment may arise. 

When it comes to data integrity, accurate and identifiable context matters most. It helps remove the risk of relying on fluctuations in behaviors and motivations. Verified is a virtue.

You might believe everything you read on the internet, HA! You might believe every promise made, HA! You might believe there are no bad uses for good data, HA! But the world of risk transfer is built on staid provenance and reliability, with a "rule of law" expectation. The only funny thing about misuse of data is that it’s not illegal until there is a law that's been broken, so trust is all we have.

In a business built on promises, only those “made and kept” create trust and value.

Saving time and money with trusted services and providers is a mutual goal for policyholders, agents and insurers. Each needs data to be exchanged and used for specific problems and use cases to achieve those goals. So eliminating any questions of integrity oils the path for friction-free trust – and governed, actionable, accurate, contextual data is that oil.

For consumers, they have a bottom line at home. They seek value for their money and appreciate good service experience with a minimum of friction and time-wasting. Above all, customers with integrity have little to hide and are ready to engage with valuable, empathetic and interesting propositions that bring peace of mind and make it easier to interact day-to-day as well as in crisis-and-recovery mode. Convenience, continuous access and customer-preference awareness are the new expectations that consumers have with the connected world around them.

See also: Don’t Neglect the Politics of Analytics

For businesses, they have a bottom line at work. They know not all customers are equal and not all cars, homes, phones, drivers, routes, territories, businesses, buildings, etc. are the same. Yet often frustratingly, businesses cannot capture the value of that knowledge. Frequently, better data becomes available, but it may be device-specific, so the cost of collecting new data may be prohibitive, or it may be talent-enabled, so a capability gap needs to be overcome. Turning data into products for scalable customer interaction and business system integration frequently takes "oil pipelines" (a.k.a. application programming interfaces, or APIs) and new ways of working. Prioritizing these and shepherding them is a continuous improvement journey.

The best-in-class businesses are run by people who are customers, too, and think in a customer-centric fashion. They always look for better data for making better decisions as trusted advisers and guard against unscrupulous exploitation, unintended consequences, disparate impact and lack of fairness even across their supply chain of vendors and networks of suppliers. They consistently audit data quality and the cost of data (paid or collected) and innovate on things like eliminating steps and tasks for things they substantively can know (e.g. pre-fill everything) while always looking for new levels of analysis and new data features to improve customer and situational understanding (e.g. recursive segmentation). This search occurs for rating and risk factors alike in a progressive fashion of rate-to-risk fit.

Insurance is a “cost plus” business, and it is mostly a compulsory product, which is a good reason for all the regulatory structure. When costs rise, consumers don’t expect service to suffer. They expect that their data should maximize their value from a company, and they want the same level of service as they get when costs flatten or go down. And they never want to feel that their trust has been mislaid. They will forget the price changes eventually, but they will remember how you made them feel about those changes. Double that for data skullduggery – blatant or inadvertent or accidental.

The interplay of customers and businesses creates a market dynamic often laden with mistrust – where what you don’t know you don’t know is a blind spot you must avoid. The other boxes in that Johari Window of shared/unshared knowledge explain the dynamic more implicitly.

Customers with motivations (fear and greed) to avoid transparency are different than those who simply don’t trust what will become of their data. The latter get information about businesses from friends, family, advertising, the internet, agents and the companies they frequent. When their "radar" creates anxiety that their money or data is being exploited, their concerns and outrage cause them to churn. So, too, when their data is NOT being used to improve their experience: Concerns and outrage cause them to churn. 

It seems that in exchange for their data, they expect it to be used as intended, for their greater good or not at all. Increasingly, this last option is dissipating as companies and products wrap “always and forever” expansive tendrils on any and all current or future "blue sky" ownership rights to everything that might be data and any inferences that those might create. This lingering infringing specter is a work in progress as is the pushback, oversight, audit, regulation and practice of law.

As for businesses, the examples of firms monetizing data in all sorts of freemium, premium and pay-per-use avenues continue to astound investors while stoking the venture forge fires. The short list of BFOs (blinding flashes of the obvious) are amazing in both the commonplace uses as well as the novel and exotic. But innovations aren’t real if no one buys them.

In a hard market, cost takeouts, "good customer" retention and focus on risk appetite get more play on the profitability jukebox than the soft market tune of "just get growth." When companies fail to understand the customer at new business, or the changes in the customer over time for renewal, they dig their own grave by assuming all customers are equal – they are not.

