Overview
The final project for this course is the creation of a fraud analysis and report. The final product represents an authentic demonstration of competency because in today’s business environment, the ability to obtain electronic evidence is crucial in any fraud investigation. Professionals must know the proper way to obtain and handle evidence in the prevention and detection of fraud. It is significantly important that the investigator has the ability to identify reliable evidence and ensure the integrity of this evidence. This project will equip you with the knowledge to perform forensic investigations using various types of electronic data. You will prepare a fraud analysis and a report to management discussing the fraud committed and the fraudsters involved.
The project is divided into three milestones, which will be submitted at various points throughout the course to scaffold learning and ensure quality final submissions. These milestones will be submitted in Modules Three, Five, and Seven. The final project will be submitted in Module Nine.
In this assignment, you will demonstrate your mastery of the following course outcomes:
- Examine the various ways information technology systems are used in committing fraud and how IT security is commonly breached or circumvented for formulating recommendations to prevent future fraud
- Evaluate the use of online resources in conducting effective fraud examinations and gathering evidence
- Analyze financial data to detect specific types of fraud, distinguish between errors and actual fraud and interpret ambiguous and conflicting evidence
- Utilize various software packages available for data extraction and analysis of financial statements that deduce the presence of fraud
- Analyze data and other types of evidence collected for the documentation and composition of reports that provide conclusions and present results to stakeholders
- Determine appropriate courses of action in various aspects of fraud and forensic accounting that are aligned with professional codes of ethics
Prompt
Assume you have just been hired by a company’s internal audit department to examine a particular data set to determine whether there have been any fraudulent disbursements/reimbursements. In addition to the circumvention of internal controls, you should look for fraudulent activity. Various data analysis software could be used in your investigation, including Microsoft Excel and Access, and data mining software such as ACL or IDEA. Once the red flags for fraud have been discovered, you should begin the process of identifying the potential fraudsters. Using internet databases and searches, identify behavior patterns or data that would serve as evidence of the person(s) involved in committing the fraud.
You will prepare a fraud analysis through the completion of three milestones and then, as part of your final submission, generate a report to management discussing the fraud committed and the fraudsters involved, as outlined in section IV below.
Specifically, the following critical elements must be addressed:
- Background
- What type of fraud could be possible in the case study? What led you to your determination?
- What approach would you use to begin a risk assessment of the situation? Why?
- How might IT relate to the commission of frauds? How might IT relate to the specific fraud in this case?
- How can reliable data be collected using online resources?
- What are appropriate ways to collect data that will result in admissible evidence? Be sure to provide a thorough description of how data is collected and what ensures it is considered admissible evidence.
- What are appropriate ways to collect data while maintaining professionalism and integrity? Support your response.
- What types of software are available to assist in analyzing large amounts of data, and how can they be implemented? How will the software assist in analyzing large amounts of data, and how it could be implemented?
- Development of Hypothesis
- Using an analysis of the fraud triangle and potential red flags, what types of fraud could be occurring in the company?
- What preventive or detective controls are present or absent that would safeguard against fraud? Support your response.
- What is your fraud hypothesis? Why do you feel it is occurring at this company?
- Based on your hypothesis, what are appropriate ways to collect evidence without violating professional standards such as the AICPA’s code of conduct?
- Testing of Hypothesis
- What analytical tests could you perform? How do you confirm that the sources for your information are reliable?
- What fraud risk inquiries are necessary? How could they be used to test your fraud hypothesis?
- What additional evidence-gathering procedures could you perform based on the response to inquiries? Support your response with examples.
- Analyze the financial information for anomalies and potential signs of fraud. What conclusions can you draw?
- What data analysis tools did you use? Why did you opt for these tools in particular?
- What online resources could you use to test the hypothesis, particularly related to the fraud suspect?
- Report to Management
- What type of fraud was committed, and who is the suspect? Elaborate on the process that led you to these conclusions.
- Through the use of the software package in your analysis, what did you determine to be the amount of misappropriation?
- Describe, in detail, the effectiveness of the online resources used in collecting evidence and conducting the investigation.
