Commercial insurance faces a growing claims adjuster staffing gap. On the retirement end, there’s a rising tide of experienced adjusters leaving the profession. According to the Pew Research Center, nearly 10,000 baby boomers retire each day in the U.S., and about 25% of them leave positions in the insurance and financial services sector. Seasoned adjusters leave with a wealth of experience built up over decades, leaving newer adjusters to handle a rising volume of claims.
On the entry side, too few adjusters are entering the business to make up for the wave of departures. According to The Hartford’s 2015 Millennial Leadership Survey, only 4% of millennials are interested in entering insurance, compared to 36% interested in education and 31% interested in health care. The gap is especially acute in commercial insurance, where few college graduates have been exposed to workers’ comp, business continuity, and other types of claims outside of personal lines.
There’s little indication COVID-19 has changed this dynamic. While job listings for “insurance adjuster” have risen according to ZipRecruiter, insurance caseloads also continue to rise, creating growing pressure on claims teams facing waves of new types of claims, from COVID-19 workers’ comp to business interruption.
One way carriers can change the game and attract a new influx of millennials is by focusing on artificial intelligence (AI), which itself is experiencing a surge of interest. AI is commonly seen as a replacement for people, a way of fully automating jobs to prevent the need to even hire in the first place. But the real value lies in machines and humans working alongside each other, where machines can enhance humans’ natural instincts.
It’s this augmentation role that makes AI an appealing solution to the industry-wide talent gap — across three broad dimensions.
Break out of the mundane
The first way AI can help is by handling aspects of the adjuster’s job that are more routine and thus less appealing. AI techniques like machine learning are optimal for handling an array of ongoing calculations, such as estimating reserves needed for a claim or tracking the ongoing cost of medical bills that have been paid. Natural language processing can identify relevant comments and insights in a sea of text, reducing the need to parse through every new document that emerges. Entity resolution detects when multiple providers, attorneys or companies are actually related in some fundamental way, which can significantly cut down time-consuming legwork that can go into sizing up the various players engaged in a claim.
In these examples, AI gives adjusters superpowers that free them up to focus on the more nuanced and interesting aspects of claims adjusting. A job description with “acquire AI superpowers” might appeal to millennials more than “study policy footnotes and calculate claim reserves.”
A natural mediator
The second major appeal AI offers is in transforming a potentially adversarial relationship into a more mutually supportive one. The traditional workers’ comp claim can feel like a one-dimensional tug-of-war between adjuster and claimant — where one’s gain feels like the other’s loss. But AI can find win-win breakthroughs by considering a wider range of factors and data.
By identifying doctors with successful track records in a specific injury type, for example, AI can get workers to providers that enable them to recover faster, while also reducing both the workload and cost for the adjuster. Automatically interpreting adjuster and provider notes can detect situations where the worker is confused about the claims process, enabling adjusters to address the confusion before it becomes a deeper source of frustration.
Aligning adjuster and claimant plays to the healing side of claims adjusting — and to a new generation that is increasingly looking for meaning in their work. In the 2019 Rising Medical Solutions survey of over one thousand claims professionals, 36% of respondents indicated that shifting to an advocacy model with workers would improve the reputation and social image of their organizations. Lifting the social image of the organization and profession will increase the appeal to millennials and Generation Z, both more mission-focused cohorts than older generations.
An expedited ramp-up
The third way AI can attract new talent is by ramping newcomers faster, helping them optimize their impact within months versus having to invest years in traditional training. AI-generated recommendations can come with explanations that show how they were arrived at. This gives the user confidence in the recommendation. It also provides them with guidance to accelerate their overall mastery of the domain.
Adjusters can generate their own insights and recommendations, looking at the various factors in the claim, then compare those to the AI-generated answers, giving them a ready-made feedback loop to train themselves over time. Newbies can play this “guessing game” until they get enough right answers to start taking action on real claims. They’ll, of course, need training from experienced colleagues, but this approach can get them up to speed faster.
Claims professionals can set themselves up well for future changes by playing up their familiarity with AI. Insurers can emphasize the AI fluency adjusters will gain from specific roles. Adjusters can increasingly reference AI strengths on their resume. Technically inclined claims professionals can shift all the way into business intelligence, machine learning or data engineering tracks, which are among the fastest-growing in the entire economy, according to LinkedIn. Claims operations end up with an increased flow of talent and a strengthened internal mobility program that they can showcase to new candidates.
The adjuster recruiting challenge didn’t appear overnight and will take years to overcome. But AI is clearly one way smart firms can accelerate progress and stand out to attract a new generation of insurance professionals.
Thomas Ash, senior vice president, brings 30 years of experience in health care, insurance and workers’ compensation to CLARA analytics, a provider of artificial intelligence (AI) technology in the commercial insurance industry. With leadership responsibility for CLARA’s business development, Ash plays an instrumental role in the execution of CLARA’s aggressive growth strategy as the company scales to meet market demand. The opinions expressed here are the author’s own.