A risk based approach to large datasets: Analysis of time series data for a large merchandising firm

Theresa J. Presley

Journal of Accounting Education, 2019, vol. 49, issue C

Abstract: This instructional case is designed to examine one approach to the analysis of large datasets using Excel software. The company annual revenue results spanned over 10 years of data for 879 functional units. Inventory counts for the company indicated higher inventory values than accounting records, running counter to the expected shrinkage, estimated at 3% of sales. As a member of the internal audit division, you are asked to examine the large database to identify stores where the consistencies seemed largest and apply the COSO ERM risk framework to report risk. The impact and likelihood of two specific risks are examined and measured: financial statement overstatement and overpayment of commissions. Using actual internal audit work papers in place at a Fortune 500 company, the results are reported. Case questions are designed to help you think about the relationship between revenues in consecutive time periods, evaluate different forecasting models, and apply the forecasting models. Completing the risk matrix using results gives a hands-on approach to risk analysis. Completing the case questions also provides a basis for analysis that could be applied in other large datasets likely to be encountered in a continuous auditing environment.

Keywords: Risk; Big data; Time series analysis; Forecasting (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:joaced:v:49:y:2019:i:c:s0748575118300678

DOI: 10.1016/j.jaccedu.2019.100639

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