Using Data Analysis to Detect Fraud - IIA Dallas Chapter

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TechnologyA sampling of technologyData Cleansing• Data Flux• FirstLogic• LAS• USPS• SSN• Addresses• OFAC• World Check• World ComplianceUsing Data Analysis to Detect and Deter FraudPricewaterhouseCoopersMarch 2007Slide 26
TechnologyA sampling of technologyContinuous Monitoring• ACL Continuous Controls Monitoring (“CCM”)• Oversight Systems• PwC General Ledger Tool• PwC Transaction Risk Identification & Analysis (“TRIA”)Using Data Analysis to Detect and Deter FraudPricewaterhouseCoopersMarch 2007Slide 27
Page 3: “There is a tendency to mistake d
Page 6 and 7: Who detects fraud?Source:Pricewater
Page 8: Data Analysis FrameworkIndustry & C
Page 11 and 12: Analytic TechniquesCompare supplier
Page 13 and 14: Analytic TechniquesGhost employeesD
Page 15 and 16: Analytic TechniquesBenford’s LawU
Page 17 and 18: Analytic TechniquesHow do you analy
Page 19 and 20: Analytic TechniquesTesting across c
Page 21 and 22: Data Quality ChallengesNo uniquekey
Page 23 and 24: Data Quality Challenges - Translite
Page 25: OutlineData Analysis FrameworkAnaly
Page 29 and 30: TRIA HighlightsTRIA applies machine
Page 31 and 32: TRIA HighlightDisbursements within
Page 33 and 34: Questions© 2007 PricewaterhouseCoo
Page 35 and 36: Accounts Payable1. Vendor Invoices
Page 37 and 38: Accounts Payable (Continued)31. Pay
Page 39 and 40: Accounts Payable (Continued)61. Ent
Page 41 and 42: Revenue91. Customer Ship Address Sa
Page 43 and 44: Revenue121.Customers with same tax
Page 45 and 46: Inventory140.Unique General Ledger

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