KEY TAKEAWAY:

--An organization’s goal should be to put in place a common resource allocation tool and real-time reporting mechanism while standardizing activities and roles aligned to individuals.

----------

As the possibility of a global recession continues to be raised by economic prognosticators, insurers are looking for innovative ways to tighten their belts. One option is slashing labor costs. However, the talent crisis plaguing the insurance industry means mass layoffs are ill-advised—400,000 insurance employees are predicted to retire within the next few years. Adding to this challenge, the generation that would theoretically be replacing the retiring generation has little interest in doing so—eight out of 10 millennials surveyed had a limited understanding of the wide-ranging employment opportunities the insurance industry can offer. 

Savvy companies recognize layoffs can stymie an organization's future growth once the macroeconomic outlook flips bullish; instead, they’re figuring out how to prioritize, measure and manage capacity—to put the right people on the right projects and ensure effective and efficient execution.

One underused method is developing structured approaches to resource allocation. Approached in a traditional, system deployment-led way, this process can often take more than a year to implement. However, it’s now possible to realize gains in resource management and efficiency much more quickly. And there’s never been a more critical time.

Better resource management boils down to prioritizing and sequencing how to allocate talent to new or existing projects. In a recent survey of 39 companies, Resource Management Institute (RMI) concluded there are many areas that are ripe for big gains in efficiency. They learned that forecasting and capacity planning, along with developing a skills inventory, continue to require improvement. Governance was another area where vast improvements could be made. Without introducing good forecasting, supported by a more exacting skills database, the resource management process remains largely ineffective, and failures are inevitable.   

A more disciplined strategic road map will help insurers avoid spending time and resources on projects that are lower-priority. Some of this process involves figuring out which projects are either strategically important to the firm’s long-term vision or produce the most short-term profit—but prioritization is only part of the needed input. The success of the approach hinges on understanding what projects people are currently working on and what they’ll be tackling in the next three to six months, then identifying priorities from the top down, ensuring that sufficient resources are allocated to prioritized matters and getting a real-time picture of how people have been allocated and how projects are staffed.

Briefly put, our recommended approach to redesigning the process distills down to having a formalized, centralized, standardized demand management/intake process, cross-organization capacity planning and the right tracking and reporting tools.

Done manually, getting just a snapshot of current project staffing can take a month or more, but with a little help from data science it’s possible to get this down to near real time. With an accurate view of where gaps exist, more advanced questions can be asked, such as, “If key projects are not properly resourced, is it possible to pull people from other, less important internal activities to deliver the projects on time without having to hire new hands?”

An organization’s goal should be to put in place a common resource allocation tool and reporting mechanism while standardizing activities and roles aligned to individuals. While it’s possible to start with Excel spreadsheets, ideally companies will want to move on to a more specific resource management software tool. Data that previously took weeks to collect becomes immediately visible.

Traditionally, insurers use internal systems to track their own resources’ time on projects, but often these tools don’t provide a broader view of what is happening now or what should be happening going forward. Additionally, in our experience, time tracking is often a neglected area of resource management.

Establishing a feedback loop between historical time tracking and forward-looking resource planning is critical. By analyzing historical data, a firm can have more reliable estimates of any new project’s resource demands and completion timeline, which can then be used for more accurate projections. In addition, in this tight labor market, you certainly don’t want to lose good people because you are burning them out—it’s important to have reliable data to identify people who are overworked and enable discussions about how to remedy this situation.

A handful of insurers are catching on to this need, and in an economic environment where revenues are not necessarily growing—indeed, when fast-growing revenues are no longer present to disguise inefficient processes—there’s a strong motive for taking a strategic approach to solving the resource gap. It’s not going to be solved simply by recruiting, hiring more contractors or going to the market and paying bonuses to hire people away from competitors—warehouses and logistics are currently the only industries with a positive correlation between signing bonuses and application rates. In this tight market, increased use of an insurer's existing workforce becomes the more attractive option. 

However, modernizing an insurance company’s resource management practices doesn’t just mean implementing a data-collecting tool. There’s a cycle, with a process for getting the right data and then using it correctly. The dashboards and the management process must work in concert with each other.

For example, one insurance organization we’ve worked with believed at the outset that they had a large gap of resources in project delivery, even though they did not have any evidence other than anecdotal feedback from managers. A high-level initial analysis seemed to indicate that the gap in resources was greater than 60 total people, representing more than 20% of their workforce. Data was fed in and a rigorous process established, role data was set accurately (e.g., “Is a data manager also a developer?”) and analysis took place of people, projects and time horizons. The gap reduced to a much more manageable 20 resources. 

With the right details, the gaps for specific roles on specific projects became clearly visible and an action plan was detailed on how to address each gap. It became possible to trust a “single source of truth” for resource allocation, no longer relying on multiple ad hoc spreadsheets of questionable accuracy. It now became possible to answer resource allocation questions in a few minutes, when in the past this would have taken a week.

See also: Value of Optimized Resource Planning

Spread that approach across an entire portfolio of projects and you can have a large overall impact in time savings and efficiency of staff use. Part of the problem, particularly during COVID, had been the lack of physical cross-team communication. But by doing a better job of using digital resource management tools, insurers can bridge this gap. Though some organizations have invested significantly in incorporating cutting-edge software to do this, the investment is frequently lopsided—optimizing individual silos as opposed to taking a broader view across the entire value chain or across different organizational teams.

While it might be tempting to make sweeping overhauls of the resource management function, insurers must remember that the most effective changes are gradual. There are several intermediate stages between an organization’s current reality and its goal. The first step toward using resources effectively is to implement monthly resource management reviews focused on identifying resource gaps, their impact and how to address them. If an organization has no resource management to speak of, a simple manual Excel process can be the steppingstone needed before incorporating more sophisticated and automated tools.

RMI’s recent survey looked into factors that prevent the efficient use of resource management tools. They found that 54% of organizations have no access to real-time project key performance indicators (KPIs), and nearly 35% of project managers formulate resource plans using Excel. A full 77% of survey respondents were not using resource management software to generate “what if” scenarios. Many of those surveyed expressed distrust and frustration with the current state of digital resource management tools. The areas for improvement they identified were varied—forecasting and capacity planning (83%), reporting, dashboards and data analytics (79%), skills development planning (65%), skills inventory and database capabilities (64%) and project staffing (52%). While the greatest deficiencies they identified remain unchanged from year to year, a desire for skills development capabilities has been gaining ground, up 13% from RMI’s previous survey.  In short, resource management software could be used more effectively. 

Once an insurer has spent time mastering the fundamentals, they’re free to add packages that contain advanced technology and analytics. However, overlaying new software onto an organization’s deficient resource management function isn’t an instant fix—the software must be tailored to the unique goals and gaps in the organization. Incorporating management software can bring about more questions than answers, often shedding light on other deficient areas in a company’s infrastructure.

In RMI’s research, 64% of those surveyed said that even after their resource management software was implemented, it still lacked some of the features they needed. 56% of participants claimed their software lacked integration with other front- and back-office systems for forecasting. Even after the incorporation of modern tools, one weak link in the chain can still invalidate much of the software’s impact.

