基于文本预训练和多任务学习的金融风险预测方法及装置

• Format: Patent
• Language: Chinese
• Published: 04.06.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

本申请涉及一种基于文本预训练和多任务学习的金融风险预测方法及装置。该方法包括：获取待处理文本；将待处理文本输入第一神经网络模型，以按照风险识别任务的处理流程确定待处理文本的内容是否包括金融风险；在待处理文本的内容包括金融风险的情况下，利用第一神经网络模型按照风险分类任务的处理流程确定金融风险的风险类型；利用第一神经网络模型按照风险主体识别任务的处理流程确定与风险类型匹配的风险主体。本申请通过预训练语言模型技术解决了缺乏对语义的深度挖掘导致模型性能不佳的问题，并采用多任务处理，解决了数据量有限而且任务之间无法进行信息共享导致模型性能不佳的技术问题。 The invention relates to a financial risk prediction method and device based on text pre-training and multi-task learning. The method comprises the steps of obtaining a to-be-processed text; inputting the to-be-processed text into a first neural network model to determine whether the content of the to-be-processed text includes financial risks according to the processing flow of the risk identification task; under the condition that the content of the to-be-processed text comprises the financial risk, determining the risk type of the financial risk according to the processing flow of the risk classification task by utilizing a first neural network model; and determining a risk subject matched with the risk type by using the first neural