Artificial Intelligence Adoption and Detection of Fraudulent Financial Statement in The Nigerian Public Sector: Role of Organisational Culture (Published)
This study investigated the association between organizational culture and the effectiveness of artificial intelligence (AI) tools in detecting financial statement fraud in the public sector, with a focus on the moderating role of organizational culture. The increasing complexity of the public sector financial system and the growing use of AI-based fraud detection tools necessitate an understanding of contextual factors that influence their effectiveness. The study is grounded in institutional theory and adopts a quantitative research design complemented by explanatory correlational analysis. A population of 820 participants from the Bayelsa State Ministry of Finance were involved in accounting and auditing functions across public sector institutions, while a sample of 380 participants was drawn using a stratified random sampling technique. Primary and secondary data were employed with a questionnaire as the major source of data collection based on a 5-point Likert scale. The questionnaire was tested using content and face validity, while reliability was determined by the Cronbach’s Alpha coefficient. The responses from the administered questionnaire were tested using univariate, bivariate and multivariate analysis. The SEM analysis revealed a positive and significant association between MAL, NLP, DTA, DIM, and EXS on the detection of financial statement fraud in the public sector. The results further revealed that organizational culture positively and significantly moderates the relationship between AI adoption and the detection of financial statement fraud in the public sector. The study concludes that AI tools alone are insufficient for optimal fraud detection performance in the public sector. Instead, their effectiveness is maximized when supported by a strong and ethical organizational culture. The study recommends that public sector institutions should integrate cultural development strategies with AI adoption policies to strengthen fraud detection systems and improve financial accountability.
Keywords: Artificial Intelligence, Fraud Detection, Organisational Culture, Public Sector, financial statement fraud detection
Fraud Prevention and Detection (Review Completed - Accepted)
Fraud has been a million-dollar business which is rapidly increasing at global level. Most organisations are victims of fraud which is committed in unlimited multifarious forms. Major threats have been prompted by new information systems, reengineering and reorganisation which weaken the existing controls. The paper addresses the anti-fraud strategy and fraud prevention and detection techniques.
Keywords: Anti-Fraud Strategy, Fraud Detection, Fraud Prevention, Perp-Walk
The New Fraud Diamond Model: How Can It Help Forensic Accountants In Fraud Investigation In Nigeria? (Published)
Fraud has been associated with human organisation from recorded history. Investigating and detecting fraud is not an easy task and requires thorough knowledge about the nature of fraud, how it can be committed and concealed. Forensic Accountants are increasingly being asked to play an important role in helping organisations investigate, prevent and detect fraud. This paper aims at broadening Forensic Accountants knowledge about fraud and why it occurs. The paper adopts secondary source of data to explain Wolf and Hermanson fraud theory and shows its relevance, presents the other fraud models and relates them to Wolf and Hermanson’s model, and proposes a “New Fraud Diamond Model’’ that Forensic Accountants could use when assessing the risk of fraud in Nigeria.
Keywords: Forensic Accountants, Fraud, Fraud Detection, Fraud Diamond Model, Fraud Investigation