In the post-pandemic landscape, achieving a cross-organization view is easier said than done. The prominence of work from home means project staffers operate in an increasingly fractured and isolated environment. As a result of the atomization of the workforce and separation of teams, it’s difficult to achieve an integrated view across the entire project portfolio. But it can be done.

By integrating a centralized demand resource management process with better use of resource management software tools, organizations can run leaner and more appropriately staffed projects.

KEY TAKEAWAYS:

--Security teams often have to play whack-a-mole, addressing cybersecurity issues as they occur but without getting ahead of malicious actors.

--Integrating new technologies--Digital Risk Protection Services (DRPS) and External Attack Surface Management (EASM), integrated with Attack Surface Management (ASM)--gives companies a comprehensive, automated view so they can identify and manage vulnerabilities and potential entry points for threat actors.

----------

Given today's expansive digital landscape and widening attack surface, the volume of threat intelligence data has reached unmanageable levels. Security leaders must reduce organizational threat exposure across a rapidly proliferating attack surface but typically lack the means to identify the threats that pose the most significant risk to their organizations. Security teams play whack-a-mole, addressing issues as they occur without getting ahead of malicious actors.

Cyber threat intelligence plays a vital role in cyber warfare and is no longer a "nice-to-have" but a "need-to-have." With the right tools, teams can derive critical insights into the emerging tactics, techniques, vectors and procedures that could expose their network to attack. But selecting the right threat intelligence products and services to maximize business value is not easy. This article provides an overview of the threat intelligence space and offers a guide for how to find the right solution(s). Essential points include:

• The importance of context and accuracy in threat intelligence offerings
• The convergence of CTI, DRPS, and EASM
• The role of data analytics and automation in threat intelligence
• The need to tailor predictions and risk assessment according to business criticality

Gain an accurate picture of the threat landscape through context and accuracy

The value of threat intelligence depends not only on the relevance and timeliness of the information. Perhaps more importantly, threat intelligence must provide critical context about threat actor groups and their tactics, techniques, procedures, vulnerability exploits, indicators of compromise and more.

For example, through the combination of advanced AI, machine learning and processing and analyzing comprehensive data from millions of online and dark web sources, organizations can receive early warnings of potential risk to their network. When threat intelligence blends context about each organization's unique attack surface and assets, security teams can operate more efficiently, knowing that they're taking action to mitigate the most urgent, dangerous threats to their corporate environment.

See also: Say Goodbye to Cyber's 'Dating Profile'

Integrate CTI, DRPS and EASM for a comprehensive view

With so much at stake and so many dollars invested in a wide range of cybersecurity solutions, organizations need to prove the value of their security stack. This need drives companies toward consolidating vendors and products to simplify their solution suites. As a result, threat intelligence vendors are beginning to integrate features from adjacent markets, such as Digital Risk Protection Services (DRPS) and External Attack Surface Management (EASM).

With DRPS, companies proactively monitor their digital footprint across the surface web and underground sites, forums and marketplaces, identifying and mitigating risks. Integrating EASM discovery capabilities with Attack Surface Management (ASM) gives companies a comprehensive view of their unknown externally facing assets so they can identify and manage vulnerabilities and potential entry points for threat actors. By combining these solutions with threat intelligence, organizations gain a unified view of their complete asset inventory and overall threat exposure.

Enhance CTI outputs with data analytics and automation

In its Market Guide for Security Threat Intelligence Products and Services, Gartner notes that analytics, data science and automation are becoming critical components of threat intelligence solutions. These capabilities can significantly reduce the time and effort needed to operationalize threat intelligence across large, mixed datasets.

CTI that autonomously infiltrates deep, dark and clear web sources enables frontline defenders to extract, process, correlate and analyze data in real time. These benefits are more significant when adding features like graph analytics, link analysis and rich threat actor modeling.

Additionally, advanced capabilities like entity extraction, visual graph analyzers, peer network analysis and a customizable dashboard interface help organizations understand their threat exposure at a glance. In essence, next-generation CTI solutions that blend robust analytics with automation and other cutting-edge capabilities give customers powerful data to rapidly respond to critical threats and mitigate risks before they can be exploited.

Tailor predictions and risk assessments according to business-criticality

Organizations can optimize their threat intelligence investments by developing a CTI program tailored to their unique business needs, risks and objectives. By refining threat intelligence with the organization's critical internal context, security teams can filter out irrelevant data and focus on the threats and insights that matter most. Additionally, business executives are better equipped to prioritize resources.

These benefits are another reason for integrating an EASM solution with CTI. EASM continuously discovers and classifies known and unknown networked assets that could expose an organization to risk, while combining the two technologies enables companies to tailor threat intelligence to their unique attack surface. 

See also: Cyber Insurance Market Hardens

Conclusion

The rapidly expanding digital landscape and proliferation of potential attack vectors have created an increasingly complex and challenging environment for security teams. The accelerated pace of technological advancements means that manual and hybrid solutions are no longer adequate to protect the expanding attack surface at the scale and sophistication of emerging threats. Threat actors increasingly leverage AI and automation, making it imperative for security vendors and defenders to incorporate these technologies in their cybersecurity strategy.

KEY TAKEAWAYS:

--We saw that there were nonprofit and government agencies that were getting neurodistinct individuals ready for employment, but the big question was: Who's getting employers ready? We exist to be a connection between employers and this untapped neurodiverse talent pool.

--Business partners who sign up and commit to hiring and advancing neurodiversity and disability inclusion through NTW will receive neurodiversity inclusion training courses for managers and access to neurodiverse job candidates, 70% with bachelor’s degrees, who will be pre-screened and trained in workplace etiquette, as well as insurance principles, insurance management systems and insurance transaction basics.

----------

Every July, organizations commemorate the passage of the landmark Americans with Disabilities Act (ADA) in July 1990. Disability pride is defined “as accepting and honoring each person’s uniqueness and seeing it as a natural and beautiful part of human diversity,” according to the Disability Community Resource Center.

Disabilities are unique and can encompass a range of conditions, both apparent and not apparent, and with varying degrees of impact. Neurodiversity embraces a diversity of minds and encompasses non-apparent conditions such as autism, dyslexia and ADHD.   

Inclusion for neurodiversity celebrates the strengths of all minds and responds to challenges without shame, removing the stigma and misperceptions of capabilities that for far too long have been attached to having a disability. It also highlights a segment of the disability community that has often been overlooked because of its non-apparent nature.

Finding and screening job candidates was the No. 1 issue facing independent insurance agencies in 2022, according to the 2022 Agency Universe Study—retaining its position as the top challenge from 2020. However, despite representing a skilled, educated, untapped talent pool, neurodiverse candidates are largely underemployed and represent a solution to independent insurance agencies’ talent problem.

Neurodiverse minds have unique ways of interpreting the world around them, thinking, communicating and processing information. In many professions and day-to-day tasks, their distinctiveness offers certain advantages, such as memory, mathematics, concentration, data analysis and pattern recognition Neurodiverse individuals might need accommodations in the workplace due to various vulnerabilities because of their mind’s profile, including susceptibility to loud noises and stimuli or different needs for processing information and communicating. What many employers do not know is that these accommodations are low-cost and actually help an entire team perform work more effectively; they are rooted in what enables every mind to perform optimally.  

