Blazing a trail for the Benford's Law of words, part 1

Fraud examiners have used Benford's Law for years to detect anomalies and possible fraud in organizations' ledgers and journals. Now the author is researching a method to analyze letters of the alphabet in business documents — "Letter Analytics" — to find fraud patterns. His new approach could expedite fraud examinations.

As fraud examiners, we analyze three types of data: numbers, dates and text. We've been trained to "follow the money" (those number fields), which is sage advice because it's the simplest path to identifying positive returns for the organizations that employ us. However, when we look at the world of information — be it written, spoken or on the Internet — we need to move from our habitual desire to look only at the 0s and 1s and realize that the majority of data is text. Otherwise, our scope of examination can be missing 50 percent to 85 percent of available data.

Imagine for a moment an accounts payable audit in which we obtain a vendor masterfile, a purchase order file and an invoice payment table. As calculated below, the textual data averages to nearly 70 percent of the data received for examination (85 percent + 70 percent + 50 percent / 3) with the "money"/numeric fields comprising nearly 10 percent of the data: