Empowering the Underwriter of the Future

I asked an audience how long it takes a new underwriter to go from zero to productive: The majority voted for 24 to 36 months. This is a ludicrous proposition in the age of AI.

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It’s become an overused little joke that most people “fell into” insurance rather than choosing it, but when we consider the talent shortage in underwriting today it’s not so funny any more. The talent gap is only growing, exacerbated by the Great Resignation and the Great Retirement. We can no longer afford to be complacent about the fact that most people in our industry had no intention of being here, and that the new talent we need for future growth – including the best business minds, data scientists, analytics pros and people who understand artificial intelligence and "speak machine" – is choosing other industries over ours. 

Insurance provides an essential foundation in maintaining the stability, health and growth of our businesses, communities and individuals – including those that are the most vulnerable. The impact is more important now than ever. Insurance also is a people business, one that is built on trust and reliant on human interaction and judgment for deal analysis and strategy, pricing and negotiation, distribution partnerships and team building. 

Regardless of line of business or size of business, there still needs to be a human touch, and there is a requirement to think about the overall business strategy, the portfolio and broker/agent relationships. It is not right to assume that AI, machine learning, and other technologies will replace the underwriters we are losing. Instead, we must look to leverage new technologies to empower and enable the human side of underwriting and create a work environment that people want to join.  

None of This Is New

Industry leaders have been talking about the talent drain for nearly a decade, but the pandemic and other economic forces have certainly accelerated it. According to U.S. Bureau of Labor Statistics estimates, 50% of the current insurance workforce will retire in the next 15 years. A study by McKinsey found that 65% of those who resigned from a job in insurance between April 2020 and April 2022 left the industry entirely. That percentage is exceeded only by the 76% in consumer/retail, which has always had a problem retaining people, and the 72% in the government/social sector. If we’re honest, we have always had a problem attracting the best talent, and now we’re running out of people entirely. The time has come to do something about it.  

Given the turnover documented in existing insurance talent, it is even more crucial to attract and retain the next generation of talent. However, if we look to younger generations, we are failing there, as well. According to the Deloitte Global 2022 Gen Z and Millennial Survey, 46% of Gen Zs and 45% of millennials feel burned out due to the intensity/demands of their working environments, while 44% of Gen Zs and 43% of millennials say many people have recently left their organization due to workload pressure.

As an industry and within individual organizations, we need to focus on creating cultures that allow people to do their best work, make an impact, connect with each other and have time and space to live their best life. Said differently: Insurance must do better at keeping up with cultural and social expectations. A good culture can exponentially improve the underwriting experience, but it needs to start with the backbone of a productive and capable work environment. Technology, tooling and workflow all have a huge impact on the underwriter’s day-to-day work environment and how they feel about their job at the end of the day.  

If we assume that insurance will remain a human business (though the roles of those humans will inevitably evolve), our efforts to modernize and digitize underwriting need to be human-centric. We need to ask ourselves how the technologies being implemented today will improve the underwriting experience for current and future underwriters and staff.

Let’s talk about the current underwriting work environment – it isn’t pretty! The technology that has been available in most insurance environments is decades behind what we are accustomed to using in our personal lives – it's slow, static and highly manual, whereas the consumer tech and apps we’ve grown used to in most every other facet of our lives are seamless, beautiful, intuitive and fast – they anticipate and enable our needs. If you think about what is holding back the insurance industry’s ability to attract and retain talent, outdated technology and tooling are a big part of it.

McKinsey has identified providing employees with “a suitable physical and digital environment that gives them the flexibility to achieve a work–life balance” as a key factor in employee satisfaction and talent retention. The right digital tools “free people up to focus on the more creative and engaging aspects of their work.” 

When we consider the significant investments insurers have made in new technologies, data sources, predictive models and digital transformation initiatives, the results are frankly not good. I’ve seen countless companies use band-aids and bubble gum to hold together the systems where underwriters transact business. Fatigue from constant change that doesn’t align with the way underwriters actually work is all too common. So, how have we missed the mark when it comes to improving the underwriting experience? 

Oftentimes, technology capabilities or operational workflows are positioned as business problems, without much consideration for the day-to-day reality of the people in the organization. As a result, the solutions proposed tend to focus on automating away manual tasks. AI and machine learning, for example, are used to replace manual tasks on an ad hoc one-to-one basis. So, rather than having an operations person taking information from an Acord submission form or email and manually rekeying it into a policy admin system, we're going to automate that piece. And that’s great! It speeds things up, right? But piecemeal task automation is only the tip of the iceberg in terms of what these advanced technologies can do, and automation is only one step on the journey toward making a real impact on underwriting and operations.

See also: The Defining Factor in Underwriting Success

Seeing Underwriting Transformation Through a Different Lens

I’d argue that we need to look at the problem through the eyes of the underwriter. It's not enough to have executive leadership spending time and cycles considering the business problems of the day in terms of cost of systems, workflow challenges and expense-ratio issues without understanding the lives of underwriters, how they think, what they feel and why they do what they do. At Federato, we believe that businesses don’t have problems, people do. To improve underwriting productivity and performance, insurers need to take an "underwriter-first" approach to technology adoption. If you take the time to listen to your teams and ask questions, you can solve workflow problems by creating a beautiful underwriting experience that supports and empowers underwriters and staff. When you do that, the business problems disappear.  

The Next Frontier of Underwriting Transformation

The next frontier in underwriting transformation will be about using data and bleeding-edge technologies like AI and machine learning to augment the art of underwriting and operationalize the science of it. 

