Shannon, a Certified Fraud Examiner (CFE), is conducting a fraud examination for Sand Corp.

Textual analytics is used to extract investigative insight from unstructured data—communications and documents that are not stored in standard database fields—such as emails, chats, memos, and other narrative text. CFE investigative guidance explains that textual analysis applies linguistic methods and statistical techniques to identify themes, anomalies, and linkages within large volumes of text. Its purpose is not to determine truthfulness or deception with certainty (Option A), because text analytics cannot reliably “detect lies” in a definitive way. Nor is its primary objective to guarantee discovery of a confession (Option B); admissions can appear, but that is not the defining function of the approach. Option C aligns more with flow-of-funds visualization or link/relationship charting for financial movements rather than analyzing language content. Instead, textual analysis is performed to categorize and structure text so patterns, sentiments, recurring topics, and relationships between people and events become visible—helping examiners prioritize leads, identify risk indicators, and focus investigative testing on communications most indicative of potential fraud.