Fraud detection skills of Thai Gen Z accountants: The roles of digital competency, data science literacy and diagnostic skills

• Digital competency and data science literacy are crucial factors of fraud detection skills. • Diagnostic skills emerge as a critical intermediary, facilitating the transition from technical proficiency to tangible fraud detection capabilities. • How proficiency in advanced data analysis, big data management, and predictive analytics fundamentally bolsters their ability to identify and mitigate fraudulent activities. • Importance of combining technological skills and data analysis abilities with ethical training and auditing to prepare for future challenges in the accounting profession. The issue of accounting fraud presents a significant challenge within the business sector, prompting an increase in scholarly investigations across various contexts. Despite this growing interest, research specifically addressing the Thai context has remained scarce. Thus, this quantitative study aimed to bridge this gap by assessing the proficiency of Thai Gen Z accountants in detecting accounting fraud, with a particular emphasis on their digital, data science, and diagnostic skills. The study collected data from 150 participants using a structured survey questionnaire distributed to licensed accountants affiliated with the Thailand accounting program. It adopted a theoretical framework inspired by social learning theory and information processing theory to examine both direct and mediated relationships among the key variables under investigation. The results were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine these relationships. The results showed that digital competency have significant direct effects on the fraud detection skills, with diagnostic skills playing a key role in the process. The study revealed that digital competency not only furnishes accountants with necessary technological expertise but also bolsters their analytical skills, which are vital for identifying fraudulent activities. Likewise, data science literacy—encompassing skills in predictive analytics, big data management, and data insight communication—significantly enhances accountants' capacity to identify and understand fraudulent patterns. The emergent role of diagnostic skills as a key intermediary emphasizes the importance of comprehensive training programs that foster both technical prowess and critical analytical thinking.

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Publication Details

Journal
International Journal of Information Management Data Insights
Published
2024-11-26
DOI
https://doi.org/10.1016/j.jjimei.2024.100308
Citations
6
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
2.08
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article

Fraud detection skills of Thai Gen Z accountants: The roles of digital competency, data science literacy and diagnostic skills

Watcharawat Promma, Berto Usman, Somnuk Aujirapongpan, Narinthon Imjai et al.
6 citations
International Journal of Information Management Data Insights
Imbalanced Data Classification Techniques
2.08
article

Fraud detection skills of Thai Gen Z accountants: The roles of digital competency, data science literacy and diagnostic skills

Watcharawat Promma, Berto Usman, Somnuk Aujirapongpan, Narinthon Imjai, Nimnual Visedsun
article en
6 citations

Abstract

• Digital competency and data science literacy are crucial factors of fraud detection skills. • Diagnostic skills emerge as a critical intermediary, facilitating the transition from technical proficiency to tangible fraud detection capabilities. • How proficiency in advanced data analysis, big data management, and predictive analytics fundamentally bolsters their ability to identify and mitigate fraudulent activities. • Importance of combining technological skills and data analysis abilities with ethical training and auditing to prepare for future challenges in the accounting profession. The issue of accounting fraud presents a significant challenge within the business sector, prompting an increase in scholarly investigations across various contexts. Despite this growing interest, research specifically addressing the Thai context has remained scarce. Thus, this quantitative study aimed to bridge this gap by assessing the proficiency of Thai Gen Z accountants in detecting accounting fraud, with a particular emphasis on their digital, data science, and diagnostic skills. The study collected data from 150 participants using a structured survey questionnaire distributed to licensed accountants affiliated with the Thailand accounting program. It adopted a theoretical framework inspired by social learning theory and information processing theory to examine both direct and mediated relationships among the key variables under investigation. The results were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine these relationships. The results showed that digital competency have significant direct effects on the fraud detection skills, with diagnostic skills playing a key role in the process. The study revealed that digital competency not only furnishes accountants with necessary technological expertise but also bolsters their analytical skills, which are vital for identifying fraudulent activities. Likewise, data science literacy—encompassing skills in predictive analytics, big data management, and data insight communication—significantly enhances accountants' capacity to identify and understand fraudulent patterns. The emergent role of diagnostic skills as a key intermediary emphasizes the importance of comprehensive training programs that foster both technical prowess and critical analytical thinking.

International Journal of Information Management Data InsightsVol. 5(1)
Nakhon Si Thammarat Rajabhat University (TH), University of Bengkulu (ID), Silpakorn University (TH), Rangsit University (TH), Walailak University (TH)
Quality Education
Openalex Percentile: Top 11%
Imbalanced Data Classification Techniques
2.08
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