Fraud Detection Tools: Benford's Law And The Beneish M Score ON DEMAND

Overview

This course provides in-depth coverage of two specific tools for fraud detection. Benford’s Law predicts the probability of the distribution of first digits in a set of accounting numbers. In a large population of accounting transactions, by comparing the actual occurrence of first digits in accounting numbers to the Benford distribution, areas of concern are highlighted for further analysis and evaluation. The Beneish M Score quantifies the possibility of financial manipulation occurring in financial statements. If the M Score is greater than (or less negative than) -2.22, it is likely that there is some manipulation of the financial results. Benford’s Law assists in the detection of transactional fraud while the Beneish M Score assists in the detection of fraud in financial reporting. Both of these are powerful tools in the detection of fraud.

Highlights

Benford’s Law Overview. History of Benford’s Law. Using Statistics to Interpret Results. Benford’s Law Example with Manipulated Data. Using Excel to Identify Subsets of Data for Further Analysis. Advantages of Benford’s Law. When to Use Benford’s Law. Benford’s Law Used with World Populations. Benford’s Law Summary.

Prerequisites

None.

Designed For

CPAs, controllers, accountants, financing professionals, business owners, managers and others responsible for prevention, detection, or evaluation of potential fraud

Objectives

Recognize how to use Benford’s Law to detect potential fraud. Identify situations where Benford’s Law is and is not applicable. Recognize the Beneish M Score and its components.

Preparation

None.

Notice

None.