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The purpose of this paper is to evaluate the possibility of rating the credit worthiness of a firm’s quarterly financial report using a dynamic anomaly detection method.

The study uses a data set containing financial statements from Quarter 1 – 2001 to Quarter 4 – 2016 of 937 Vietnamese listed firms. In sum, 24 fundamental financial indices are chosen as control variables. The study employs the Mahalanobis distance to measure the proximity of each data point from the centroid of the distribution to point out the extent of the anomaly.

The finding shows that the model is capable of ranking quarterly financial reports in terms of credit worthiness. The execution of the model on all observations also revealed that most financial statements of Vietnamese listed firms are trustworthy, while almost a quarter of them are highly anomalous and questionable.

The study faces several limitations, including the availability of genuine accounting data from stock exchanges, the strong assumptions of a simple statistical distribution, the restricted timeframe of financial data and the sensitivity of the thresholds for anomaly levels.

The study opens an avenue for ordinary users of financial information to process the data and question the validity of the numbers presented by listed firms. Furthermore, if fraud information is available, similar research can be conducted to examine the tendency for companies with anomalous financial reports to commit fraud.

This is the first paper of its kind that attempts to build an anomaly detection model for Vietnamese listed companies.

This study aims to explore the relationship between digital transformation, transformational leadership style and artificial intelligence (AI) in accounting in the context of Vietnam as an emerging market. Additionally, it examines the role of transformational leadership style as a moderator in the nexus between digital transformation and AI in accounting.

Data was collected through e-survey questionnaires distributed to Vietnamese manufacturing firms following comprehensive screening to ensure representativeness of the entire population. A final sample of 510 responses was analyzed.

Using partial least squares structural equation modeling, our findings reveal that digital transformation and a transformational leadership style positively influence AI in accounting. Furthermore, transformational leadership style demonstrates a significant moderating effect on the relationship between digital transformation and AI in accounting.

This study discusses the benefits of incorporating AI in accounting for managerial decision-making. It underscores the critical importance of digital transformation in contemporary accounting practices, particularly with regards to AI in accounting. Consequently, managers are encouraged to embrace digital transformation, leveraging national policies, to enhance their firm's utilization of AI in accounting. Moreover, managers should focus on developing their transformational leadership style to maximize the aforementioned outcomes.

This study contributes to the literature on AI in accounting by highlighting the positive effects of digital transformation and a transformational leadership style. Additionally, our findings underscore the effectiveness of a transformational leadership style and its moderating influence. Finally, this study presents a pioneering empirical investigation that integrates transformational leadership style with AI in accounting within developing economies, specifically Vietnam.