Generative AI: automation accelerates processes and risk assessment in the insurance industry

Findings from a pilot project

Artificial intelligence (AI) is revolutionizing various industries, such as healthcare, banking, and publishing. The insurance industry is no exception. In a pilot project with a large Swiss insurer, we gathered experience in underwriting based on the thesis that AI prevents wrong decisions. The realization: AI helps, but not quite as expected.

AI plays a decisive role in changing and supporting underwriting in the insurance industry. It allows insurers to optimize processes, assess risks more accurately, and offer personalized insurance products. By using predictive analytics, machine learning, and advanced data analysis, insurers can work more efficiently and strengthen their competitiveness in an increasingly digital market environment.

How can AI support insurance companies?

Automate data processing

One of the biggest problems is the manual collection and analysis of customer data from applications, presentations, and other documents. This process is extremely time-consuming and error-prone and ties up valuable underwriting resources. AI can help here: It automatically extracts data from various sources and structures and evaluates it. Using machine learning and natural language processing, relevant information can be captured and prioritized in a matter of seconds.

More precise risk assessment

Manual risk assessments are often slow, inconsistent, and based on limited data, resulting in longer response times and inefficiencies. AI systems can analyze large amounts of data in real-time and assess risks quickly, consistently, and based on comprehensive information. Predictive underwriting enables proactive risk assessment and more precise premium calculation.

Personalization of policies

By precisely analyzing individual risk profiles, AI can develop personalized insurance products better tailored to customers' needs. Insurers can offer specific cover that better matches the individual risks and needs of the insured. AI also enables dynamic pricing: AI can adjust premiums in real-time based on the insured’s current risk profile.

Results of the AI pilot project

Fast information extraction through AI

In a pilot project with a large Swiss insurance company, we were able to show how AI helps to efficiently extract relevant information from over 5,000 different documents. Without the use of AI, employees would have had to search through the documents manually and type out the required information. By combining AI with existing structured data, we were able to significantly speed up this time-consuming process.

Efficiency thanks to AI through automation of simple cases

A central use case of the pilot project was the support of the underwriting process through AI. The AI solution was tasked with making decisions based on form data. More than 80 percent of these decisions were correct.

Simple cases, in particular ("green cases"), can be automated with AI as a first step. Automation speeds up the processing of clear-cut cases and the entire process for insurers and policyholders. This gives the technical experts time for the more complex cases and potentially reduces the error rate. For example, people who are rejected even though they would have been good customers.

The results of the pilot project show that the use of AI brings significant benefits to the underwriting process in insurance companies:

  • Faster decisions for the customer

  • Important inputs and preparatory work for personalized premiums

  • More efficient processing of the mass of clear cases with at least the same decision quality

  • Better deployment options for technical experts in complex cases, as simple cases can be processed by AI.

Based on these general findings, we can develop AI solutions for use cases tailored to your business needs in underwriting and other areas.

Let us show you how. Get in touch with us today:

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