Data Mining for Fraud
Fraud auditing is about locating and recognizing fraud, and data mining is the tool used in locating fraud. Data mining for fraud auditing purposes can be thought of as both a science and an art—a science because there is a discovery and exploration aspect to it. The art of it is derived through the auditor's ability to analyze the data from many perspectives to arrive at a summary of targeted information. Think of a painter who uses his tools, a brush and paint, to make numerous strokes into a recognizable pattern. If that analogy is a bit of a stretch for you, think of it as the auditor's ability to interpret the data to find the proverbial needle in the haystack. From a Las Vegas view, then, the odds are against the auditor in detecting a fraudulent transaction with visual judgmental or random selection. Obviously, databases are very large; that's why they are electronically stored. Business systems process millions of transactions on a daily basis with the dollar value of the transactions in the billions of dollars. What can an auditor do? As with any tool, the auditor needs to develop the skills to use the tool of data mining effectively.
Simply, auditors need the ability to group data into homogeneous groups in order for any anomalies to become apparent. Granted, the world's best audit program will not detect fraud if the sample, no matter how well organized for analysis, does not include a fraudulent transaction. Obviously, no method of searching ...