CRISC Exam Dumps - Certified in Risk and Information Systems Control

The PRIMARY reason for an organization to ensure the risk register is updated regularly is to make sure that risk information is available to enable risk-based decisions, because the risk register is a tool that documents and tracks the identified risks, their characteristics, their status, and their responses. The risk register provides a comprehensive and current view of the risk profile and exposure of the organization, and it supports the decision-making process and the risk management activities. The other options are not the primary reason, because:

Option A: Risk assessment results are accessible to senior management and stakeholders is a benefit of updating the risk register regularly, but not the primary reason. Risk assessment results are the outputs of the risk analysis process, and they should be recorded and communicated to the relevant parties, but they are not the only or the most important information in the risk register.

Option B: Risk mitigation activities are managed and coordinated is a result of updating the risk register regularly, but not the primary reason. Risk mitigation activities are the actions taken to address the identified risks, and they should be monitored and reported in the risk register, but they are not the only or the most important information in the risk register.

Option C: Key risk indicators (KRIs) are evaluated to validate they are still within the risk threshold is a process that involves updating the risk register regularly, but not the primary reason. KRIs are indicators that measure and monitor the risk exposure and performance of the organization, and they should be compared with the risk threshold to determine if the risk level is acceptable or not, and if any action is required, but they are not the only or the most important information in the risk register. References = Risk and Information Systems Control Study Manual, 7th Edition, ISACA, 2020, p. 108.

A key risk indicator (KRI) is a metric that measures the changes in the level of risk exposure, such as by monitoring the risk drivers, triggers, or events. A KRI indicates a reduction in the percentage of appropriately patched servers means that the enterprise is not applying the latest security updates or fixes to its servers, which could expose them to vulnerabilities or threats. The best course of action for the risk practitioner when a KRI indicates a reduction in the percentage of appropriately patched servers is to determine changes in the risk level. The risk level is the measure of the impact and likelihood of the risk, and it should be consistent and comparable across the enterprise and over time. By determining changes in the risklevel, the risk practitioner can assess the current or emerging risks, and decide on the appropriate risk response strategy and actions. The other options are not the best course of action, as they involve different aspects or outcomes of the risk management process:

Outsource the vulnerability management process means that the enterprise transfers the responsibility or burden of identifying, analyzing, prioritizing, and remediating the vulnerabilities in the IT systems and applications to a third party, such as a vendor or a contractor. This may not be a feasible or effective way to address the risk of unpatched servers, as it may not reduce the exposure or impact of the risk, or may introduce new risks, such as contractual disputes, quality issues, or intellectual property rights.

Review the patch management process means that the enterprise evaluates the existing procedures and practices for applying the security updates or fixes to the servers, and identifies the gaps or weaknesses that need to be addressed. This may be a useful step in the risk management process, but it is not the best course of action, as it may not provide immediate or sufficient information or action to address the risk of unpatched servers, or may not account for the uncertainties or complexities of the risk.

Add agenda item to the next risk committee meeting means that the enterprise communicates the risk of unpatched servers to the senior executives who oversee the enterprise-wide risk management program, and provide guidance and direction to the risk owners and practitioners. This may be a helpful step in the risk management process, but it is not the best course of action, as it may not provide timely or adequate information or action to address the risk of unpatched servers, or may not reflect the urgency or priority of the risk. References = Risk and Information Systems Control Study Manual, 7th Edition, Chapter 4, Section 4.3.2.1, pp. 171-172.

When selecting a risk mitigation option, management should consider the cost of control implementation, as well as the benefits and residual risks. The cost of control implementation includes the direct costs of acquiring, installing, and maintaining the control, as well as the indirect costs of potential side effects, suchas reduced performance, increased complexity, or decreased user satisfaction. The cost of control implementation should be balanced with the expected reduction in risk exposure and the alignment with the enterprise’s risk appetite and tolerance. The maturity of the enterprise architecture, the reliability of key performance indicators (KPIs), and the reliability of key risk indicators (KRIs) are relevant factors for risk identification and assessment, but not for risk response selection. References = Risk and Information Systems Control Study Manual, Chapter 4: Risk Response, page 149.

A key risk indicator (KRI) is a metric used to measure and monitor the level of risk associated with a particular process, activity, or system within an organization1. KRIs are typically used in risk management to provide early warning signs of potential risks and to help organizations take proactive steps to mitigate those risks. KRIs are designed to be quantitative and measurable, allowing organizations to track changes in risk levels over time and to identify trends and patterns that may indicate an increased likelihood of risk. A negative security return on investment (ROI) would be most beneficial as a KRI, as it would indicate that the organization is spending more on security than the value it is generating or protecting. A negative security ROI would suggest that the organization is either over-investing in security, under-utilizing its security assets, or facing significant security threats or incidents that erode its security value. A negative security ROI would alert the organization to review its security strategy, budget, and performance, and to adjust them accordingly to optimize its security ROI and reduce its risk exposure2. Current capital allocation reserves are not the most beneficial as a KRI, as they do not directly measure the level of risk associated with a particular process, activity, or system. Capital allocation reserves are the amount of capital that an organization sets aside to cover potential losses or liabilities arising from its activities. Capital allocation reserves may reflect the organization’s overall risk appetite and tolerance, but they do not provide specific information on the sources, types, or impacts of risks that the organization faces3. Project cost variances are not the most beneficial as a KRI, as they do not directly measure the level of risk associated with a particular process, activity, or system. Project cost variances are the differences between the actual and planned costs of a project. Project cost variances may indicate the performance or efficiency of a project, but they do not provide specific information on the risks that may affect the project’s objectives, scope, quality, or schedule4. Annualized loss projections are not the most beneficial as a KRI, as they do not directly measure the level of risk associated with a particular process, activity, or system. Annualized loss projections are the estimates of the potential losses that an organization may incur in a year due to various risk events. Annualized loss projections may help the organization to plan and budget for its risk management activities, but they do not provide specific information on the likelihood, frequency, or severity of riskevents that may occur5. References = 1: Key risk indicator - Wikipedia2: What Is A Key Risk Indicator?3: Capital Allocation - Overview, Importance, and Methods4: Project Cost Variance: Definition, Formula, and Examples5: [Annualized Loss Expectancy (ALE) - Definition, Formula, and Example]

