A Multimodal Dataset for Bank Failure Prediction in Vietnam
收藏资源简介：
This dataset integrates textual, financial, and macroeconomic indicators to support research on bank failure prediction and financial distress forecasting in Vietnam. It includes financial news from the BKAI News Corpus Dataset (2009–2023) and financial crisis data from "A Dataset for the Vietnamese Banking System (2002–2021)" (Tu Le et al., 2022), covering crisis-related events such as restructuring, special control, mergers, and acquisitions.The dataset was systematically processed to align textual and financial data by time and entity (banks). Bank mentions in news articles were identified using common spelling variations and abbreviations. Macroeconomic and banking sector indicators were collected from the World Bank and the General Statistics Office of Vietnam. A categorical variable indicates whether a bank was classified as weak based on official State Bank of Vietnam reports.This dataset is suitable for time-series analysis and machine learning applications, enabling researchers to explore relationships between financial narratives, macroeconomic factors, and banking crises. It facilitates the development of predictive models, including deep learning architectures, for early warning systems in financial risk management.Proper attribution to BKAI, Tu Le et al. (2022), the World Bank, and the General Statistics Office of Vietnam is required when using this dataset.Keywords: Bank failure prediction, multimodal dataset, financial news analysis, CAMELS rating, time-series analysis, machine learning, deep learning, Vietnam banking system.
本数据集整合了文本、金融与宏观经济指标，以支撑越南银行业破产预测及财务困境预警相关研究。其数据涵盖来自BKAI新闻语料库数据集（BKAI News Corpus Dataset，2009–2023）的金融新闻，以及《越南银行业数据集（2002–2021）》（Tu Le等，2022）中的金融危机相关数据，涉及重组、特别监管、并购等危机关联事件。本数据集已完成系统化处理，实现文本与金融数据按时间维度与实体（银行）进行对齐。新闻文本中的银行提及项，通过通用拼写变体与缩写形式完成识别。宏观经济与银行业部门指标采集自世界银行与越南统计总局。数据集设置了分类变量，用于标识依据越南国家银行官方报告划定的弱势银行。本数据集适用于时序分析与机器学习应用，可助力研究者探索金融叙事、宏观经济因素与银行业危机间的关联关系，并可助力开发包含深度学习架构在内的预测模型，应用于金融风险管理领域的预警系统。使用本数据集时，需正确标注BKAI、Tu Le等（2022）、世界银行及越南统计总局的来源。关键词：银行破产预测、多模态数据集、金融新闻分析、CAMELS评级（CAMELS Rating）、时序分析、机器学习、深度学习、越南银行业体系。