Up until now, insurers have essentially identified more information, more tools and more places for an underwriter to go to assess and price a risk. Insurers have layered on all of these new “versions of the truth” in a way that has left the underwriting community feeling like they are overwhelmed and drowning in data, instead of being empowered to make good decisions. To create workplaces where people want to stay, we need to make this information more accessible and digestible within the underwriter’s core workflow. Finding risk selection data, guidelines and rules shouldn’t be a scavenger hunt.

If we start from first principles, what are the core functionalities and data that underwriters need to be productive and make the right risk decisions, and how can technologies like AI and ML be applied exponentially to help underwriters in these areas? I see three key areas where intelligent, next-gen underwriting technologies can make a huge impact on underwriting productivity and performance: portfolio management, action-oriented workflow and single-pane-of-glass visibility into all relevant account information.

Portfolio Management

Number one is how your underwriters understand, manage and balance their portfolio. Today, there’s a good chance that they use static analysis and a bunch of fancy, macro-enabled spreadsheets – and there’s an even better chance that your organization’s portfolio targets are routinely missed. Insurers can use AI to let underwriters see into their portfolio at the most granular level, enabling them to see what’s happening in real time so they can dynamically course-correct, balance and shape the portfolio in the direction that they want. Imagine being able to view the state of your portfolio this morning versus looking at stale booked premium data that is 45 days out of date. Underwriters want to know how they’re tracking toward their goals and how their portfolio is doing relative to every other underwriter’s transactions across the entire organization. Having the ability to set goals and rules, dynamically track progress toward them, do what-if modeling and forecast with information in real time is truly transformative. 

Action-Oriented Underwriting Workflow

A lot of "first wave" technology is task-oriented and assumes that underwriting is a linear process. It isn’t. As an underwriter, you have to compile a lot of information at any given time. You have to price a deal, do a referral to give a quote, go back and forth with the broker on pricing and do another referral before you can quote again. If you have a list of 33 items and the technology forces you to get through items one through 30 before you can do 31, that's not very intuitive. We need to shift to an action-oriented approach to workflow, enabling underwriters to really quarterback an account. And we need to support them by digitally enabling risk-selection assistance and prompting, account triage to surface the best deals based on appetite and winnability and task management directly within the workflow. Underwriters are not unskilled labor who are content taking orders and following checklists. They are highly trained, strategic thinkers who really want to do the right thing for their organization. By treating them as such, and providing the right tooling for them to be effective, we can, in fact, attract the very sort of intelligent, creative and entrepreneurial people we want to the profession.  

See also: Why Underwriters Don’t Underwrite Much

Single Pane of Glass

As insurers adapt to new and emerging risks, there are always new data sources that should be considered for every decision, new places to go, new tools to use and new guidance to review. Underwriters shouldn’t have to remember which guidelines to look up, which websites to visit, which tools to use and which Excel Workbook to download. Having all of this information, both proprietary and third-party, all in one place is a tremendous advantage for underwriters looking to out-select the competition. AI and machine learning can do the work of a thousand people to comb the web for every piece of data that might apply to a given account, and do it almost instantly, to run the most complex analytical models to guide underwriters to the right decision. They can go out and gather and distill the right information and then serve it up to the underwriter who is making the decision at just the right point in the process. Rating data, pricing models, exposure information, loss information, third-party data, CAT modeling – having all of these disparate data elements compiled in a “one-stop-shop” is incredibly important, and it’s one of those things that machines can do better and faster. 

Summing Up

These are only a few of the ways that advanced technology can empower underwriters to focus on value-added, human-centric tasks. When you use AI and machine learning to create a digitally enabled workplace and match up risk selection and portfolio insights with operational execution at the account level, there’s no longer any separation between your business strategy and your underwriting execution. 

That's the power of what technology can do when it’s applied in a thoughtful, human-centric way. The endgame here is freeing up humans to focus on the tasks to which they are best suited – things like analyzing market dynamics, negotiation, relationship building, pipeline development and joint selling – rather than consuming their precious time on rote admin tasks and "data foraging." Technology does not eliminate the need for underwriters. It just enables them to use their skills, knowledge and judgment more productively.

Of course, all of this can have a huge impact on underwriting performance, but I see the primary benefit here as creating work environments that are going to help insurers attract new talent, retain the talent they already have and decrease the time it takes for new hires to achieve proficiency in their role. At the CPCU In2Risk 2022 conference, I asked the room how long it takes a new underwriter to go from zero to productive: The majority voted for 24 to 36 months. This is a ludicrous proposition. AI and machine learning can accelerate onboarding by engaging new underwriters with systematic knowledge, contextual prompting and recommendations on the "next best action" based on the insurers’ rules, guidelines and strategic goals. 

People who feel supported, informed, capable and good at what they’re doing tend to stick around – and if we can help them feel that way quicker, we can ward off burnout and churn. Insurers who show a commitment to advanced technologies like AI and ML – the really cool stuff – will be much more likely to attract the right talent. Empowering the next generation of underwriters is the way that we solve the people problems that have plagued insurance for too long and get new generations to seek out and choose our industry first above all others.


Megan Bock Zarnoch

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Megan Bock Zarnoch

Megan Bock Zarnoch, CPCU, ARM, is chief operating officer at Federato, the leading provider of AI-driven RiskOps software in P&C and specialty insurance.

Bock Zarnoch has spent 20 years in the commercial P&C insurance space leading teams at global insurance carriers. Prior to joining Federato, she was founder and CEO of Boundless Consulting, and previous roles included senior vice president P&C Underwriting, QBE Group; second vice president, Travelers Middle Market; and various underwriting leadership roles at Liberty Mutual Group.

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