Fraud Data Analytics Methodology

Chapter 10Fraud Data Analytics for Theft of Revenue and Cash Receipts

The opportunity to commit theft in the revenue and cash receipts cycle is greatly dependent on a number of factors ranging from quality of internal controls to management override and nature of the industry—the list goes on and on. With that said, I believe theft in the revenue cycle occurs with greater frequency than in many of the published reports regarding fraud.

The fraud scenarios in the revenue cycle occur through the theft of revenue, theft of inventory through the revenue cycle, theft of customer remittances, theft of other cash receipts, theft of customer credits or false sales returns, or false sales adjustment or credit scenarios. Also, there are conflict‐of‐interest schemes called pass‐through customer schemes and bribery scenarios associated with preferential terms. The primary focus of this book is theft committed by an internal source and bribery involving an internal person. Fraud scenarios committed by organized crime groups or customers are not a primary focus of this chapter.

The difficulty in providing a framework for fraud data analytics in the revenue and cash receipts cycle is that business systems vary in this cycle depending on the nature of the industry, type of cash receipts, billing, and accounts receivable systems. Is the customer an individual or a multinational corporation? Is the industry a retail location or international steel manufacturer? There are so many variables that ...