Anti Corruption Series Data Analytics Slide Deck

According to the Association of Certified Fraud Examiners, in the past only 14% of detected corruption has been found by internal audit. E&Y has determined that this is because traditional internal audit tests are not effective for identifying high-risk transactions that may indicate the presence of bribery and corruption. But there are new approaches to data analytics that integrate statistical analysis, anomaly detection, data visualization and text mining to detect bribery and corruption at an early stage.

Our expert panel will discuss the tools, technologies and methodologies to mine financial accounting data and identify areas where potential improper activity may exist within your organization.

Learning Objectives:

• Learn how text mining can identify potentially suspicious terms within financial transactions
• Understand the methods for finding anomalous relationships within your global footprint
• Know how to analyze your financial data to prevent and detect corrupt activity

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