In an open letter published in 2021, Sir Richard Branson, founder of the Virgin Group, remarked, “The world needs a neurodiverse workforce to help try and solve some of the big problems of our time.”

Between 15% and 20% of the population is neurodiverse, according to the National Library of Medicine, which includes up to 10% of people who are diagnosed with dyslexia, 6% with dyspraxia, 5% with ADHD and 1% to 2% with autism.

According to recent estimates from the Centers for Disease Control and Prevention, 1 in 36 children is on the autism spectrum. 50,000 teenagers with autism leave school each year, and there are now approximately 2.5 million adults with autism living in the U.S., according to the advocacy organization Autism Speaks. Underemployment in the neurodiverse demographic is exemplified in the fact that only 22% of autistic adults are in any form of employment, according to the National Autistic Society. 

See also: Keys to Finding and Nurturing Talent

To address the 80% unemployment rate, my co-founders and I started NeuroTalent Works (NTW), a nonprofit dedicated to advancing neurodiversity inclusion and employment in the workplace, and in July 2023 launched a (Neuro)diversity in Insurance Job Training & Hiring Program in partnership with the California Department of Rehabilitation. This industry-specific program encourages and enables job opportunities in the insurance industry for individuals with disabilities and neurodistinctions. Through partnership with Insurance Community University, job candidates are provided training on fundamental principles of insurance.

Initially focused on autistic job candidates, we have branched out to all neurodiversity and have a two-pronged approach, connecting business readiness and talent readiness for neurodiversity inclusion and employment.

We saw that there were nonprofit and government agencies that were getting neurodistinct individuals ready for employment, but the big question was: Who's getting employers ready? We exist to be a connection between employers and this untapped neurodiverse talent pool.

Business partners who sign up and commit to hiring and advancing neurodiversity and disability inclusion through NTW will receive neurodiversity inclusion training courses for managers and access to neurodiverse job candidates, 70% with bachelor’s degrees, who will be pre-screened and trained in workplace etiquette, as well as insurance principles, insurance management systems and insurance transaction basics.

As we started working with business partners, we started to see that there's a difference between being ready for employment and being ready for a professional setting where there are many hidden rules of the workplace. We provide what we call "final-mile training" to debunk some of these unwritten rules of the workplace that some of us might pick up on but someone with autism might not pick up on as easily.

A key part of the employee readiness portion of NTW’s training is interviewing, which is the biggest barrier to employment for the neurodiverse community because the traditional interview relies on oral communication and persuasion skills. NTW attempts to overcome this barrier by using skills-based interviewing, including training on a mock agency management system (AMS), to prepare candidates and provide a medium for demonstration of skills and experience of their capabilities to employers. This provides a more equitable approach to hiring and enables all candidates to demonstrate and showcase their skills for a job.

The program also offers employers a grant for the first two weeks of employment of individuals hired through the initiative. In addition, NTW will provide six months of support and coaching over 25 sessions post-hire to facilitate talent onboarding and a smooth transition for both the new hire and hiring manager.

One of the companies that first signed up for our program—and gave NTW the impetus to delve deeper into the insurance industry—is Weaver Insurance & Associates in Acadia, California, which was recently announced as a monthly winner of Liberty Mutual and Safeco’s Make More Happen program. 

Make More Happen partners with independent agents by awarding grants to nonprofits that agencies support, as well as providing social media and public relations support to help agencies spread the word with awareness campaigns.

“We met [with NTW] to discuss their business plan, and, at the time, they had not landed on an industry to work with,” recalls Dana Dattola, agency principal of Weaver & Associates. “We suggested insurance due to its detail-oriented tasks that require skill and knowledge.”

After hiring her first employees, Dattola found that “training posed challenges as we lacked established processes and procedures. But this turned out to be beneficial for all employees, not just those who are neurodiverse, as it enhanced our training methods.”

Despite some challenges, as with any new hire, “the benefits are great,” Dattola says. “You have employees who are grateful for their job, try their hardest and don't tend to burn out or skip steps in processes.”

“There are so many smart individuals looking for good, long-term jobs,” she adds. “Staff turnover is the toughest thing with owning a business, and I feel that once you make the investment in the staff, you have more loyalty than from your average employee because they are grateful that someone gave them the opportunity and took the time with their training.”

The talent shortage, particularly for entry-level roles, has encouraged agencies to look offshore for assistance with repetitive and administrative tasks. However, those companies face similar turnover issues. 

See also: What Are Insurers’ Top Talent Objectives?

But the neurodiverse, and specifically autistic, community can thrive in routine and predictability and are detail-oriented, and many would want to continue such work for several years. Some companies that hired with us ended up letting go of a couple of their outsourced workforce companies so as to invest in the community, do something meaningful and give an opportunity to a community that's been so overlooked.

Among the other benefits of hiring neurodiverse candidates are cultural benefits to the agency, specifically in the eyes of younger employees, who more frequently demand that their employers are engaged with community-focused and charitable initiatives and demonstrate their commitment to diversity, equity and inclusion through action.

But most of all, managers who work with us tell us it’s the most meaningful thing they’ve ever done in their careers because it’s made them a better manager for all their people. When you understand an individual’s needs—both their challenges and strengths without shame—you’re going to be a better manager for everybody, not just an individual.

To learn more and hire from NeuroTalent Works’ (Neuro)diversity in Insurance program, visit: www.neurotalentworks.org/insurance.

KEY TAKEAWAYS:

--One of the core problems that makes it difficult for large carriers to innovate with their data and IT strategy is the scattered architecture that is the logical result of growth and acquisitions over a long time. To address the challenge, many insurance IT leaders and consultants propose a central data lake or enterprise data warehouse that gathers all the data into one place. But it’s extremely difficult to execute a data lake or data warehouse project, and it usually takes years and hundreds of millions of dollars to implement.

--There is an often-overlooked alternative that stems from the microservices architecture that many startups have adopted: a federated data architecture. Instead of moving all the data from the different sources into one central location, a query layer is built on top of existing data sources and only gathers data upon request. What makes this approach much easier to set up and maintain is that there is no need to configure the architecture for storing and maintaining a large amount of data. 

----------

With all the buzz around generative AI, P&C carriers are rushing to evaluate how and where to best apply this emerging technology. But is the insurance industry ready for this next wave of innovation, or are the same limitations that have limited real progress in the past a cause for concern? 

There are positive signs. Recent innovations in data querying, caching, pipelining and transformation should give insurers reason for optimism. In fact, I’d argue that these innovations in underlying data architecture are as exciting for our industry as the changes we’re seeing in AI – if not more so. This article looks at how federated data graph technology can help carriers overcome long-standing obstacles in harnessing their data to fully unlock insurance’s AI moment. 

Insurers Can No Longer Afford to Underuse Data

One of the core problems that makes it difficult for large carriers to innovate with their data and IT strategy is the scattered architecture that is the logical result of growth and acquisitions over a long time. Of the top 10 P&C carriers in the U.S., the newest kid on the block was founded in 1937. This creates a multitude of challenges: There is a huge barrier for data engineers and analysts to derive actionable insights across different systems, and every new initiative takes 10x the time because it involves multiple data migration projects.

