AIP-C01 · Question #72
A bank is building a generative AI (GenAI) application that uses Amazon Bedrock to assess loan applications by using scanned financial documents. The application must extract structured data from…
The correct answer is A. Deploy Amazon Textract and Amazon Augmented AI within the same Region to extract relevant B. Use AWS Lambda functions to detect and redact PII from submitted documents before inference. D. Store uploaded documents in Amazon S3 and apply object metadata. Configure IAM policies to. The correct combination is A, B, and D because these three options collectively satisfy the mandatory requirements for structured extraction, PII redaction before inference, regional human review, data residency, auditability, and high-scale availability with managed AWS…
Question
A bank is building a generative AI (GenAI) application that uses Amazon Bedrock to assess loan applications by using scanned financial documents. The application must extract structured data from the documents. The application must redact personally identifiable information (PII) before inference. The application must use foundation models (FMs) to generate approvals. The application must route low-confidence document extraction results to human reviewers who are within the same AWS Region as the loan applicant. The company must ensure that the application complies with strict Regional data residency and auditability requirements. The application must be able to scale to handle 25,000 applications each day and provide 99.9% availability. Which combination of solutions will meet these requirements? (Select THREE.)
Options
- ADeploy Amazon Textract and Amazon Augmented AI within the same Region to extract relevant
- BUse AWS Lambda functions to detect and redact PII from submitted documents before inference.
- CUse Amazon Kendra and Amazon OpenSearch Service to extract field-level values semantically
- DStore uploaded documents in Amazon S3 and apply object metadata. Configure IAM policies to
- EUse AWS Glue Data Quality to validate the structured document data. Use AWS Step Functions
- FUse Amazon SageMaker Clarify to generate fairness and bias reports based on model scoring
How the community answered
(39 responses)- A59% (23)
- C23% (9)
- E13% (5)
- F5% (2)
Explanation
The correct combination is A, B, and D because these three options collectively satisfy the mandatory requirements for structured extraction, PII redaction before inference, regional human review, data residency, auditability, and high-scale availability with managed AWS services. Option A is essential because Amazon Textract is the AWS-managed service designed to extract structured data from scanned documents such as forms, tables, and financial statements. Textract provides confidence scores, and Amazon Augmented AI (A2I) is purpose-built to route low-confidence extractions to human reviewers. Deploying Textract and A2I within the same Region ensures that the human review loop remains regionally constrained, meeting strict data residency requirements for applicants. Option B satisfies the requirement to redact PII before inference by using AWS Lambda preprocessing. It also adds Amazon Bedrock guardrails to enforce safety controls on model outputs. Region-specific IAM roles ensure that only authorized principals in the correct Region can access the extracted data and invoke downstream services, strengthening residency enforcement and auditability. Option D ensures that source documents are stored in Amazon S3 in the same Region as the applicant. Object metadata and tagging provide an auditable trail, supporting compliance reporting and traceability. S3 also provides the durability and availability needed to support 99.9% application availability as part of a well-architected pipeline.
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