Predictive Analytics in Audting

This is fascinating how simple methods like Benford’s law could have helped identify something unusual is going on and hence would have helped predict the current Europe’s economic condition.

Fact and Fiction in EU-Governmental Economic Data

Bernhard Rauch1,
Max Göttsche1,
Gernot Brähler2,
Stefan Engel3

in German Economic Review.

I was fascinated by the article abstract from the reference, which is

“To detect manipulations or fraud in accounting data, auditors have successfully used Benford’s law as part of their fraud detection processes. Benford’s law proposes a distribution for first digits of numbers in naturally occurring data. Government accounting and statistics are similar in nature to financial accounting. In the European Union (EU), there is pressure to comply with the Stability and Growth Pact criteria. Therefore, like firms, governments might try to make their economic situation seem better. In this paper, we use a Benford test to investigate the quality of macroeconomic data relevant to the deficit criteria reported to Eurostat by the EU member states. We find that the data reported by Greece shows the greatest deviation from Benford’s law among all euro states.”

Benford’s law says that a truely randomly occuring measurements first digits are likely to follow a certain type of probability distribution

I think this is applicable in IRS auditing, predicting fraud activity, and also in a positive way to identify and measure whether somebody is systematically working towards a goal. The key word here is ‘systematically’. Fascinating! So the question is what type of regression method one has to use to bring in covariate models.

picture and equation reference: wikipedia

From Data Monster & Insight Monster

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