What happens to brand and reputation if you make promises and assurances and then abandon them? Will customers learn they cannot rely on you and your data practices? Or will you commit to a way of working to always be segmenting and improving experiences for personalized risk transfer, safety, prevention and loss management.

The cost of doing nothing with data is your future. Handling your data poorly accelerates your ex-date.

Technology standards are never sexy, but they can be awfully important. You've likely never heard of 802.11b, but it unleashed a revolution in how we and all our devices communicate when the Institute of Electrical and Electronics Engineers released it in the late 1990s. You know it as Wi-Fi.

An industry group has now rallied the major players involved in smart homes and produced a software standard that lets all their devices talk to each other as effortlessly as your computer links to the cloud. You will now be able to see and use your devices woven into a network rather than as a series of individual devices.

The real innovation begins now.  

The rollout of the standard, called Matter, has been in the works for a while. Here is me writing about it when it was announced a year and a half ago: "Smart Homes Are Finally Getting Smarter." What's new is that devices supporting the standard have been steadily introduced for almost a year and that there has been a flurry in recent weeks, suggesting that Matter has achieved liftoff. According to the Connectivity Standards Alliance, the group that developed Matter, more than 1,800 applications and devices have been tested and approved to support the standard.

A headline in the Wall Street Journal last week declared, "It's Finally Time to Add Some Smart Tech to Your Dumb Home." The article begins: "Up to now, the defining feature of most smart-home technology has been that no normal person should buy it.... But finally, we are at what promises to be a breakthrough moment."

Whether that breakthrough happens depends on the creativity of those who develop and deploy the technology -- and the insurance industry has been playing an important role because of the potential for smart homes to prevent damage from water leaks and fires and to head off burglars. 

On the carrier side, State Farm has been the most aggressive. It announced a year ago that it had purchased 15% of ADT, the home security company, for $1.2 billion and was going to put $300 million into an "opportunity fund" for further innovation.

State Farm also announced early this year that it was offering homeowner clients a free sensor called Ting, from Whisker Labs. The device plugs into a wall socket and monitors the electricity flows in the whole house or apartment, spotting anomalies that indicate danger of a fire. In the announcement with State Farm, Whisker Labs said it was mitigating or preventing 250 home fires a month -- and the rollout has just begun.

On the insurtech side, in addition to Whisker Labs, Roost offers a robust set of sensors that detect water leaks, fires and home intruders. Pepper/Notion is another leader, providing inexpensive devices about the size of hockey pucks that can be distributed through a home, apartment or building in spots where leaks are most likely to occur.

(If you're interested in more detail on what the industry is doing, check out a recent article we published, "How Smart Homes Are Changing Insurance" or the less recent but still very informative "Connected Insurance Comes of Age.")

What changes now for insurers and their customers is that everything becomes more flexible and easier with devices that are built to the new standard or that can be retrofitted with the Matter software. You could have window sensors from ADT to detect break-ins, a Ring front-door camera from Amazon, a fire sensor from Whisker Labs and a water sensor from Pepper/Notion, all integrated into a single app that monitors your home from your phone. You would no longer need the sort of monitoring panel that Roost, ADT and other home-security firms install in homes. And you won't have to worry about disabling your app if you switch from an Apple phone to an Android phone, because both will support the Matter standard. 

From that same app on your phone, you'll also be able to control other aspects of your home. You'll be able to adjust your Nest thermostat. You'll be able to remotely control lights, in case you want to make it appear that you're home even though you and your family are on vacation. You'll be able to unlock the front door if you want a neighbor to check something for you while you're gone. 

The group that developed Matter designed security into the standard from the get-go, so devices connected using it should be better protected than devices are now. That's the theory, anyway. Hackers are clever and persistent, so we'll have to see what happens.

To date, adoption of smart-home devices has been disappointing. Yes, Ring front-door cameras and Nest thermostats caught the public imagination, but that's about it for hits. Amazon thought its Echo device would make it easy for people to buy more stuff from Amazon, but it turns out that just about any purchase is more complex than, "Alexa, buy me some XYZ." Google's Home device hasn't caught on as a way to manage a home. And when Facebook tried to get users to install its cameras to enable constant video chat -- well, nobody wanted to let Mark Zuckerberg roaming around in their homes.

So there definitely needs to be some innovation if the smart-home trend is going to take off.

