Assessing practicalities of Benford’s Law - A study of the law’s potential to detect fraud in transactional data
Abstract In modern anti-money laundering operations, data analysis plays a vital role. One method of detecting fraudulent data is Benford’s law, which predicts the distribution of the first significant digits in logarithmically distributed data. Deviation from Benford’s law in data where it should be present might indicate manipulated data. We investigate the Chi2 and Kolmogorov-Smirnov tests’ pr