Detection using the XL Audit Commander

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Example ReportsXL Audit CommanderDetection of Fraud PatternsAll of the reports were obtained using the test data provided with the softwareinstallation, and named “clmdenbp.txt”. This data is a set of hypothetical insuranceclaims submitted by “billing providers – BILLPROV”. The data includes the claimamount paid (PAIDAMT), the date of service “FDOS” and other data.This data has been sorted in billing provider sequence.Each of the seven types of tests was run against the test data.Benford’s LawTests of population components using Benford’s Law enables the auditor to focus onthose transaction groups which differ the most from expected, as measured using valuesexpected per Benford’s Law. This enables the auditor to more quickly identify suspectpopulation components and focus on those which may be the most likely to containerrors. There is wide applicability of Benford’s Law, including tax returns, insuranceclaims, inventory counts, invoice amounts, etc.BILLPROV N Chi Squared DF D-Stat High Digit3403054 8 0 0 0 03404390 18 5.14 8 0.183 13404392 46 18.88 8 0.1957 23404410 150 20.49 8 0.086 73404420 26 14.99 8 0.2493 23404424 89 23.88 8 0.1 73404425 25 10.54 8 0.095 33404426 29 10.74 8 0.2759 33404427 94 14.1 8 0.0882 43404428 26 10.92 8 0.2892 23404429 19 22.45 8 0.3158 13404430 13 14.98 8 0.3571 43404431 35 14 8 0.2286 13404432 48 13.41 8 0.1973 23404434 116 32.81 8 0.1421 23404440 67 23.49 8 0.1584 13404441 61 31.3 8 0.2575 1Sort in descending sequence by Chi Squared (using Excel sort on column)http://www.ezrstats.com Detection of Fraud Patterns EZ-R Stats, LLC © 2007-2008
XL Audit CommanderDetection of Fraud PatternsBILLPROV N Chi Squared DF D-Stat High DigitFile Totals 65264 5,585.07 8 0.0663 78996806 420 496.43 8 0.6156 58990187 1585 468.67 8 0.1452 689012P6 1424 404.38 8 0.2108 58994865 678 298.58 8 0.1667 689014NG 982 271.82 8 0.2031 37996465 686 251.9 8 0.2915 48.90E+11 2177 246.53 8 0.0809 789013MP 1703 216.3 8 0.0892 7899019P 206 197.53 8 0.5194 58998934 142 189.06 8 0.6408 589013U4 1002 185.48 8 0.1513 389015CV 897 183.91 8 0.1717 3899014C 124 182.63 8 0.724 57901933 1070 171.71 8 0.0887 789015C2 1026 171.08 8 0.0898 78990168 534 163.79 8 0.1891 1Sort in descending sequence by d-stat (using Excel sort on column)BILLPROV N Chi Squared DF D-Stat High Digit89902TT 10 17.66 8 0.8182 68993443 90 142.17 8 0.7556 5899014E 30 48.92 8 0.7333 5899014C 124 182.63 8 0.724 58995790 85 125.8 8 0.7202 58994771 64 93.25 8 0.7153 58992155 14 24.27 8 0.7143 58990267 103 137.21 8 0.6796 58998797 11 17.35 8 0.6667 58997763 17 25.58 8 0.6471 48994644 13 15.12 8 0.6429 48998934 142 189.06 8 0.6408 57999405 25 28.19 8 0.6317 58902986 41 49.26 8 0.6287 58992243 94 112.82 8 0.6254 58995839 21 25.57 8 0.619 58996806 420 496.43 8 0.6156 5Univariate StatisticsThe coefficient of variation (CV) is the ratio of the standard deviation divided by theaverage and presents a comparable statistic which enables the comparison of two groupsof amounts. The larger the value of the CV, the larger the relative variation.http://www.ezrstats.com Detection of Fraud Patterns EZ-R Stats, LLC © 2007-2008
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Detection using the XL Audit Commander

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