The good news is that, once a standard is in place, it isn't just the devices that attach to it that improve rapidly. The technology underlying the standard does, too, making it ever more robust.

802.11b was a breakthrough when it offered an inexpensive way to allow wireless communications at 11mbps (megabits per second) in the late 1990s. Some 25 years and dozens of iterations later, 802.11ax allows for speeds almost 1,000 times that fast -- and speed is just one of many vectors along which the technology has improved by orders of magnitude. 

Smart homes should only get smarter from here.

Cheers,

Paul 

KEY TAKEAWAY:

--Call centers for 911 emergency services are woefully underfunded and understaffed. So are emergency medical technicians (EMTs), which are not considered essential services in 39 states and thus have to be paid for through community fundraisers. The lack of funding needs to be fixed.

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The National Emergency Number Association (NENA) recently released a study reporting that over 80% of 911 call centers across the country are understaffed and underfunded. There are simply not enough operators and dispatchers in the 911 system.

For example, Montgomery County in Maryland, which fields 2,200 calls to 911 every day, has seen staffing levels decline 47% in the past year.

The reason revolves around long shifts, mandatory overtime, low pay and abusive behavior faced by the dispatchers.

At the same time, there is a shortage of emergency medical technicians (EMTs), especially in rural America. (See, "Fixing the EMT Crisis in Rural America.") The combination puts millions of Americans at risk during a medical emergency, especially in a potential life or death situation. The dual crises severely complicate the long-standing overcrowding and inefficient use of emergency medical services that has been wreaking havoc in emergency departments since long before the COVID-19 pandemic further overwhelmed the system. 

According to the Centers for Disease Control and Prevention’s (CDC) most recent statistics, there are 131 million emergency room visits annually in the U.S., with 18.6 million, or roughly 14% of those visits, resulting in hospital admissions. Over 28 million people are taken by ambulance service each year to the local ER, with two-thirds transported by the local fire department or municipal government. Roughly 3 million people per year who are taken by ambulance are in a critical, or even life-and-death situation. Tragically, the majority are due to auto accidents from aggressive and impaired drivers. 

See also: What Is 988? Future of Crisis Services

Our healthcare system is the best in the world, but it is simultaneously expensive, wasteful and inefficient, failing to address underlying basic barriers for access to primary healthcare. When the next trillion-dollar budget negotiations begin in Washington, instead of wasting millions on pet projects, federal funding should help state and local governments provide the necessary funding for 911 emergency call center operations around the country with highly paid career opportunities.

And how about funding and training for EMT squads around the country? How about funding for new medical research and technologies, including AI, to diagnose and treat people in emergency medical situations?

I spent my career in employee benefits consulting and have found that virtually everybody understands the need for health insurance, if not for themselves, at least for their families. However, nobody thinks they are going to get in an accident, have a medical emergency or get hurt on the job, even though the CDC reports that one in five Americans will have an emergency room visit each year.

The big picture includes helping address overcrowded ERs and the waste of critical time, money and resources. There are now non-emergency call center operations in some local areas (you dial 311) to free up 911 emergency call center time; these need to be promoted. We need to fund community health centers so people can have access to primary healthcare without going to the local emergency room. Even people with health insurance are having lengthy delays in getting primary healthcare. Recent data show the wait times for new patients is 26 days on average. OBGYN and orthopedic wait times for new patient visits are even longer. 

I am delighted to see the growth of local urgent care facilities, which played a huge role in COVID-19 vaccinations, and the growing use of telemedicine – especially given the long waits for primary care visits. But for heaven’s sake, we need to properly fund the 911 call center operations and first responders and EMT squads around the country.

Now.

Paul Carroll

To start out, can you tell us a bit about your role at Conner Strong & Buckelew and how it has evolved?

Taruja Deshmukh

I joined the firm about 12 years ago working on the P&C account management side. I started as an account analyst and eventually moved into an account executive role, managing a book of business. About four or five years ago, I raised my hand to get more involved in projects focusing on data and new technology platforms. It was clear to me that there was going to be a lot of opportunity in that space, especially at a brokerage.

From there, I helped to form an internal insurtech practice group. I now lead our “labs. by Conner Strong” initiative, which is focused on improving operational efficiencies, enhancing the customer experience and creating an innovative and inclusive culture. I support the firm's relationships with external partners, both in the insurtech community as well as our initiatives with BrokerTech Ventures.

Paul Carroll

Twelve years is basically a lifetime in the insurtech world. How have you seen things evolve in those 12 years in terms of the technology you're able to use and what you're able to do with it?

