Textual Analytics
Intermediate
Online
Description
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
Prerequisites
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 |
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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:
- Internet access: High-speed connection recommended
- Speakers required for video sound
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