Benefits of Data Analytics for External Audit

Data analytics has emerged as an essential contributor in the field of auditing. The contribution of data analytics is diverse weighed on the basis of application with various forms of data used in auditing both internally and on an external basis. However, data analytics is a wider area of study with big data inclusive. Pence (2014) defines big data to include a vast form of information with a higher level of complexity and variety. The speed at which the data is analyzed and delivered is also part of the definition of big data as it relies on a high level of technology to handle the data within a shorter time than would have occurred using the traditional data handling approaches. For this reason, data analytics have benefited external audit in a number of ways including an improvement in value , an enhancement of audit quality and ensuring the process of transformation is possible and achievable. Comment by Microsoft Office ??: Not sure what this sentence means…consider revising. Comment by Microsoft Office ??: This is unclear. Comment by Microsoft Office ??: To whom? What value?

First, the ability of auditors to attain an additional value to audit emanates from the presence of data analytics which enables the possibilities of using external market prices to re-price investments. The ability to adjust prices as above emanates from the increased ability of the auditors to handle vast volumes of data at a faster rate and hence improving the level of accuracy. Data analytics boasts of improved processes and systems that external auditors rely on in their work to attain the required results. Reliance on exceptions and outliers in auditing has proven possible through the process of auditing with big data analytics providing avenues of improvement and attainment of this objective (Kogan, Vasarhelyi & Appelbau, 2017, May 25). The resulting information obtained is what is used in repricing of investments to ensure the returns are adequate and a true and fair reflection of the investment. The process involved in auditing also includes encounters with data presented on the interest and foreign exchange rates of the country. Changes in GDP of an economy and other growth metrics are also part of the data presented in companies and contribute towards the success of companies. However, the decision-making process is based on the ability to choose from a number of options with a high degree of uncertainty which affects the entire value of the processes and operations of the enterprise. External auditors have relied on data analytics to examine historical data on the above and hence reducing the margin of error or failure that the organization encounters. A reduced margin of error enables external auditors therefore add value to the entire process as reduced costs of errors are evident with improved performance and quality. Therefore, data analytics helps in adding value to the audit process and enhancing the results obtained in the process. Comment by Microsoft Office ??: This sounds very specific, but I’m not entirely sure I understand what point you are trying to make. Consider revising and more broadly discussing the value proposition of DA for external audit. Comment by Microsoft Office ??: What required results? Comment by Microsoft Office ??: Again, this is a very specific case. Might be better as a “for example,” rather than a focal point of the paragraph. Comment by Microsoft Office ??: Overall, this paragraph is very nebulous. Try to clarify your point throughout. I’m still not sure what you mean by “improvement in value”.

Secondly, relying on data analytics may help external auditors enhance the quality of their audit work entirely with improved abilities such as visualization of graphics, and simplicity for use by non-specialists in this area. The implementation of data analytics in audit work has enabled the development of visualization for the work presented in various forms including graphs, and tables (EY Reporting, 2015, April 1). The data handled by auditors involves various forms of presentation with each having a varying degree of complexity. Users of the data presented in audit also vary in level pf skills and abilities in handling, understanding and interpreting audit reports. The high complexity of data collected in majority of cases is deciphered by use of simple tools and formats in presenting the results easing the work for the auditors in turn improving the overall quality presented. Also, the numerical nature of the data presented in audit reports proves complex for non-specialists to understand and handle or implement in their activities. The use of data analytics has made it possible for non-specialist users to obtain the information adequately, store it in reliable formats and present it to handlers with ease for auditing. The possible distortion of data due to complexity would affect the results and hence data analytics is important in the organization setting. External auditors may not present a full-time availability within the organization and hence the need to have efficient systems in place to help in the data collection process. Data analytics have presented these possibilities hence providing the required quality audits irrespective of the mode in which the data is collected and the persons involved. Comment by Microsoft Office ??: There are a lot of ways in which DA can improve quality other than visualization. Why focus on this aspect Comment by Microsoft Office ??: But the performance of analytics requires some level of specialized skills, correct? You’re focusing on a value of the potential output, but should also talk about the process to perform analytics and how they integrate into the external audit process. Comment by Microsoft Office ??: But these are important considerations, and some of the key challenges that analytics implementation present. You should highlight the challenges in this space as to not take for granted the complexities.

Still under quality audits, the use of data analytics has enabled scaling and speed in handling audit works. Scaling is important in the auditing process as it helps in identification of data considered necessary for the process and that which is not. The ability to handle data and ensure reliable reporting is enhanced by the level of technology used in data analytics without which scaling in auditing would prove a difficult task. The work of external auditors involves handling data collected by other parties other than the auditor and hence is exposed to a number of mistakes and errors that may require examining and eliminating prior to presenting the results. Also, reliance on data analytics enables external auditors handle work with an enhanced speed to reduce delays in presentation whilst maintaining the quality of the yielding reports. The vast volume of data handled by auditors requires an efficient system that eases handling with improved speeds that do not affect the level of accuracy and quality of reports. Data analytics has enabled both scaling and speed to improve the quality of audits. External auditors have also gained a deeper insight into the works by employing data analytics. Murphy and Tysiac (2015, April 13) affirm to the need for external auditors to have a deeper understanding of the business prior to conducting audits. A deeper insight into the business emanates from reliable data on the company which is presented by data analytics. Understanding the company entirely enhances the auditing process in turn producing quality audits that provide solutions to problems faced by companies. Therefore, data analytics in external auditing enables scaling of data, enhanced speeds in handling the same besides enabling auditors gain a deeper insight into the business. Comment by Microsoft Office ??: How do auditors get assurance that the data they rely upon is complete and accurate? How do they handle the risk of mistakes and errors? Comment by Microsoft Office ??: What does this mean? Unclear. Also, the next sentence seems to duplicative with this one. Comment by Microsoft Office ??: What does this mean? Comment by Microsoft Office ??: s this really the focus? Is it more that a sound understanding of the company allows for effective planning and scoping of analytics? Think about potential negative outcomes if analytics are executed without such knowledge.

