The 2016 version of the “Report to the Nations on Occupational Fraud and Abuse” ¹ by the Association of Certified Fraud Examiners (ACFE) highlights some trends and statistics that any professional involved in fraud investigation and related processes should be aware of:
- “Typical organization loses 5% of revenues in a given year as a result of fraud”
- “Average loss per case of $2.7 million” (from 2.4K cases in the study)
- “23.2% of cases causing losses of $1 million or more”
- “Nearly one third of fraud least two years before they were detected”
- “The longer a fraud lasted, the greater the financial damage it caused. At the extreme end, schemes that lasted more than five years caused a median loss of $850,000”
- “When fraud was uncovered through active detection methods, such as surveillance and monitoring or account reconciliation, the median loss and median duration of the schemes were lower than when the schemes were detected through passive methods”
- “The presence of anti-fraud controls was correlated with both lower fraud losses and quicker detection”
What Is the Ideal Solution for These Challenges?
Given such a challenging environment, organizations combating fraud need an enterprise solution that can:
- Tackle all these situations now, and be ready to address new ones in the future resulting from evolving fraud patterns that fraudsters are constantly thinking of.
- Automatically analyze huge volumes of data from multiple and heterogeneous data sources, in real time or batch mode depending on the types of fraud scenarios. Early detection of a potential fraud case is critical because it can allow transactions to be blocked before any financial losses occur.
- Work with predictive analytics, allowing users to extract insights from analyzing data with predictive algorithms and keeping up with changing fraud patterns that a rules-only approach might not be able to detect.
- Allow alerts to be created manually because an organization might receive whistle-blower type of notifications and/or staff might encounter transactions which seem suspicious. (This is in addition to automatically triggering alerts for suspicious transactions that meet certain predefined criteria.)
- Provide analytical tools to help users visualize and understand all this information, considering the large amounts of data typically analyzed during fraud investigations.
Wide Range of Use Cases: Asset Misappropriation, Purchasing, Corruption, Foreign Corrupt Practices Act, Industry Scenarios, and So On
Given the nature of fraud and the different requirements across industries and regions, a solid enterprise solution should be a flexible platform that allows users to define the relevant detection criteria for the multiple fraud scenarios they are interested in, whether it’s for a particular division/organization within a corporation or for a corporate-wide initiative.
Example of a Map with Alert Distribution Information
Example of Network Analyzer Showing Relationships among Different Objects in a Suspicious Case
SAP Fraud Management
At SAP, we’ve worked to create an enterprise solution that meets all these needs. Learn more about SAP Fraud Management and how it could help your organization fight fraud by leveraging the power and speed of HANA.
- Read the solution brief.
- Get started with a free trial.
¹Report to the Nations on Occupational Fraud and Abuse, 2016 Global Fraud Study, ACFE
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