An Intelligent Risk Assessment Model Based on NLP

In the field of computer artificial intelligence, traditional data analysis methods face challenges of incomplete data and low processing efficiency. To address this issue, this paper proposes a novel risk assessment model based on Natural Language Processing (NLP) technology. Utilizing deep learning, Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM) networks, the model analyzes unstructured data such as text, social media information, and news reports, thereby improving the accuracy and efficiency of data processing. The research results show that, compared to traditional methods, this model has significant advantages in data processing efficiency and accuracy. Future research will focus on enhancing the adaptability and practicality of the model, providing a more effective risk assessment tool for the field of computer artificial intelligence.