Taruja Deshmukh

It's definitely come a long way. Usage has accelerated rapidly.

One of the reasons we decided to help launch BrokerTech Ventures was that, when we saw new technologies rolled out, those solutions were typically geared toward insurance carriers, consumers, clients or risk managers. They weren’t designed for brokers. Over the last couple years, we've been able to participate more to actually create and help scale solutions for brokers.

Paul Carroll

Can you tell us a bit about the work the lab is doing and how you identify and support those insurtechs that are relevant to brokers?

Taruja Deshmukh

With BrokerTech Ventures, which is the first broker-centric, broker-led insurtech hub of scale, we have created an ecosystem across the country—really the globe, considering the international outreach with our Israel and Latin American partners. Within that ecosystem, we attract insurtech start-ups by providing access to forward-thinking brokers, the ability to reach POCs [proofs of concept] and pilot with different partners, and by providing hands-on mentorship. The support we provide is both financial and strategic, and the wide distribution that we represent really appeals to insurtechs as they look to scale their companies.

Outside of the BTV accelerator program, we focus heavily on collaboration and employee engagement. We're looking at what the pain points are within different departments and ways to solve them. We are continually evaluating both start-ups and established insurtechs and providing the ability for employees to test out solutions to see what’s going to actually help our operations and our clients, and we engage with our external partners in sharing experiences and feedback on what has and has not worked.

Paul Carroll

What are people finding useful? What's the secret sauce?

Taruja Deshmukh

A big focus for us has been on data. The ability to extract and aggregate data in a scalable way and reduce our reliance on manual and time-consuming processes has had a big impact on our operations. We're better able to leverage unstructured data, including PDFs and handwritten documents, to enhance our analytical capabilities. We've also used RPA [robotic process automation] technology quite a bit over the last couple of years to incorporate more efficiencies into day-to-day processes. When it comes to our clients, we've also been able to elevate their experience by doing things like implementing a digital application platform and connecting them with tech-forward risk management tools like wearable devices and sensors.

Paul Carroll

There's so much unstructured information out there. Eventually, AI will get to the point where you can get a recommendation that is much better for the underwriter or you can handle the claim or whatever. In the meantime, you can certainly amass all the information more efficiently.

Are you doing anything with ChatGPT?

Taruja Deshmukh

We're in the early experimental stages right now. There are some folks who are embracing the technology and others who are more skeptical, especially considering data security issues. But, overall, we understand the potential it has and are testing use cases using non-proprietary and non-confidential information to see how ChatGPT can help teams perform certain tasks quicker with a head start from AI. We're also looking at long-term ways that we can harness the power of generative AI to have an even bigger impact on our operations, including with training and development and accelerated data analysis.

Paul Carroll

With the lab, you find yourself collaborating with other brokerages on technology, That must be a little weird.

Taruja Deshmukh

It actually works very well. One of the main objectives in creating BrokerTech Ventures was that we can have a greater impact on the industry working together rather than any one firm working on its own. The collaboration with like-minded brokers has been invaluable. And the access to insurtechs through

the accelerator program has definitely helped us with our innovation objectives. The partners in BTV have been very open. Many of us are trying to solve the same pain points, and it's allowed us to leverage the collective innovative thinking of brokers and carriers from across the country.

Paul Carroll

You're one of the people who deliberately went into insurance, I talk to so many people who say they just fell into it as a career, but you actually studied it at Temple. Could you ever have imagined yourself evolving into this sort of role? Tell me a little bit about that journey.

Taruja Deshmukh

No, I would not have pictured myself where I am today. When I decided to major in risk management and insurance, my main objective was just to get a job when I graduated. I started college in 2007, and then in 2008 the economic crisis happened. Seeing all of those people struggling to find jobs scared me a little. I was in the business school trying to figure out what to major in when I happened upon risk management. I liked the material that we were studying, and Temple University has a really great risk program that had some unheard-of, like 90-something percent, job placement rate upon graduation.

Paul Carroll

People talk a lot about the war for talent, and it seems to me that when you start talking about doing the kinds of things you're doing, that might be a way to get people more revved up than they would have been about the industry.

Taruja Deshmukh

I 100% believe that. I think embracing technology and innovation is critical when it comes to attracting and retaining the next generation of talent. Recruiting for the insurance industry is already a challenge. Not many individuals even know about insurance and all of the opportunities. And once we bring people in, we can't undermine our efforts by not giving them the tools and technology they need to excel in their roles.