- What evidence proves that the elements of the fraud triangle are present? Support your response with examples.
- How can internal controls, particularly IT-related controls, be updated/revised to prevent this fraud from occurring again?
- Describe how the investigation adhered to professional codes of conduct.
Milestones
Milestone One: Background In Module Three, you will submit the Background section of your fraud analysis. After reviewing the case studies in Chapter 11 of Data Analytics for Auditing Using ACL and choosing one of the four for your final project, you will identify the possible fraud in the case study selection. You will explain your approach to risk assessment and define how IT might relate to the fraud. You will discuss the data collection in terms of admissible evidence and the professionalism and integrity used to collect the data. Lastly, you will explore the different types of software that will assist you in analyzing large amounts of data. This milestone will be graded with the Milestone One Rubric.
Milestone Two: Development of Hypothesis In Module Five, you will submit the Development of Hypothesis section of your fraud analysis. You will identify the types of fraud that could be occurring. You will examine preventive controls that might safeguard against fraud. Finally, you will state your fraud hypothesis. This milestone will be graded with the Milestone Two Rubric.
Milestone Three: Testing of Hypothesis In Module Seven, you will submit the Testing of Hypothesis section of your fraud analysis. You will explain the analytical tests you performed. You will identify what fraud risk inquiries are necessary. Based on this information, you will determine what additional evidence-gathering procedures you will need to perform. You will analyze the financial statements for potential anomalies and draw a conclusion. You will explain your use of data analysis tools and describe other online resources that could be used to test the hypothesis. You will determine the appropriate ways to collect evidence without violating professional standards. This milestone will be graded with the Milestone Three Rubric.
Final Submission: Fraud Analysis and Report to Management In Module Nine, you will submit your final project. It should be a complete, polished artifact containing all of the critical elements of the final product, including section IV: Report to Management. It should reflect the incorporation of feedback gained throughout the course. This submission will be graded with the Final Project Rubric.
What to Submit
Your Fraud Analysis and Report to Management should be 10–12 pages in length, double-spaced, with one-inch margins, 12-point Times New Roman font, and APA format.
Final Project Rubric
| Criteria | Exemplary | Proficient | Needs Improvement | Not Evident | Value |
|---|---|---|---|---|---|
| Background: Fraud | Meets “Proficient” criteria and determination is well supported with concrete examples (100%) | Determines the type of fraud that could be possible in the case study and explains what led to this determination (90%) | Determines the type of fraud that could be possible in the case study but does not explain what led to this determination, or determination is cursory or contains inaccuracies (70%) | Does not determine the type of fraud that could be possible in the case study (0%) | 4.25 |
| Background: Risk Assessment | Meets “Proficient” criteria and response is supported with concrete examples (100%) | Explains the approach to be used to begin a risk assessment of the situation and why (90%) | Explains the approach to be used to begin a risk assessment of the situation, but does not explain why, or explanation is cursory or illogical (70%) | Does not explain the approach to be used to begin a risk assessment of the situation (0%) | 4.25 |
| Background: IT Relate | Meets “Proficient” criteria and discussion is supported with concrete examples (100%) | Discusses how IT might relate to the commission of frauds and the specific fraud in this case (90%) | Discusses how IT might relate to the commission of frauds, but does not discuss how IT might relate to the specific fraud in this case, or discussion is cursory or contains inaccuracies (70%) | Does not discuss how IT might relate to the commission of frauds (0%) | 4.25 |
| Background: Online Resources | Meets “Proficient” criteria and describes, in detail, various types of data collected using online resources (100%) | Explains how reliable data can be collected using online resources (90%) | Explains how reliable data can be collected using online resources, but explanation is cursory or contains inaccuracies (70%) | Does not explain how reliable data can be collected using online resources (0%) | 4.25 |
