  This paper explores the application of Natural Language Processing (NLP) in
financial risk detection. By constructing an NLP-based financial risk detection
model, this study aims to identify and predict potential risks in financial
documents and communications. First, the fundamental concepts of NLP and its
theoretical foundation, including text mining methods, NLP model design
principles, and machine learning algorithms, are introduced. Second, the
process of text data preprocessing and feature extraction is described.
Finally, the effectiveness and predictive performance of the model are
validated through empirical research. The results show that the NLP-based
financial risk detection model performs excellently in risk identification and
prediction, providing effective risk management tools for financial
institutions. This study offers valuable references for the field of financial
risk management, utilizing advanced NLP techniques to improve the accuracy and
efficiency of financial risk detection.
