Fraud data analytics methodology the fraud scenario approach to uncovering fraud in core business systems

The Wiley Corporate F&A series provides information, tools, and insights to corporate professionals responsible for issues affecting the profitability of their company, from accounting and finance to internal controls and performance management Founded in 1807, John Wiley & Sons is the oldest independent publishing company in the United States With offices in North America, Europe, Asia, and Australia, Wiley is globally committed to developing and marketing print and electronic products and services for our customers’ professional and personal knowledge and understanding Table of Contents Cover Title Page Copyright Dedication Preface Acknowledgments Chapter 1: Introduction to Fraud Data Analytics What Is Fraud Data Analytics? Fraud Data Analytics Methodology The Fraud Scenario Approach Skills Necessary for Fraud Data Analytics Summary Chapter 2: Fraud Scenario Identification Fraud Risk Structure How to Define the Fraud Scope: Primary and Secondary Categories of Fraud Understanding the Inherent Scheme Structure The Fraud Circle The Five Categories of Fraud Scenarios What a Fraud Scenario Is Not How to Write a Fraud Scenario Understanding Entity Permutations Associated with the Entity Structure Practical Examples of a Properly Written Fraud Scenario Style versus Content of a Fraud Scenario How the Fraud Scenario Links to the Fraud Data Analytics Summary Appendix Appendix Chapter 3: Data Analytics Strategies for Fraud Detection Understanding How Fraud Concealment Affects Your Data Analytics Plan Low Sophistication Medium Sophistication High Sophistication Shrinking the Population through the Sophistication Factor Building the Fraud Scenario Data Profile Fraud Data Analytic Strategies Internal Control Avoidance Data Interpretation Strategy Number Anomaly Strategy Pattern Recognition and Frequency Analysis Strategies for Transaction Data File Summary Chapter 4: How to Build a Fraud Data Analytics Plan Plan Question One: What Is the Scope of the Fraud Data Analysis Plan? Plan Question Two: How Will the Fraud Risk Assessment Impact the Fraud Data Analytics Plan? Plan Question Three: Which Data Mining Strategy Is Appropriate for the Scope of the Fraud Audit? Plan Question Four: What Decisions Will the Plan Need to Make Regarding the Availability, Reliability, and Usability of the Data? Plan Question Five: Do You Understand the Data? Plan Question Six: What Are the Steps to Designing a Fraud Data Analytics Search Routine? Plan Question Seven: What Filtering Techniques Are Necessary to Refine the Sample Selection Process? Plan Question Eight: What Is the Basis of the Sample Selection Process? Plan Question Nine: What Is the Plan for Resolving False Positives? Plan Question Ten: What Is the Design of the Fraud Audit Test for the Selected Sample? Summary Appendix: Standard Naming Table List for Shell Company Audit Program Chapter 5: Data Analytics in the Fraud Audit How Fraud Auditing Integrates with the Fraud Scenario Approach How to Use Fraud Data Analytics in the Fraud Audit Fraud Data Analytics for Financial Reporting, Asset Misappropriation, and Corruption Impact of Fraud Materiality on the Sampling Strategy How Fraud Concealment Affects the Sampling Strategy Predictability of Perpetrators' Impact on the Sampling Strategy Impact of Data Availability and Data Reliability on the Sampling Strategy Change, Delete, Void, Override, and Manual Transactions Are a Must on the Sampling Strategy Planning Reports for Fraud Data Analytics How to Document the Planning Considerations Key Workpapers in Fraud Data Analytics Summary Chapter 6: Fraud Data Analytics for Shell Companies What Is a Shell Company? What Is a Conflict of Interest Company? What Is a Real Company? Fraud Data Analytics Plan for Shell Companies Fraud Data Analytics for the Traditional Shell Company Fraud Data Analytics for the Assumed Entity Shell Company Fraud Data Analytics for the Hidden Entity Shell Company Fraud Data Analytics for the Limited Use Shell Company Linkage of Identified Entities to Transactional Data File Fraud Data Analytics Scoring Sheet Impact of Fraud Concealment Sophistication Shell Companies Building the Fraud Data Profile for a Shell Company Fraud Audit Procedures to Identify the Shell Corporation Summary Chapter 7: Fraud Data Analytics for Fraudulent Disbursements Inherent Fraud Schemes in Fraudulent Disbursements Identifying the Key Data: Purchase Order, Invoice, Payment, and Receipt Documents and Fraud Data Analytics FDA Planning Reports for Disbursement Fraud FDA for Shell Company False Billing Schemes Understanding How Pass Through Schemes Operate Identify Purchase Orders with Changes False Administration through the Invoice File Summary Chapter 8: Fraud Data Analytics for Payroll Fraud