Role of Continuous Controls Monitoring for P-Cards

July 22, 2019

In a recent article on corporate payments, PYMNTS examined the data that the researchers Dr. Mahendra Gupta and Richard J. Palmer did for their “P-card Benchmark Survey.” Here are two surprising figures that they quoted from the report:

“$87,272,852: the average annual spend on p-cards for a public Fortune 500-size company. These businesses make an average of 173,898 p-card transactions a year, with millions of dollars in savings linked to working capital float, card-issuer rebates and supplier discounts.

17 per cent of transactions between $10,001 and $100,000 are paid by p-card at Fortune 500 firms, researchers calculated. The figure suggests that, despite their reputation for being used only for small, one-off purchases, p-cards can indeed be deployed for high-value procurement. On average, employees with access to a p-card at these Fortune 500 firms spend $300 each per month.”

With so many transactions, users and vendors, it can be difficult to track whether an organization’s p-card program is performing well or how many instances of misuse or fraud there are in the program. This is where a continuous controls monitoring solution with specific analytics can help to review all transactions, rather than a sample, to track the performance of the program, reduce liabilities and identify possible instances of fraud.

To give an example, a university uses Alessa to monitor the purchases made with their p-cards. Specific vendors and merchant category codes (MCC) they monitor include:

  • (Apple, Dell, BestBuy) purchases
  • Automotive purchases
  • Computer purchases
  • Electronic device purchases
  • Even dollar purchases
  • Fuel purchases
  • Grocery store purchases
  • Internet services
  • Jewelry purchases
  • Keyword purchases
  • Memberships and fees (subscriptions)
  • Office supply purchases
  • PayPal purchases
  • Personal purchases
  • Restaurant purchases
  • Toys and craft purchases
  • Travel-related purchases

The primary purpose of these analytics is to test for approval of expenses on sponsored projects and flag those that pose the highest risk, but analytics can also be used to flag other high-risk scenarios including:

P-Card management:

  • Cardholder using unauthorized card
  • Cardholders with zero activity within a specific time period
  • Transactions made by terminated/on leave/retired employees
  • Elevated liability – card usage vs. credit limit
  • Employees not dealing with approved vendors
  • Lack of review and approval of vendors until after the fact
  • Limited documentation and traceability of purchases

Suspicious Activities and Claims:

  • Duplicate payments through Accounts Payable and/or T&E (travel and entertainment)
  • Duplicate transactions (same merchant, same amount, same day)
  • Multiple cards with same transactions (i.e., same merchant & amount)
  • Split transactions over single and multiple cards
  • Transactions outside of business hours, during holidays or vacation
  • Managers approving own transactions or outside of their cost center
  • Keyword search of non-compliant purchases such as jewelry, tobacco
  • Excessive small dollar transactions
  • Personal purchases

You can download a more comprehensive list of p-card analytics or contact us to find how we can help you improve the performance of your program and reduce abuse, waste and fraud.

About Anu Sood

Anu Sood (LinkedIn | Twitter) is the Director of Marketing at CaseWare RCM and is responsible for the company’s global marketing strategy. She has over 20 years of experience in product development, product management, product marketing, corporate communications, demand generation, content marketing and strategic marketing in high-tech industries.

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