Paul Carroll

If we have a conversation five years from today, what accomplishments will you tell me about based on the kind of work you're doing now?

Taruja Deshmukh

A longer-term goal is to change the mindset of the way we're doing business to be a much more data-driven process. That's a challenge. But data is key.

Today, we rely quite a bit on disparate, legacy systems. Ideally, I would like to see a more advanced foundation, where our data is connected, visible and easily accessible, which creates a better framework for standardization, increased automation and the reduction of time-consuming manual work.

If we can do that, then people can instead spend more time focusing on the important things: talking to clients, digging into exposures, building solutions and improving program design.

Paul Carroll

Thanks, Taruja.

About Taruja Deshmukh

Taruja Deshmukh is the InsurTech Solutions Manager for Conner Strong & Buckelew. In this role, Deshmukh leads labs. BY CONNER STRONG, the firm’s centralized innovation hub, focused on improving operational efficiencies, enhancing the customer experience, creating an innovation and inclusive culture, and driving innovation forward in the industry. Deshmukh manages various projects designed to explore, evaluate, and implement insurtech solutions to achieve the firm’s innovation goals through collaboration with leadership across all departments and active engagement with employees. Deshmukh also supports relationships with external partners in the insurtech community, as well as the company’s initiatives within BrokerTech Ventures, the first broker-centric, broker-led insurtech platform. Deshmukh joined Conner Strong & Buckelew in June 2011, after graduating Temple University with her undergraduate degree in Risk Management & Insurance and International Business. While at Temple University, Deshmukh was actively involved in the Risk Management & Insurance program and completed internships with Travelers Insurance and Marsh USA. Most recently, Deshmukh earned her AIDA (Associate in Insurance Data Analytics) designation, which focuses on the conception and application of utilizing big data in the insurance industry and adopting innovation into the company culture.

Some years ago, a friend and former colleague wrote a book about pioneering companies that mentioned a bakery franchise that had the motto, "Nobody is as smart as everybody." The company's bakeries around the country put that motto into practice by not only sharing recipes but also by sharing insights on, say, how rainy weather affected walk-in traffic. 

I've stolen... er, borrowed... er, cited... that idea frequently. In fact, it's the organizing principle at Insurance Thought Leadership, where we provide a platform for the best thinkers with the best ideas on innovation in risk management and insurance. I know a lot of smart people, but -- repeat after me -- nobody is as smart as everybody.

That motto is the background for my interview this month with Taruja Deshmukh, insurtech solutions manager at Conner Strong & Buckelew. It is a superregional broker based in Camden, NJ, with offices up and down the East Coast, with about $175 million in annual revenue and with aggressive goals for growth. 

As she explains, Conner Strong has become a leader in BrokerTech Ventures, which has pulled together roughly a dozen brokers and a dozen carriers to take advantage of a variety of technology innovations and help brokers address a variety of pain points, especially those that require so much manual, time-consuming work. 

I think you'll find her approach illuminating.

Nobody is as smart as everybody.

Cheers,
Paul

4 PRINCIPLES OF SUSTAINABLE SELLING

Sustainable business is higher-quality business. It’s achieved by getting clients to not just buy but to also “buy-in.”

The first time I really thought about wiring the world with sensors came in 2007, when I was speaking at a boutique conference right after -- to drop a name -- Mike Mullen. Mullen was at that point the chief naval officer and a few months later was named chairman of the Joint Chiefs of Staff.

He stayed for the full three days of the conference, and I kept bumping into him at the coffee bar, where I found him charming in a geeky, four-star-admiral kind of way. I've always appreciated it when famous/important people can laugh at themselves, and he told me he'd been surprised to learn that one of the perks of becoming chief naval officer was that then-President George W. Bush invited him to the National Prayer Breakfast, where Bono would speak. 

"Bono?" Mullen said he asked himself. "The singer who was married to Cher? Didn't he die in a skiing accident 10 years ago?"

Fortunately, Mullen wasn't there to talk music or pop culture. He wanted to lay out an idea he called the "1,000-ship navy." The U.S. has some 250 ships in active service at any given time, so he wasn't just describing a U.S. initiative. He was talking about finding a way for many of the world's navies to coordinate on issues of common interest and patrol the oceans in ways that no single navy could manage. He especially had his eye on the Somali pirates who were such a scourge at the time -- and a coalition of more than a dozen nations did, in fact, cooperate and greatly reduce piracy by 2010.