Inherent Fraud Schemes for Payroll Planning Reports for Payroll Fraud FDA for Ghost Employee Schemes FDA for Overtime Fraud FDA for Payroll Adjustments Schemes FDA for Manual Payroll Disbursements FDA for Performance Compensation FDA for Theft of Payroll Payments Summary Chapter 9: Fraud Data Analytics for Company Credit Cards Abuse versus Asset Misappropriation versus Corruption Inherent Fraud Scheme Structure Real Vendor Scenarios Where the Vendor Is Not Complicit Real Vendor Scenarios Where the Vendor Is Complicit False Vendor Scenario Impact of Scheme versus Concealment Fraud Data Analytic Strategies Linking Human Resources to Credit Card Information Planning for the Fraud Data Analytics Plan Fraud Data Analytics Plan Approaches File Layout Description for Credit Card Purchases FDA for Procurement Card Scenarios Summary Chapter 10: Fraud Data Analytics for Theft of Revenue and Cash Receipts Inherent Scheme for Theft of Revenue Identifying the Key Data and Documents Theft of Revenue Before Recording the Sales Transaction Theft of Revenue after Recording the Sales Transaction Pass through Customer Fraud Scenario False Adjustment and Return Scenarios Theft of Customer Credit Scenarios Lapping Scenarios Illustration of Lapping in the Banking Industry with Term Loans Currency Conversion Scenarios or Theft of Sales Paid in Currency Theft of Scrap Income or Equipment Sales Theft of Inventory for Resale Bribery Scenarios for Preferential Pricing, Discounts, or Terms Summary Chapter 11: Fraud Data Analytics for Corruption Occurring in the Procurement Process What Is Corruption? Inherent Fraud Schemes for the Procurement Function Identifying the Key Documents and Associated Data Overall Fraud Approach for Corruption in the Procurement Function Fraud Audit Approach for Corruption What Data Are Needed for Fraud Data Analytics Plan? Fraud Data Analytics: The Overall Approach for Corruption in the Procurement Function Linking the Fraud Action Statement to the Fraud Data Analytics Bid Avoidance: Fraud Data Analytics Plan Favoritism in the Award of Purchase Orders: Fraud Data Analytics Plan Summary Chapter 12: Corruption Committed by the Company Fraud Scenario Concept Applied to Bribery Provisions Creating the Framework for the Scope of the Fraud Data Analytics Plan Planning Reports Planning the Understanding of the Authoritative Sources FDA for Compliance with Company Policies FDA Based on Prior Enforcement Actions Using Transactional Issues FDA Based on the Internal Control Attributes of DOJ Opinion Release 04 02 or the UK Bribery Act: Guidance on Internal Controls Building the Fraud Data Analytics Routines to Search for Questionable Payments FDA for Questionable Payments That Are Recorded on the Books FDA for Funds That Are Removed from the Books to Allow for Questionable Payments Overall Strategy for the Record Keeping Provisions FDA for Questionable Payments That Fail the Record Keeping Provision as to Proper Recording in the General Ledger FDA for Questionable Payments That Have a False Description of the Business Purpose Summary Chapter 13: Fraud Data Analytics for Financial Statements What Is an Error? What Is Earnings Management? What Is Financial Statement Fraud? How Does an Error Differ from Fraud? Inherent Fraud Schemes and Financial Statement Fraud Scenarios Additional Guidance in Creating the Fraud Action Statement How Does the Inherent Fraud Scheme Structure Apply to the Financial Statement Assertions? Do I Understand the Data? What Is a Fraud Data Analytics Plan for Financial Statements? What Are the Accounting Policies for Assets, Liabilities, Equity, Revenue, and Expense Accounts? Summary Chapter 14: Fraud Data Analytics for Revenue and Accounts Receivable Misstatement What Is Revenue Recognition Fraud? Inherent Fraud Risk Schemes in Revenue Recognition Inherent Fraud Schemes and Creating the Revenue Fraud Scenarios Identifying Key Data on Key Documents Fraud Brainstorming for Revenue FDA for False Revenue Scenarios False Revenue for False Customers through Accounts Receivable Analysis Fraud Concealment Strategies for False Revenue Fraud Scenarios Fraud Data Analytics for Percentage of Completion Revenue Recognition Summary Chapter 15: Fraud Data Analytics for Journal Entries Fraud Scenario Concept Applied to Journal Entry Testing The Why Question The When Question Understanding the Language of Journal Entries Overall Approach to Journal Entry Selection Fraud Data Analytics for Selecting Journal Entries Summary Appendix A: Data Mining Audit Program for Shell Companies About the Author Index End User License Agreement List of Illustrations Chapter Figure 1.1 Improving Your Odds of Selecting One Fraudulent Transaction Figure 1.2 Circular View of Data Profile Chapter Figure 2.1 The Fraud Risk Structure Figure 2.2 The Fraud Circle Figure 2.3 The Fraud Scenario