Data Sleuth Using Data in Forensic Accounting Engagements and Fraud Investigations

by Wietholter, Leah

• ISBN13: 9781119834380
• ISBN10: 1119834384
• Edition: 1st
• Format: Hardcover
• Copyright: 2022-04-19
• Publisher: Wiley

Summary

Straightforward, practical guidance for working fraud examiners and forensic accountants

In Data Sleuth: Using Data in Forensic Accounting Engagements and Fraud Investigations, certified fraud examiner, former FBI support employee, private investigator, and certified public accountant Leah Wietholter delivers a step-by-step guide to financial investigation that can be applied to almost any forensic accounting use-case. The book emphasizes the use of best evidence as you work through problem-solving data analysis techniques that address the common challenge of imperfect and incomplete information.

The accomplished author bridges the gap between modern fraud investigation theory and practical applications and processes necessary for working practitioners. She also provides:

• Access to a complimentary website with supplementary resources, including a Fraud Detection Worksheet and case planning template
• Strategies for systematically applying the Data Sleuth® framework to streamline and grow your practice
• Methods and techniques to improve the quality of your work product

Data Sleuth is an indispensable, hands-on resource for practicing and aspiring fraud examiners and investigators, accountants, and auditors. It’s a one-of-a-kind book that puts a practical blueprint to effective financial investigation in the palm of your hand.

Author Biography

Leah Wietholter is a Certified Fraud Examiner, private investigator, Certified Public Accountant, and CEO of Workman Forensics in Tulsa, Oklahoma. She previously worked with the Federal Bureau of Investigation and as a Senior Certified Fraud Examiner at a public accounting firm in Tulsa. She runs The Investigation Game, an interactive continuing education experience and podcast that explores financial investigation strategies.

