How AI reduces cancellations, promotes upselling, and accommodates true customer proximity in the service center

The digital revolution in the insurance industry is advancing. AI is changing the way insurance companies engage with their customers and design their sales operation processes. Numbers based on BSI Software’s real-life experience speak for themselves: State-of-the-art AI applications lower cancellation rates by up to 30 percent while increasing the potential for upselling significantly at the same time.

The key to this success lies in different AI applications, including large language models (LLMs). They can be used within AI systems for data collection, document verification, responses to customer requests and inquiries, and process automation. AI can be used with great flexibility and can boost the sales efficiency of insurance companies by making data-based processes the foundation of the sales operation.

There are vastly different application areas. One of them is churn prediction: By analyzing customer data and interaction histories, AI detects warning signs before customers actually cancel their policy. Insurers are then able to take proactive steps to stabilize at-risk customer relationships.

Another application area is cross-selling and upselling, where AI systems identify behavior patterns in customer data. They can recommend additional products for customers that meet those customers’ individual needs. This translates into offers that are meaningful to customers, measurably increases the conversion rate, and enhances the customer experience.

Another critical application area for AI is the automation of routine tasks, which frees up service employees to devote their time to more demanding tasks. They can now focus on customer concerns that require human expertise and true customer proximity. As a result, customers feel that they are receiving better service and are therefore more satisfied.

Additionally, AI systems ensure 24/7 customer service availability. At a minimum, they can seamlessly process common requests and inquiries, particularly when it comes to standard products such as car or liability insurance products. There is already a lot of automation present in these areas today, but AI-based automation will provide increased flexibility.

The next evolutionary stage is multi-agent systems where specialized AI modules communicate with each other and solve tasks in collaboration. Here is an example: One AI agent might analyze risks, a second one might evaluate documents, and a third agent might manage fraud detection. This work-sharing approach boosts efficiency and improves accuracy.

This arrangement creates end-to-end automation that can even be used to automate entire insurance processes. Ultimately, it can also speed up black box processing, as many claims can be auto-processed in a few minutes from notification to payment.

These successes speak for themselves. The processing time for insurance claims decreases significantly, and a large part of all transactions are handled with black box processing. This increases customer satisfaction, as most insured people will accomplish their objective quickly. On the insurance side, there are positive results as well, as processing costs decrease significantly.

In a study, McKinsey predicts that underwriting could be almost entirely automated by 2030. Processes that still take days today will be shortened to seconds. LLMs play a key role in this because they are capable of providing a high degree of personalization. Thanks to their communication capabilities, policies can be individualized to meet the needs of each individual customer even without the intervention of employees.

In brief: AI is the pivotal competitive factor for insurance companies. If insurers follow this trend only superficially, they risk being passed up by their AI-savvy competitors. The future belongs to insurers that utilize AI strategically and achieve high profitability as well as customer satisfaction with highly efficient service centers equipped with AI support.