Machine learning is an essential part of artificial intelligence (AI). As the new Head of Machine Learning at ERGO, Sebastian Kaiser deals with a large amount of unstructured data such as texts, images, sound recordings and videos, in order to organise this data, link it to the knowledge base and thus extract value-adding information: "We develop business cases from a large amount of data in order to create more freedom for employees. This puts the focus on customer interaction and demanding, creative activities, repetitive and simple tasks can be automated - and customer loyalty and business growth are supported."
He and his team are currently working on supporting ERGO's inbound management with AI. The goal is to classify relevant documents, read them automatically and make the data available to the right person. This is because subsequent processes should also be simplified, for example by automatically entering application parameters or summarising extensive expert opinions. "With our work, we want to achieve an ideal interaction between employees and AI, which will increasingly provide us with a new, human-validated database that we can later use for further automation," reports the newly appointed Head of Machine Learning.
Kaiser is convinced that ERGO will have achieved a significantly higher level of digitalisation and automation in five years' time. A case of the future could be, for example, that a severe hailstorm, which is extensively reported in the news, is recognised by the algorithm and the sales partner does not react but actively approaches affected customers with important information and documents for claims processing. In addition, it would be conceivable that the customer calendar already suggests appointments for appraisal (possibly even digitally) and repair at the nearest workshop. "Of course, it would be great if we had more comprehensive customer data at our disposal. This would allow us to develop our concepts even more in line with demand and thus further increase customer satisfaction," Kaiser describes his thoughts for future scenarios. Of course, this would always have to happen under the applicable data protection regulations.
Sebastian Kaiser moved from Munich Re to ERGO in July 2021. "The AI team at ERGO is excellently positioned, has a clear strategy and a very good concept for how AI and machine learning will be used in the insurance environment in the future. For me as a data person, this offers a large field of action that is very close to the customer. In addition, I see ERGO as a leader in the field of digitalisation in the insurance industry in Germany, which is why I am very excited to be able to help shape the future," says Kaiser.
After studying statistics at Ludwig Maximilian University in Munich, Kaiser spent a research period at the university in Wollongong (Australia), because number-crunching and statistics played a much bigger role here than in other countries, he says. He then returned to the LMU in Munich and did his doctorate on the topic of "Biclustering: Grouping of high-dimensional data (Big Data), methods, software and applications". This involves filtering out similar objects with similar properties in large groups. Such methods are often used in gene expression analyses or in marketing - for example, to find out which customers with which characteristics often buy certain insurance products together.
Kaiser was already a mathematics ace as a child. Today, the 40-year-old lives with his family in Augsburg and loves football - for the experience - and baseball - for the numbers. "In baseball, everything can be analysed exactly, that's what I like most about this sport."
Text: Barbara Czech-Ettinger