A Model Analysis of Continuous Auditing in the Era of Big Data: A Case Study

Abstract

In today's dynamic operating environment, continuous auditing (CA) can greatly improve the risk management, control and audit activities of business enterprises. However, relatively few enterprises have realised their full potentials because a clear, strong business case for establishing an effective CA system in their enterprises is lacking. The main objective of this study is to uncover the key decision-making factors of the CA strategy in the era of big data and to develop an evaluation model for the CA system when evaluation criteria conflict with one another. This study provides a model analysis of CA engagement and details the methodological issues in how to effectively construct a tailored-made CA mode for an enterprise. The MCGDM model consists of decision-making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and zero-one goal programming (ZOGP) to simulate the practical problem of choosing the appropriate CA system to help decision-makers find the optimal solution, which incorporates both considerations of experts' opinions and resource constraints within an organisation. The findings of this paper would help business professionals in assessing the current status of their CA system and provide important managerial implications for continually reviewing business process to achieve their intended levels of performance and effectiveness.