To address the challenge of disparate data, many insurance IT leaders and consultants propose a central data lake or enterprise data warehouse that gathers all the data into one place. Although this approach can solve the problem, it’s extremely difficult to execute a data lake or data warehouse project, and it usually takes years and hundreds of millions of dollars to implement. 

Building the jobs that move all data from different sources into one place is not easy, and even though there are open source solutions available, maintaining and building them requires skilled staff and can be prohibitively expensive. What’s more, once the data has been moved, it often requires significant transformation in the context of any given business use case.

In the case of mainframe data, for example, making even a minor change to the data format is non-trivial and may require workarounds because the people who know how to work with mainframe data are now few and far between. One global P&C insurance carrier we work with built a data lake, only to realize, after the multi-year project was completed, that they needed a way to transform the information from the data lake back into the mainframe format to keep their current business running. All this means that the promise of building applications on top of your data lake always seems “just around that next corner.”

Data Volumes Outpace Architecture 

According to Stanford University’s AI Index 2022, it is now a proven fact that data grows faster than Moore’s Law. In other words, the amount of data we collect tends to grow more quickly than the growth of our computing power and processing efficiency. This means data lake spending will only increase, just to maintain the large amount of data an insurance carrier collects year after year.

This issue manifests itself across the enterprise and is often felt acutely by front-line underwriters and operations staff who struggle to turn mountains of data into insights they can actually use to guide risk selection and portfolio management decisions. Underwriters routinely tell us that they aren’t swimming in data, they’re drowning. As a whole new generation of innovators continues to build more sophisticated data-driven insurance products – telematics, anyone? – these problems become worse, and the back-end IT challenge of data organization grows exponentially.

Consider a Federated Data Layer Versus a Data Lake

If an insurer is willing to pay and has the patience, the data lake may make sense long-term. But many carriers are under increasing pressure to implement new underwriting applications right now to improve the workflow and boost underwriting productivity and performance. They’re also working to come to grips with emerging risks like climate-change-related natural catastrophes, cyber attacks and social and economic inflation. For insurers that do not have a decade to wait, there is an often overlooked alternative that stems from the microservices architecture that many recent technology startups have adopted: a federated data architecture. 

Instead of moving all the data from the different sources into one central location, a federated data layer is a query layer built on top of the insurer’s existing data sources that only gathers data upon request. What makes this approach much easier to set up and maintain is that there is no need to configure the architecture for storing and maintaining a large amount of data. 

Using open source solutions like GraphQL and Apollo, insurers can implement the query-able data layer in less time than it typically takes to establish a data lake. Once the query-able layer has been established, the bulk of the work that remains to set up an agile and configurable federated data architecture is mainly in building out specific connectors for every source of data.

On top of shortening time-to-value versus a data lake, the federated data graph gives the end user the ability to access data in real time, which is great for building modern applications (for example, dynamic dashboards or workflows) on top of existing databases.

In an interview with Carrier Management, Greg Puleo, vice president, digital transformation at QBE North America ,explained the power of a modern underwriting application that leverages an underlying federated data graph: “We now have the chassis that we can start to bolt other things to, and all those other data providers now just become an API [application programming interface] integration seamlessly in the workflow. The underwriters can make better decisions using that data without having to do extra steps.” 

Challenges like retainment of data, change control and disaster recovery remain at the individual data sources, which most likely were set up to solve these challenges in the first place. As the insurance industry goes from static analysis and historical data to more dynamic and AI-powered models like "predict and predict," the ability for end users to access relevant data and insights in real time is essential.  

A Few Caveats

A federated data layer is not a “solve it all” remedy for an insurer’s ills. There are real challenges in maintaining the schema as data changes, and building customer connectors is not always an easy task given the number of legacy databases still around.

Today’s most popular policy administration systems and other core insurance systems are already 20-plus years old and are not designed for easy data access and sharing outside the system – and as insurance technologists know all too well, there are still mainframes and AS/400 midrange servers lurking in dark corners of the data center. 

Insurers Don’t Have to Do It Alone

The right insurtech partner can be of enormous value in helping insurers build out a modern data architecture in lockstep with efforts to build new applications and workflows. Insurers should look for partners who share their vision of how better data can fundamentally transform insurance and who have demonstrated experience in employing advanced technologies and architectures to solve long-standing data issues. In addition to augmenting internal IT resources and expertise, an insurtech partner often serves as a forcing function, motivating internal IT teams to move projects to the finish line.

"From a business perspective, we weren’t looking for a vendor,” Thomas J. Fitzgerald, former president of commercial insurance at QBE North America told Carrier Management. “We were looking for a partner. We were looking for somebody who could ultimately come in and understand the myriad needs that we had, and had the flexibility and the agility to come along on a journey with us." 

As with any large-scale change, it’s essential to have a destination in mind and to focus on what you’re trying to improve for your end users and the business. In this way, you can avoid “data modernization for its own sake’ and ensure that modernizing your architecture happens in the context of meaningful innovations to core insurance processes and workflows – things that can actually affect your users and lead to better business outcomes.

A Real-World Insurance Use Case

Let’s look at a real example of why a federated data graph can be advantageous from a business and end user perspective. Underwriters have three main levers that they can manipulate when balancing their portfolio: rate, retention and new business. The business challenge is that these levers often seem to work counter to one another. If you increase the rate for an account, for example, it may hurt your ability to retain the client when the policy comes up for renewal. It’s a constant balancing act for front-line underwriters to navigate the inevitable tradeoffs among rate, retention and new business.

So, let’s say you want to calculate your retention. Sounds easy, right? But not so fast. If policy administration information is dumped into a data lake or enterprise data warehouse, it is often dumped partially or without full context. For example, total premium on a property schedule and premium by coverage might be available for analysis, but premium by building/location or in relation to total insurable value (TIV) may not. 

Down the line, when the business wants to build a simple retention dashboard but chooses to calculate retention on a "same exposure" basis (i.e., accounting for changes in buildings or the value of those buildings, not just new premium/old premium), they often cannot do it. Inevitably, the data about the exposure base is trapped in two worksheets, one from each year, and so yet another worksheet is created to take those exposure bases and the premium values and calculate a simple metric.

When an organization builds a business-centric application using a federated data graph with direct connection to data sources, they often get ahead of the transformations for simple core metrics like retention. A data graph forces the business to organize their data in a way that is aligned with how the business operates, saving an enormous amount of time and effort down the road. 

In other words, without investing an appropriate amount of time into getting data into the format the business can actually use to measure its effectiveness and progress toward organizational goals, a data lake is simply a lake/sink. This often renders future application builders helpless – the data lake contains hundreds of thousands of data points, but the relevant data they need remains inaccessible.  

From the business perspective of empowering end users, a hybrid approach that recognizes that sometimes a given application needs to be built in a federated way to be most effective makes more sense than an “all or nothing” approach that forces application builders to build their apps on top of a data lake. Ultimately, the business and IT need to think about the form factor in which data needs to exist to empower their users to achieve their goals.