| Background: Admissible Evidence | Meets “Proficient” criteria and uses industry-specific language to establish expertise (100%) | Determines appropriate ways to collect data that would result in admissible evidence and provides a thorough description of how data is collected and what ensures it is considered admissible evidence (90%) | Determines appropriate ways to collect data that would result in admissible evidence, but does not provide a thorough description of how data is collected and what ensures it is considered admissible evidence (70%) | Does not determine appropriate ways to collect data that would result in admissible evidence (0%) | 4.25 |
| Background: Professionalism and Integrity | Meets “Proficient” criteria and demonstrates a nuanced understanding of appropriate ways of collecting data (100%) | Determines appropriate ways to collect data that would maintain professionalism and integrity and supports response (90%) | Determines appropriate ways to collect data that would maintain professionalism and integrity, but determination is cursory or contains inaccuracies or does not support response (70%) | Does not determine ways to collect data that would maintain professionalism and integrity (0%) | 4.25 |
| Background: Analyzing Data | Meets “Proficient” criteria and demonstrates a nuanced understanding of appropriate ways of collecting data (100%) | Determines types of software available to assist in analyzing large amounts of data, discussing how it will assist and how it could be implemented (90%) | Determines types of software available to assist in analyzing large amounts of data, but does not discuss how it will assist or how it could be implemented (70%) | Does not determine types of software to assist in analyzing large amounts of data (0%) | 4.25 |
| Development of Hypothesis: Types of Fraud | Meets “Proficient” criteria and describes how the red flags could be proven as evidence for fraud (100%) | Identifies what types of fraud could be occurring in the company, utilizing an analysis of the fraud triangle and potential red flags (90%) | Identifies what types of fraud could be occurring in the company, utilizing an analysis of the fraud triangle and potential red flags, but there are inaccuracies present (70%) | Does not identify what types of fraud could be occurring in the company (0%) | 4.25 |
| Development of Hypothesis: Safeguard | Meets “Proficient” criteria and discusses how these controls directly relate to the fraud hypothesis presented (100%) | Determines preventive or detective controls that are present or absent that would safeguard against fraud, and supports response (90%) | Determines preventive or detective controls, but lacks an application to controls that are present or absent in this fraud, or does not support response (70%) | Does not determine the preventive or detective controls that would safeguard against fraud (0%) | 4.25 |
| Development of Hypothesis: Fraud Hypothesis | Meets “Proficient” criteria and describes how the fraud hypothesis can be proven as the fraud occurring at this company (100%) | Discusses fraud hypothesis and why fraud is occurring at this company (90%) | Discusses fraud hypothesis and why fraud is occurring at this company, but discussion lacks detail or hypothesis is illogical(70%) | Does not discuss fraud hypothesis (0%) | 4.25 |
| Testing of Hypothesis: Without Violating Professional Standards | Meets “Proficient” criteria and cites scholarly research that is aligned with claims (100%) | Determines appropriate ways to collect evidence without violating professional standards based on hypothesis (90%) | Determines appropriate ways to collect evidence without violating professional standards, but does not base determination on hypothesis (70%) | Does not determine appropriate ways to collect evidence without violating professional standards (0%) | 4.25 |
| Testing of Hypothesis: Analytical Tests | Meets “Proficient” criteria and cites scholarly research that is aligned with determination (100%) | Determines which analytical tests could be performed and how to confirm that the sources are reliable (90%) | Determines which analytical tests could be performed, but does not discuss how to confirm that the sources are reliable, or discussion is cursory or contains inaccuracies (70%) | Does not determine which analytical tests could be performed (0%) | 4.25 |
| Testing of Hypothesis: Fraud Risk Inquiries | Meets “Proficient” criteria and cites scholarly research that is aligned with determination (100%) | Determines which fraud risk inquiries are necessary and how the fraud risk inquiries can be used to test the fraud hypothesis (90%) | Determines which fraud risk inquiries are necessary, but does not determine how the fraud risk inquiries can be used to test the fraud hypothesis (70%) | Does not determine which fraud risk inquiries are necessary (0%) | 4.25 |
| Testing of Hypothesis: Additional Procedures | Meets “Proficient” criteria and demonstrates keen insight into the evidence-gathering process (100%) | Identifies additional evidence-gathering procedures that could be performed based on the response to inquiries, and supports response with examples (90%) | Identifies additional evidence-gathering procedures that could be performed based on the response to inquiries, but does not support response with examples (70%) | Does not identify additional evidence-gathering procedures that could be performed (0%) | 4.25 |
