Development of an Anti-Fraud Program
See attached outline of the paper, including preliminary references, that demonstrates the initial research of components of a real-world anti-fraud program/model.
A typical organization loses a certain percentage of annual revenue to fraud. The potential for fraud occurs in all organizations, regardless of the industry in which it operates, financial structure, or size. Every organization is vulnerable to fraud. The risk of fraud should be reduced as much as possible to improve the longevity of the organization. Hence, preventing, deterring, and detecting fraud are crucial to the success of organizations. Deterring and preventing fraud can be more economical than detecting, investigating, and recovering from fraud after the fact. These anti-fraud measures must start at the top and must be communicated throughout the organization. They must go beyond internal controls yet consider the cost-benefit.
Develop an anti-fraud program, or model, that can be implemented in any organization. In other words, don’t apply the model to a specific organization. The model, if applied correctly, must be efficient in preventing, detecting and deterring fraud. At minimum, your model must address the following factors:
• Fraud risk assessment
• Employees’ Code of Conduct
• Policies and procedures to prevent, deter, and detect fraud
• Technical tools to prevent, deter, and detect fraud (i.e. SQL, ODBC, Digital Analysis, etc.)
• Cost-benefit analysis
Requirements for the paper:
• Demonstrate your comprehension of the course material.
• Use professional business language.
• 10-12 pages in length (double-spaced), not including the cover and reference pages. Supporting documents (i.e. charts, graphics, etc.) should be included as addendums to your report and not in the body of the report.
• Include a minimum of six credible, academic or professional references
Use the following references at a minimum:
Chan, A. S. (2019). Leveraging common sense in building an effective ERM program. CPA Journal, 89(3), 24–28.
Miller, L., Puri, N., & Dorries, J. (2019). Leverage what you have to integrate ERM and fraud risk management. Journal of Government Financial Management, 68(2), 18–23.
Misra, A., & Walden, V. (2016). Proactive fraud analysis. Internal Auditor, 73(2), 33–37.
Rad, M., Amiri, A., Ranjbar, M. H., & Salari, H. (2021). Predictability of financial statements fraud-risk using Benford’s Law. Cogent Economics & Finance, 9(1), 1889756. https://doi.org/10.1080/23322039.2021.1889756
Sever Mališ, S., & Novak, A. (2016). Fraud risk assessments: an empirical analysis. International Journal Vallis Aurea, 2(1), 19–29. https://doi.org/10.2507/ijva.2.1.2.24
Yang, C.-H., & Lee, K.-C. (2020). Developing a strategy map for forensic accounting with fraud risk management: An integrated balanced scorecard-based decision model. Evaluation and Program Planning, 80, 101780. https://doi.org/10.1016/j.evalprogplan.2020.101780
Other resources to consider:
• AICPA. (n.d.). Managing the business risk of fraud: A practical guide (Links to an external site.). https://competency.aicpa.org/media_resources/209048-managing-the-business-risk-of-fraud-a-practical-gu/detail
• Protiviti. (n.d.) Evaluating your anti-fraud program (Links to an external site.). (Links to an external site.)https://www.protiviti.com/US-en/insights/suggestions-evaluating-your-anti-fraud-program (Links to an external site.)
