...Stewart Jones; Clinton Free Purpose This paper provides a comprehensive and conceptually grounded review of how artificial intelligence ( AI ) and machine learning ( ML ) are transforming professional judgement in accounting. It clarifies the epistemic foundations of AI and ML , synthesises...

...) with supervised machine learning techniques to evaluate the professional level of investor inquiries on China’s Investor Interaction Platforms (IIPs). We construct a professional inquiry index and combine it with firm-level data to identify the source of professional inquiries. Empirical analyses, including...

..., and XGBoost algorithms, focusing on education level and work experience as sensitive attributes. To mitigate data bias in historical datasets, we employ the Metropolis-Hastings (M-H) algorithm for data preprocessing. Findings (1) Machine learning models like Random Forest and XGBoost outperform...

...Wenyan Wu; Liangbo Ma; Shiguang Ma Purpose This study aims to evaluate the effectiveness of machine learning (ML) in detecting accounting fraud among Chinese-listed firms from 2007 to 2022. It aims to determine whether advanced ML techniques outperform traditional logistic regression models...

... portrayals of corporate ESG performance influence corporate financing and investment behaviors. Design/methodology/approach The research employs a sophisticated analysis using machine learning and natural language processing to evaluate 2,276,364 ESG-related news articles from the Baidu news website...

... machine learning approach to provide additional insights into the role of investment opportunities in predicting private firms’ performance. Findings We find a positive association between private firms’ investment opportunities and their performance. Furthermore, our study demonstrates that female...

... research themes over time, identifying key areas where AI is influencing financial services. Findings The study confirms an exponential growth in research output on AI applications in finance, particularly in recent years. This growth is driven by increasing interest in machine learning algorithms, big...

... discrepancy Machine learning Text analysis Environmental, Social, and Governance (ESG) factors represent a systematic investigation of the sustainable development ability of enterprises. In 1992, the United Nations Environment Programme Financial Initiative (UNEPFI) recommended financial...

...Jinfang Tian; Xiaofan Meng; Lee Li; Wei Cao; Rui Xue Purpose This study aims to investigate how firms of different sizes respond to competitive pressure from peers. Design/methodology/approach This study employs machine learning techniques to measure competitive pressure based on management...

... articles. After examining these 88 articles, the results imply that the current literature is shifting from traditional statistical approaches towards computational methods, specifically machine learning (ML), for predicting and detecting FSF. This evolution of the literature is influenced by the impact...

... such as state-of-the-art machine learning and textual analysis. Through these sophisticated methodologies, we demonstrate that the level of firm-specific exposure to climate change significantly influences the extent of foreign currency hedging. Lastly, our research makes a valuable contribution to the body...

..., particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings...