CONTROL MEASURES FOR PREVENTING AND DETECTING VIOLATIONS IN BANKING OPERATIONS BASED ON A RISK MAP AND A CONTROL MATRIX

Анотація

This article proposes an applied approach to designing control measures in banking operations by combining a risk map with a control matrix. It argues that the most persistent practical gap is not the absence of controls, but weak linkage between identified risks and the actual design of controls, which undermines traceability and auditability. To close this gap, risks are formulated as concrete scenarios at specific control points (what can go wrong, enabling conditions, and consequences) and prioritized using a simple score R = P×I, where P and I are rated on a 1–5 scale. For each prioritized risk, the control matrix records a standardized set of attributes: control objective and type (preventive, detective, corrective), control owner, frequency or trigger, execution method, evidence to be retained (logs, exception registers, reconciliation reports, approval records, access review acts), and the testing procedure. Effectiveness is assessed through configuration testing, exception analysis, sampling, and rule-quality review (including thresholds and false positives), followed by remediation tracking to keep the control system current as products, channels, and IT architecture evolve. The approach is illustrated for payment operations and remote channels, covering typical scenarios such as unauthorized payments, limit or approval bypass, sanctions and AML screening failures, suspicious transaction patterns, beneficiary data errors, accounting mismatches, excessive access rights and segregationof-duties breaches, and incomplete event logging. The proposed risk-to-control-to-evidence-to-testing chain improves consistency of control design, strengthens the evidence base for internal audit, supports compliance with supervisory expectations, and provides a replicable template that can be scaled to other banking processes such as lending, treasury, and cash operations. Future work may operationalize this template into KPI dashboards for continuous control monitoring and residual-risk measurement. The model is intentionally lightweight and can be implemented using existing log repositories and GRC tools without major IT investment, while still enabling audit-ready documentation and clearer accountability.

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