Customer Risk Scoring (AML) : les pratiques conformes

Attentes de la FINMA, pratiques de marché, risk scoring dynamique

• Key risk indicators, data points, poids des risques…: qu’est-ce qu’un risk scoring compliant ?
• Risk scoring dynamique / “continu” : attentes de la FINMA, déficiences observées
• Intégrer le suivi des transactions et le scoring du risque

9.00 Identifier les facteurs de risque dans le KYC

• KYC: problématiques, attentes et qualité
  • Exemples tirés de l’expérience d’audit
• Des key risk indicators (KRI) variés : caractéristiques du client et les produits et services offerts au client
  • En général : différents KRI / quels data points sont des facteurs de risque qui peuvent être utiles pour la classification du risque ?
  • Comment analyser les différents indicateurs ?
  • Comment peut-on / doit-on mettre en oeuvre techniquement les indicateurs ?
  • Quel poids attribuer aux différents indicateurs de risque ?
  • Expérience de la pratique d’audit

Marc Kilcher, Associé, Regulatory & Compliance, Financial Services, KPMG Suisse, Genève

9.45 Les méthodes de Customer Risk Scoring : pratiques de marché

• Facteurs de risque, risk scoring et risk categorization (high, medium, standard)
• Benchmarking : comparaison des méthodes de risk scoring
• La classification des clients à risque standard en différentes sous-catégories dans le but de prioriser / optimiser la revue périodique : quels éléments du KYC utiliser ?

Marc Kilcher, Associé, Regulatory & Compliance, Financial Services, KPMG Suisse, Genève

Hedi Radhouane, Senior Manager, KPMG Forensic, Genève

10.30 Pause-café

10.50 Dynamic risk scoring; updating / refreshing the risk

• Observed deficiencies
• FINMA’s expectations
• How can real-time monitoring achieve dynamic risk scoring?
• What role does data integration play in keeping risk scoring models current?
• How are behavioral analysis and machine learning used for timely updates to risk scores?
• What benefits come from scenario-based testing for dynamic risk scoring models?
• How do automated risk mitigation strategies contribute to AML risk management?
• Why is regular calibration essential for dynamic risk scoring models?
• Why is maintaining documentation and an audit trail crucial for dynamic risk scoring compliance

Jha Madhumita, Senior Manager, Forensic & Integrity Services, EY, Zurich

Jawad Husseini, Senior Manager, Forensic & Integrity Services, EY, Zurich

11.25 Connecting Transaction Monitoring and Risk scoring

• How does integration connect transaction monitoring and risk scoring for comprehensive risk assessment?
• What is the role of correlated transactional patterns in identifying anomalies when connecting data with risk scoring results?
• How do threshold-based triggers dynamically adjust risk scores based on transactional thresholds?
• Why are adaptive machine learning models important for refining risk scores and adapting to emerging risks?
• How does the feedback loop between monitoring and scoring enhance overall risk assessment and detection capabilities?
• Why is real-time alerting in transaction monitoring critical for prompt investigation of flagged transactions?
• What benefits come from defining granular risk categories for transactions and assigning weights based on inherent risk?
• Why is transparent communication between transaction monitoring and risk scoring teams essential for effective collaboration and response to risks?

Jha Madhumita and Jawad Husseini

12.00 Fin du séminaire