Chapter Figure 3.1 Fraud Concealment Tendencies Figure 3.2 Fraud Concealment Strategies Figure 3.3 Illustration Bank Account Number Figure 3.4 Improving Your Odds of Selecting One Fraudulent Transaction Figure 3.5 Maximum, Minimum, and Average Report Produced from IDEA Software Chapter Figure 4.1 Audit Procedure Design to Detect Fraud Chapter Figure 5.1 The Fraud Scenario Chapter Figure 6.1 Categories of Shell Companies Figure 6.2 Address Field Chapter Figure 7.1 Pass Through Entity: Internal Person Figure 7.2 Pass Through Entity: External Salesperson Fraud Data Analytics Methodology The Fraud Scenario Approach to Uncovering Fraud in Core Business Systems LEONARD W VONA identifying, process internal control circumvention matching concept, precision ranking related match Reference checking Related match Reliability test Remittance number Repeating number transaction Report design, modification Resellers, disbursements Resell fraud scenario, purchase Resell fraud scheme, purchase Retirement code, absence Retrospective analysis (favoritism) real entity targeted statement retrospective analysis Return scenarios FDA, impact Returns, technique Revenue accounting policies defining accounts, fraud scenario (uncovering) creation data, understanding fraud brainstorming fraud data analytics plan, defining overstatement, techniques scenarios Revenue fraud brainstorming scenarios, creation Revenue misstatement documents, data identification fraud data analytics, usage GAAP, misapplication Revenue recognition fraud, defining GAAP, application problem impact statement inherent fraud risk schemes Revenue theft data/documents, identification fraud data analytics, usages inherent scheme planning reports sales transaction, recording Reversal entries, reversal design Reversals, occurrence Risk assessment Round invoice amounts, identification Routine transactions, journal entry type Sale of goods Sales adjustment hiding rebate, equivalence Sales bonuses, occurrence Sales commissions, inflation Sales contracts, identification Sales invoice fraud data analytics, usage number unit price, comparison Sales journal, debit origination Sales order number anomalies Sales paid in currency, theft Sales recordation Sales representative assignation number, assignation (absence) Sales transaction commission code, absence recording Sample selection basis criteria, importance process (refinement), filtering techniques (usage) Sampling strategy change transactions, importance delete transactions, importance fraud concealment, impact (process) fraud materiality, impact manual transactions, importance override transactions, importance perpetrators, predictability (impact) void transactions, importance SAS See Statement of Auditing Standard Scheme, concealment (contrast) Scoring sheet concept, usage Scrap income, theft Scrap sales Search process, one-dimensionality Search technique Sector risks Selection criteria identification usage Selection process basis example Senior management, commitment Senior manager, vendor (collusion) Sequential number Service charging customer purchase, avoidance records, indication rendering transaction, alpha description Sham sales, FDA (impact) Sham sales transactions, occurrence Shell companies accounts payable setup, management (impact) assumed entity shell company bank routing number categories country/city/state customer operations data mining audit program date, creation defining email address employee operations entity pattern false billing schemes FDA, usage internal control avoidance fraud data analytics plan fraud data profile, building fraud scenarios, relationship government registration number hidden entity shell company high sophistication, impact homogenous categories identification intelligence information, summary internal person creation limited use shell company low sophistication, impact medium sophistication, impact name one-time use pass-through schemes composition pass-through shell company operation postal code profile information project, background record creator ID sales representative setup sophistication, impact street address telephone number temporary use terms, definition time, creation traditional shell company Shell corporations business capacity test entity verification identification, fraud audit procedures (usage) legal existence, verification physical existence, verification reference checking Shipping address, differences Shipping concealment strategies, variation Shipping data Shipping documents, examination Shipping process, occurrence Shipping records, indication Site visit Small-dollar entries, theft layering Small-dollar invoices submission Small-dollar purchase orders Small-dollar purchases, circumvention Small-dollar transactions Society, changes Soft sale FDA, impact recordation Sophistication factor, usage levels Source journal, usage