Analytics mindset Peach State University Hotel Fraud

In the case background, you learned how big data and data analytics are transforming the audit. You also became better prepared to ask the right questions after you learned about basic business and accounting operations at Peach State University Hotel $($PSU Hotel$)$ and gained insight into the hotel industry. You also have become familiar with the accounting data available to you about PSU Hotel and learned that the extract, transform and load $($ETL$)$ process has been completed by your audit data capture team.

In the Understanding audit analytics case, you learned in more detail how data analytics is used in the audit and became more familiar with your audit analytics tool, called EY Helix General Ledger Analyzer for students $($GL Analyzer$).$

Audit analytics can also help auditors better identify and assess risks for a material misstatement of the financial statements due to fraud, as well as more effectively perform substantive procedures related to those risks. In your lecture, you learned that:

$$ Fraud is difficult to detect, and often accomplished in multiple steps $($series of journal entries$).$

$$ It is important to test the effectiveness of controls over journal entries to assess the fraud risk.

$$ Select substantive analytical procedures can be performed to help detect fraud.

$$ Journal entry testing can be done to detect fraud and it$$s important to focus on the nature and complexity of the accounts and transactions and the characteristics of fraudulent entries while conducting this testing.

In this fraud case, you will utilize these insights and the GL Analyzer to detect fraud at PSU Hotel. Keep in mind, there might be some procedures that you cannot perform because of the limitations of the GL Analyzer tool or the data that is available to you. Additionally, there are multiple ways that you can use the GL Analyzer to perform these procedures. Because of the difficulty in detecting fraud, you should anticipate needing to use multiple views within the tool to identify any fraudulent journal entries.

To help you understand the scope of the fraud that you are trying to detect, it is material. It is in excess of $20\%$ of the net income of PSU Hotel for the fiscal year $2016.$

Required

$$ Ensure that you have the latest version of Tableau available and open the Helix General Ledger Analyzer for students workbook $($PSU$\_$Hotel$\_$fraud.twbx$).$ Note that this is a different GL Analyzer than the one you used previously for the initial cases. The data is different and there is one minor addition of functionality with the addition of a $$date of month$$ filter in the date analysis tab.

$$ You can reference other curriculum materials from the previous cases, including the User guide for the GL Analyzer, as appropriate.

$$ Identify any journal entries that you might consider fraudulent for fiscal year $2016.$ Prepare a write$-$up of your audit findings that includes the following:

$$ Provide the key journal entry details.

$$ Show the dollar impact on the total assets, total liabilities, total equity, total revenues and total expenses.

$$ Explain why you think the entries are fraudulent and which GL Analyzer views you utilized to make that determination.

$$ Be prepared to walk through the GL Analyzer views with the class.