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AIF-C01 Practice Question: A financial services company uses Amazon Bedrock…
A financial services company uses Amazon Bedrock to power a customer-facing chatbot that provides investment advice. The company must ensure that the chatbot's responses comply with regulatory standards, meaning that the model should not generate advice that is speculative or promises returns. The company has implemented Bedrock Guardrails with content filters. However, during testing, the chatbot still generates responses that violate the guidelines. A review of the guardrail configuration shows that the content filters are set to the lowest sensitivity. The company wants to enforce stricter filtering without completely blocking legitimate responses. What should the company do?
⚠ Common exam trap
Watch out — candidates often think adding a deny topic (Option D) is the simplest way to enforce compliance, but they overlook that it completely blocks all investment advice, which violates the requirement to allow legitimate responses; the exam tests understanding of granular guardrail tuning versus blunt blocking.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the sensitivity of the content filters in the Bedrock Guardrails configuration.
Increasing the sensitivity of the content filters in Bedrock Guardrails directly addresses the issue: the current filters are set to the lowest sensitivity, allowing speculative or promise-based responses to pass through. By raising the sensitivity, the guardrails will block more non-compliant content while still permitting legitimate investment advice, striking the required balance between regulatory compliance and functionality.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the sensitivity of the content filters in the Bedrock Guardrails configuration.
Why this is correct
Raising content filter sensitivity tightens the confidence thresholds Bedrock Guardrails apply when classifying prompts and responses against harmful categories, so speculative or return-promising advice is intercepted more aggressively. Because filters remain category-based rather than blanket-blocking, legitimate investment responses still pass, satisfying the requirement for stricter filtering without wholesale denial.
- ✗
Use a different foundational model that has built-in compliance filters.
Why it's wrong here
Swapping the foundational model does not alter the guardrail configuration that is actually permitting the speculative advice; the filters remain at their lowest sensitivity, so violations persist. Built-in model filters are chosen when no configurable policy layer exists, not when Bedrock Guardrails already sit in front of the model.
- ✗
Configure the chatbot to route all responses to a human reviewer before delivering to the customer.
Why it's wrong here
Human review inserts latency and manual cost into every response rather than tightening the filter thresholds that are letting speculative advice through. Routing to reviewers suits low-volume, high-risk outputs where automation is unacceptable, not a customer-facing chatbot needing real-time, scalable enforcement.
- ✗
Add a deny topic for investment advice to completely block that topic.
Why it's wrong here
A deny topic blocks the entire investment-advice subject, eliminating legitimate responses the company wants to keep. It is tempting when a topic must be prohibited outright, such as preventing discussion of competitors or regulated products entirely.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.