Benford's law first significant digit and distribution distances for testing the reliability of financial reports in developing countries

TL;DR

This paper evaluates the reliability of financial reports in developing countries using Benford's law and distribution distance tests, identifying anomalies and confirming the law's usefulness in detecting data irregularities.

Contribution

It demonstrates the effectiveness of Benford's law and distribution distance tests in assessing financial data reliability in developing countries over a 14-year period.

Findings

Many anomalous data points were identified and removed.

Distributions aligned better with Benford's law after data cleaning.

Some outliers persisted, indicating potential data issues.

Abstract

We discuss a common suspicion about reported financial data, in 10 industrial sectors of the 6 so called "main developing countries" over the time interval [2000-2014]. These data are examined through Benford's law first significant digit and through distribution distances tests. It is shown that several visually anomalous data have to be a priori removed. Thereafter, the distributions much better follow the first digit significant law, indicating the usefulness of a Benford's law test from the research starting line. The same holds true for distance tests. A few outliers are pointed out.