 The most important requirement to include in an outsourcing contract to help ensure sensitive data stored with a service provider is secure is a third-party assessment report of control environment effectiveness. This will help to verify that the service provider has implemented adequate security controls and practices to protect the data, and that they comply with the enterprise’s security policies and standards. A third-party assessment report also provides an independent and objective assurance of the service provider’s security posture and performance. Incidents related to data loss, risk assessment results, and cyber insurance policy are also important requirements to include in an outsourcing contract, but they are not as important as a third-party assessment report. References = Risk and Information Systems Control Study Manual, 7th Edition, Chapter 5, Section 5.2.1.2, page 2461

1: ISACA Certified in Risk and Information Systems Control (CRISC®) Exam Guide, Answer to Question 643.

The risk practitioner’s best course of action is to review the design of the machine learning model against the control objectives, because this will help to evaluate the suitability, effectiveness, and reliability of the model as a control measure. A machine learning model is a type of artificial intelligence that can learn from data and make predictions or decisions based on the data. A machine learning model can be used to automate or enhance the access management process, such as by identifying excessive access privileges, detecting unauthorized access, or recommending access rights. However, a machine learning model also introduces new risks and challenges, such as data quality, model accuracy, model bias, model explainability, model security, and model governance. Therefore, the risk practitioner should review the design of the machine learning model against the control objectives, which are the specific goals or outcomes that the control is intended to achieve. The control objectives can be derived from the IT risk management strategy, the IT governance framework, the IT policies and standards, and the regulatory requirements. The review of the machine learning model should cover the following aspects: - The data sources and inputs: The risk practitioner should verify that the data used to train and test the machine learning model is relevant, complete, accurate, consistent, and representative of the access management process and the access rights. The risk practitioner should also check that the data is collected, stored, processed, and transmitted in a secure and compliant manner, and that the data privacy and confidentiality are protected. - The model algorithms and outputs: The risk practitioner should validate that the model algorithms are appropriate, robust, and transparent for the access management process and the control objectives. The risk practitioner should also evaluate that the model outputs are accurate, reliable, and interpretable, and that they provide meaningful and actionable insights orrecommendations for the access management process and the control objectives. - The model performance and monitoring: The riskpractitioner should measure and monitor the model performance and effectiveness against the control objectives and the predefined metrics and indicators. The risk practitioner should also ensure that the model is updated and maintained regularly to reflect the changes in the access management process and the access rights, and that the model is audited and reviewed periodically to ensure its compliance and quality. By reviewing the design of the machine learning model against the control objectives, the risk practitioner can ensure that the model is fit for purpose and adds value to the access management process and the control objectives. The risk practitioner can also identify and mitigate any potential risks or issues that may arise from the use of the machine learning model as a control measure. References = Risk and Information Systems Control Study Manual, Chapter 3: Risk Response and Mitigation, Section 3.3: Control Design and Implementation, pp. 124-1271, Manage roles in your workspace - Azure Machine Learning2, Dataset Inference: Ownership Resolution in Machine Learning3

 A risk heat map is a visualization tool that shows the likelihood and impact of different risks on a matrix, using colors to indicate the level of risk. A risk heat map can help prioritize the risks that need the most attention and resources, and support the decision making and planning process for risk management. Mapping open risk issues to an enterprise risk heat map best facilitates risk response, which is the process of selecting and implementing the appropriate actions to address the risks. Risk response can include strategies such as mitigating, transferring, avoiding, or accepting risks. By mapping open risk issues to a risk heat map, an organization can identify the most suitable risk response for each risk, based on the risk appetite, criteria, and objectives. A risk heat map can also help evaluate the effectiveness and efficiency of the risk response, by showing the change in the level of residual risk after the risk response has been executed. References = What Is a Risk Heat Map & How Can It Help Your Risk Management Strategy, What Is a Risk Heat Map, and How Can It Help Your Risk Management Strategy, Risk Map (Risk Heat Map), How To Use A Risk Heat Map.

According to the CRISC Review Manual1, risk nomenclature and taxonomy is the set of terms and definitions that are used to describe and classify risks and their attributes. Risk nomenclature and taxonomy is the most important consideration when aligning IT risk management with the enterprise risk management (ERM) framework, as it helps to ensure a common and consistent understanding and communication of risks across the organization. Risk nomenclature and taxonomy also helps to integrate and harmonize the IT risk management processes and activities with the ERM framework, and to facilitatethe aggregation and reporting of risks at different levels of the organization. References = CRISC Review Manual1, page 197.