During the process of transformation in businesses, data analytics works in enabling an ease in communication for all parties involved in the audit process. External auditors requiring support from internal staff in handling their audit responsibilities. Communication in accounting is the backbone to accuracy and an improvement in the performance of the company as those involved in the processes take part in contributing towards achievement of the set results. External auditors interact with parties including internal accountants, management and other staff within the organization in handling audit responsibilities. Chan et al. (2018) define continuous audits as a set of automated tasks and activities in auditing performed by computers in real-time. The ability of the entire process to function adequately is enhanced by the presence of trained personnel that contribute towards the process. External auditors rely on these to make decisions and effectively handle the audit process. Communication between these parties is important to enable external auditors understand the data held by the automated systems. Also, the reports presented by auditors is a form of communication to various groups including shareholders and other stakeholders of the company. Ensuring effective communication on the same is also important with presentation of reports that adequately cover the needed aspects of the audit work. External auditors are in position to attain this due to the process of transformation enforced by adoption of data analytics in the process which includes automation of processes. Comment by Microsoft Office ??: The opening of this paragraph is unclear Comment by Microsoft Office ??: Why are you getting into continuous auditing? It is relevant but needs to be better introduced. As it stands, CA seems to come out of left field. Comment by Microsoft Office ??: If I understand correctly, I think you can summarize the point of this paragraph to focus on how DA for external audit allows for enhanced communication regarding firm risk between the auditor and auditee. Also, once established in a sustainable and repeatable way, the tools allow for fewer manual activities in audit processes, which improve coordination with the client. If this is the case, you should state these points more clearly.

Lastly, the process of transformation enforced by data analytics also enables the spread of audit effort over the year rather than concentrating it at the end of the year. The efficiency of the auditing process is in the ability of the process to take into account activities within the company throughout the year and not that which occur at the end of the year alone. Examining the data as it occurs daily in the audit process contributes towards an improved ability to monitor the process and ensure adequate handling of the data generated and reported daily within the organization. The vast nature of transactions handled by companies increases the level of complication that auditors may face at the year end while handling audit responsibilities. In addition to the above, external auditors in most cases handle auditing work at the end of the year for the company and hence if not relying on efficient systems may pay attention to the data collected at the end of the year ignoring the daily data gathered on a regular. Data analytics ensures that the spread of the data is over the entire year and hence improving the results obtained as the external auditors have an enhanced level of accuracy and reliability due to the process transformation with a higher degree of automation and accuracy. A business that has entirely undergone the transformation in its data analytics aspects presents a reliable process however, compared to that still undergoing the same. Comment by Microsoft Office ??: Again, try to stay away from the esoteric descriptions and get to the point directly. If you’re view is that DA allows auditors to alleviate resource constraints in busy season by spreading work out over the year, say that, and then explain how Comment by Microsoft Office ??: Sentence is too long and seems to cut off in the end. Comment by Microsoft Office ??: still unclear on what you mean by transformation after reading this. The focus of the paper is on the use of DA by the auditor, not directly by the client, correct?

The implementation of data analytics has enhanced the audit process allowing external auditors attain a higher degree of efficiency and reliability on their work. External auditors have benefitted from the improvement in value that data analytics brings to the organization including market price use in repricing of investments while also factoring in other data needs including interest rates, foreign exchange rates and changes in GDP. Data analytics has also enhanced the quality of audits performed by external auditors as revealed by the improvement in presentation with visualization a factor, simplicity, scaling and speed. Lastly, data analytics have enabled external auditors improve the communication in the audit process and spread their efforts through the entire year and not the year end as the complete transformation in processes through data analytics enhanced audits. Data analytics has therefore, significantly improved the external audits. Comment by Microsoft Office ??: These are the types of direct and clear sentences that you should strive for throughout the paper. Comment by Microsoft Office ??: Overall, you raise some good points, but the writing style is generally wordier than necessary, and you should focus on conciseness and clarity in the next version with the help of the Writing Center (http://www.temple.edu/writingctr/). I would like to see some evidence that you visited the writing center (they can send me an email confirmation).

References Comment by Microsoft Office ??: you should strive for 10 references. Also, you can make this page single spaced.

Chan, D. Y., Chiu, V., & Vasarhelyi, M. A. (2018). New Perspective: Data Analytics as a Precursor to Audit Automation. Continuous Auditing, 315-322. doi:10.1108/978-1-78743-413-420181016

EY Reporting. (2015, April 1). How big data and analytics are transforming the audit. Retrieved from https://www.ey.com/en_gl/assurance/how-big-data-and-analytics-are-transforming-the-audit

Kogan, A., Vasarhelyi, M. A., & Appelbau, D. (2017, May 25). Introduction to Data Analysis for Auditors and Accountants – The CPA Journal. Retrieved from https://www.cpajournal.com/2017/02/16/introduction-to-data-analysis-for-auditors-and-accountants/

Murphy, M. L., & Tysiac, K. (2015, April 13). Data analytics helps auditors gain deep insight. Retrieved from https://www.journalofaccountancy.com/issues/2015/apr/data-analytics-for-auditors.html

Pence, H. E. (2014). What is Big Data and Why is it Important? Journal of Educational Technology Systems, 43(2), 159-171. doi:10.2190/et.43.2.d