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Caught in the act

Rounded-up mileage claims or telephone expenses? Private cab rides or overnight hotel stays? Whether on a large or small scale, inconsistencies in travel expense reports are not considered a trivial offense.
E-3 Magazine
February 7, 2022
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This text has been automatically translated from German to English.

Nevertheless, current study results from the SAP Concur organization show that employees often take minor cheating in expense reports lightly. In Germany, more than half - 53 percent - of employees have no objections to expense fraud, making them particularly carefree in a Europe-wide comparison.

On average, German respondents consider it acceptable to submit a knowingly incorrect statement up to an amount of 106 euros. The figures for Swiss respondents are even more surprising: Here, as many as 54 percent state that cheating on expense reports is acceptable - for twelve percent in an amount of up to CHF 100. In neighboring Austria, only 39 percent of employees think it's okay to submit false travel expense claims, but on average they still consider overstatements of up to 92 euros to be acceptable.

Travel Management

"In many companies, it costs travel managers and finance teams a lot of time and resources to audit employee expenses. The reasons for this are not only a lack of guidelines, but also a lack of appropriate training and development for employees. If companies take this seriously, they can close knowledge gaps and increase employee satisfaction.", says Götz Reinhardt, Managing Director MEE of the SAP Concur organization. "Intelligent expense management solutions such as Concur Detect by Oversight also ensure that fraud patterns are identified more quickly and that travel managers and finance teams can use data analytics to make tailored policy adjustments. This is an essential step to prevent future expense fraud and stay ahead of the competition."

Creativity and ignorance

When employees make false claims on expense reports, they show creativity, and that's exactly what makes it difficult for companies to uncover fraud patterns and identify black sheep. Looking at the study results, five expense types stand out where cheating is particularly common: Many employees in the DACH region have already rounded up kilometer costs. Another frequently used way to increase the reimbursement sum is to submit private restaurant bills or costs for privately used office equipment. Reaching into the minibar, for example, is popular: this is how respondents account for alcoholic beverages that are not covered by the expense guideline.

Cheating is most common in these five expense types. The results come from an SAP-Concur study conducted in August and September 2021 with the market research institute Opinium Research among 1,200 respondents in Germany, Austria and Switzerland.
Cheating is most common in these five expense types. The results come from an SAP-Concur study conducted in August and September 2021 with the market research institute Opinium Research among 1,200 respondents in Germany, Austria and Switzerland.

As multifaceted as the forms of expense fraud are, as different are
also the motives of the employees. While most of their
fall victim to their own ignorance, some act quite consciously. The current figures indicate that many are guided by their own understanding of justice.

AI Tools

The problems around expense fraud are not only due to the behavior of employees, who often do not know travel and expense policies in detail. Nearly a quarter of travel and finance decision-makers say their expense management is not digitized and they lack the data to detect expense fraud.

The lack of digitization also results in high personnel costs: Travel managers and finance teams have to spend up to two working days a week uncovering fraud and responding to compliance issues.

The shift to artificial intelligence is also slow because new tools still raise questions. Nearly half of travel and finance decision makers are concerned about the impact on data security and/or privacy. Likewise, nearly half worry that AI tools could lead to erroneous conclusions.

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