AI-powered fraud prevention platform combining behavioral biometrics and cross-institutional learning for mid-sized financial institutions, achieving 12% faster anomaly detection.
FraudShield+ redefines financial security through federated machine learning that analyzes transaction patterns across institutions without exposing raw data. Designed for mid-tier banks processing 50k+ monthly transactions, the solution reduces false positives by 18% compared to legacy systems while maintaining strict GDPR/PSD2 compliance through self-updating regulatory modules.
Core Functionality
Patented three-layer analysis combining:
- Behavioral biometrics tracking 120+ device interaction parameters
- Federated ML models trained across anonymized datasets
- Auto-updating compliance engine covering 14 regulatory frameworks
Target User Segment
Mid-sized banks (€1-10B assets) and payment processors in North America/Europe needing enterprise-grade protection without seven-figure contracts. Initial focus on UK EMI license holders and US regional banks.
Recommended Tech Stack
- ML Core: Python 3.10 + TensorFlow Federated
- API Layer: Golang with gRPC microservices
- Security: AWS Nitro Enclaves for encrypted data pooling
- Database: PostgresQL + TimescaleDB for timeline analysis
MVP Development Costs
800 engineering hours (€80,000) distributed across:
- Core API (320h)
- Biometric SDK (220h)
- Compliance Module (160h)
- Stress Testing (100h)
SWOT Analysis
- Strengths: 12% faster fraud pattern recognition vs isolated systems
- Weaknesses: Requires minimum 8 institutional partners for effective learning
- Opportunities: PCI-DSS auditor partnerships
- Threats: Quantum computing risks to encryption by 2028
Customer Acquisition Strategy
Blended €2,400 CAC through:
- Co-selling via ValidiFI partners (35% conversion)
- LinkedIn ABM campaigns (€120 CPA)
- Compliance webinar funnel (7.2% signup rate)
Monetization Model
- €0.0028 per transaction + €15k/month compliance fee
- Break-even at 14 clients processing 5M tx/month (€98k MRR)
- 6-person core team (2 ML engineers, 1 compliance lead)
Market Positioning
€7.3B fraud prevention market growing at 14.8% CAGR. Differentiated from Featurespace/Sift Science through privacy-preserving data collaboration. Initial focus on EU/NA markets with PSD2/GDPR compliance needs.
