Data Mining for Auditors
Overview
This course will provide Internal Auditors with foundational and practical knowledge of data analytics and mining. This course is designed to differentiate these two concepts while providing auditors with tools to increase audit effectiveness. This course covers data mining techniques, maximizing data, data methodologies, and trend analysis. Participants will also identify ways to improve their continuous audit process and enhance outcome reporting through dashboard visualizations.
Why you should take this course.
For users with an introductory knowledge of this topic, and are searching for additional information and its application.
Here are the topics we'll cover.
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Define Data Mining and Continuous Auditing Overview
- Data Mining
- Data Analysis
- Exploratory Analysis
- Continuous Auditing
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Maximizing the Use of Data Overview
- Enhancing the Audit Plan with Analysis
- Risk Assessment Procedures
- Data Testing Procedures
- Multi-Purpose Tools
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Data Methodologies Overview
- Poisson Distribution
- Binomial Distribution
- Linear Regression
- Linear Regression Outliers
- Moving Averages
- Pivotal Points of Change Analysis
- Measure of Dispersion – Standard Deviation
- Mean Dispersion Analysis
- Period-to-Period Analysis
- Correlation Analysis
- Concentration Testing
- Data Patterns and Fraud Factors
- Beneish M-Score Calculator
- Keyword Searches for Manual Journal Entries
- Duplicate Transactions
- Horizontal Ratio Analysis
- Vertical Ratio Analysis
- Compliance Testing
- Compliance Testing with Excel Functions
- Operational Audit Tests with Excel Functions
- Financial Audit Tests with Excel Functions
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Defining a Continuous Audit Process
- Embedded Audit Routines
- Excel Templates
- Triggers or Thresholds
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Report Outcome Focus
- Audience Analysis
- Dashboard Planning
- Excel Data Cleaning
- Applying Functions to Testing for Dashboards
- Consolidating Data Techniques
- Visual-Centric Audit Reporting
- Future Improvement and innovations
Learning Style
Level
Who this course is for
NASBA Certified CPE
Field of Study
Length of course
Advanced Preparation
Here are the learning objectives we'll cover
- Differentiate between data mining and data analytics.
- Demonstrate how data analytics can optimize audit effectiveness.
- Identify additional audit analytics tools and describe innovations and improvements to these tools.
- Identify data patterns through hands-on exercises and activities.
- Explain how different visualization tools can be employed to build practical and useful dashboards.