The Impact of Balanced Scorecard on Improving the Accuracy of Compliance Audit Predictions Through the Use of Machine Learning Techniques — Oak Academic Publishing
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The Impact of Balanced Scorecard on Improving the Accuracy of Compliance Audit Predictions Through the Use of Machine Learning Techniques
Accounting Department, Faculty of Business Administration, Taif University, Taif, Saudi Arabia
1 Accounting Department, Faculty of Business Administration, Taif University, Taif, Saudi Arabia
Compliance audits play a crucial role in ensuring organizations adhere to regulatory requirements and internal policies. Accurate predictions of compliance audit outcomes can help organizations proactively address compliance issues and enhance overall performance. This study explores the application of machine learning techniques to predict compliance audit results and introduces the Balanced Scorecard as an independent variable to improve prediction accuracy. The research leverages historical audit data, encompassing audit findings, violations, and various organizational attributes. Machine learning models are trained to forecast the likelihood of non-compliance events, while also incorporating the Balanced Scorecard metrics as an independent variable. The Balanced Scorecard framework offers a comprehensive analysis of the performance of a company, encompassing financial, customer, Internal operations, and learning and growth perspectives. By integrating the Balanced Scorecard metrics into the predictive models, this study aims to assess the impact of strategic and operational performance on compliance audit outcomes. Preliminary findings suggest that the inclusion of Balanced Scorecard data enhances the predictive capabilities of machine learning models, enabling organizations to identify compliance risks aligned with their strategic objectives. The implications of this research are significant, offering organizations a proactive approach to compliance management. The ability to anticipate compliance issues through machine learning-driven predictions, coupled with insights from the Balanced Scorecard, empowers decision-makers to allocate resources strategically and align compliance efforts with broader organizational goals. This study provides valuable insights into the synergy between compliance audit prediction, machine learning, and the Balanced Scorecard, offering a promising avenue for organizations to enhance their compliance management strategies and overall performance.
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