| Testing of Hypothesis: Conclusions | Meets “Proficient” criteria and describes ratios or trends in the financial statements to draw conclusions (100%) | Draws conclusions based on an analysis of the financial statements (90%) | Draws conclusions, but does not base them on an analysis of the financial statements, or conclusions are cursory or contain inaccuracies (70%) | Does not draw conclusions (0%) | 4.25 |
| Testing of Hypothesis: Data Analysis Tools | Meets “Proficient” criteria and illustrates how the data analysis tools selected were optimal for this particular fraud (100%) | Explains which data analysis tools were used and why those tools were selected (90%) | Explains which data analysis tools were used, but does not explain why they were selected (70%) | Does not explain which data analysis tools were used (0%) | 4.25 |
| Testing of Hypothesis: Test | Meets “Proficient” criteria and describes why these online resources are superior to other online resources (100%) | Describes which online resources were used to test the hypothesis, particularly related to the fraud suspect (90%) | Describes which online resources were used to test the hypothesis, but does not address the fraud suspect (70%) | Does not describe which online resources were used to test the hypothesis (0%) | 4.25 |
| Report to Management: Committed | Meets “Proficient” criteria and uses industry-specific language to establish expertise (100%) | Explains the type of fraud that was committed and who the suspect was, and elaborates on the process that led to these conclusions (90%) | Explains the type of fraud that was committed and who the suspect was, but explanation is cursory or contains inaccuracies or does not elaborate on the process that led to these conclusions (70%) | Does not explain the type of fraud that was committed and who the suspect was (0%) | 4.25 |
| Report to Management: Amount | N/A | Accurately determines the amount of misappropriation through the use of the software package (100%) | Determines the amount of misappropriation through the use of the software package, but contains inaccuracies (70%) | Does not determine the amount of misappropriation (0%) | 4.25 |
| Report to Management: Effectiveness | Meets “Proficient” criteria and describes the pros and cons of various online resources (100%) | Describes the effectiveness of the online resources used in collecting evidence and conducting the investigation (90%) | Describes the effectiveness of the online resources used in collecting evidence and conducting the investigation, but description is cursory or lacks detail (70%) | Does not describe the effectiveness of the online resources (0%) | 4.25 |
| Report to Management: Evidence | Meets “Proficient” criteria and determines how evidence specifically applies to the related element of the fraud triangle (100%) | Determines what evidence proves that the elements of the fraud triangle are present and supports response with examples (90%) | Determines what evidence proves that the elements of the fraud triangle are present, but does not support response with examples, or determination contains inaccuracies (70%) | Does not determine what evidence proves that the elements of the fraud triangle are present (0%) | 4.25 |
| Report to Management: Internal Controls | Meets “Proficient” criteria and explains how these internal controls could be implemented most effectively (100%) | Explains how internal controls could be updated or revised to prevent this fraud from occurring again (90%) | Explains how internal controls could be updated or revised to prevent this fraud from occurring again, but explanation is cursory or contains inaccuracies (70%) | Does not explain how internal controls could be updated or revised to prevent this fraud from happening again (0%) | 4.25 |
| Report to Management: Investigation Adhered | Meets “Proficient” criteria and describes the repercussions of not following the related professional codes of conduct (100%) | Describes how the investigation adhered to professional codes of conduct (90%) | Describes how the investigation adhered to professional codes of conduct, but discussion is cursory or contains inaccuracies (70%) | Does not describe how the investigation adhered to professional codes of conduct (0%) | 4.25 |
| Articulation of Response | Submission is free of errors related to citations, grammar, spelling, syntax, and organization and is presented in a professional and easy-to-read format (100%) | Submission has no major errors related to citations, grammar, spelling, syntax, or organization (90%) | Submission has major errors related to citations, grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas (70%) | Submission has critical errors related to citations, grammar, spelling, syntax, or organization that prevent understanding of ideas (0%) | 2.25 |
| Total: | 100% |