Big Data and Analytics in the Audit

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Introduction

The article titled “How Big Data and Analytics are Transforming the Audit” written by Roshan Ramlukan examines the impact of big data on the audit. This paper aims to explore how modern technological development influences the audit process by analyzing the information presented in the article.

Analysis

Recent technological advancements promise to change the current audit process. Namely, big data and analytics have the potential to transform audit into something more than sample-based testing (Ramlukan 16). New technology is associated with the benefits of analyzing “entire populations of audit-relevant data” with “higher quality of audit evidence and more relevant business insights” (Ramlukan 16). By introducing bid data and analytics into the audit, it is possible to obtain a better picture of fraud and risks to business continuity. Therefore, these technological solutions can transform the way financial reporting is being analyzed. In short, big data and analytics will help to deliver a more credible and relevant audit (Ramlukan 16).

In order to realize the benefits of new technologies, it is necessary to overcome some barriers to integration. The most significant technological difficulty that has to be surmounted is data capture. Due to numerous security concerns, companies are not willing to share data with auditors and spend significant amounts of money to create multilayered approval processes (Ramlukan 17). Another difficulty has to do with the fact that sub-ledger information that can be processed with the help of big data and analytics substantially increases the process of data extraction. Given that companies use different accounting systems, data capture can be time-consuming. Therefore, it is necessary to overcome these difficulties in order to efficiently analyze audit evidence.

In order to introduce big data and analytics in the auditing profession, it is necessary to align them with auditing standards that govern it (Ramlukan 17). These standards and regulations were put in place many years ago; therefore, they are not suitable for leveraging big data (Ramlukan 17). Substantive analytical procedures is an area of auditing standards that examines “the reasonableness of relationships in financial statement items to uncover variations from expected trends” (Ramlukan 17). At the time when these standards were conceived, modern analytics techniques allowing to obtain substantive evidence with the help of bid data were not existing; hence, this standard has to be revised.

Validation of data is another area of auditing standards that should be overhauled. The current regulations providing guidance for the process of validation of “the accuracy and completeness of the data” (Ramlukan 18) are not suited for modern types and volumes of information. Defining audit evidence is another standard that requires re-thinking. In order to make big data and analytics a part of the auditing process, it is necessary to indicate what type of audit evidence is derived with their help. The audit is a process that is governed by precision. However, it is not clear how precise big data should be when any material misstatements are essential for data analytics.

Conclusion

The article suggests that the use of big data and analytics will substantially transform the audit. Modern technological solutions will help auditors to obtain a better picture of fraud and risks to business continuity. However, in order to realize these benefits, it is necessary to overcome some technological difficulties. Moreover, four areas of auditing standards have to be reviewed before the introduction of new technologies in the auditing process.

Work Cited

Ramlukan, Roshan. “How Big Data and Analytics are Transforming the Audit.” Financial Executive, vol. 31, no. 3, 2015, pp. 14-19

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