Natural Language Processing (NLP) is transforming the analysis of economic reports by enabling automated extraction of key insights from complex financial documents. Central bank statements, employment reports, GDP data, and inflation announcements contain critical information that impacts financial markets. NLP models, such as BERT and GPT, help process and interpret these reports in real time. Techniques like named entity recognition (NER) identify key economic indicators, while sentiment analysis determines the tone of reports—whether they signal economic growth or contraction. Topic modeling helps categorize sections of lengthy reports, making them easier to analyze. Financial institutions and traders use NLP-powered tools to detect trends, assess policy impacts, and make informed trading decisions. Additionally, NLP algorithms can compare historical economic reports with market reactions to improve predictive accuracy. Despite challenges such as understanding nuanced policy language and handling unstructured data, NLP remains an essential tool for automating and enhancing economic report analysis.