Table of Contents

FOREWORD

PREFACE

ACKNOWLEDGEMENTS

CHAPTER 1: Building a Data Sleuth Team

The First Team

The Forensic Accountant

Technical and Strategic

Thorough and Efficient

Detail Oriented and Effective Communication

Accounting Knowledge and Legal Knowledge

Meeting Deadlines and Developing Business

Forensic Accountant Problems

The Scalability Problem

The Strategy Problem

The Review Problem

The Sustainability Problem

Data Sleuth Solutions

The Scalability Solution

The Strategy Solution

The Review Solution

The Sustainability Solution

References

CHAPTER 2: The Data Sleuth Process

Engagement Types

The Case of the Reimbursing Controller

Data-Driven Results

Simultaneously Managing Client Expectations and Objectivity

The Case of the Mistaken Divorcee

Don't Be a Hired Gun

There is a Middle Ground

The Case of the Sentencing Hearing

Professional Standards

Professional Standards of Objectivity

Conflicts of Interest

Objectivity and Investigating Facts

The Data Sleuth Process

Client Onboarding

The Case of the Next Day Deposition

Risk-Based Analysis

Case Planning

Key Interviews

Open-Source Research

The Case of the Missing Inventory

Data Analysis

Other Data Sources and Evidence

Subject Interviews

Communication of Findings

CHAPTER 3: The Data Sleuth Necessity

Forensic Accounting Engagements versus External Financial Statement Audits

The Evolution of Forensic Accounting

The Case of the Cash Back Payroll Scheme

Start with the Evidence, Not the Scheme

The Case of the Gambling Executive Director

CHAPTER 4: Data Sleuth Considerations

Investigations Impact Real People

The Case of the Non-Existent Inventory

The Fraud Formula

Staying on Task with Purpose in Mind

The Investigation Decision Tree for a Data Sleuth

Ensure the allegations fall within the investigator’s expertise

Identify analysis and evidence required to verify allegations

Verify the legitimacy of the allegations

Investigate with client goals and possible recovery avenues in mind

Recovery Avenues

Recovery Avenue: Criminal Prosecution

Recovery Avenue: Civil Proceedings

Recovery Avenue: Insurance Reimbursement

The Case of the Man Cave

CHAPTER 5: Client Communication and Involvement

The Case of the Client’s Drama

Client Inquiry and Initial Meetings

Initial Client Meetings

Client Expectations

Data Procurement

Client Involvement During an Investigation

Client Feedback

The Case of the Overlooked Loss

Ongoing Client Communication

CHAPTER 6: The Data Sleuth Case Plan

The Data Sleuth Process

The Case of the Duplicate Payroll

The Client’s Investigation Priorities

Evaluate the Subject’s Access through Risk-Based Analysis

Data Sleuth Analysis Framework

Data Sleuth Analysis Framework Applications

Case Example: Estate Dispute

Case Example: Embezzlement

Case Example: Partnership Dispute

Case Example: Divorce

Case Example: Economic Damages

From Conceptual Venn Diagram to Comparative Data Analysis

The Data Analysis Plan

Investigation Priority Number 1

Investigation Priority Number 2

Investigation Priority Number 3

Data and Information Gathering

Communication of the Case Plan

The Case of the Duplicate Payroll – Conclusion

CHAPTER 7: Risk-Based Analysis

The Case of the Puzzling Entries

Focus on Cash

Money In

Money Out

Accounting Records and Interviews

The Benefits of Risk-Based Analysis

The Case of the Puzzling Entries - Conclusion

Risk Focus in Audits v. Risk Focus in Investigations

The Case of the Mom of the Year

Consideration of Risk in Fraud Investigations

Money In

Money Out

Case Findings 1

Altered Bank Statements

Investigation Findings

The Case of the Mom of the Year - Conclusion

Evaluating Risk in Divorce Cases and Estate and Trust Disputes

Divorce Cases

Estate and Trust Disputes

CHAPTER 8: Data Sources and Data Processing Techniques

Data Sources Explained

Quantitative and Qualitative Data Sources

Data Sources for Quantitative Evidence of Missing Money or Loss or Subject’s Benefit

Standard Data Sources

Standard Data Source: Bank Statements

Standard Data Source: Credit Card Statements

Standard Data Source: Payroll Reports

Non-Standard Data Sources

Non-Standard Data Source: System Exports

Non-Standard Data Source: Paper Conversion

Data Sources for Qualitative Evidence

Using Quantitative and Qualitative Data Sources

Data Processing Techniques

Relevant Period

Getting organized before beginning data processing

Considerations before Processing Data

Account Scheduling Steps

Formatting Account Schedules and Normalizing Payees

CHAPTER 9: Standard Data Sleuth Analyses: Comparative Analysis and Source and Use Summaries

Comparative Analysis

The Case of the Cash Flow Fiasco

Source and Use Summary and Analysis

Bank Account Source and Use Analysis

Sources (Deposits/Credits)

Uses (Expenditures/Debits)

How to Use the Bank Account Source and Use Summary Results

Credit Card Account Source and Use Summary

Sources (Payments/Credits)

Uses (Purchases/Advances/Balance Transfers/Other Charges)

How to Use the Credit Card Source and Use Summary Results

CHAPTER 10:Standard Data Sleuth Analyses: Interesting Data Findings, Risk Indicator Analysis, and Payroll Analysis

Interesting Data Findings

Standard IDF Data Analysis Tests

Benford’s Analysis

Even-Dollar Amounts

Large Individual Payments

Month-Over-Month Pivot Table

Extract Detailed Transactions from Source and Use Summaries

Using Accounting Records in the Interesting Data Findings Analysis

Create an Interesting Data Findings Summary

Risk Indicator Analysis

Risk Indicator Analysis Steps

Example for Using Risk Indicator Analysis

Payroll Analysis

Ghost Employees

Data Analysis Test: Number of Employees

Data Analysis Test: Duplicate Social Security Numbers

Data Analysis Test: Employee Records without Addresses

Data Analysis Test: Employee Records with Duplicate Addresses

Data Analysis Test: Total Risk Indicators and Comparing to Payroll Records

The Case of the Limited Payroll Records

Overpayments of Payroll

Data Analysis Test: Pay Date Review

Data Analysis Test: Even-Dollar Payments of Net Pay and Expense Reimbursements

Data Analysis Test: Days of the Week

Data Analysis Test: Large Individual Payments

Data Analysis Test: Number of Payments to Employees Per Month

Risk Indicator Analysis and Comparative Analysis

The Case of the Overpaid Administrator

CHAPTER 11: Findings, Reports and Testimony

Findings

Reports

AReport for Criminal Charges

Report Recommendations for Law Enforcement Referral

An Expert Report for Civil Litigation

An Expert Report for Insurance Reimbursement

Report Organization Recommendations

Testimony

CHAPTER 12:Practice the Data Sleuth Process

Review of the Data Sleuth Case Plan

Review of Data Sleuth Data Processing

Review of The Data Analysis Plan and Standard Data Sleuth Analyses

Case Study: The Case of the Disappearing Business

Case Study 1: Exercise 1

Case Study: The Case of the Sneaky CFO

Case Study 2: Exercise 1

Initial Client Meeting with Jack

Case Study 2: Exercise 2

Chapter 13:The Cases That Went Wrong

The Client Who Believes He was Wronged

The Case of the Inaccurate Insurance Claim

The Case of the Unreconciled Cash Drawer

The Client Whose Decisions Impact an Investigation

The Case of the Overworked Office Manager

The Office Manager

The Analysis

The Interview

The Client’s Decision

Chapter 14: Data Sleuth Expansion

Data Sleuth Empowers the Curious

Data Sleuth Divisions

Public Accounting Firms

Consulting and Advisory Firms

The Case of the Phony Professional

Law Firms

Law Enforcement

The Future of Data Sleuth

Data Sleuth as Prevention

Licenses, Credentials, and Professional Development

Appendix: Case Study Exercise Solution Recommendations

Case Study 1: Exercise 1 - Solution Recommendations

Case Study 2: Exercise 1 - Solution Recommendations

Case Study 2: Exercise 2 - Solution Recommendations

ABOUT THE AUTHOR

ABOUT THE WEBSITE

INDEX