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BIMSA Digital Economy Lab Seminar
Integrating managerial and investor textual data for financial distress prediction: A framework combining multi-source financial information fusion network with LLM
Integrating managerial and investor textual data for financial distress prediction: A framework combining multi-source financial information fusion network with LLM
演讲者
时间
2025年09月26日 15:00 至 16:00
地点
A3-2-303
线上
Zoom 435 529 7909
(BIMSA)
摘要
Leveraging multi-source data for financial distress prediction (FDP) has gradually attracted growing attention. In this study, we propose a novel FDP framework that integrates simultaneously financial ratios, Management Discussion and Analysis (MD&A), and investor comments from social media. First, we develop a fine-grained feature extraction approach that leverages both large language model (LLM) and the BERT model to capture aspect-level sentiments and rich semantic information from MD&A data. Second, we utilize FinBERT to extract sentiment features from investor comments. These textual features are then combined with financial ratios and integrated into a Multi-source Financial Information Fusion Network (MFIFN), which is trained using a focal loss function to effectively address data imbalance in FDP. Based on the dataset of 24,429 firm-year samples from Chinese listed companies between 2014 and 2023 (including both distressed and non-distressed firms), experimental results demonstrate that incorporating social media and MD&A features enhances predictive performance compared with financial ratios alone. In particular, the proposed MFIFN model achieves an AUC of 0.9541. Furthermore, the LLM-BERT based triplet extraction method improves feature quality, delivering consistent performance gains across compared with traditional textual feature extraction methods.
演讲者介绍
Ruize Gao is an assistant professor at Beijing Institute of Mathematical Sciences and Applications. His research interests include digital economy and data mining. He has published in leading journals such as Decision Support Systems, Information Sciences, Knowledge-based Systems, Financial Innovation, Expert Systems with Applications, Technology in Society, International Journal of Accounting Information Systems. He hosts one funding project under the China Postdoctoral Science Foundation.