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.

翻译：本文探讨了自然语言处理在金融风险检测中的应用。通过构建基于自然语言处理的金融风险检测模型，本研究旨在识别和预测金融文档与通信中的潜在风险。首先，介绍了自然语言处理的基本概念及其理论基础，包括文本挖掘方法、自然语言处理模型设计原则和机器学习算法。其次，描述了文本数据预处理和特征提取的过程。最后，通过实证研究验证了模型的有效性和预测性能。结果表明，基于自然语言处理的金融风险检测模型在风险识别和预测方面表现优异，为金融机构提供了有效的风险管理工具。本研究利用先进的自然语言处理技术提高金融风险检测的准确性和效率，为金融风险管理领域提供了有价值的参考。