This thesis aims to investigate abstractive methods for financial narrative summarization based on data from the Financial Narrative Processing workshop series. The goal is to produce coherent summaries from annual financial reports of public companies. After the successful undertaking of the project, the students will be able to use NLP tools to analyze text data, harness the power of large language models, and understand and use the appropriate evaluation measures in the area of automatic text summarization.