Praxisnahe Anwendungsfälle
Entdecken Sie, wie Finanzinstitute in verschiedenen Branchen nerous.ai nutzen, um Geldwäsche zu erkennen, Fehlalarme zu reduzieren und regulatorische Compliance aufrechtzuerhalten.
Banking & Traditionelle Finanzdienstleistungen
Modernisieren Sie die AML-Compliance für Privatkundenbanken, Geschäftsbanken und Vermögensverwaltung.
Regional Commercial Bank
Challenge
Legacy rule-based system generating 12,000 false alerts monthly, overwhelming compliance team of 15 analysts. Unable to detect sophisticated layering schemes across business accounts.
Solution
Deployed nerous.ai with Graph Neural Network analysis of account relationships. Integrated with core banking system via API for real-time wire transfer monitoring. Custom models trained on 5 years of historical transaction data.
Results
Private Wealth Management
Challenge
High-net-worth clients with complex international transactions triggering excessive alerts. Manual review taking 4-6 hours per case. Risk of losing clients due to friction.
Solution
Implemented behavioral profiling for each UHNW client using LSTM models. Created personalized risk baselines considering typical transaction patterns (art purchases, real estate, investments). Real-time risk scoring with context-aware alerts.
Results
Kryptowährungen & Digitale Assets
Erweiterte Blockchain-Analytik und On-Chain-Transaktionsüberwachung für Krypto-Plattformen.
Cryptocurrency Exchange
Challenge
Processing 500K+ daily transactions across multiple blockchains. Traditional chain analysis tools missing cross-chain patterns. Mixer and tumbler transactions requiring manual investigation. Regulatory pressure to identify high-risk counterparties.
Solution
Deployed multi-chain transaction graph analysis. Machine learning models trained on known mixer patterns and sanctioned addresses. Automated wallet clustering and entity resolution across Bitcoin, Ethereum, and major L2s. Integration with Chainalysis and Elliptic for enhanced coverage.
Results
DeFi Platform
Challenge
Complex DeFi interactions creating false positives. Flash loan attacks and wash trading manipulation. Smart contract interactions difficult to classify as legitimate or suspicious. Need to monitor liquidity pools, yield farming, and cross-protocol transactions.
Solution
Built custom models for DeFi-specific patterns including flash loans, MEV, and protocol interactions. Smart contract code analysis to understand transaction intent. Behavioral analysis of wallet patterns across protocols. Real-time monitoring of liquidity pool manipulations and sandwich attacks.
Results
Zahlungsabwickler & PSPs
Hochvolumige Transaktionsüberwachung für Zahlungsgateways und Händlerdienstleister.
Global Payment Processor
Challenge
Processing 10M+ transactions daily across 45 countries. Money mule networks moving funds rapidly through legitimate accounts. High-velocity merchant fraud. Real-time scoring needed without adding latency to payment flow.
Solution
Deployed real-time risk scoring with <50ms latency. Network graph analysis identifying mule account clusters. Merchant risk profiling using historical patterns and velocity checks. Integration with card networks for fraud intelligence sharing.
Results
Peer-to-Peer Payment App
Challenge
Fraud rings using social engineering to recruit money mules. Legitimate friends/family payments difficult to distinguish from mule activity. Account takeover leading to unauthorized transfers. Balancing fraud prevention with user experience.
Solution
Social network analysis identifying suspicious relationship patterns. Behavioral models detecting account takeover through device, location, and usage pattern changes. Progressive friction (step-up authentication) based on risk scores. Real-time collaboration with other P2P platforms via consortium.
Results
Fintech & Neobanken
Eingebettete AML-Lösungen für digitale Finanzdienstleistungen und Kreditplattformen.
Digital-Only Neobank
Challenge
Startup bank needing full AML/CFT compliance before launch. Limited budget and team (no compliance staff initially). Need to scale from 0 to 100K customers in first year. Regulatory scrutiny on new digital banks.
Solution
Implemented nerous.ai as complete AML solution - transaction monitoring, customer screening, suspicious activity detection, and SAR filing workflows. Configured pre-built rules for common typologies plus ML models. Automated customer risk rating and ongoing due diligence. Cloud-based deployment with API integration.
Results
Buy Now, Pay Later Provider
Challenge
Return fraud and merchant collusion schemes. Synthetic identity fraud using stolen PII. Rapid growth outpacing manual review capacity. Merchant onboarding risk (fraudulent sellers). CFPB increasing scrutiny of BNPL sector.
Solution
Multi-layered approach: identity verification at signup using document verification and biometrics, transaction monitoring for return patterns and merchant collusion, merchant risk scoring based on return rates and customer complaints, network analysis identifying fraud rings across platforms.
Results
Wie wir diese Ergebnisse erzielen
Unser technischer Ansatz kombiniert mehrere KI-Techniken für umfassende AML-Abdeckung.
Graph Neural Networks
Analysieren Sie Beziehungen über gesamte Transaktionsnetzwerke, um Layering, Strukturierung und Mule-Account-Ringe zu erkennen, die lineare Systeme übersehen.
Verhaltensanalyse
Lernen Sie normale Muster für jede Entität und erkennen Sie Abweichungen. Reduziert Fehlalarme und identifiziert neuartige Geldwäsche-Techniken.
Echtzeitverarbeitung
Transaktionsanalyse unter 100ms ermöglicht sofortige Risikoentscheidungen. Verteilte Architektur skaliert auf Millionen von Transaktionen pro Tag.
Sehen Sie, wie nerous.ai für Ihre Branche funktioniert
Planen Sie eine personalisierte Demo, um Ihre spezifischen AML-Herausforderungen und -Anforderungen zu besprechen.