Pleo Plies Smart Corporate Cards

Pleo has introduced corporate cards that can be used in person or virtually and can coordinate with expense reporting, via tech, in a “smart” way, as CEO Jeppe Rindom explains.

Receipts in a shoebox. Expense reports scrawled by hand. Reconciliation that takes hours, matching up trips and meals, and at times, wondering who used the corporate card last.

Expense reporting is taking strides (in some cases, baby steps) toward more intuitive and less manual filing of corporate expenses from travel to meals. To that end, one firm, Pleo, has introduced a corporate card that operates both as a physical card and as a virtual one, designed to allow for better visibility into, and control over, employee spend and also to automate the creation of expense reports.

CEO Jeppe Rindom told PYMNTS that the Pleo MasterCard prepaid card, used by a firm’s employees, has the ability to set individual spending criteria, which can extend to limits governing a set transaction amount, daily amount or time limit, such as a given week. Key decision-makers are able to monitor compliance through a dashboard.

The wrinkle here is that Pleo has the ability to take data as the cards are used, capturing transaction amounts, categorizing them as certain transaction types and then feeding them back towards an enterprise’s back-end office for use within the accounting system.

There’s a need for this type of seamless integration between employee spend, reconciliation of data in real time and presentation to key decision-makers, and according to Rindom, the time is ripe for a smart card, as traditionally over the past few decades, “there have been bank cards, and there have been multiple offerings, and none have really succeeded jointly.”

With prepaid and virtual cards, the expense management is tailored to employees typically on the go, as Rindom noted, with data being fed directly into the employee’s inbox and arranged by purchase type and with machine learning in place that allows for categorization, classification and reconciliation across merchants. Rindom stated that the use of machine learning can also point out spending behavior that follows set patterns (from transaction data that has already been logged, eating meals at a fueling station, for example) versus behavior that does not, which can be flagged for re-examination on the chance of uncovering fraudulent activity. Should behavior be flagged, a blocked card can be overridden with input from the holder, satisfying via, say, PIN or other inputs, which can ascertain that the card has not fallen into the wrong hands. Hence, the smart attributes of the cards.

Rindom stated that Pleo’s initial efforts, in the U.K. and Denmark, will likely extend throughout more areas in Europe before moving to more far-flung markets, like the United States.



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