💼 Soluciones Industriales

Casos de Uso del Mundo Real

Descubra cómo las instituciones financieras de diversas industrias aprovechan nerous.ai para detectar el lavado de dinero, reducir falsos positivos y mantener el cumplimiento regulatorio.

100+
Financial Institutions
$10B+
Daily Transaction Volume
50+
Countries Covered
85%
Avg. False Positive Reduction

Banca y Finanzas Tradicionales

Moderniza el cumplimiento AML para banca minorista, banca comercial y gestión de patrimonio.

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

89%
False Positive Reduction
1,320
Alerts per Month
+45%
True Positive Rate
8x
Analyst Productivity

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

-92%
False Positives
45 min
Review Time per Case
+38%
Client Satisfaction
0
Regulatory Findings

Criptomonedas y Activos Digitales

Análisis blockchain avanzado y monitoreo de transacciones on-chain para plataformas cripto.

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

12 chains
Blockchain Coverage
<5 sec
Analysis Speed
99.3%
Mixer Detection
-70%
SAR Preparation Time

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

100%
Flash Loan Detection
96%
Wash Trade Identification
50+
Protocols Monitored
-81%
False Positives

Procesadores de Pagos y PSP

Monitoreo de transacciones de alta velocidad para pasarelas de pago y proveedores de servicios comerciales.

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

10M/day
Daily Volume
35ms
Scoring Latency
+250%
Mule Detection
-0.3%
False Decline Rate

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

+180%
Fraud Ring Detection
-65%
User Friction
94%
Mule Identification
<0.1%
Legitimate User Impact

Fintech y Neobancos

AML integrado para servicios financieros digitales y plataformas de préstamos.

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

4 weeks
Time to Launch
Passed
Regulatory Audit
-85%
vs. Traditional AML Cost
12x
Operational Efficiency

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

+320%
Return Abuse Detection
87% found
Synthetic Identity Fraud
Automated
Merchant Risk Assessment
100%
Compliance Coverage

Cómo Logramos Estos Resultados

Nuestro enfoque técnico combina múltiples técnicas de IA para una cobertura AML integral.

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Redes Neuronales de Grafos

Analiza relaciones en toda la red de transacciones para detectar estratificación, estructuración y redes de cuentas mula que los sistemas lineales pasan por alto.

📊

Análisis Comportamental

Aprende patrones normales para cada entidad y detecta desviaciones. Reduce falsos positivos mientras identifica técnicas novedosas de lavado de dinero.

Procesamiento en Tiempo Real

Análisis de transacciones en menos de 100ms que permite decisiones de riesgo inmediatas. Arquitectura distribuida que escala a millones de transacciones por día.

Vea Cómo nerous.ai Funciona para Su Industria

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