Risk analysis is a systematic process used in Business Continuity Planning (BCP), Disaster Recovery (DR) planning, and audit functions to identify, evaluate, and prioritize risks that can affect organizational operations, assets, and stakeholders. It helps organizations prepare for disruptions such as natural disasters, cyberattacks, system failures, or human errors by developing preventive and recovery strategies. Effective risk analysis ensures business resilience, regulatory compliance, and operational continuity. Organizations often align their risk analysis practices with frameworks developed by bodies such as International Organization for Standardization and National Institute of Standards and Technology to ensure consistency and reliability. One major technique of risk analysis is qualitative risk analysis. This method evaluates risks based on descriptive characteristics such as likelihood and impact using categories like high, medium, or low. It is widely used during initial BCP and DR planning phases because it is simple and quick to implement. Risk matrices are commonly used in this technique, where probability and impact are plotted to determine risk severity. For example, in BCP, qualitative analysis helps identify critical business processes that must be restored first during disruption. In audits, qualitative risk analysis assists auditors in prioritizing areas requiring deeper examination based on perceived threat levels. Another important technique is quantitative risk analysis. Unlike qualitative analysis, it uses numerical values and statistical models to measure risk exposure. Techniques such as Monte Carlo simulation, sensitivity analysis, and decision tree analysis fall under this category. Quantitative risk analysis is useful in financial impact assessment, where organizations calculate potential losses due to downtime or data breaches. In DR planning, it