There is new guidance just released on fraud risk management for COSO principle 8 and the full COSO framework.
[Excerpt from the ACFE Forum]
We are excited to announce the publication of the new Fraud Risk Management Guide, a resource jointly sponsored by COSO and the ACFE. This guide is an update to the previously released ACFE/IIA/AICPA publication, Managing the Business Risk of Fraud, and is designed to build on both COSO principle 8 and the full COSO Internal Control–Integrated Framework as a foundation for a comprehensive fraud risk management program.
The Executive Summary of the guide is attached to this post. We’ve also created a website (ACFE.com/fraudrisktools) that provides interactive tools and other resources to assist in implementing the practices put forth in the guide. We hope you find this new guide a valuable resource in assessing and improving your organizations’ fraud risk management programs.
Andi McNeal CFE, CPA
Director of Research
Association of Certified Fraud Examiners
Taxonomy of Fraud in Microfinance
One of the challenges we face in the antifraud industry is the lack of congruity between various thought leaders in how we define fraud and its many schemes. Each industry group or academic expert added great value to the advancement of the antifraud field. However, while every new distinction created a little more clarity, they all seemed to be inputs into a larger equation of the dynamic nature of what we face on a daily basis. In an effort to create a standardized fraud classification system that would apply across all fraud schemes, the Framework for a Taxonomy of Fraud was published by the Stanford Center on Longevity in July of 2015. It really was the first time a coding scheme was attempted that would allow for the vast universe of fraud schemes whether it be against an individual or an organization, from an insider threat such as from occupational fraud, against the public or private sector, or even industry specific fraud schemes.
Click here to download the model.
We have developed a new model for Benford’s Law analysis.
You can analyze naturally occurring numbers (e.g. transaction level data) to see if the actual distributions conform to Benford’s Law. Under certain conditions, deviations from Benford’s could indicate the possibility of human manipulation, i.e. fraud. Therefore, those results would require additional scrutiny. This analysis provides a direction of inquiry.
This is a model for Benford’s Law analysis built in MS Excel which calculates graphical and tabular results for the following tests: Continue reading