THE EFFECT OF INTERNAL AUDIT ON FRAUD PREVENTION AND TRANSACTION SECURITY IN DIGITAL PAYMENTS: A SYSTEMATIC LITERATURE REVIEW

Internal Audit Quality and Fraud Detection Effectiveness in Manufacturing, Banking, and Oil and Gas Sectors: A Systematic Review

Fraud remains one of the most significant threats to organizational performance, accountability, and long-term sustainability across both public and private sectors. Despite considerable investments in internal control systems, organizations continue to experience financial losses resulting from fraudulent activities such as financial statement manipulation, procurement fraud, cybercrime, and asset misappropriation. In response to these challenges, internal auditing has evolved beyond its traditional compliance role to become a strategic governance mechanism for risk management and fraud prevention. This paper reviews existing theoretical and empirical literature on the relationship between internal audit quality and fraud detection effectiveness in the manufacturing, banking, and oil and gas sectors. Drawing on Agency Theory, Fraud Triangle Theory, and Institutional Theory, the study examines how factors such as auditor independence, professional competence, technological capability, and regulatory compliance influence organizations' ability to detect and prevent fraud. The review further highlights how industry-specific characteristics shape the effectiveness of internal audit functions and fraud management practices. The findings indicate that organizations with strong internal audit systems are generally more successful in identifying control weaknesses, detecting fraudulent activities, and enhancing overall governance performance. While the banking sector demonstrates relatively higher fraud detection effectiveness due to advanced technology and strict regulatory oversight, the oil and gas sector faces persistent governance challenges despite significant audit investments. Manufacturing firms, on the other hand, continue to grapple with operational vulnerabilities associated with inventory management and procurement processes. By providing a comparative synthesis across multiple sectors, this study extends existing literature that has largely focused on single-industry investigations. The paper concludes that strengthening auditor independence, embracing technological innovation, and investing in continuous professional development are essential for improving fraud detection effectiveness and promoting organizational accountability.

“Enhancing Fraud Detection in Core Banking Systems Through Risk-Based Internal Controls and Forensic Auditing”

The proliferation of Core Banking Systems (CBS), digital banking, cloud computing and real-time payment platforms has made financial fraud more sophisticated. Current fraud detection techniques are not effective anymore against new cyber assaults and complex financial crimes. This paper discusses the role of forensic auditing, risk-based internal controls and emerging technologies in enhancing fraud prevention in commercial banks. It discusses the application of forensic auditing with a combination of digital forensics, artificial intelligence (AI), machine learning, behavioural analytics, blockchain, and continuous auditing to improve fraud detection, fraud investigation, and regulatory compliance. The study also discusses contemporary issues in banking fraud such as insider threats, data privacy, legacy system integration, and regulatory requirements and suggests strategic measures to enhance fraud resilience. The findings indicate that the implementation of intelligent technologies with strong governance and forensic auditing mechanisms enable proactive fraud management, strengthen operational resilience, protect customer assets, and build trust in digital banking ecosystems.

Strengthening internal controls to reduce fraud in U.S. financial institutions: Enhancing financial integrity and public trust

Financial fraud remains a constant and evolving threat to U.S. financial institutions, damaging market integrity, diminishing public trust, and causing significant economic losses. Internal control systems serve as the first line of defense against such fraud, yet many institutions still face control failures that allow internal and external schemes to thrive. Despite comprehensive regulatory requirements and compliance measures, fraud incidents persist, highlighting ongoing weaknesses in the design and execution of internal controls. This underscores the need for stronger, technology-driven prevention strategies. This research analyzes the effectiveness of internal control systems in preventing and detecting fraud in U.S. financial institutions. It proposes an integrated framework combining governance mechanisms, risk assessment, technological advancements, and human capital development to improve fraud deterrence. The study uses an applied qualitative approach to systematically review and compare evidence from academic journals, government reports, banking regulations, and industry publications. The evidence indicates that successful fraud prevention requires a multi-layered strategy incorporating robust corporate governance, comprehensive risk assessment, segregation of duties, ongoing monitoring, and sophisticated data analytics. Technology-based solutions, especially machine learning and artificial intelligence, typically surpass traditional detection methods. Additionally, corporate governance elements, such as the effectiveness of audit committees and board oversight, are vital in ensuring the effectiveness of internal controls. Based on these findings, financial institutions should enhance their governance frameworks, implement risk-focused internal controls, invest in ongoing monitoring technologies, upgrade employee training programs, and foster stronger collaborations with regulators. Collectively, these measures establish robust fraud prevention systems capable of safeguarding institutional integrity and maintaining public trust. Keywords: Internal Controls, Fraud Prevention, Fraud Detection, Corporate Governance, COSO Framework, Financial Institutions, Data Analytics, Machine Learning, Regulatory Compliance, Audit Committees.

the expectation performance gap in fraud detection: A systematic review of external auditors' responsibilities, audit failures, and regulatory responses

Data analytics and internal controls in U.S. financial systems: A review of fraud detection and financial reporting integrity

The study concludes that strengthening fraud detection and financial reporting integrity requires integrating analytics and internal controls within a unified governance framework supported by continuous monitoring, institutional accountability, and transparent oversight mechanisms.

From Detection to Prevention: Examining the Associations Between Forensic Accounting Practices, Governance Quality, Transparency, Disclosure, and Accountants’ Perception of Financial Fraud Control

Amid the massive digitization of financial flows, forensic accounting is emerging as a strategic lever to strengthen the prevention, detection, and control of financial irregularities. This study aims to examine the associations between forensic accounting practices and perceived financial fraud control, and to analyze the mediating roles of corporate governance quality, transparency, and disclosure. A quantitative survey was conducted with 325 audit, control, and accounting professionals. The data were analyzed using structural equation modeling to assess the direct and indirect relationships. Fraud prevention mechanisms have the strongest correlation with financial fraud control (β = 0.310; p < 0.001), followed by forensic data analysis (β = 0.270; p < 0.001), litigation support (β = 0.084), and fraud detection techniques. Forensic data analysis is associated with the quality of corporate governance (β = 0.480; p < 0.001), while transparency and disclosure practices are the most important determinants of perceived financial fraud control (β = 0.463; p < 0.001), followed by governance quality (β = 0.165). Mediation analyses show that corporate governance and transparency primarily amplify the relationship between prevention mechanisms and forensic data analysis, whereas the mediating effects of detection techniques are not significant. Financial fraud control is strongly associated with an integrated approach that combines prevention, analytical capabilities, quality governance, and transparency, rather than with detection activities alone. The findings provide an explanatory model that highlights the organizational mechanisms by which forensic accounting practices strengthen governance and control over financial fraud.