Why underwriters need to become AI pioneers

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Artificial intelligence (AI) is not only changing processes in insurance companies—it is changing the interaction throughout the entire value chain. Thanks to their greater agility and clear focus on their business model, underwriters have a good chance of quickly embedding AI deeply into their processes and thus becoming early adopters in the industry. This will increase their efficiency – and at the same time make them more attractive to risk carriers and investors.

Assureurs are a particularly relevant example. They handle underwriting and claims processing, develop and market their own insurance solutions, and work in close partnership with primary insurers and reinsurers. Their success lies in their agility, their proximity to the market, and their ability to design products quickly and with a customer-centric approach.

The main focus of the use of artificial intelligence (AI) in the insurance industry is now rightly on embedding AI in business processes. If implemented consistently, this can lead to enormous efficiency gains and quality improvements. This applies not only to the operational areas within insurers, but also to all other players in the industry who map comparable processes.

However, underwriters face the same challenges as established insurers: the need to process enormous amounts of unstructured data – from risk information and claims documents to contract details. For underwriters, efficient handling of this data is particularly crucial because their margins depend directly on efficiency and market success. Every unnecessary process step and every manual check reduces the result – and cannot be offset by the risk result.

Hybrid collaboration as a model for success.

This is exactly where the underwriting agent can use artificial intelligence – as a precisely integrated component in the operational workflow. When AI in underwriting and claims processing not only collects data but also understands correlations, it can provide experts with prepared, structured decision-making bases. AI analyzes, prioritizes, and filters – the final decision is still made by the experienced underwriter or claims manager, i.e., the “human capital” of the underwriter. This hybrid interaction is the real model for success.

Practical experience shows that underwriters who embed AI deeply in their processes can assess risks more quickly, settle claims more accurately, and at the same time create a level of transparency for their risk carriers that was previously almost unattainable. For reinsurers, on the other hand, this provides completely new insights into portfolios, performance indicators, and risk profiles. This strengthens trust and opens up additional margin potential for the underwriter.

Underwriters must leverage their agility

Practical implementation is carried out by specialized AI agents – systems that not only use language models but are also embedded in operational processes and can perform tasks independently. While large language models used in isolation typically achieve an accuracy of around 70 percent in insurance processes, agents specializing in insurance processes deliver over 95 percent – and up to 99 percent when integrated into the workflow. In practice, this performance leads to noticeable improvements in the combined ratio – by up to ten percentage points.

Underwriters can – and should – leverage their agility, manageable business models, and clear focus to be among the early adopters. They will likely be able to integrate AI agents into their processes faster than many insurers. This will increase their efficiency – and at the same time make them more attractive to risk carriers and investors.

However, insurers and underwriters will agree on one point: only those who start now will be able to secure a decisive advantage.

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