Summing Up

As the insurance industry eyes a potential AI arms race, the carriers that will gain a real advantage from AI will be those that can harness their underused data investments to drive meaningful advances to core insurance processes. Federated microservice-based architectures and data graph technology provide insurers with a viable alternative to data lakes as a means of tackling legacy tech debt and bringing much-needed agility and data-driven innovation to insurance.

KEY TAKEAWAYS:

--We have inadvertently allowed the insurance story to become an amalgamation of carrier advertising, less-than-flattering attorney commercials and the media’s appetite for bad news. Insurance needs to talk about its noble purpose and reclaim its brand in the world.

--Flexibility is also key because the needs of both the organization and its employees evolve. Companies need to master the selection and transformation of existing employees into new roles that blend business expertise with analytical and technical acumen. Some of the expert talent that is quitting due to lack of a perceived career path, or retiring, could be the strongest candidates for these new positions.

----------

The insurance industry continues to find itself in a talent crisis. The workforce challenges we are facing are not entirely new. Some are the lasting impact of the pandemic, while others have come and gone over time as a result of a changing world.

There are some challenges that I believe are self-inflicted, albeit unintentional. The good news is that they are also within the industry’s power to change. It won’t happen overnight, but let’s get started. Because people are the industry’s most valuable asset and are at the heart of everything we do, doing nothing cannot be an option.

People do not want to join the insurance industry

Younger members of the workforce do not see a career in insurance. Only 4% of respondents to The Hartford’s 2015 Millennial Leadership Survey found insurance to be appealing. And ACORD’s 2020 survey found even less interest from the generation that will make up 75% of the global workforce by 2025. Keep in mind that only 25% of insurance employees are under the age of 35.  

People are leaving the insurance industry

The insurance industry will lose half its workforce between now and 2036 as almost 400,000 employees retire. Most P&C carriers expect to increase staff during the next 12 months but are finding most positions challenging to fill and are facing more than 10% voluntary turnover. The hiring pool is limited for both entry-level and experienced talent; 65% of people leaving an insurance job also exit the industry. The leading reason why employees quit is a need for more career development and advancement.

Our call to action

Insurance needs to reclaim its brand in the world. This is above and beyond the hard work that individual carriers, brokers and agencies do to articulate and reinforce their products, services and experience. I am referring to an industrywide effort for insurance to take back its voice to tell its own story. Borrowing a page from Simon Sinek’s “Start With Why,” we can state that insurance has a noble purpose and a critical reason to exist. But we have inadvertently allowed the insurance story to become an amalgamation of carrier advertising, less-than-flattering attorney commercials and the media’s appetite for bad news. 

Insurance has a compelling and unique talent story that, if told, can both drive employee engagement and strengthen recruiting. If you’ve not worked within an insurance organization, all you may understand comes from a few insurance interactions and advertising. You wouldn’t have had the exposure to realize there is work that matches any combination of creative, analytical and technical passions. You wouldn’t have the context to appreciate the motivation that comes with a larger sense of purpose.   

A multi-dimensional talent development strategy is critical to build an organization that operates both horizontally and vertically and can adapt to change. Companies need specialists and generalists for strategies and execution to have both a top-down and bottom-up perspective. Career journeys that are co-owned by the employee and employer replace a career path predefined by the company. Flexibility is vital to recognize that vertical and horizontal journeys are not mutually exclusive.

Flexibility is also key because the needs of both the organization and its employees evolve. Technology has been driving change within insurance for a long time, requiring the elimination of some roles and the creation of others. AI keeps accelerating the rate and pace of change, as seen most recently with generative AI. Companies need to master the selection and transformation of existing employees into new roles that blend business expertise with analytical and technical acumen. Some of the expert talent that is quitting due to lack of a perceived career path, or retiring, could be the strongest candidates for these new positions.

My advice to all employees is to have a goal for their next potential role but also keep their peripheral vision unblocked. Their best next move could be something in a completely different area or perhaps a role that doesn’t even exist yet. I offer that guidance from my own career journey.

The next time someone asks you what you do in the insurance industry, don’t forget to include your “why.” I confess that I paused for a moment the first time I was asked why I chose to become a claims adjuster as my first job after college. Then it all came back to me, along with a great sense of pride and gratitude.

We love to think about disruption as simply a modern-day term. Yet four historic industrial revolutions offer ample evidence that disruption occurs far more frequently than we might ever imagine.

Each of the three past industrial revolutions has ushered in seismic change: The original Industrial Revolution was powered by steam, the second was driven by electricity, assembly lines and mass production and a third industrial revolution introduced computers and the internet. Industry 4.0 —where we find ourselves today — is moving exponentially faster than its predecessors. Defined by digital transformation, connectivity and the rise of real-time data, Industry 4.0 has already evolved from on-premises to the cloud and from intricate programming languages to no-code. Now, it is embracing AI and quantum computing.

As Industry 4.0 shifts the world around us, it also creates tremendous opportunity to shape insurtech solutions and the insurance industry in incredible ways for those ready to embrace it. 

Insurance through each revolution

Insurance, of course, pre-dates all four industrial revolutions. Historic points that involved or created insurance opportunities include the advent of benevolent societies to aid ancient Greeks with burial costs, the Spanish maritime explorations that led to the discovery of America, the Great Fire of London, the discovery and proliferation of electricity, the introduction of the automobile, the rise of computer hackers and countless other pinnacle moments. At each point, societies have progressed, in part, either because insurance has been interwoven in these efforts or because insurance products developed because of those pivotal developments. 

The insurance industry has provided peace of mind the world over with each evolutionary step of humanity and technology. With steam engines and railroads, the telegraph and steel mills, electricity, nuclear energy and the advent of the internet — humanity made gigantic strides, and, in each instance, insurance adapted accordingly.

See also: Embedded Artificial Intelligence (AI) in Financial Services

Why Industry 4.0 is radically different

While insurance historically advanced with societal progress, the actual insurance product — the agreement that obligates an insurer to cover a policyholder’s risks — remained steadfast as a written, physical document.  

Arguably, the establishment of the Hartford Steam Boiler Inspection and Insurance Company (circa 1860s) was an astounding leap forward in industrial safety, as these insurers encouraged smart practices related to steam energy. Henry Ford’s assembly line led to a radical shift in how society moved. Computer technology took us to the moon. Again, at each step, that perennial paper insurance policy was a bedrock.

Industry 4.0 has changed that fundamental principle of insurance. As we move forward, the insurance policy itself, while remaining steadfast and reliable, is forever changed. That physical document is digitized, existing now as data, often in the form of a digital PDF and shareable with nearly anyone. This opens an incredible marketplace for insurers in an increasingly digital, connected global community leveraging technology as complex as satellites and as common as the ubiquitous smartphone. 

This radical shift in the constitution of insurance creates a challenge: How to increase the appetite for insurance to achieve greater market penetration? This is where insurtech will help to define the future of the industry.