Specification scheme, structuring Split purchase orders fraud scenario Stand-alone company Statement of Auditing Standard (SAS) no 99, auditor requirement no.106 Street address field Style, content (fraud scenario contrast) Subcontractor, FDA (usage) Supervisor employee, collusion fraud scenario occurrence Suppliers documents, data elements (usage) external suppliers (collusion), internal person involvement (absence) false selection, occurrence historical supplier, relationship (continuation) invoice data, basis line item fulfillment, inability scheme, false evaluation (occurrence) System codes, usage System generated date Tangible good descriptions, alpha/numeric descriptions (inclusion) Tangible items identification resell value Targeted expenditures approach fraud data analytics plan fraud scenario, inherent scheme (conversion process) identification approach Targeted purchases Telephone number field Telephone verification Temporary companies, identification Temporary employee Temporary entity Temporary takeover, permanent takeover (contrast) Termination date Term loans, lapping (usage) Terms bribery scenarios negotiation, internal person allowance schemes, favored negotiation Theft, layering Theft of sales paid in currency Theft scheme, committing (intent) Third-party due diligence/payments Time, creation Time record file, data Time reporting database Top-sided transactions, journal entry type Total acquisition, split Trade association Traditional lapping scenario, FDA (impact) Traditional shell company usage Transactional analysis, guidelines Transactional data concealment level, identification example false entity, association (guidance) file, identified entities (linkage) identification strategy, focus real entity, association (guidance) Transactional red flags Transactions alpha description amount analysis fraud data analytics, usage frequency analysis, association availability change transaction, importance data errors, presence data file, strategies data, guidance date delete transactions, importance exclusion FDA basis identification anomaly pattern illogical sequence, usage illogical order location manual transaction importance numbers false entity schemes, association numeric description override transactions codes, usage importance pattern, predictive analysis form population, shrinkage recordation process source journal, usage timing, determination red flags, correlation reliability reversal risk speed, test time type void transactions, importance volume Transfers, occurrence Travel payments, management (impact) Travel-related purchase scenario Travel-related purchase scheme, occurrence Trial balance UK Bribery Act Guidance on Internal Controls internal control guidance, FDA basis Unauthorized fraud scenario Undisclosed return policy FDA, impact scheme, recordation Unit price changes Unqualified entity scheme, identification Unresponsive bids, usage Upfront fees FDA, impact Usability analysis Vendor accounts payable, collusion bid rigging budget owner, collusion change absence complicitness country code, purchases duplicate invoice, submission examination expenditures, summarization false vendor scenario file, matching identification ID number, purchases internal person, collusion internal source, collusion master, comparison noncomplicitness number invoice splitting, internal control avoidance report (creation) summarization usage overbilling scenario paper check/electronic payments, occurrence procedures, weakness (impact) real vendor scenarios, vendor noncomplicitness rebates/refunds retail sites, usage search senior manager, collusion usage Vendor invoice amount line items number duplicate date/line item sequential pattern structuring summary usage Vendor master file duplicate address search street address, matching testing Voids, occurrence Void transactions, importance Voluntary deductions, absence Voluntary government tax withholdings, absence When question Who question Why approach Why question Word searches, usage Workforce, real employee departure Work papers, requirement World Customs Organization Write-off journal entry, absence timing, concealment WILEY END USER LICENSE AGREEMENT Go to www.wiley.com/go/eula to access Wiley’s ebook EULA ... 5: Data Analytics in the Fraud Audit How Fraud Auditing Integrates with the Fraud Scenario Approach How to Use Fraud Data Analytics in the Fraud Audit Fraud Data Analytics for Financial Reporting,... existence of a fraud scenario in the core business system Assumptions in Fraud Data Analytics The certainty principle The degree of certainty concerning the finding of fraud will depend on the level... auditing profession Fraud auditing is a methodology tool used to respond to the risk of fraud in core business systems The methodology must start with the fraud risk identification Fraud data analytics