With those conversations as a starting point, I've followed a variety of attempts since then to wire the world with eyes and ears and all sorts of other sensors, some on the ground, some in the air, many in space. And we're making great progress.

Advances in data collection and in the supercomputers that make sense of all that data are helping us predict the paths and intensity of hurricanes and other types of extreme weather, which means governments and insurers can help protect people and their possessions. Advances will also help governments and insurers reduce fraud.

Way back in 1987, when I was young and invincible and spent 27 days sailing across the Atlantic in a 42-foot boat as a crew member in a race, we could only get a satellite fix on our position six times a day. We got so little weather information that we stumbled into 12 days of nearly constant storms and a stretch of 70-foot waves that caused such mayhem on the QEII that there were national news stories.

(Did I mention that I'd never sailed before? Or that I was at the helm in the middle of the darkest night imaginable for some of the worst of the storms, with the rain blowing so hard in my face that I couldn't have seen anything anyway? Digression.... I know....)

Today, my particular form of recklessness would barely be possible. There are so many satellites up there that they're in danger of running into each other. They will tell you precisely where you are at any moment, even in the middle of an ocean. They will also give you such good information on the weather that you won't, just to pick a situation at random, head straight toward the middle of a massive low-pressure system and spend 12 days getting beaten silly by storms in a little boat, 1,500 miles from the nearest land.

The processing of the data from all those satellites has maybe moved even faster than all the launches. The MIT Technology Review reports that, because of advancements in supercomputers, "Average errors in hurricane path predictions dropped from about 100 miles in 2005 to about 65 miles in 2020. The difference might seem small when storms can be hundreds of miles wide, but when it comes to predicting where the worst effects from a hurricane will hit, 'every little wiggle matters,'" according to the head of the Hurricane Specialist Unit at the National Hurricane Center. And two new supercomputers delivered to the National Weather Service at the end of 2021 should continue the progress. 

The article adds: "Understanding and predicting hurricanes’ intensity has been more challenging than predicting their paths, since the strength of a hurricane is driven by more local factors, like wind speed and temperature at the center of a storm. Still, intensity predictions have also started to improve in the past decade. Errors in the intensity forecast within 48 hours decreased by 20% to 30% between 2005 and 2020."

A more recent MIT Technology Review article says AI is even getting better at predicting the intensity of storms because it is being trained on the basics of the physics that determines intensity, not just on historical storm data. That sort of improvement might have, for instance, mitigated the disaster in Ft. Lauderdale, Florida, in April, when what was expected to be a routine thunderstorm lasted hours and dumped some 25 inches of rain. 

Getting better at predicting paths and intensity will at least allow for enough warning that residents can evacuate ahead of a major storm and will save lives. The improvements may eventually also allow for people to do a much better job of securing their homes before they leave.

The profusion of satellites is also making it far easier to track shipping, helping governments and insurers spot fraud. Some shippers have figured out how to turn off transponders that broadcast where their vessels are and use sophisticated technology to "spoof" their locations so they can appear to be in international waters while actually picking up Russian oil or delivering cargo to a pariah nation such as North Korea. But those ships can no longer hide from satellites. So governments can know when rogue shippers and their national sponsors are violating sanctions, and insurers can know when shippers are violating the terms of their policies.

The world is becoming so wired that military analysts are using earthquake sensors (underground, not in space, in this case) to track where Russian missiles and bombs are striking in Ukraine. As a result, the analysts not only have pictures that document the damage from the attacks but can show exactly when they occurred, based on the readings from dozens of earthquake sensors nearby -- information that could be useful in any war crimes trials.

We have a long way to go before the world is truly wired, but we've come a long way, with great benefits for governments, citizens and insurers -- and any 20-something kid reckless enough to decide it'd be cool to sail across an ocean.

Cheers,

Paul

KEY TAKEAWAY:

--Generative AI will automate processes, free up time for personalized care, help detect fraud, improve employee morale and make underwriting more accurate.

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The launch of generative artificial intelligence (AI) will be a seismic change in how the insurance sector operates, fast-tracking the industry toward intelligent, automated and customer-friendly claims management.  

