ISO-IEC-42001-Lead-Auditor 試験問題を無料オンラインアクセス
| 試験コード: | ISO-IEC-42001-Lead-Auditor |
| 試験名称: | ISO/IEC 42001:2023Artificial Intelligence Management System Lead Auditor Exam |
| 認定資格: | PECB |
| 無料問題数: | 200 |
| 更新日: | 2025-09-03 |
During an audit, the auditor uncovers sensitive data regarding the AI system's algorithms and their decision-making processes. Which principle must the auditor adhere to when handling this information?
A few months after an audit, the auditor returns to the company to verify that corrective actions have been effectively implemented and that the issues identified have been resolved. Which step of the management system audit process does this activity correspond to?
During an audit, the auditor employed data analytic technology to identify anomalies and unusual patterns in the decision-making processes of an AI system used by a financial institution to approve or reject loan applications. Which data analytic technology did the auditor use?
Based on Scenario 4, the audit team employed the same level of effort and techniques across all audit areas. Is this recommended?
Scenario 4: Finalogic leads the application of artificial intelligence in the financial services sector, which is used to improve risk assessment, fraud detection, and customer service. The company has implemented an artificial intelligence management system AIMS based on ISO/IEC 42001 to ensure operational quality, ethical Al use, regulatory compliance, and transparency, allowing for consistent oversight and structured governance.
This month, Finalogic is undergoing an audit to obtain certification against ISO/IEC 42001, a critical step in demonstrating its commitment to responsible Al. To evaluate Finalogic's conformity to the audit criteria, the audit team adopted a comprehensive, evidence-based approach. The gathered evidence ranged from analyses of unquantifiable information to analyses of samples related to determining the audit criteria-including internal reports generated by Finalogic's own Al system-which assert successful integration and compliance with the standard.
Additionally, presentations by the company's Al team during the audit highlighted the system's success in customer service enhancements and fraud detection, emphasizing improved efficiency, decision making accuracy, and user trust. An evaluation report prepared by an independent third party firm specializing in Al systems also provided an objective review of Finalogic's AIMS. It assessed the system's effectiveness, bias, and compliance through a thorough examination.
During the audit, the audit team applied the same level of effort and utilized the same techniques across all audit areas, regardless of their risk level. This strategy ensured a consistent and thorough evaluation of the AIMS, uncovering any latent weaknesses or inefficiencies that might otherwise go unnoticed.
Despite Finalogic's advanced AIMS and adherence to ISO/IEC 42001 for ethical Al practices, there remains a risk of Al algorithms inadvertently perpetuating bias or making inaccurate predictions due to unforeseen flaws in training data or algorithmic models. This could lead to unfair loan rejections or approvals, potentially causing financial losses or damaging the company's reputation for fairness and accuracy in its financial services. By acknowledging these risks. Finalogic remains committed to refining its Al governance, implementing bias mitigation strategies, and enhancing transparency to uphold its reputation as a leader in Al driven financial services.
Scenario 3 (continued):
ArBank is a financial institution located in Brussels, Belgium, which offers a diverse range of banking and investment services to its clients. To ensure the continual improvement of its operations, ArBank has implemented a quality management system QMS based on ISO 9001 and an artificial intelligence management system AIMS based on the requirements of ISO/IEC
42001.
Audrey, an experienced auditor, led an internal audit focused on the AIMS within ArBank. She assessed the chatbots integrated into the bank's website and mobile app, analyzing communications using big data technology to identify potential noncompliance, fraud, or unethical conduct. Instead of relying solely on the information provided by the chatbots, Audrey sought out evidence that would either confirm or challenge the validity of the data, ensuring her conclusions were based on reliable and accurate information. Her review of selected chatbot interactions confirmed they met their intended purpose.
For the specific context of ArBank's operations, Audrey utilized an Al system to assess the efficiency of the bank's digital infrastructure, focusing on tasks critical to the Finance Department. This Al system was able to analyze the functionality of chatbots integrated into ArBank's website and mobile app to determine if it adheres to ISO/IEC 42001 requirements and internal policies governing customer service in the banking sector.
In addition, Audrey conducted a deeper assessment of the bank's AIMS. Her evaluation included observing different stages of the AIMS life cycle, from development to deployment, to ensure that roles and responsibilities were clearly defined and aligned with ArBank's operational goals. She also evaluated the tools used to monitor and measure the performance of the AIMS.
Audrey continued the audit process by auditing ArBank's outsourced operations. Upon checking the contractual agreements between the two parties, Audrey decided that there was no need to gather audit evidence regarding the contractual agreement. She reviewed the company's processes for monitoring the quality of outsourced operations, determined whether appropriate governance processes are in place with regard to the engagement of outsourced persons or organizations, and reviewed and evaluated the company's plans in case of expected or unexpected termination of the outsourcing agreement.
Based on the scenario above, answer the following question:
Question:
What big data technology did Audrey utilize? Refer to Scenario 3.