What is possible for insurance

The rise of insurance as a digital product means our industry is inextricably tied to the acceleration of technological advances. Similar to the impact of the sewing machine or advanced robotics on our culture, the digitalization of insurance will drive the industry well beyond what was previously imagined. Solutions already exist that allow carriers, brokers and MGAs to design, rate, underwrite, quote and create products across multiple lines. As these tools grow in sophistication, they deliver higher levels of accuracy, allowing insurers to enter new markets more quickly and confidently.

Where our industry goes next will be defined by how technology transforms other areas of insurance. Consider the possibility for infusing new digital pathways into the claims settlement process. While there will always be a physical component — such as replacing windows shattered by wind or hail — tech giants like Amazon have already opened massive distribution channels for faster delivery of products needed to rebuild or repair as part of a claim. This gives insurers the potential to settle claims faster, so long as the supply chain can keep pace.

The most radical change to come is in another area of insurance that has remained static for nearly a century: the customer experience. As the relationship between technology and humans grows more symbiotic, there exists the potential for insurance to become increasingly entwined in people’s daily lives.

Consider a future state where people wear augmented reality-capable smart goggles or glasses— powered by AI — to receive information in real time. This gives insurers the capability to serve as a concierge, delivering in-the-moment risk management advice to keep customers safe. 

Imagine the transformative impact this could have on a family vacationing on Mt. Washington. First, they use their smart goggles to secure a rental car. Then, as they traverse the mountain in their vehicle, an AI-powered concierge notifies them if they are driving through high-risk areas and delivers real-time alerts as the road narrows and guardrails disappear. The family arrives safely at the top of Mt. Washington, they enjoy a one-of-a-kind experience and their safety is prioritized across every mile. Just as GPS changed how people travel, augmented reality and AI will reshape our relationships with all that surrounds us.

This future is closer than you might think. Industry 4.0 has created a paradigm shift in insurtech. The rigid legacy systems of the past have been replaced by more flexible, accessible and rapidly integrated solutions that have accelerated the delivery of new products. These best-in-class tools will give insurers the capabilities needed to combine the digital and physical worlds. From telematics to wearables, predictive modeling and virtual reality, insurance has the potential to continue its long history of being connected into the ways we live, the ways we do business, the ways we travel and transport goods, as well as the future we build.

See also: 'Law of Computability' Powers the Bionic Era

How will insurance careers evolve?

One of the unfortunate corollaries of the explosive growth in technology — and in AI specifically — has been the growing fear of massive job losses. Yet if there is one thing we have learned from past industrial revolutions, it is that, on a macroeconomic level, each job displaced by innovation gets replaced by one or more jobs in emerging industries. 

A great example can be found in both the times of the steam and combustion engines. Yes, wagoneers and barge captains fell out of favor as technology advanced. But the new technologies provided opportunities for retraining and creating entirely new industries. Long-haul trucking, much in the news of late, might never have come to be if society had looked on the combustion engine as a job killer for the horse and buggy business. In much the same way, we cannot be afraid to embrace these new and sophisticated technologies.

I am tremendously optimistic that as insurance grows more technologically sophisticated in the next few decades, the labor market will shift. While some roles may disappear, such as those in data entry, new and potentially better ones will emerge. What those roles might be is still largely speculative, but insurance professionals who commit themselves to upskilling will be rewarded for their ability to adapt and evolve.

Embrace a spirit of adventure

The golden thread through each industrial revolution has been the spirit of adventure. Johannes Gutenberg did not know exactly how his printing press would advance the speed of knowledge. Henry Ford had no guarantees his assembly line would revolutionize manufacturing. Yet they were unafraid to explore the unknown by employing the technology they believed would usher in a better future. 

Now, in Industry 4.0, it is time for insurers to embrace their own adventurous spirit. Those that answer the call and seize these digital opportunities will lead insurance to amazing new heights.

KEY TAKEAWAY:

--With access to precise geocoding data, claims departments can swiftly assess risks, verify policy coverage and estimate claim values. This streamlined approach minimizes manual intervention, reduces errors and enhances operational efficiency.

----------

Geocoding plays a crucial role in the insurance industry, particularly for underwriters, claims departments and adjusters, by delivering accurate structure location. Geocoding can increase profit margins, improve risk assessment, minimize losses on claims and empower claims and adjusting teams.

Geocodes are available with varying degrees of precision, such as ZIP9 geocodes, interpolated geocodes, parcel geocodes and rooftop geocodes—each offering a different level of accuracy. However, only true rooftop geocoding can maximize an insurer's investment and enhance risk assessment. 

The two most popular types of geocodes are parcel-centric geocodes and rooftop geocodes. Parcel-centric geocodes identify the center of a parcel or lot, while rooftop geocodes find the exact roof of a structure. Certain providers, including major search engines, may pass off parcel-centric geocodes as rooftop-accurate. 

Relying on parcel-centric geocodes when writing policies can lead to inaccurate risk assessments and underwriting compliance issues. Parcel-centric geocoding may increase the number of full-limit-losses paid, decrease revenue or even get your company in hot water with regulatory agencies. 

When vetting geocoding providers, it's worth verifying the absolute accuracy of the geocodes they return. 

Great Geocoding Requires Great Address Validation

Address validation cleanses and standardizes the geocoded addresses to reduce false positive matches. Using address validation, geocoding can also identify the address type, including non-postal address, residential or business, or determine if there is a multi-unit structure.

Pairing Geocoding and Data Enrichment Maximizes ROI

Whether you're writing a business owner's policy (BOP), vacant land policy, property policy or product liability policy, you must ask your clients questions about their home or business. However, peppering your clients with property attribute questions regarding their home or business can be tedious. Often, clients don't know the answer, and sometimes, they may even give incorrect information. Rooftop geocoding enriched with property attributes can improve the experience for you and your clients. 

Insurers using property attributes to augment the data they already have typically do so through a separate company's application programming interface (API). Through this API, insurers can obtain hundreds of supplementary data points and use them to paint a clearer picture of the risks involved with insuring the property in question. 

In addition to generating a positive ROI on the front-end, geocoding and data enrichment provide insights that enable insurers to enhance their risk management strategies. By identifying specific property characteristics and associated risks, insurers can develop loss-prevention initiatives and offer valuable risk mitigation advice to their clients. 

Geocoding Using Cloud-Based APIs Adds Flexibility and Speed

Historically, geocoding uses on-premise systems that tie up hardware resources and require time-consuming updates and processes. Geocoding using cloud-based APIs is more efficient because all data updates and hardware maintenance aren't needed. The flexibility of chaining together multiple cloud-based APIs is a huge plus.

Cloud-based geocoding can also be very fast. Some cloud-based providers can process geocodes much quicker than most on-premise systems for a fraction of the overall cost.

Persistent Unique Identifiers (PUIDs) Are Key 

Addresses can sometimes change due to street name modifications, address renumbering or subdivision developments. Getting the most out of geocoding means choosing a provider with persistent unique identifiers (PUIDs)—a type of digital fingerprint. PUIDs remain constant even when the underlying address data changes—allowing insurers to link historical data and maintain data integrity.

Considering how often addresses can change, it's not cost-effective for carriers, brokers and agents to manually correct them. PUIDS can help insurers automate this process, saving time and cost. 

