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This study develops a Dynamic Business Impact Analysis and Dependency-Aware Recovery Optimization framework for mission-critical banking operations. The objective is to assess time-dependent service impact, model cascading disruption across interconnected banking resources, and prioritize recovery actions under constrained technical, financial, and human resources. The methodology combines operational and incident data preparation, multilayer dependency-network modeling, scenario-based simulation, dynamic impact scoring, and multi-criteria recovery optimization using service impact, customer exposure, financial loss, RTO breach, RPO breach, and recovery cost. Evaluation covers core account services, payment processing, online banking, ATM and card services, customer authentication, and fraud monitoring across cyber, infrastructure, communication, payment-network, and third-party disruption scenarios. Compared with criticality-only, shortest-recovery-time, and static business impact analysis baselines, the proposed method reduced mean recovery time to 4.6 hours and cumulative impact to 0.47, while increasing RTO compliance to 82.9% and RPO compliance to 88.6%. The findings show that dependency-aware, time-sensitive recovery prioritization provides more reliable system-level decisions than fixed service rankings. The framework supports resilience testing, impact-tolerance assessment, incident command, recovery planning, and investment decisions for banking infrastructure.
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Sudipta Banik Chowdhury (2026) studied this question.
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