The Predictive Audit Framework

Abstract

Abstract.Assurance is an essential part of the business process of the modern enterprise. Auditing is a widely used assurance method made mandatory for public companies since 1934. The traditional (retroactive) audit provides after-the-fact audit reports, and is of limited value in the ever changing modern business environment because it is slow and backwards looking. Contemporary auditing and monitoring technologies could shorten the audit and assurance time frame. This paper proposes the predictive audit, a forward looking contemporary audit that will bring the assurance processes, financial and non-financial, closer to the corresponding events. Rather than merely looking backward to historical data and past errors or anomalies, a predictive audit will identify possible exceptions proactively by comparing each transaction to a normative model before that transaction is executed. The paper also discusses the possibility of performing a predictive audit in a preventive manner -a preventive audit where transactions are blocked prior to execution.Key words: auditing, assurance, continuous auditing, predictive auditing, preventive audit. INTRODUCTION"Clearly the vast majority of internal auditors think that the traditional retrospective audit process adds far less value than the ability to inform the organization of risk and control trends and issues that are of importance to management" (Verver, 2012) 38 The International Journal of Digital Accounting Research Vol. 13Most accounting and auditing standards were set prior to the existence of current information technologies. This fact does not by itself invalidate their necessity but raises questions about their desirability, efficiency, and effectiveness. Auditing is the process of validation of the measurement provided by management to stakeholders and depends upon 1) the formality and quality of measurement rules, 2) the economics of the verification process, and 3) the purpose of the particular verification effort.The formality and quality of measurement rules affects verifiability. Poor accounting rules that lead to vague accounting procedures allow for a wide range of allowable measures that are difficult to verify. On one hand, historical cost measures are more reliable than fair value, and, therefore, easier to verify, on the other hand the measurement relevance may counterbalance the difficulties of its verification.The economics of the verification process determine the acceptability/framework of audit rules. Sampling procedures balanced the costs and benefits of audit verification, creating the concept of materiality which allows for "fair representation" as opposed to exact measurement. The development of faster and more effective verification processes using information technology have changed this cost/benefit equation, but the accounting and auditing standards have not yet been adapted to reflect this fact.

Auditing with Smart Contracts

“…The case studies to demonstrate the practical applications of the use of technology in auditing were limited to the internal audit sector since they are less bound by restrictive statutory requirements (Kuenkaikaew and Vasarhelyi, 2013). However, as technologies continue to develop at an exponential rate, it is logical for the external auditing profession to respond to such changes in order to remain relevant in a modern and digitally-enabled world.…”

Data‐driven auditing: A predictive modeling approach to fraud detection and classification

“…Therefore, there is an increasing call for technology-based auditing techniques to reduce the subjective judgment of auditors (Loughran & McDonald, 2016). Continuous auditing and measuring provide a regular framework for positive assurance in audits (Corona & Randhawa, 2010;Kuenkaikaew & Vasarhelyi, 2013). As our model shows, data-driven approaches to auditing can reduce manual intervention and avoid subjective judgment.…”

Identifying Influencing Factors of Audit Risk Model: A Combined Fuzzy ANP-DEMATEL Approach

“…According to the report by PCAOB (2015), the audit firms have encouraged to consider deficiencies related to the risk assessment. The suggested example of remedial actions has included considering impounding modern analytical methods (Kuenkaikaew and Vasarhelyi, 2013). Given the limitations of the audit risk model and thus current audit decision-making process, we develop a case study of using a fuzzy multi-criteria decision support framework in assessing audit risk to provide an in-depth understanding of the factors involved in.…”