CyberTRIZPEDIA

AML Model Complexity vs Operational Transparency

Embed explainability layers and confidence scoring into AML models to satisfy regulatory review requirements without sacrificing detection sophistication.

CyberTRIZ analysis · Banking contradiction AML034 · one of 8,235 worked contradictions published by CyberTRIZ.AI

Regulations

FATFEU_AI_ACTNIST_AI_RMFBE_NBB_GOVERNANCE_MANUAL_2022IIA_STANDARDS

Business Context

Sophisticated detection models improve financial crime identification but become increasingly difficult for investigators, auditors, and regulators to understand.

Banking TRIZ Resolution

Combine advanced analytics with explainable outputs, visual risk indicators, confidence scores, and standardized investigation summaries.

Recommended Banking TRIZ Principles

Principle 17 - Another Dimension

Principle 23 - Feedback

Principle 28 - Replacement of Mechanical Systems

Principle 40 - Composite Materials

Expected Outcome

Better explainability

Higher investigator confidence

Stronger governance

Easier regulatory review

TRIZ principles applied

P17 Another DimensionP23 FeedbackP28 Replacement of Mechanical SystemsP40 Composite Materials

Controls that address this (13)

FATF-AML-001 - Implement Risk-Based AML/CFT Approachoperational · critical priority · Implement a risk-based approach to AML/CFT covering: national risk assessment awareness, institutional risk assessment, risk-based allocatioFATF-CDD-001 - Implement FATF-Standard Customer Due Diligenceoperational · critical priority · Apply CDD measures to all customers: identify and verify customer identity, identify beneficial owners, understand the purpose of the busineFATF-R1-001 - Institutional AML/CFT Risk Assessmentgovernance · critical priority · Conduct a comprehensive institutional AML/CFT risk assessment covering: products and services, customer types, delivery channels, and geogra