Data Analytics for Fraud Detection (AUDT8915)

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Data Analytics for Fraud Detection

Description:

This seminar is a condensed, quick paced overview of the principles, tools, techniques, and applications of data analytics to support forensic investigative work in detecting possible fraud. Large amounts of electronic data present an enormous challenge and opportunity to identify trends, correlations, activity, risks, red flags of possible fraud, and otherwise hidden anomalies, or association connections. This seminar will demonstrate the application of software and case studies to demonstrate the power of available tools to extract, sort and identify specific information from databases and the cloud. This seminar will also demonstrate approaches to displaying and visualizing data for reporting and evidential presentation.

For the virtual version, students must have Excel-with the Data Analysis ToolPak activated (this is included with Excel software).

Who Should Attend?

Investigators, Special Agents, auditors, and analysts,

Tuition:

$579.00

Credits:

8 CPE's

Class Type:

This course is currently being offered in the following training modalities:

Learning Outcomes:

  • Explain the importance of data analytics in support of investigations and fraud detection
  • Identify patterns and outliers quickly to assess possible improper activities
  • Describe the difference between structured and unstructured data
  • Use the Data Analysis Maturity Model to identify or search for specific red flags of fraud
  • Practice on multiple case studies doing analysis with specific forensic data analysis tools
  • List common data analysis tools that can be used in support of investigations
  • Explain various trends in data analysis, data architecture, and data governance and their implications on investigations

Register For Online Course

  

Bring This Class To My Location

Morning Session
- Why Data Analytics in Investigations and Fraud Detection?
- Approaches to Data Analysis in Fraud Detection
- Data Analytics Maturity Model
- Leveraging Data Visualization
- Common Data Analysis Tools

Afternoon Session
- What to Analyze in an Investigation
- Hands-On Case Studies
- Advanced Data Analysis Considerations
- Trends in Data Analysis

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