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People are the lifeblood of the insurance industry. It is the underwriters, claims professionals, SIU investigators, and countless others working to protect individuals, their families, and their businesses and property, who keep the industry moving forward. Their experience and expertise are invaluable.

At the same time, insurers around the world are facing a rapidly approaching personnel crisis. According to figures from the U.S. Bureau of Labor Statistics and as reported by the U.S. Chamber of Commerce, the number of insurance industry employees nearing retirement age has increased by 74 percent over the last 10 years. Why is that important? Fundamentally, those figures mean we can reasonably predict that 50 percent of the active insurance workforce will retire sometime during the next 15 years. And those predicted numbers cover only the U.S. population. We see strikingly similar figures associated with mature insurance markets around the world.

Basically, people are leaving the industry faster than they can be replaced. The “Great Retirement” is estimated to create 400,000 openings, the majority of which will go unfilled. How do we know that? The same U.S. Bureau of Labor Statistics numbers indicate that younger employees are showing little interest in taking employment in the insurance industry. Less than a quarter of employees currently working in the industry are under age 35. Research from PWC confirms these findings and shows that 21 percent of millennials globally would prefer not to work in insurance. Many cite the industry’s image as a key reason.

But why should we care? Simply put, the insurance industry does not function without people. Multiple experts maintain that the talent shortage is one of the critical risks facing the industry. Despite advances in automation and other technology innovations, insurance is still an industry that relies on the human touch for its ongoing success. This is not going to change any time soon.

So, what should insurers do? Advances in artificial intelligence (AI), and more specifically generative AI (GenAI) can provide the industry’s valuable, and valued, employees a way to augment their skills to drive efficiency, accuracy and productivity across several key insurance processes.

Underwriting

The advent of online, one-click shopping changed the way consumers interacted with the world around them. In short order, shopping, banking, and even renewing your driver’s license could be done in minutes without having to interact with another human. People wondered why it could not be the same way for insurance. The insurance industry responded with portals and mobile apps where one could apply for insurance without talking to a broker, but those policy applications still require review by a professional underwriter before the policy can be written and the business booked. Applicants who are already expecting real-time responses from their commerce and banking sites do not necessarily understand why it is not necessarily the same for insurance.

Underwriting professionals who are already under pressure to provide the right level of due diligence for the business while at the same time delivering an exceptional customer experience are now facing a whole new challenge: fewer underwriters to get the job done. Fortunately, GenAI is extremely well positioned to mitigate the problem. GenAI is ideally suited to reading, analyzing, and summarizing massive amounts of data. It can compare the information provided by an applicant with the insurer’s historical data as well as that of relevant third parties. And it can provide its analysis back in easy-to-understand natural language. Perhaps most important, GenAI can do this all in seconds to provide underwriting professionals with the information they need to determine how to best proceed with an application.

Claims Handling

The online revolution did not just impact underwriting, it also changed the way policyholders felt about making a claim. If insurance could be purchased via an app or portal, the rationale soon followed that claims should be able to be filed and settled this way as well. But again, much like underwriting, we cannot forget that there is a human claims professional on the other side of the app. And while claims automation initiatives (often supported by AI) have alleviated some of the burden, it is still assessed that only 7-10 percent of claims are appropriate for straight through processing.

In this environment, it is estimated that claims professionals typically spend more than 30 percent of their workday reading documents to gather the information required to do their jobs. Claims handlers and adjusters are responsible for reviewing the facts of the claim, identifying if there may be a subrogation and recovery opportunity, or even if the claim is suspicious or includes suspicious elements. That is a lot to do, even without facing a dwindling workforce. These manual processes are time consuming and can result in delays that degrade the policyholder experience.

GenAI is perfect for removing this responsibility from a claims handler’s daily “to do” list. The technology’s demonstrated accuracy provides confidence in everything from simple document review and information extraction to subrogation and fraud detection efforts. Again, natural language summaries and “next steps” appraisals make it easy for claims professionals to know what is happening with a claim and as importantly, what to do with it.

The SIU

We know that claims professionals are going to find incidents of expected fraud. With the right strategies in place, that number will actually go up. And those suspicious claims are ultimately referred to the SIU for further review and investigation. Unfortunately, the SIU is not immune to the outside forces impacting underwriters and claims professionals. Like their colleagues, investigators are seeing their numbers shrink at the same time their workload is increasing.

GenAI can have a profound impact on how suspected claims fraud gets investigated, especially in the area of case management. Even before a case is referred to the SIU, GenAI can create an easy-to-understand rationale for why the claim was identified as suspicious and what steps may have been taken historically to investigate similar claims. This gives the assigned investigator a head start that can continue to be built upon. This is incredibly advantageous to newer and less experienced investigators who have found their more experienced colleagues leaving the industry. GenAI also allows investigators to not only review and summarize hundreds of documents relevant to the case, but also quickly and easily generate reports on their findings.

Conclusion

GenAI is already making it possible for insurance companies and their employees to bridge the talent gap. Insurance is a business of documents. Before you can do anything effectively, you need to know what those documents contain, and what that data is really telling you. It can be highly manual, highly time consuming work. If you have enough employees to tackle the problem, it may not seem insurmountable. When the workload exceeds your talent pool, something needs to be done to bridge the gap. GenAI is that bridge.

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