Textual Analytics

Textual Analytics
Course Level
Delivered via
2 Credits


Textual analytics is a type of data analytics that is used to explain, understand and interpret a situation or a person’s actions or thoughts. Its goal is to extract usable information from unstructured text data, such as email communications or social media content, which can provide valuable insight into potential fraud.

Text mining and other textual analysis techniques are discussed in this course, and examples are provided on how they can be used during an investigation or as a proactive anti-fraud measure. The use of textual analytics to assess fraud risk, analyze text in emails and social media, and understand sentiment in the right context is discussed. This course also includes a discussion on using components of the Fraud Triangle to create pre-defined keyword lists aimed at detecting fraud.

Key Takeaways:

  • Textual analysis techniques such as text mining  
  • How textual analytics can be used reactively or proactively  
  • Using the Fraud Triangle to create pre-defined keyword lists to detect fraud 
  • Benefits and challenges of textual analytics in fraud investigations 


Fundamental knowledge of data analysis procedures

You Will Learn How To:

Determine how textual analysis can be used in the prevention and detection of fraud

Identify the various textual analytic techniques used to detect fraud

Determine how textual analysis can be used to assess fraud risk

Recognize the benefits and challenges associated with using textual analytics

Table of Contents

Lesson 1 What Is Data Analysis?
Lesson 2 Types of Data
Lesson 3 What Is Textual Analytics?
Lesson 4 Benefits of Using Textual Analytics
Lesson 5 Challenges Faced When Performing Textual Analysis
Lesson 6 The Basics of Textual Analytics
Lesson 7 Text Mining
Lesson 8 Other Textual Analytic Techniques
Lesson 9 Fraud Triangle Components and Keywords
Lesson 10 Textual Analytics Using Sentiment
Lesson 11 Textual Analytics Using Emails
Lesson 12 Textual Analytics Using Social Media
Lesson 13 Combining Textual Analytic Techniques
Lesson 14 Displaying Results
Lesson 15 Data Privacy and Security
Lesson 16 Using Textual Analytics to Conduct Fraud Risk Assessments

CPE Information

CPE Credit: 2
NASBA Information: Auditing
Advanced Preparation: None
Last Updated: February 2022
Delivery Method: QAS Self-Study


CPE Credit

Please note: To be eligible for CPE credit, you must complete the final exam within one year of purchase date. You may only claim CPE credit for a course once.

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System Requirements:

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The Association of Certified Fraud Examiners, Inc. is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website:


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