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Fraud Detection Model
High RiskReal-time transaction monitoring system flagging suspicious patterns. Handles 2M+ transactions daily across all payment channels.
Assessment Progress6/10 questions
EU AI ActColorado AI ActNIST AI RMFISO 42001
Assessment Questionnaire
Risk Management
Does the fraud detection system have a documented risk management process for false positives impacting legitimate transactions?
Yes — risk management framework established Q4 2025, reviewed quarterly. False positive impact on customer experience is a tracked KPI.
EU AI ActAre risks of discriminatory fraud flagging across demographic groups identified and mitigated?
Fundamental rights impact assessment completed. Key risks: disproportionate flagging of transactions from certain regions. Mitigations include demographic-aware threshold calibration.
EU AI ActData Governance
Is the transaction data used for model training documented with provenance and quality metrics?
Partial — data sources documented, but quality metrics for representativeness across transaction types still pending.
NIST AI RMFAre bias testing procedures in place for fraud flagging rates across customer demographics?
Awaiting response
Colorado AI ActTransparency
Is there a mechanism for customers to contest fraud flags and request explanations?
Awaiting response
EU AI ActHuman Oversight
Can a fraud analyst override or release transactions flagged by the model?
Yes — all flagged transactions are routed to a human analyst queue. Override capability with audit logging is built in.
EU AI ActAre fraud analysts trained on model limitations, known blind spots, and failure modes?
Awaiting response
NIST AI RMFTechnical Robustness
Has the fraud model been tested for adversarial robustness against evasion attacks?
Awaiting response
ISO 42001Accuracy
Are fraud detection precision, recall, and false positive rates monitored in production?
Precision: 94.2%, Recall: 87.8%, F1: 90.9% — monitored daily with automated drift alerts.
EU AI ActRecord Keeping
Are fraud detection decision logs and alert dispositions maintained for the required retention period?
Yes — all decision logs retained for 5 years per EU AI Act Art. 12 requirements.
EU AI ActGap Analysis
3 gaps identified
Art. 9 — Risk ManagementHigh
Bias monitoring for fraud flagging rates across customer demographics not yet implemented.
Recommendation: Deploy demographic-aware false positive rate monitoring with automated alerting.
MAP 2.3 — Data ProvenanceMedium
Training data quality metrics for transaction type representativeness are incomplete.
Recommendation: Complete dataset documentation including transaction type distribution analysis and coverage gaps.
SB 205 — TransparencyHigh
No mechanism for customers to contest fraud flags and request explanations.
Recommendation: Implement explanation API endpoint and consumer-facing dispute workflow.