<body><div><figure><img src="https://img.particlenews.com/image.php?type=thumbnail_580x000&amp;url=3fXseZ_0w6EprXE00" alt="https://img.particlenews.com/image.php?url=3fXseZ_0w6EprXE00" width="750" height="500" ></figure>(Image credit: Thomas Lefebvre/Unsplash.)I spend a lot of time thinking about insurance and the things that drive the industry. How can carriers deliver consistent profitability and growth? What are the technologies insurers are turning to in their efforts to gain operational efficiencies and reduce costs? Where do these technologies intersect with the policy and claims lifecycle?Although the claims process—including automation, fraud detection, and subrogation and recovery—captured a fair amount of attention while combined ratios were soaring, claims are only one piece of the larger puzzle. When thinking about profitability and growth, it is imperative to begin at the beginning. That beginning is underwriting. Simply put, writing new policies is what drives new revenue for insurers. A long-term healthy book of business hinges on being able to quickly write new policies, while at the same time avoiding premium leakage and excessive claims in the future. Experienced underwriting professionals are key to ensuring this happens consistently and reliably.Yet, we cannot ignore that the insurance industry is facing an upcoming talent gap. We have seen the predictions. It is estimated that the insurance industry in the U.S. alone will lose nearly half a million employees—including underwriters—in the next 10-15 years. It is also anticipated that those jobs will not be replaced. As an aging workforce retires, younger workers are simply not joining the insurance ranks in the numbers they once were. So, the question is, “How do we ensure the health of our industry in the face of this very real challenge?”A Problem of ScaleSince insurance starts with the policy, let us explore the problem from the perspective of the underwriter. As we have previously addressed, the goal of the underwriting process is to generate profitable business for the insurance company. Understanding the risk associated with an application and then pricing the policy correctly according to that risk is the core responsibility of the underwriter. It can take years of experience to develop the expertise required to make the best underwriting decisions possible, avoiding premium leakage and leading to a profitable book of business and long-term success.It is also important to recognize that while the underwriting process is increasingly benefiting from automation, complex underwriting decisions still come down to the judgement of individuals. The speed at which applications can be approved and policies written and bound corresponds directly to how quickly an insurer can bring in new business. Even with the benefit of automation, it stands to reason that the more underwriting professionals an insurer employs the better positioned they are to write a greater number of policies that are good for the business.It is within this scenario where insurers begin facing a problem of scale. Current underwriting automation strategies are designed to streamline processes and generate operational efficiencies. They are not designed to help underwriters make important decisions about the applications that come to them. In the face of a shrinking talent pool, automation may soon start causing more problems than it solves.The Uncertainty of AutomationAs we have seen in other insurance processes, automation strategies can introduce unintended consequences. The main problem is that rules-based solutions can be easily manipulated when their logic or thresholds are discovered. Not only does simple misrepresentation with the aim of securing a lower premium become easier, but also attempts at more organized fraud. While it is certainly true that automation may help insurers write more policies and write them more quickly, they must also face the risk that automation without intelligence may be negatively impacting their book of business in the long run.Applying Generative AI to the ChallengeIf automation alone is not enough to overcome the underwriting talent gap, what options do insurers have? Artificial intelligence (AI) generally, and generative AI (GenAI) more specifically, are already proving adept at bringing added value to core automation initiatives. As we have previously addressed, simply speeding up the underwriting process via simple automation is not enough if the human element—which is still crucial to truly successful underwriting—becomes a bottleneck.When AI and GenAI are paired with other automation strategies, insurers benefit not only from speed, but also from having critical knowledge and information delivered directly to their underwriters. GenAI can read, analyze, and summarize new applications. It can quickly and accurately identify those applications that require little if any additional review. Or, GenAI can spot missing details or other aspects of an application that may require additional scrutiny from the underwriter. As important, the actionable insights delivered by GenAI can be provided to underwriters as natural language recommendations, making it easier to determine the best next steps.What might this look like in real life? Take for example an applicant that wants to insure four heavy duty trucks. Where the vehicles will be garaged is identified as a residential address. There is only one listed driver on the application. In this scenario, a rules-based automation solution may not trigger a review if the number of vehicles on the policy is within the insurer’s threshold. Or, an inexperienced underwriter, pressed to quickly move from one application to the next may miss a lot of the red flags in this application. While an experienced underwriter may check to see if the residence abuts a construction business owned by the applicant or recognize that the vehicles in question are clearly not “daily drivers,” those considerations may be missed by someone with less expertise. The misrepresentation on the application sets the insurers up for significant premium leakage and the potential for greater exposure in the event of a loss. With GenAI analyzing the application, every underwriter, independent of experience or expertise, is provided with everything needed to make a fast, accurate and fair assessment of how to best proceed. When used in support of an underwriting automation strategy, GenAI can give insurers greater confidence that the applications requiring further review are identified as such and routed for human intervention.ConclusionUnderwriting is the lifeblood of the insurance industry. Insurers around the world rely on this group of highly experienced professionals to make decisions every day that could mean the difference between profitability and loss. At the same time, the industry is facing a rapid decrease of this expertise, not to be replaced. While this situation may be unavoidable, its impact can be mitigated. AI and GenAI, when deployed effectively, can mimic the minds of our industry’s best underwriters. It can help all underwriters make better decisions, write better policies and protect the bottom line.</div></body>

Mountain View, CA

NewsBreak

AI, Underwriting and the Coming Talent Gap

(Image credit: Thomas Lefebvre/Unsplash.) I spend a lot of time thinking about insurance and the things that drive the industry. How can carriers deliver consistent profitability and growth? What are the technologies insurers are turning to in their efforts to gain operational efficiencies and reduce costs? Where do these technologies intersect with the policy and claims lifecycle?