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Wednesday, 03 January, 2024

Smart processes in response to the shortage of skilled labor– why the insurance industry can’t do without artificial intelligence

The shortage of skilled labor is putting the insurance industry under considerable strain. More than ever, insurance companies are reliant on data-driven tools and artificial intelligence (AI) to compensate for staff bottlenecks, and claims management in particular holds great potential.

This article war first published in Handelsblatt (German)

In the field of claims processing in particular, data-driven processes are proving to be indispensable. They enable insurers to respond quickly and in a customer-centric manner, especially in situations where the number of claims rises sharply. A typical scenario for this would be extreme weather events such as heavy rain, storms, hail, snowfall or flooding, which cause considerable damage to buildings every year.

Shortage of experts: Claims management under pressure

Take a classic example: The roof of a house was severely damaged by snow load after a sudden onset of winter. The owner urgently needs her insurance company to pay compensation to cover the repair costs but her insurer is in a state of emergency. The claims agent is faced with a deluge of claims, overworked and unable to provide the customer with the service she is used to. In the meantime, the homeowner is waiting for a speedy resolution.

Weather damage to buildings represents an ever-increasing proportion of insurance claims. For insurance companies, this means an increased workload. © Eucon, AI-generated image

For insurance companies, scenarios like these are costly: experts lack the time to properly check claims, resulting in unjustified claims, inflated repair costs and attempted fraud going undetected. At the same time, extreme weather events, such as storms, are occurring with increasing frequency and intensity, while it is becoming more and more difficult to find qualified specialists to process claims. As a result, the quality of service deteriorates, with the potential impact that satisfaction with the insurer decreases and the customer is lost.

AI tools help insurers process claims more efficiently

This is the “moment of truth” when insurance companies must deliver on their promises and prove their worth. Policyholders expect rapid assistance, especially in the event of a claim. AI tools can take the pressure off and help insurers keep track of claims and speed up the settlement process, even when staffing levels are low. One example of this is the pre-checking of documents using AI. All documents contain a wealth of data, both structured and unstructured, which can serve as the basis for processing a claim. AI can automatically record, organize and evaluate this data, making it possible to settle plausible claims quickly using an automated process. The homeowner from the example case would then receive her money faster and be able to get her roof repaired. Instead of processing this routine case, the claims agent can then focus on more complex cases that require closer attention. Additional AI tools support them in this process: the more complex cases are routed out directly with a recommendation for action, which is then reviewed by the claims agent. Based on their expertise, they then decide whether to accept the recommendation or process the case individually.

Fast claims processing not only results in more satisfied customers, but also reduces the workload of claims agents. © Eucon, AI-generated image

Alternatively, insurance companies may also forward these cases to an experienced claims service provider with recommendations for action, where they are reviewed by experts using data-based tools. This further reduces the strain on employees, allowing their resources to be used more effectively elsewhere.

Augmented intelligence: the smart solution for AI-based claims management

Eucon’s AI-based pre-check combines two approaches to artificial intelligence: on the one hand, it includes AI-supported and fully automated processing and, on the other, it integrates the concept of augmented intelligence, where human decision-making is merged with machine intelligence.

This supports claims agents in their decision-making, but without taking over the actual decision-making on their behalf. The advantage over process-centered automation is that humans remain at the heart of complex decision-making processes, while AI is “only” there to provide relevant information or immediate data-based recommendations for action. In this way, human judgment is enhanced through the fast and precise processing of large amounts of data by AI. At the same time, the AI constantly learns through built-in feedback loops, thus becoming more and more efficient. This approach reduces the workload at times of scarce resources, not only during periods of high-volume claims, but also in day-to-day business for insurers.

Greater customer satisfaction and a leaner claims process with AI

AI-based approaches provide insurance companies with a dual benefit in the claims process: they can make more efficient use of their existing expertise and at the same time offer claimants a more customer-friendly claims journey, creating a win-win situation. Customer needs are addressed in a faster and more targeted way, while the technology simultaneously relieves the strain on experts, who need to handle more and more claims in times of a shortage of skilled labor. This allows them to use their expertise and problem-solving skills constructively instead of spending time on standard cases. Ultimately, insurers save money by complementing human expertise with the analytical skills of AI. Even an exponential increase in submitted claims documents, as in the example mentioned above, cannot disrupt tried-and-tested checking processes, but enhances the customer experience through swift processing.

AI alone, however, will not be capable of solving the challenges posed by the shortage of skilled labor, but it can significantly mitigate them. Already today, data-based tools are supporting the insurance industry in many process steps and increasing employee efficiency. We will see great progress in this area in the future as new developments in the field of generative AI lead to groundbreaking changes in the market.