And, by linking the property to previous claims, property updates, loss trends and other data, underwriters can more easily determine policy premiums and program eligibility. 

Geocoding Streamlines Straight-Through Processing

Rooftop geocoding has become a necessity for streamlining straight-through processing in claims departments. With access to precise geocoding data, claims departments can swiftly assess risks, verify policy coverage and estimate claim values. This streamlined approach minimizes manual intervention, reduces errors and enhances operational efficiency.

Rooftop geocoding also aids in efficiently deploying adjusters. Empowered with exact coordinates, insurers can assign adjusters who are geographically closest to the claim site, send them to the right place the first time and reduce travel expenses while providing timely and responsive claims handling. 

The future of geocoding holds exciting possibilities. With advancements in artificial intelligence, machine learning and data analytics, insurers can harness the power of geocoding to extract deeper insights from location data. This enhanced understanding of risks and exposures will enable insurers to develop more tailored policies, promote risk management and drive ROI

KEY TAKEAWAY:

--Smart homes offer a vast array of benefits in: risk mitigation and prevention, data collection and analysis, personalized premiums, faster claims processing, home monitoring services, liability coverage, premium discounts, the environment and health and wellness.

----------

Smart homes, equipped with various Internet of Things (IoT) devices and technologies, have the potential to change the insurance industry.

Insurers have a natural synergy with smart home technologies. With almost 69% of U.S. households owning at least one smart home device, it is clear that such technologies help consumers manage, protect and efficiently run their homes via mobile applications.

While smart home technology is not a new concept, many insurance companies and homeowners are adopting it like never before to optimize housing efficiency, streamline daily tasks, improve quality of life and well-being and reduce urban household risks.

What Are Smart Homes?

Smart home technology integrates various devices and appliances with internet connectivity, enabling remote monitoring and control through mobile applications. Implementing smart home devices, such as smart security cameras, door locks, thermostats and water leak detectors, significantly reduces the risk of potential hazards and damages, affecting insurance policies in many ways.

Here's how smart homes and insurance are connected

Risk Mitigation and Prevention

Smart homes are equipped with sensors, cameras and connected devices that can help prevent accidents and damages. For example, smart smoke detectors, water leak sensors and security cameras can detect potential hazards and alert homeowners in real time. Insurance companies can offer lower premiums or incentives to homeowners who invest in these technologies, as they reduce the risk of costly claims.

Data Collection and Analysis

Smart home devices generate a wealth of data related to occupancy patterns, usage of appliances and environmental conditions. Insurance companies can leverage this data to better understand customer behavior and assess risks accurately. For instance, if a homeowner's data shows responsible use of heating and cooling systems, they might be eligible for lower energy-related insurance premiums.

Personalized Premiums - Usage-Based Insurance (UBI)

By leveraging data from connected devices, insurance providers can tailor premiums based on homeowners' usage patterns and behaviors.

The data collected from smart homes can be used to create personalized insurance policies. Traditionally, insurance policies were based on statistical models and generalized risk assessments. However, with the advent of smart home technology, insurers can now offer UBI. This way, homeowners have more control over their premiums, and insurance companies can better assess individual risk profiles.

Faster Claims Processing

In the event of a claim, IoT devices can provide valuable data to insurance companies for faster and more accurate claim assessment. For instance, if a burglary occurs, security camera footage can help verify the claim and expedite the claims process.

Home Monitoring Services

Insurance companies might offer home monitoring services as part of their policies. These services could include continuous monitoring of security systems, smoke detectors and other safety devices. This not only enhances home security but also provides peace of mind for homeowners.

Devices, such as connected security cameras, smart locks and water leak sensors, offer real-time monitoring and early warning capabilities. These devices can detect potential threats, such as fires, gas leaks or water damage, in real time. In case of emergencies, the devices can automatically trigger alerts and notifications to homeowners and relevant authorities, helping mitigate risks and minimize the extent of damage and potential insurance claims.

For example, The Flo by Moen Smart Water Security System learns your home's water usage and can automatically shut off the water supply if there's a detected leak, reducing the likelihood of insurance claims.

Liability Coverage

Smart home devices can potentially assist in liability claims. For instance, if a guest is injured on the property, data from smart security cameras or access logs could provide evidence about the circumstances, helping to determine liability and claims settlement.

Premium Discounts

Some insurance companies already offer discounts for homeowners who implement certain smart home technologies, such as security systems or leak detectors. These discounts can encourage homeowners to invest in these technologies and enhance their overall safety and security.

The Environment

Smart homes often have sustainable and eco-friendly features to improve homeowners' carbon footprint. For instance, smart homes can be equipped with thermostats to automatically adjust a room's temperature to help people conserve energy and cut their utility bills. Insurance companies can encourage eco-friendly initiatives by offering incentives for homeowners who purchase such environmentally responsible devices.

The adoption of smart home technologies and their impact on insurance can vary by region and insurance company. As technology continues to evolve, the insurance industry will likely find new ways to leverage smart home data to provide more personalized and efficient services to their customers.

Health and Wellness

Many smart home devices help improve the health and well-being of homeowners. For example, smart fridges can be programmed to reorder healthy food, and smart bathroom mats can monitor your weight and posture. Insurers that create programs and incentives encouraging plan members to adopt smart home wellness technology can help them live healthier and longer lives. Lower mortality and morbidity can help employee benefits insurers increase profits while reducing strains on healthcare systems.

A Smart Future

While smart homes offer many benefits, there are also concerns related to data privacy and cybersecurity. Insurance companies must ensure that the data collected from smart devices is properly protected and used responsibly to maintain customer trust.

Smart home and smart city technologies radically change the insurance value and are integral to creating more resilient and sustainable urban environments.

KEY TAKEAWAY:

--AI can help with customer service through a careful use of chatbots, can speed underwriting in ways that will let agents be more responsive to clients and can automate aspects of the claims process that currently distract agents from more meaningful work.

----------

What would you say is the most prominent theme throughout human history? Many argue that conflict or culture defines humanity. Still, when we examine the entirety of human existence, I see one central point that outshines the rest: advancement. 

Each age of humanity has been defined by an innovation that changed the course of history. Whether it be the wheel, the invention of steel or the internet, humans seem determined never to settle for their current reality and are always rushing toward that next defining moment. 

We believe that the next defining moment is already here, and it has come in the form of artificial intelligence (AI). The floodgates are open, and in as little as five years AI will likely have significantly altered how we live and work.

What does this mean for insurance agents? Well, if history has taught us anything, it is that those who properly implement innovative technologies are rewarded while those who don’t either fade into obscurity or serve as a cautionary tale for why you shouldn’t blindly charge forward into uncharted territory. 

In this article, we explore how the emergence of AI could affect independent insurance agents and make the case for why agents should carefully implement this technology into their agencies’ operations. 

First Things First 

The burning question that professionals of all stripes are asking themselves is, “Can AI do my job better than I can, and will it make my role obsolete?"

Insurance agents are not immune to this line of thinking, but, thankfully, it is unreasonable to assume that machines will eliminate the need for human agents. Most consumers are not experts on the different types of coverages available and defer to the expertise of an insurance agent. While AI tools such as ChatGPT do a great job scouring the internet and organizing information to answer a question, purchasing insurance requires trust, and consumers trust that their agent can advise them on their potential risks and securing the right coverage for their needs.

