A structured, multi-factor risk scoring methodology calibrated for the Nigerian banking environment, aligned to CBN AML/CFT Regulations and FATF's risk-based approach.
The Nigerian AML Risk Scoring Model™ is a proprietary multi-factor framework developed by AI Shield Nexus to assign dynamic, continuously updated risk scores to customers, transactions, and relationships within the Nigerian financial system.
Unlike generic global risk models, it is calibrated specifically for Nigerian transaction patterns, regulatory thresholds, fraud typologies, and the CBN's risk-based supervision expectations, producing more accurate scores and fewer false positives.
Composite score (0–100) calculated as a weighted average across all dimensions
| Risk Band (Score) | Required Compliance Action |
|---|---|
| Low (0–30) | Standard CDD, periodic review (annual) |
| Medium (31–60) | Enhanced monitoring, 6-month review cycle |
| High (61–80) | EDD required, 3-month review, senior approval |
| Critical (81–100) | Immediate case creation, possible account freeze, SAR consideration |
Beyond static rule-based scoring, the model incorporates a machine learning layer that analyses behavioural baselines and detects deviations over time. This means risk scores evolve dynamically, a customer who was low-risk at onboarding can be re-scored in real time if behaviour changes significantly.
Establishes normal transaction patterns per customer segment and flags meaningful deviations.
Compares customer behaviour against similar cohorts to surface outliers with greater precision.
Risk thresholds adjust automatically based on seasonal patterns, economic conditions, and fraud trends.
Every score change is accompanied by a plain-language explanation for investigator review and audit documentation.
The Nigerian AML Risk Scoring Model™ is a multi-factor framework developed by AI Shield Nexus to assign dynamic risk scores to customers, transactions, and relationships within the Nigerian financial system. It combines rule-based triggers with AI-driven behavioural analytics.
Risk is scored across five dimensions: customer risk, geographic risk, transaction risk, channel risk, and product risk. Each dimension carries weighted inputs calibrated for Nigerian regulatory standards and common fraud patterns.
The model is calibrated to the CBN Risk-Based Supervision Framework, CBN AML/CFT Regulations 2022, and FATF's risk-based approach guidance, ensuring that scoring outputs align with regulatory examination expectations.
Book a demo and see how dynamic, Nigeria-calibrated risk scoring reduces false positives, improves investigator efficiency, and satisfies CBN examination requirements.