What’s New About Generative AI and Why It Is So Important 

The first step to harnessing the power of generative AI in insurance is to understand this new capability and how it differs from current AI applications. The insurance sector is most familiar with discriminative AI and its ability to identify and classify patterns in existing data. Generative AI goes beyond organization and pattern recognition. Using deep learning techniques like neural networks, it creates content and conclusions; it not only learns patterns from large datasets but also generates new data that follow those patterns.

See also: 3 Key Uses for Generative AI

The Future With Generative AI

Here are five ways generative AI will transform claims and case management. 

1. Automating processes and providing answers to questions. Adjusters and nurses spend countless hours reading information, spotting action steps, communicating findings and documenting. With generative AI, this tedious process can be automated. Instead of humans reading, analyzing and updating, the technology can complete the research and analysis and can draft conclusions. Medical documents are summarized, keywords are extracted and issues that need attention are brought to the adjuster’s attention. Generative AI also allows users to query the system via keyboard or voice to get answers to particular questions. 
2. Transforming customer service and enabling person-centered care. Generative AI will transform the insurer/customer relationship in three ways:
   • Because adjusters and case managers will spend much less time analyzing and processing information, they will have more time with their customers, listening to and responding to their needs.
   • As adjusters and case managers focus more on patients and customers, this personal attention adds the “human touch” to an impersonal and confusing process.  People now expect higher personal regard and customer service in all transactions; this new type of experience meets those rising expectations for the insurance sector 
   • Generative AI provides intelligent, automated, up-to-date information to customers or injured workers at their convenience and from multiple devices. Intelligent chatbots can “think” through a conversation and respond appropriately as questions evolve. This capability provides the instant, accurate information that customers today have come to expect. 
3. Detecting fraud. Just as generative AI can identify potential problems in a developing claim or case, it can also spot anomalies that might indicate fraud. These danger signs can include excessive use of medical resources, inconsistent injury complaints or lengthy recovery periods with slight improvement. Generative AI can also find information about previous events or claims, incidents and pre-existing conditions that might lead to questions about a claim’s legitimacy. Adjusters, fraud investigators, healthcare providers and other stakeholders can then look further to determine what is going on. 
4. Increasing employee satisfaction. When insurance employees can spend less time handling objective, repeatable administrative tasks and more time on the people aspects of their jobs, job satisfaction will increase.  Re-engineering these jobs will lead to higher satisfaction, more attractive career paths for recruits and retention of valued employees.  
5. Lowering risk. Third-party administrators and their customers will achieve a significantly greater understanding of risk factors with generative AI algorithms. As a result, they can develop more accurate underwriting models and strategies for claims mitigation. They can then more accurately price insurance policies and reduce the risk of losses due to inadequate premiums. Conversely, they can avoid overcompensating for risk factors. 

The improvements powered by generative AI will transform claims management and the insurance world, revolutionizing how carriers, third-party administrators and medical management firms operate and the results they can deliver. 

In this new world, time-consuming, manual tasks are eliminated, information is automatically analyzed and presented with action steps and all stakeholders can interact with a humanized intelligence that makes the process easier and more personalized. All participants will benefit from higher efficiency and accuracy, reduced costs, improved employee retention and better customer service.

Implementing a multichannel approach to customer experience is a continuous project for the modernizing insurance firm. With offline interactions yet to rebound since the pandemic drove consumers online, "low-code" digital tools are simplifying CX management and providing consumers more self-service capabilities. 

Customer journeys are increasingly digitized, and low-code and AI-powered platforms can be deployed to spin up virtual agents and build websites and digital applications, among other uses. While the insurance industry has been slow to adopt self-service capabilities, potential improvements to digital experience beyond the more traditional live agent chat or phone call can place more power in the hands of customers.

Low-code tools require little technical expertise to use, allowing those without a development background to play a role in the rollout and improvement of digital experiences. Take, for example, a platform managing a customer-facing virtual agent. With a low-code platform on the back end, employees from different specialties and points across the customer journey can more directly provide input on the agent’s capabilities, subject matter expertise and position in overall CX. With technical barriers reduced, an enterprise can devote more resources to ideation and improvement.

Low-code customer service tools unlock more for firms than just saving time and resources. Maintaining customer satisfaction is a continual process, and seeking out channels that can quickly respond to and source feedback is most effective. With fewer barriers between ideation and deployment, firms can devote resources to improving customer journeys, which includes fine-tuning self-service capabilities.

