Large language models (LLMs) have emerged as powerful tools in natural language processing showing outstanding performance across a spectrum of tasks and garnering considerable attention in research. Their capacity to generate human-like language and potential to reshape science and technology have encouraged their exploration across various industries, including insurance. The insurance sector faces the challenge of managing vast volumes of data from both internal and external sources and therefore formulating effective strategies for data management becomes crucial for maintaining competitiveness in an evolving marketplace. This thesis investigates the application of LLMs in classification and information extraction tasks within the context of complaints management.