Auditing Travel and Entertainment Using Data Analytics
February 13, 2019
Broadening the scope of data being examined helps bridge gaps and allows you to see fraud schemes that would be impossible to detect otherwise.
Most people are honest, but it only takes a few employees taking advantage of an unwatched system to start a culture of non-compliance. When looking at exceptions, are you able to determine whether an employee that used their travel and entertainment (T&E) card to fill up their car while on vacation was an isolated incident? Perhaps it was due to a misunderstanding of the policy that needs to be communicated better. Or, maybe it is a habitual problem. Chances are, if you are not analyzing 100% of transactions, that answer may not be one you can stand behind.
A culture of misuse that goes undetected can be quite costly for any organization. While T&E may not seem like a significant area to impact the profit and loss margin, in some organizations total annual T&E administrative expenses are second only to payroll (operating expenses). Data analytics has become the go-to tool for analyzing and testing data to prevent misuse and fraud.
Appropriate data analysis tools, like CaseWare IDEA, allow the auditor to:
- Examine large volumes of data in different formats, including print reports and PDFs
- Run multiple queries to look for and extract unknown information
- Analyze 100% of transactions to uncover improper claims and expenses
- Report findings in various formats, including graphs, charts, and other visualizations
Start With Good Data
Auditors must have a clear understanding of the business and T&E processes, including procedures for approving, recording, and reimbursing T&E expenses. Results from prior audits, including key findings and an updated status of both open and closed issues, can be helpful. Broadening the scope of data being examined helps bridge gaps and allows you to see fraud schemes that would be impossible to detect otherwise. Your request should include:
- Employee reporting forms
- Travel advances
- Authorization levels
- Travel agency booking
- Budgets
- Credit card transaction data
- Merchant databases including Merchant Category Codes (MMCs)
- Foreign exchange currency rates
- Employee master file including file of employees with details such as employee name, identification number, department, vacation schedule, and employment status
Additionally, if the organization uses an expense management system (e.g., Concur), the extraction of data can be automatic and analyzed to ensure compliance. Expense management systems allow employees to submit expenses for approval and/or reimbursements online.
T&E Analytics to Uncover Improper Claims and Expenses
In T&E engagements, the accuracy and propriety of the expense report transactions, as well as the integrity and reliability of the performance management information system, are key objectives. Various volume and service level agreements may require testing as well. Here are some effective tests to perform:
Duplicates
- Duplicate claims across T&E (e.g., expenses charged as both an out-of-pocket and as a University credit card charge)
- Same claim across multiple employees’ expense reports (e.g., groups who traveled together to the same location via taxi but submitted individual receipts)
Airfaire Claims
- Costs outside of policy or costly late bookings
- Determine whether appropriate seat class is used
- Instances where an employee exchanged a first-class ticket for an economy seat but did not return the balance
- Employees claiming to travel to multiple cities on the same day
- Last minute ticketing when unnecessary, especially cases where it resulted in being bumped to first-class travel
Car and Gas Mileage
- Match claims for personal vehicle usage and rental car for the same period and/or trip
- Mileage claims made for the same period as car rental/gas/other transportation
- Compare mileage claims to actual distances
Lodging and Meals
- Suites with multiple employees requesting reimbursement for the same room
- Lodging expenses different than the normal amount (by location, month, etc.)
- Employees who arrive earlier or stay additional nights when unnecessary
- Stays at expensive hotels (work with management to set the amount, such as $250-$300 per night)
- Returning home early but claiming to have stayed in a hotel
- Duplicate claims for meals (e.g., multiple persons, same day, same location)
- Meals charged by employees who were not traveling for business reasons
Entertainment
- Alcohol when company policy prohibits it
- Low job grade charging items to entertainment
- Large per person average expensed (e.g., expensive wine or alcohol)
- Excessive expenses (e.g., sporting events, theater tickets, cruises, green fees, etc.)
Suspicious Expenses
- Unusual MMC codes (e.g., sports centers, nightclubs, retail stores, etc.)
- Purchases made on weekends or holidays
- Expense claims for periods when the employee is on vacation
- Airfare payments/claims with no corresponding hotel or meal charges
- T&E claims that never materialized or were canceled
- Credits that have not been expensed but have corresponding debits that have been reported/reimbursed
Additional Analytics
- Identify the top 20 spenders to pinpoint which cardholders have the highest total purchases
- Identify cards used by terminated employees and/or employees on leave of absence
- Check for unused or duplicate cards, which may be causing unnecessary liability
Money-Recovery Test: Best Practice for Fraud Prevention
The challenge is knowing what to look for and using the right tools to make the process both efficient and effective.
The challenge is knowing what to look for and using the right tools to make the process both efficient and effective. For example, data analytics can be used to compare card charges against expense report totals. Gather 12 months of credit card and expense report data then summarize and compare the totals. If expense report totals are significantly higher than credit charges, this may indicate fraud or non-use of the card. If expense reports are significantly lower than credit card charges this may indicate personal or misuse of the card.
Auditors who have access to data analysis technologies can easily analyze large volumes of transactional data and are more likely to identify the root causes of why procedures are missing, deficient, or defective. They are also in the best position to generate cost savings and recoveries or identify fraudulent activities.
Findings can be shared with management to determine where the greatest risks are, and to help management determine which tests to run on a regular basis to prevent future infractions and improve controls or efficiencies.
When an organization is working toward a problem-free environment, it provides a sustainable process to proactively look for and address issues. When employees know every transaction is being monitored, it creates a catalyst for behavioral changes within the organization.
Learn More about Using Data Analytics for T&E Audits
Join us at the ACUA Midyear Conference in Savannah, GA for a special hands-on workshop on Travel & Entertainment Fraud (Track 3). If you are not planning to attend, join us online for our half-day course starting February 26, 2019. Visit the Training and Events section of our website for upcoming courses at www.audimation.com.
ACUA members also receive preferred pricing on IDEA software, support and maintenance, and IDEA training. Contact sales@audimation.com for details. We look forward to helping you put data analytics to work!
About the Author
Ricardo Murillo
Ricardo Murillo is a data analysis and programming expert with extensive experience employing IDEA and IDEAScripts to streamline audits and forensic engagements. He leads the Technical Services team at Audimation and can be reached at Read Full Author Bio