Senior Editor at Allianz SE
Integrating ‘technology with heart’:
Allianz and Accenture’s insights on GenAI
Senior Editor at Allianz SE

First, what is the essence of GenAI
Barbara Karuth-Zelle opens by referring to science fiction movies about robots, how “in the end, we give them a human touch.” GenAI does that, giving the machine a human touch. She explains further, “What you saw in science fiction movies was people talking with machines in natural language, and that is what you’re seeing today.” While traditional AI relies on specific programming languages and human intervention, GenAI enables machines to generate original content from simple natural language prompts. That allows anyone to easily access and use huge amounts of information. It will have profound benefits for society, science and for us in our work, so it is important that everyone quickly learns how best to use it.
Building on that, Sirma Boshnakova underscores the role GenAI will play in business transformation. "It's important to talk about how emerging technologies will drive this change," she says. Consumers' feelings toward GenAI are split between fear and excitement. Fear arises from speculation, misinformation, and concerns about technology creating "Frankensteins," Sirma notes. On the other hand, excitement stems from GenAI's potential to create a seamless and borderless world, improving lives by removing friction and providing timely, guided care.
Industry and societal impact: Beyond efficiency
GenAI and the insurance landscape: Utilizing GenAI across the entire value chain
The transformative potential of GenAI isn't limited to healthcare and education; it extends deeply into the insurance sector as well. In this context, GenAI's applications are manifold, ranging from accelerating underwriting processes to enhancing customer interactions, thereby streamlining operations and significantly improving service delivery.
Both Sirma Boshnakova and Barbara Karuth-Zelle point out the potential of GenAI to eliminate outdated legacy IT systems and processes by giving people simpler ways of doing complex things, which will increase operational agility and efficiency. This vision is part of Allianz's broader strategy to integrate GenAI across the entire value chain, from underwriting and claims processing to customer service.
Innovations in underwriting and claims processing
In underwriting, GenAI can analyze vast amounts of data, including unstructured data, to provide a comprehensive understanding of potential risks. As Sirma Boshnakova notes, "We have great examples in the area of underwriting, where we can accumulate a lot of unstructured data. With GenAI, we can grant our underwriters much more accuracy and preciseness. "Not only does this enhanced precision improve the efficiency of underwriting processes, but it also contributes to more accurate risk assessment, and far more competitive and fair pricing for customers.”
Claims processing is another area where GenAI can drive significant improvements. By automating the assessment of claims and detecting fraudulent activities through pattern recognition, GenAI can reduce the time and cost associated with claims management. Karuth-Zelle shares a tangible example: "For pet insurance, they can actually, with the use of GenAI, not only do a straight-through processing of the claim, but also the deduction of what is not insured." This automation enables faster claim resolutions, enhancing customer satisfaction and operational efficiency.
GenAI benefits directly experienced by the customers
Operational agility and continuous learning
By automating routine tasks, GenAI frees up employees to focus on more strategic, value-adding activities. This shift not only enhances productivity but also fosters a culture of innovation within the organization. To enable this, Karuth-Zelle refers to the training and development initiatives underway at Allianz: "Allianz Technology created an AI Run that we offered to the entire company. We already reached more than 4,000 employees in the first round."
Allianz’s approach ensures that it remains at the forefront of ethical AI deployment, building trust through transparent practices and rigorous ethical standards.
Julie Sweet reinforces this sentiment by highlighting Accenture's commitment to learning and training, “We believe that it is absolutely essential to the success of Accenture—and our ability to serve clients and be a place where people can build long-term careers—to have a company of learners.”
Ethical considerations and challenges: Responsible integration of GenAI
The integration of GenAI into the insurance sector carries with it significant ethical considerations as well. Julie Sweet emphasizes the necessity for responsible AI use, particularly in a heavily regulated industry like insurance.
Allianz is committed to these principles, with both of the Allianz Board Members stressing the need for rigorous checks and regular audits to ensure AI models remain unbiased and equitable. This effort is crucial for developing AI systems that lead to fair decision-making, preserving the integrity and trust in their services. Allianz promotes a model where AI supports human decision-making, ensuring that complex or sensitive situations receive the nuanced understanding that only human agents can provide.
Looking ahead
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** As of September 30, 2024.