Isaca Updated CRISC Exam Questions and Answers by aminah

Assessing the risk of using production data for testing before making a decision is the best recommendation for the risk practitioner, because it helps to balance the benefits and drawbacks of using real data for the proof of concept (POC) of a security tool. A POC is a demonstration or trial of a proposed solution or product to verify its feasibility, functionality, and value. A security tool is a software or hardware device that helps to protect the IT systems or networks from threats or attacks. Using production data for testing purposes can yield the best results, as it reflects the actual data that the security tool will handle in the operational environment. However, using production data for testing also poses risks, such as data leakage, data corruption, data privacy violation, or regulatory non-compliance. Therefore, assessing the risk ofusing production data for testing before making a decision is the best recommendation, as it helps to identify and evaluate the potential risks and issues, and to determine the appropriate controls or mitigating factors to reduce or eliminate them. Accepting the risk of using the production data, benchmarking against what peer organizations are doing, and denying the request are all possible recommendations, but they are not the best recommendation, as they do not consider the risk assessment process and the trade-offs involved in using production data for testing. References = Risk and Information Systems Control Study Manual, Chapter 5, Section 5.4.1, page 208

The most important factor for the organization to consider before implementing a new in-house developed artificial intelligence (AI) solution is the expected algorithm outputs, as they define the desired outcomes and objectives of the AI solution, and guide the design, testing, and validation of the AI algorithm. The other options are not the most important factors, as they are more related to the research, input, or monitoring of the AI solution, respectively, rather than the output of the AI solution. References = CRISC Review Manual, 7th Edition, page 153.

The correct answer isAbecause the greatest risk when using apublic AI systemto process credit card transactions is thepotential exposure of sensitive information. Credit card data is highly sensitive, and use of a public AI platform can introduce serious confidentiality, privacy, and data handling concerns. Exposure of that data can lead to fraud, regulatory issues, contractual violations, and significant business impact.

The other options are important, but not the greatest primary risk:

B. Use of financial data to train the AI modelis a specific form of data misuse, but it falls within the broader and more critical risk of sensitive information exposure.

C. Noncompliance with security standardsis also significant, but it is often a consequence of exposing or improperly handling sensitive payment data.

D. AI hallucinations and biasare important AI risks, but they are not the primary concern in payment card processing.

Exact Extracts supporting the answer:

“The MOST important consideration when transmitting personal information across networks is ensuring the privacy of the personal information.”

“The data security control that BEST protects the confidentiality of data stored on backup media in transit to a third-party storage facility is encryption.”

“The MOST significant risk associated with handling credit card data through a web application is failure to store credit card data in a secure area segregated from the demilitarized zone.”

“To determine the level of protection required for securing personally identifiable information a risk practitioner should PRIMARILY consider the sensitivity property of the information.”

These extracts support that the primary concern with payment-card-related processing is protecting the confidentiality of sensitive data. Therefore, the greatest risk is thepotential exposure of sensitive information.

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Risk scenarios should reflect probable events to ensure relevance and practicality in risk assessments. This guidance supports theRisk Identification and Scenario Developmentprocess.