See also: Unlocking the Power of 'No-Code'

Seeking Continuous Improvement to Empower Customers

Still, when it comes to adopting self-service, there is more that can be done. Improving a multichannel strategy requires a deeper examination of service flows, compiling details related to how frequently customers encounter barriers and pain points. And, despite the opportunities in self-service, research from Gartner underscores the need to allow for a smooth transition to a live support agent.

Taking a more responsive and agile approach to customer experience improvements, especially across channels, can feel like an immense undertaking. When using low-code platforms, where possible, teams can access additional resources without increasing their overhead, and develop more value for customers. If agents are saved time, their satisfaction with their roles can increase, just as a set of customers may be pleased to find an account-specific function that can now be done in less time and with more ways to do it.

Depending on the type of end-implementation, a low-code platform can also aid data collection, generating easy-to-digest suggestions to improve query resolution and real-time feedback on customer sentiment.

In the end, unique factors to both the contact center and the insurance industry require critical considerations to improve efficiency and customer satisfaction. A technical approach can be varied in its objectives, but placing emphasis on improving staff and customer experiences can enable more positive outcomes.

Low-code tools represent an opportunity to increase self-service functionality while encouraging firms to be more responsive in how CX is managed.

In the U.S. alone, a vehicle is stolen every 30 seconds, costing individual owners and businesses over $8 billion. With thieves also targeting individual parts such as catalytic converters, valuables stored in vehicles or on jobsites and expensive heavy equipment, fleet and field service organizations have been prime targets. 

These security concerns are plaguing mixed fleet organizations’ bottom lines at a time when they are already dealing with increasing fuel prices, a volatile supply chain and long-term inflation struggles, However, recent developments in tracking technology capabilities and artificial intelligence (AI)-powered software solutions have emerged as a formidable solution. 

Telematics-Driven Asset Management

Mixed fleet industries, those with assets including vehicles and equipment, can practice best-in-class asset management by using telematics to secure their assets, identify larger work trends and implement necessary solutions more quickly. 

Organizations in industries such as construction or landscaping often conduct field service work that requires taking lengthy transportation routes to large job sites. GPS tracking enables operators to pinpoint their assets' locations at all times, whether en route or left overnight on a jobsite. Further, GPS technologies can be used to install geofencing boundaries around work sites so organizations can be notified if an asset is removed. 

These tracking technologies significantly increase the likelihood of recovering stolen assets while sending a warning to potential thieves about the increasingly innovative and effective security capabilities their targets possess. 

Ensure Greater Accountability and Operational Efficiency

Tracking is only one-half of the telematics approach to asset management. Its broader capabilities are only realized when organizations also use robust, AI-driven software solutions.

For example, GPS tracking technologies can be paired with AI-powered cameras to automate review and evaluation, so managers only receive alerts when specific security and behavioral thresholds are exceeded. This process fast-tracks the traditionally time-consuming process of manually reviewing security footage. Most AI-powered security cameras are also capable of live streaming, enabling real-time monitoring of transportation routes and job sites. 

This risk identification system employs machine learning, computer vision and edge computing to automatically detect specified incidents. For drivers, these might include unsafe and inefficient processes such as idling or speeding violations. For equipment operators, these might include improperly storing equipment or obstructing cameras. As a result of greater accountability, mixed fleet organizations can improve their fuel efficiency, asset lifespan, operational efficiency and worker safety. 

See also: Quantum Technologies, Cybersecurity and the Change Ahead

Turning GPS-Tracked Data and Analytics Into Solutions

AI-powered telematics solutions are not limited to operation and field teams, as office employees can also be cued into the real-time processes and results stemming from transportation routes and job sites. Office workers can identify larger trends and implement necessary solutions, such as for inventory management and maintenance. 

Storing data and relevant insights in the cloud ensures easy and simple accessibility. While cloud-based accessibility isn’t anything new, when combined with available automated asset tracking it can help employees simplify the auditing process and streamline maintenance logging. As a result, mixed fleet organizations can safeguard sensitive information and ensure regulatory compliance. 

Integrating complex, automated GPS tracking software shows insurance providers that an organization is deeply committed to reducing potential risks concerning both physical and digital assets and can reduce premiums.  

Protecting Indispensable Assets Elevates All Aspects of the Business 

GPS tracking is simultaneously a simple, self-explanatory practice and a complex, tech-centered best practice for mixed fleet organizations of all sizes.

Fleet and field inefficiencies waste valuable time and money. Telematics technology enables organizations to harness AI-powered analytics to make data-driven decisions that secure inventory, extend asset lifespan and increase operational efficiency.