The explosion in the sheer magnitude and complexity of financial news data in recent years makes it increasingly challenging for investment analysts to extract valuable insights and perform analysis. We propose FactCheck in finance, a web-based news aggregator with deep learning models, to provide analysts with a holistic view of important financial events from multilingual news sources and extract events using an unsupervised clustering method. A web interface is provided to examine the credibility of news articles using a transformer-based fact-checker. The performance of the fact checker is evaluated using a dataset related to merger and acquisition (M\&A) events and is shown to outperform several strong baselines.

翻译：近年来，金融新闻数据的规模与复杂性急剧增长，使得投资分析师从中提取有价值信息并开展分析工作日益具有挑战性。我们提出金融领域的"事实核查"系统——一个集成深度学习模型的网络新闻聚合平台，旨在通过无监督聚类方法从多语新闻源中提取重要金融事件，为分析师提供全局视角。该系统提供网页界面，支持用户利用基于Transformer的事实核查器评估新闻可信度。我们采用与并购事件相关的数据集对事实核查器性能进行验证，结果表明其性能优于多个强基线模型。