RVACFES April Seminar Sold Out!

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On behalf of our Central Virginia Chapter and our co-sponsors the Virginia State Police and national ACFE, I want to thank all of you, our Chapter members and more than 80 attendees for making our April two day seminar, ‘Using Analytics to Detect Fraud’ such a resounding success!

Bethmara_3Our nationally renowned speaker, Bethmara Kessler, the Chief Audit Executive at the Campbell Soup Company, shared her extensive experience as a fraud examiner and field audit leader in the application of analytics to a wide range of differing fraud scenarios.

BethMara began by defining data analytics, as it applies to fraud examination, as the use of analytics software to identify trends, patterns, anomalies, and exceptions within data. She emphasized that numerous data analytics techniques exist to assist internal auditors, external auditors, forensic accountants, investigators, and fraud examiners in uncovering red flags in data and focusing on the areas of greatest risk. BethMara gave examples of data analysis techniques being used re-actively (i.e., in response to frauds that have already occurred) or proactively (i.e., as a means to monitor data to identify signs of fraud). Data analysis technology is especially useful when fraud is hidden in large volumes of data and manual reviews are ineffective. If fraud is a needle in a haystack, data analytics tells us where in the haystack to look for it. Performing data analysis techniques, including the necessary data extraction and cleansing, requires a combination of fraud investigation skills, technical savvy, relevant industry knowledge, and common-sense judgment.

BethMara went on to emphasize that fraud examiners must be able to:

–Translate knowledge of their organization and understanding of common fraud indicators into analytics tests.
— Effectively employ the technological tools used for analyzing the data.
— Resolve any errors in data output due to incorrect logic or scripts.
— Apply their fraud investigation skills to the data analysis results in order to detect potential instances of fraud.

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Our speaker next recommend that all seminar participants read the ACFE’s 2014 Report to the Nations on Occupational Fraud and Abuse. According to the report, 42 percent of frauds reported by survey respondents were detected by whistle-blowers. That means nearly 60 percent of frauds were detected by other means. Effective and continuous data analysis might allow for the detection of frauds long before a whistle-blower notices any wrongdoing.

Data analysis techniques alone are unlikely to detect fraud; human judgment is needed to decipher results. For example, many techniques use automated software or applications to apply logic to large volumes of data to find anomalies or exceptions. Once these anomalies are identified, the fraud examiner can perform a more detailed review of the results to determine whether there are signs that fraud has occurred.

Data that is relevant to analytically supported fraud examinations comes from numerous sources and takes numerous forms, including:

— Accounting and financial data
— Human resources data
— Customer data
— Vendor data
— Internal communications and documents
— External bench-marking data

The bottom line is that to conduct an effective examination, a fraud examiner must take a comprehensive approach and apply all appropriate analytical tests to all relevant data. The more creative fraudsters get in hiding their schemes, the more creative the fraud examiner must become in analyzing data to detect these schemes. For this reason, it is essential that fraud investigators consider both structured and unstructured data when planning their engagements. It is also important that the fraud examiner not only be knowledgeable about the data to be analyzed, but also consider how a fraudster would use the data to commit and conceal fraud.

All in all, a most successful seminar for which all participants receive high marks!

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