[OR] [AmB] [E3] [CBS] [1] [SuPS] Identify Severe but Plausible Scenarios

CBS-1 Retail & Digital Banking

Identifying severe but plausible scenarios is a core requirement of operational resilience, enabling AmBank to test whether its Retail & Digital Banking services can remain within defined impact tolerances under extreme yet realistic conditions.

These scenarios go beyond traditional risk assessments by focusing on service disruption outcomes, rather than isolated causes, and by considering compound events such as cyber incidents, technology failures, third-party outages, and people's unavailability occurring concurrently.

For CBS-1 Retail & Digital Banking, the scenarios below are designed to reflect high-impact disruptions that could materially affect customers, regulatory compliance, financial stability, and trust.

Each scenario explicitly links to the integration of cyber and ICT risks, and demonstrates proactive risk management actions that evidence AmBank’s preparedness, response capability, and continuous improvement in line with modern operational resilience expectations.

Table P5: Identify Severe but Plausible Scenarios for CBS-1

Sub-CBS Code	Sub-CBS	Severe but Plausible Scenario	Impact / Effect	Proactive Risk Management Action	Link to Integration of Cyber and ICT Risks
1.1	Customer Onboarding & KYC	Core KYC systems unavailable for 48 hours due to a ransomware attack on the identity verification platform	Inability to onboard new customers; regulatory breach risk; revenue loss; customer dissatisfaction	Offline KYC fallback procedures; diversified third-party KYC providers; regular cyber incident simulations	Cyber attack on third-party SaaS; ICT resilience of identity platforms; data integrity and availability controls
1.2	Digital Banking Platform Provisioning	Major cloud service outage affecting mobile and internet banking platforms during peak hours	Customers unable to access accounts; reputational damage; increase in call centre volumes	Multi-region deployment; active-active architecture; periodic cloud exit and failover testing	Cloud ICT dependency; resilience of hosting infrastructure; integration with cyber resilience testing
1.3	Transaction Processing Services	The core banking transaction engine fails due to a corrupted database following failed patch deployment	Delayed or failed transactions; potential financial loss; regulatory reporting issues	Strict change management; pre-production testing; real-time transaction reconciliation	ICT change risk; cyber-related integrity risk; recovery point objectives (RPOs)
1.4	Digital Payments & Settlement	National payment network disruption, combined with internal gateway failure	Payment backlogs; missed settlements; merchant and customer impact	Alternate payment routing, liquidity buffers, and coordination with payment schemes	External ICT dependency: cyber-physical interconnection with payment ecosystems
1.5	Loan & Credit Product Management	Credit decisioning engine unavailable due to AI model service outage and data feed failure	Loan approvals delayed; SLA breaches; customer attrition	Manual credit assessment playbooks; model redundancy; data feed monitoring	ICT resilience of AI/ML platforms; data pipeline integrity and cyber monitoring
1.6	Deposit & Savings Product Management	Unauthorized configuration change causes incorrect interest calculations for 24 hours	Financial misstatements; customer complaints; remediation costs	Segregation of duties; automated controls validation; customer impact remediation plans	ICT configuration risk; cyber-related access control weaknesses
1.7	Customer Support & Service Resolution	Contact centre systems are unavailable due to a DDoS attack coinciding with a staff shortage	Customers unable to obtain support; escalation to regulators; reputational harm	Omnichannel support diversification; cyber DDoS protection; cross-trained staff	Cyber availability risk; ICT resilience of CRM and telephony systems
1.8	Compliance, Risk & Security Monitoring	Security monitoring tools fail during active cyber intrusion	Delayed detection; regulatory non-compliance; extended breach impact	Redundant SOC tooling; independent threat intelligence feeds; 24/7 escalation protocols	Cyber detection capability; ICT resilience of monitoring and logging infrastructure
1.9	Data Analytics & Personalization	Data lake corrupted due to malware infection affecting analytics workloads	Loss of customer insights; impaired marketing and risk analytics	Data segmentation, immutable backups, malware detection on analytics platforms	Cyber data integrity risk; ICT resilience of big data environments
1.10	Back-office Support & Reconciliation	Reconciliation systems are unavailable due to third-party software failure during the month-end	Financial reporting delays, audit issues, and operational backlog	Manual reconciliation contingencies; third-party resilience assurance; recovery testing	Third-party ICT risk; cyber and operational dependency integration

Banner [Summing] [OR] [E3] Identify Severe but Plausible Scenarios

The severe but plausible scenarios identified for CBS-1 Retail & Digital Banking demonstrate how disruptions can arise from interconnected failures across people, process, technology, and third parties, often amplified by cyber and ICT risks.

By grounding scenarios in realistic threat conditions—such as ransomware attacks, cloud outages, data corruption, and third-party failures—AmBank can meaningfully test its ability to continue delivering critical services within acceptable impact thresholds.

Importantly, the inclusion of proactive risk management actions provides tangible evidence of AmBank’s commitment to operational resilience, showing not only how risks are identified but also how they are actively mitigated, monitored, and rehearsed.

This approach strengthens regulatory confidence, protects customers, and ensures that Retail & Digital Banking services remain resilient even under extreme but credible disruption scenarios.

Operational Resilience Framework: A Case Study of AmBank Malaysia
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CBS-1 Retail & Digital Banking
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Operational Resilience Framework: A Case Study of AmBank Malaysia

[OR] [AmB] [E3] [CBS] [1] [SuPS] Identify Severe but Plausible Scenarios

Operational Resilience Certified Planner-Specialist-Expert

CBS-1 Retail & Digital Banking

Table P5: Identify Severe but Plausible Scenarios for CBS-1

More Information About OR-5000 [OR-5] or OR-300 [OR-3]

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Operational Resilience Framework: A Case Study of AmBank Malaysia

[OR] [AmB] [E3] [CBS] [1] [SuPS] Identify Severe but Plausible Scenarios

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Operational Resilience Certified Planner-Specialist-Expert

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Table P5: Identify Severe but Plausible Scenarios for CBS-1

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CBS-1 Retail & Digital Banking