Operational Controls in Operational Risk Management

This curriculum spans the design and execution of operational risk controls across governance, incident management, third-party oversight, technology integration, and regulatory compliance, comparable in scope to a multi-phase advisory engagement supporting the implementation of an enterprise-wide operational risk framework.

Module 1: Establishing the Operational Risk Governance Framework

• Define the scope of operational risk ownership across business units versus centralized risk functions.
• Select and justify the use of RCSA (Risk Control Self-Assessment) over third-party audits based on control maturity.
• Determine reporting lines for operational risk incidents to ensure timely escalation to the board or risk committee.
• Implement a risk taxonomy that aligns with regulatory expectations (e.g., Basel, SOX) and internal audit requirements.
• Negotiate authority thresholds for local control owners versus centralized risk overrides in decentralized organizations.
• Integrate operational risk appetite statements into business planning cycles and capital allocation models.
• Decide on the frequency and format of risk reporting dashboards for executive versus operational stakeholders.
• Balance regulatory compliance requirements with business agility when defining risk governance policies.

Module 2: Designing and Implementing Key Risk Indicators (KRIs)

• Select leading versus lagging indicators based on the predictability of control failure in high-risk processes.
• Set KRI thresholds using historical incident data, stress testing, or industry benchmarks.
• Integrate KRI data feeds from HR, IT, and operations systems into a centralized risk data warehouse.
• Address false positives in KRI alerts by tuning sensitivity levels without compromising early warning capability.
• Assign accountability for KRI monitoring and escalation to specific operational roles.
• Validate KRI effectiveness through back-testing against actual operational loss events.
• Adjust KRI definitions when business process changes (e.g., automation, outsourcing) alter risk profiles.
• Coordinate with compliance teams to ensure KRIs support regulatory reporting obligations.

Module 3: Operational Risk Control Self-Assessment (RCSA) Execution

• Determine the optimal frequency of RCSA cycles (quarterly vs. annual) based on control volatility.
• Train process owners to assess control design and operating effectiveness without over-reliance on internal audit.
• Standardize scoring methodologies across business units to enable aggregation and benchmarking.
• Resolve discrepancies between self-assessed control ratings and internal audit findings.
• Link RCSA outcomes to action plans with assigned owners and timelines for remediation.
• Use RCSA data to inform insurance purchasing decisions and capital modeling.
• Implement digital RCSA tools while maintaining audit trails and version control.
• Address resistance from business units by aligning RCSA outcomes with performance incentives.

Module 4: Incident Management and Loss Data Collection

• Define materiality thresholds for operational loss event reporting across business lines.
• Implement a centralized incident logging system with mandatory fields for root cause and financial impact.
• Classify incidents using standardized event types (e.g., internal fraud, system failure) for regulatory reporting.
• Conduct root cause analysis using techniques like 5 Whys or Fishbone diagrams for major incidents.
• Ensure incident data feeds into capital models and scenario analysis for OpRisk VaR.
• Enforce timely incident reporting by integrating with HR and compliance disciplinary processes.
• Validate loss data accuracy through reconciliation with financial ledgers and insurance claims.
• Manage reputational risk by coordinating incident disclosure protocols with legal and PR teams.

Module 5: Third-Party and Outsourcing Risk Controls

• Conduct due diligence on third-party vendors using standardized risk assessment questionnaires.
• Negotiate SLAs and penalties that reflect operational risk exposure in outsourcing contracts.
• Implement ongoing monitoring of vendor performance using KRIs and audit rights.
• Map critical third-party dependencies to business impact analysis and continuity plans.
• Enforce segregation of duties between vendor staff and internal employees in shared systems.
• Require vendors to report security incidents and control failures within defined timeframes.
• Assess concentration risk when multiple business units rely on a single third-party provider.
• Conduct on-site audits of high-risk vendors or require independent attestation reports (e.g., SOC 2).

Module 6: Technology and Cyber Risk Integration

• Map IT system dependencies to critical business processes for risk prioritization.
• Integrate cyber incident data into the operational risk loss database for aggregation.
• Define roles for IT, security, and risk teams in managing technology-related operational risks.
• Implement automated controls monitoring for privileged access and configuration changes.
• Align technology risk assessments with RCSA cycles and update frequency.
• Use penetration testing results to update threat models and control gaps.
• Ensure backup and recovery procedures are tested and documented as part of operational resilience.
• Address shadow IT by enforcing governance over unsanctioned software and cloud services.

Module 7: Change Management and Project Risk Oversight

• Embed operational risk assessments into project initiation and stage-gate approval processes.
• Require project managers to identify and mitigate new control gaps introduced by system changes.
• Assess the operational risk impact of organizational restructuring or site closures.
• Review post-implementation reviews for control effectiveness within 90 days of go-live.
• Coordinate with IT change advisory boards (CAB) to evaluate risk of production deployments.
• Track change-related incidents to identify patterns in failed rollouts or configuration errors.
• Define rollback procedures and fallback controls for high-risk system upgrades.
• Ensure training and documentation are updated before operational handover of new systems.

Module 8: Operational Resilience and Business Continuity

• Conduct business impact analyses (BIA) to prioritize recovery of critical functions.
• Define recovery time objectives (RTO) and recovery point objectives (RPO) with business owners.
• Test disaster recovery plans annually with participation from IT, facilities, and operations.
• Validate alternate site readiness, including data replication and workforce access.
• Integrate cyber resilience scenarios into business continuity testing.
• Update crisis management communication trees and escalation protocols quarterly.
• Ensure third-party providers have aligned business continuity plans for critical services.
• Document lessons learned from tests and real incidents to refine response plans.

Module 9: Regulatory Compliance and Supervisory Expectations

• Map operational risk controls to regulatory requirements such as Basel III, GDPR, or SOX.
• Prepare regulatory submissions (e.g., Pillar 3 disclosures) using auditable risk data.
• Respond to supervisory findings by linking control gaps to remediation plans.
• Coordinate with legal and compliance teams to interpret new regulatory guidance on OpRisk.
• Maintain evidence of control testing and monitoring for regulatory examinations.
• Adjust risk appetite metrics in response to supervisory feedback or thematic reviews.
• Implement governance controls for model risk in operational risk capital calculations.
• Report material operational losses to regulators within mandated timeframes.

Module 10: Data Governance and Risk Analytics

• Define data ownership and stewardship roles for operational risk data sources.
• Establish data quality rules for loss, control, and KRI datasets used in reporting.
• Integrate risk data from siloed systems (ERP, HRIS, ITSM) into a unified data model.
• Apply statistical methods to identify trends and anomalies in operational loss patterns.
• Use scenario analysis to estimate potential losses where historical data is insufficient.
• Validate the accuracy of risk models through back-testing and expert challenge.
• Ensure data privacy and access controls are enforced in risk analytics platforms.
• Support stress testing exercises with scenario-driven operational risk loss projections.