Fraud Analytics: Strategies and Methods for Detection and Prevention

Foreword

MY FIRST job as a newly minted accounting graduate was—no surprise here—as an auditor. I worked for a top accounting firm that was one of the “Big Eight” at the time. This was the 1970s, when accountants kept a set of books on manual ledgers using pencil and paper. I found my job as an auditor to be excruciatingly repetitive. Most of the work, I wryly observed, could be done by a trained monkey: adding columns of figures, reconciling bank statements and observing inventory counts. Back then, auditors spent their time looking for careless errors made by bookkeepers rather than conducting any sort of sophisticated analysis. The term “data analytics” wasn't even in the vernacular at that time.

Fortunately, long gone are the days of most manual accounting records. In modern electronic ledger systems, ending balances are automatically rolled forward to start the next year; accruals are programmed to occur monthly; and error messages alert you if a journal entry fails to balance. Columns can be totaled instantly and accurately with the click of a button. Auditors' and investigators' time is now spent doing work that actually involves critical thinking.

The digitization of data has made business systems more complex, robust and dynamic. Companies are no longer limited in the amount of numbers they can generate or store. In addition to accounting transactions, information technology systems house research and development, marketing, communication and human resources files. All ...