That level of trust is not easily transferable to an artificial machine (do you prefer navigating an automated customer service menu or speaking with a live person?), especially considering the nuance required to properly advise and service a client. As such, it is highly unlikely that consumers would ever prefer their risk profile to be assessed and managed by a programmable machine instead of a real person. 

No one knows what the future holds, but we firmly believe that no matter how sophisticated AI becomes, it can never replicate the interpersonal value and expertise provided by agents. 

See also: AI in a Post-Pandemic Future

On the Bright Side

That being said, AI can potentially eliminate the need for agents to perform repetitive and mundane tasks and empower them to focus on where they provide the most value: advising and servicing their clients. How will it do this? Let’s take a look. 

Customer Service 

The use of AI chatbots to answer basic customer questions is an increasingly popular feature. These chatbots help companies stay connected to consumers and are especially useful outside normal business hours. For example, imagine a customer needing information about your agency’s renewal process after you’ve locked up shop for the day and your customer service team has gone home. Featuring an AI chatbot on your website that is capable of answering this customer’s questions will add value to your customer and in turn strengthen their loyalty to your agency.

Even today, using AI to enhance your level of customer service can reduce service costs by up to 30%, according to Entrepreneur. Imagine what that number will be in 10 years as AI continues to advance. Additionally, companies such as Synthesia allow users to create AI videos that could be used for employee training or continuing education purposes. 

AI chatbots are best used in tandem with your customer support team and should primarily be used when your team is unavailable (holidays, weekends, non-business hours, etc.) or as a fast reference for your team members when issues arise outside of their circle of competence. In our opinion, having a live person responding to customer inquiries is the preferred method (especially because being an insurance agent is a service role), but when a live person is not available an AI chatbot can provide an acceptable level of support in the interim and is certainly better than no support. Remember, AI should not replace your customer service staff but instead work in tandem with them to increase the service your agency can provide customers. 

Underwriting 

AI and machine learning (ML) technologies are already transforming the underwriting process by improving data collection and risk assessment methods. For example, instead of relying on potentially inaccurate data provided by customers on an application, insurance companies are beginning to use technology that can automatically gather data through many different sources and more accurately discern the level of risk present in each policy.

According to McKinsey, by 2030 underwriting processes will be almost entirely handled by machines, and most policies will be quoted instantaneously. This removes the need for underwriters to handle repetitive tasks such as data entry and allows them to focus their energy on handling complex submissions. These innovations will be groundbreaking for carriers and brokers. However, independent agents stand to benefit as their customers receive increasingly accurate and error-free assessments of their risk profiles and instant quotes on most policies, allowing agents to focus on other items, such as product education and customer retention. 

Claims 

Claims processing can be a tedious task that requires hours of investigative work and the examination of countless documents. McKinsey estimates that by 2030 AI and ML will play a significant role in the claims process, with nearly half of all claims being fully processed without human oversight or intervention. (Lemonade already handles half of their claims via AI.) 

What does this mean for agents? It means less time focusing on data collection and information sharing with carriers and more time providing support and counsel to their customers. AI will never be able to match the interpersonal touch of a live agent, but using AI and ML to eliminate tasks such as data collection and information sharing allows agents to focus their efforts on ensuring their customers have the guidance needed to properly file their claims. 

See also: Achieving a 'Logical Data Fabric'

A Pivotal Moment 

AI has already proven itself capable of enhancing customer support, underwriting and claims processes. The technology is here to stay and will only become more prevalent. The way we see it, insurance agents have three options: 

1. Reject its implementation and become the equivalent of an agency still using a typewriter in 2010 
2. Rush to implement the technology without cause or consideration and watch it blow up in your face 
3. Identify the areas where AI can increase efficiencies and cut costs and meticulously implement the technology over time 

The key to mastering the age of AI is to choose option three. If you don’t, you may be overtaken by competitors that are more efficient and better serve their customers.

Recently, we announced the winners of the 2023 Datos Insights Insurance Technology Impact Awards. I’m writing a blog series examining industry trends as seen through the lens of the 2023 Impact Awards’ 65 case studies, which catalogue real tech projects that real insurers delivered to create real success. Today, I’ll be diving into trends from data and analytics projects across the industry.

Unlike digital projects, data tends to be a smaller category, because it so often captures projects that are intensive, multi-year efforts: things such as training algorithms to automate underwriting decision making or migrating an on-premise data warehouse to a cloud data lake environment. “Easier” data projects might be setting up a self-service data mart where business users can independently use reporting tools like Tableau to get their own analytics and insights.

Data projects are large, complex and difficult, but also crucial and unavoidable.

What’s clear from this year’s Impact Awards data case studies—and from the digital and core case studies, for that matter—is that practically anything an insurer would like to do ultimately comes down to effective data and analytics capabilities. Accurate, available data is the secret key to all the other capabilities insurers want to implement.

Take midsize property/casualty winner Mosaic Insurance (now a back-to-back Impact Award winner!). Mosaic implemented an underwriting portal to improve customer experience for high-end specialty lines customers. Creating the speed the team wanted required Mosaic to embed AI-based decision making capabilities within the portal so the system could quote, bind and issue policies automatically. What seems like a digital initiative on its face (“let’s sell specialty insurance online”) is actually a data initiative, because the algorithm is such a crucial component of the overall function.

To that point, the data used to train an algorithm must also be high quality, and any third-party data invoked in the new business process must be reliable. Fellow winner CNA is an example of the latter. CNA wanted to provide faster quotes, and its path to doing so was to build an AI-enabled automation solution to improve data extraction from forms.

These needs also extend beyond new business. Life winner Lincoln Financial wanted to improve customer experience, but what the team built was a holistic customer data view, because the core of that customer experience is being able to serve accurate information about accounts, on demand, to the portal or channel where the customer wants to view it.

See also: Achieving a 'Logical Data Fabric'

It’s data all the way down.

Whether an insurer wants to sell more, manage risk better, serve customers more effectively or differentiate itself from the competition with superior user experiences—all of it ultimately comes down to data and analytics capabilities.

Want to provide a superior distribution experience by providing instant quotes? Underwriting components are typically core, but you definitely need good data and good analytics.

Want to improve customer experience by pre-filling fields for your digital FNOL user flow? You need to be able to pull that information from a data lake.

Want to save on claims costs by more effectively flagging potential fraud or more accurately predicting claim severity? Pure data and analytics, which will have a clear impact on profitability.

Insurers, like everyone else, are rightly paying a lot of attention to generative AI and large language models like ChatGPT. But at baseline insurers need data that’s accurate, reliable and available, as well as algorithms that are trained on quality data and that produce decisions that can be trusted. More and more, data is core, data is digital, data is everything.

To check out all 13 data and analytics case studies, read Insurance Technology Impact Awards Case Study Compendium 2023: Data Initiatives. Interested to see what’s happening in the world of digital, core and IT practices? Find information about all of this year’s Insurance Impact Awards winners here.