Which type of financial documents can Natural Language Processing help analyze? Get the detailed answer for the IBM Artificial Intelligence Fundamentals certification exam and understand how NLP is applied in financial document analysis.
Table of Contents
Question
Which type of financial documents can Natural Language Processing help analyze?
A. Marketing reports
B. Earning call reports
C. Human-resource records
D. Customer outreach reports
Answer
B. Earning call reports
Explanation
Natural Language Processing (NLP) can help analyze earning call reports.
Earning call reports (Option B) are transcripts or summaries from quarterly meetings where company executives discuss financial performance and answer analyst questions. These documents contain complex language, financial terms, and qualitative insights. NLP techniques are highly effective in extracting sentiment, identifying trends, summarizing content, and detecting signals from these unstructured textual records.
Marketing reports (A) might also use NLP, but they are less central to financial analysis in the context of AI exam requirements.
Human-resource records (C) and customer outreach reports (D) are typically less relevant types of financial documents for NLP-driven analysis as framed by AI fundamentals certification content.
Understanding how NLP applies to financial documents such as earning call reports is a critical topic frequently examined in the IBM Artificial Intelligence Fundamentals certification exam.
IBM Artificial Intelligence Fundamentals certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Artificial Intelligence Fundamentals graded quizzes and final assessments, earn IBM Artificial Intelligence Fundamentals digital credential and badge.