April 16, 201115 yr Hi All , I m going to share the use of six sigma beyond process improvement ,that is detecting fraud in accounting data. This tool predicts the frequency of numbers (digits), and hence an anomaly, in naturally-occurring data sets. When used properly, it allows the fact-finder to identify suspect values in a given data set. For example, it is particularly suitable for identifying vendors that submit fraudulent invoices.Using this Rule nonconforming invoice amounts are flagged as systemic errors that corrupt the data set. These fraudulent invoices reveal themselves because the amount (dollar value) does not correspond to a predicable ,This distribution when compared to the other invoice amounts in the sample. It appears that a simple but powerful mathematical phenomena exists that quickly predicts the distribution of numbers for "pointing suspicion at frauds, embezzlers, tax-evaders, sloppy accountants, and even computer bugs." Certain nonrandomly behaved numbers in non-normally distributed data sets (i.e., those that are highly skewed, not uniform in distribution, and not bell-shaped) followed the algorithm defined by: Models the data set against the probability distribution of each digit as itm appears in any number. This is a predictive tool called digital frequency analysis Please read it and let me know if that sounds fruitfull will upload a minitab macro for first digit frequency ThanksMahi
May 12, 201115 yr Hi Mahi,Thanks for sharing the information. Is it possible to expalin this by small example.
May 16, 201115 yr A small data set can help most of the people in the group to understand what you are stating. Also it will help lot of people to complete their projects. Regards,Mahipal
May 16, 201115 yr hi mahi,This is the real power of SIX SIGMA we just need to aply it. Thank you very much....Manish
May 19, 201115 yr Hi, Its great..... Please share the macro as mentioned. And explain with an example. RegardsSumukha
November 9, 201510 yr Dear Mahendra, One useful approach in fraud detection is the use of Benford Law. Here is a link that should help - http://www.statistics.gov.hk/wsc/CPS021-P2-S.pdf
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