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This research empirically investigates the important distinction between fraud identification and forensic accounting in the Nigerian public sector. The study utilized a research survey design with a sample size of 100 respondents, including accountants and auditors from four ministries selected from the Federal Capital Territory (FCT) of Abuja, Nigeria. The primary statistical method employed to test the hypotheses was Analysis of Variance (ANOVA). The research found that forensic accounting is an effective tool in detecting fraud within the Nigerian public sector. It was also revealed that there is a strong correlation between forensic accounting and litigation support services, which play a crucial role in Nigerian courts in handling fraud cases. Additionally, the study highlights the role of forensic accounting in preventing fraudulent activities by enhancing transparency and accountability. Based on the findings, the study recommends that the public sector adopts a robust and transparent accounting system that ensures effectiveness in fraud detection and prevention. Furthermore, there is a need for continuous improvement in the internal control systems within government agencies to detect and prevent fraudulent behavior proactively. The research also stresses the importance of public sector officials embracing core values such as integrity, objectivity, fairness, and accountability in their operations. Finally, it is crucial for forensic accountants to receive specialized training in forensic accounting techniques and procedures to better detect and resolve fraud cases in the public sector. These actions will contribute to reducing fraud levels and improving the overall governance of Nigeria’s public sector.

Fraud in the government sector is a serious issue that can threaten the stability and efficiency of governance. This study aims to analyze the role of internal government auditors in mitigating fraud risk. The method used is a literature review with a qualitative descriptive approach, examining 10 relevant journals. The results indicate that internal auditors play a crucial role in detecting and preventing fraud by thoroughly examining internal control weaknesses and utilizing modern technology such as Whistleblowing Systems. The effectiveness of internal audits is supported by strong leadership and high awareness of fraud risks, as well as appropriate structural reform policies. The study concludes that effective internal auditing is essential in enhancing transparency and accountability and recommends the need for comparative analysis across regions to evaluate the diversity of internal audit practices. Additionally, further research is needed to explore the impact of information technology and Whistleblowing Systems in fraud prevention, as well as the role of leadership and organizational culture in supporting the internal audit function.

This study aims to analyze the role of forensic audit, proactive fraud audit, good corporate governance (GCG), financial reporting compliance, organizational culture, human resource (HR) competency, and whistleblowing system in preventing fraud. The method used is a literature review with data sources from academic literature, scientific journals, and reliable reports. The results of the analysis show that forensic audit is effective in identifying and resolving fraud cases through in-depth investigations of the organization's financial system. Proactive fraud audit supports early detection by analyzing potential risks before violations occur. Good GCG implementation increases transparency and accountability, while compliance with financial reporting helps maintain data integrity and prevents manipulation. An organizational culture that prioritizes ethics and integrity, as well as adequate HR competency, creates a strong foundation to minimize the risk of fraud. In addition, a safe and confidential whistleblowing system allows for fearless reporting of violations, thereby strengthening early detection. The combination of these factors forms a comprehensive and effective approach to preventing fraud, providing significant benefits to organizations in building stakeholder trust and maintaining the sustainability of their operations .

This Research Aims To Examine The Influence of Forensic Audit, Anti-Fraud Awareness, External Audit, Individual Morality, And Fraud Knowledge On Fraud Prevention In Organizations. Fraud is a common problem That Often Occurs in Companies Financially and Financially. Using A Literature Review Approach, This Research Compiles And Examines Various Previous Studies Related to Understanding The Relationship Between These Factors. The Results of the Study Show That Forensic Audits Are A Determining Factor in Detecting and Preventing Conditions by Strengthening Supervision and Transparency. Understanding Anti-Fraud Among Employees Is Proven To Strengthen Compliance With Existing Procedures And Provisions. Additionally, External Audits Provide Independent Assessments That Can Reduce Financial Risks. Individual Morality Contributes to the Selection of Ethical Decisions, While Knowledge of Fraud Strengthens The Ability of Individuals and Organizations to Recognize and Prevent Acts From Occurring. These Fings Call for Integrating All of these Factors Into Fraud Prevention Strategies to Create a Safer and More Accountable Environment. It is hoped that this Research Will Provide Insight for Practitioners and Scientists in Designing Effective Policies to Prevent Fraud in Various Sectors.

Focus study This is how forensic audits , internal control , whistleblowing systems , good corporate governance (GCG), and culture organization have an impact on fraud prevention in a organization . Fraud is problem big that can cause loss financial big and destructive reputation company . Research this , based on review comprehensive literature , finding​ that forensic audits are very helpful prevent fraud . Forensic audit use the intended technique For detect fraud . Good internal controls are also important. For build a system that can supervise and manage source Power organization with good , reduce possibility fraud . In addition , the whistleblowing system is considered as tool important For prevent fraud because allows people to report Allegation violation without worry will consequence negative . The study also found that culture strong organization​ can help prevent fraud with create environment work that is moral and transparent . Many studies show that positive culture​ can increase awareness and compliance to policy fraud prevention . As a result , research This suggest that the organization minimize fraud risk with implementing forensic audits , strong internal controls , and a culture of good organization . The result will become more organization​ healthy , transparent and accountable .

Fraud in digital transactions has become a serious issue threatening the security and integrity of the fintech and e-commerce sectors. To address this problem, machine learning technology has emerged as an effective solution for automatically detecting anomalies and fraudulent transactions. This study aims to analyze the application of machine learning algorithms, specifically Support Vector Machine (SVM), Random Forest, and Ensemble Learning, in detecting fraud in digital transactions. The research adopts a quantitative approach with experimentation, testing the effectiveness of the three algorithms using a digital transaction dataset consisting of both fraudulent and non-fraudulent transactions. The results show that the Random Forest algorithm performs the best in terms of accuracy and recall, followed by Ensemble Learning, which enhances fraud detection performance by combining multiple prediction models. Meanwhile, SVM demonstrates satisfactory performance but is prone to overfitting issues when handling large and complex datasets. The study also finds that the problem of imbalanced data can affect model accuracy, and data balancing techniques such as oversampling are required to improve fraud detection performance. Overall, the findings suggest that machine learning, particularly Random Forest and Ensemble Learning algorithms, can be relied upon to improve fraud detection in digital transactions. However, challenges such as model interpretability and the need for periodic algorithm updates still need to be addressed to enhance the effectiveness of fraud prevention systems in countering the ever-evolving nature of fraud.