Abstract
The role of internal audit has evolved from traditional compliance monitoring to a strategic function that enhances risk management and corporate governance frameworks. In today's dynamic business environment, organizations face increasing complexities, necessitating a shift toward technology-driven and streamlined internal audit processes. This paper explores methods for enhancing internal audit efficiency to ensure robust risk management and strengthen corporate governance structures. By leveraging advanced tools such as data analytics, artificial intelligence (AI), and automation, internal auditors can deliver more accurate insights, improve operational efficiency, and mitigate organizational risks effectively. The integration of technology allows internal audit functions to shift from reactive to proactive risk management strategies, enabling real-time monitoring and analysis of controls, transactions, and compliance. Enhanced efficiency in internal audits fosters greater transparency, accountability, and alignment with corporate governance objectives. Furthermore, by implementing standardized frameworks and innovative methodologies, internal audit can contribute to strategic decision-making and value creation across the organization. This study highlights key challenges, including technological adoption barriers, skills gaps, and resource limitations, while providing actionable recommendations for improving audit efficiency and resilience. Emphasis is placed on aligning internal audit processes with strategic goals, ensuring timely identification and mitigation of risks, and reinforcing governance mechanisms. Ultimately, enhancing internal audit efficiency serves as a cornerstone for promoting sustainable organizational growth, stakeholder trust, and long-term accountability in an ever-evolving corporate landscape.
Cite
CITATION STYLE
Udoh, O. R. (2024). Enhancing Internal Audit Efficiency for Effective Risk Management and Corporate Governance Frameworks. International Journal of Research Publication and Reviews, 5(12), 3646–3659. https://doi.org/10.55248/gengpi.5.1224.250122
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