Fraud examination forensic accounting

Case Study: Tampa Electronics
The objective of this case study is to build and test your ability to apply the fraud detection concepts we learned in chapters 5 and 6.
The case study involves the identification of potentially fraudulent travel expense reimbursements. In the case scenario, traveling salespersons submit expensereimbursement claims, which are subject to a number of business rules. Using the data provided as well as data analysis techniques, you are required to identify potentially fraudulent travel expensereimbursements.
Along with the case study facts, you have been provided with a data file containing the following data sheets: salespersons, cities, rates, approvals, and travelexpenses.
The case will require you to read the facts, examine the data set and prepare a report on your examination using the requirements as outlined on page 4 and 5 of the case study.
To analyze the data and prepare a report you will be required to have a basic working knowledge of EXCEL to perform fraud examination procedures. To perform your analysis, you may be required to perform certain functions such as identifying duplicates and gaps or more advanced features like joiningtables, finding unmatched records, filtering data based on various criteria, and classifyingand summarizing data.
As part of your analysis, you should consider reviewing the data for some or all of the following indicators of fraud:

Travel expense reimbursement transactions without corresponding approvals.
Approvals being used more than once, i.e., two or more travel expense reimbursementtransactions referencing the same approval number.
Travel expense reimbursement transactions where the total expense is higher than the maximum approval amount as indicated in the approval record for thattravel.
Travel expense reimbursement transactions that include both car rental and taxi expenses.
Travel expense reimbursement transactions that include both airfare and mileage reimbursement.

There may be other potential fraud indicators you note in your review of the data.
As with other written assignments, you will be graded not only on the substance of your paper but on grammar and punctuation etc.
Good luck!

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