AI-driven fraud prevention platform using behavioral biometrics and device fingerprinting to protect mid-market eCommerce merchants. Real-time analysis cuts fraud losses while maintaining seamless checkout experiences.
CheckoutShield tackles the $48B global eCommerce fraud problem through proprietary AI analyzing behavioral biometrics during checkout. By detecting subtle patterns in user interactions combined with device fingerprinting, it identifies fraudulent transactions with higher accuracy than rule-based systems while minimizing false positives that frustrate legitimate customers.
Core functionality
Real-time AI analysis of behavioral biometrics (keystroke dynamics, mouse movements) and device fingerprints during checkout. Machine learning models identify fraud patterns with automated decision engine. Integrates via API with major eCommerce platforms, providing merchant dashboard for flagged transaction review.
Target user and segment
Mid-market to enterprise eCommerce merchants in high-fraud verticals (electronics, luxury goods, digital services) operating in North America and Western Europe. Focus on businesses processing 10k+ monthly transactions.
Recommended tech stack
- Python (TensorFlow/PyTorch)
- Node.js API layer
- React dashboard
- PostgreSQL
- Redis for real-time processing
- AWS infrastructure
- Kubernetes orchestration
Estimated MVP hours and costs
Backend development: 400h (€40,000)
Fraud ML models: 350h (€35,000)
API integrations: 200h (€20,000)
Dashboard UI: 150h (€15,000)
Total MVP cost: €110,000 at €100/hour
SWOT-analysis
Strengths: Proprietary behavioral biometrics, Real-time decisioning <300ms, Seamless platform integrations
Weaknesses: Requires transaction history for model training, Potential false positives during ramp-up
Opportunities: Partnerships with payment processors, Expansion to emerging markets, Upsell to chargeback protection
Threats: Established players (Signifyd/Forter), Regulatory changes in biometric data usage
First 1000 customers strategy
Acquisition: Shopify/Magento marketplace listings, Targeted LinkedIn ads ($75 CPL), Fraud prevention webinars (30% conversion), Payment processor co-marketing
Projected CAC: €220
Timeline: 8 months via product-led growth
Monetization
Model: Tiered SaaS subscription + transaction fee
Pricing: Starter: €299/month (15k transactions), Pro: €799/month (50k transactions + €0.02/additional)
Break-even: 320 Pro-tier clients cover €70k monthly ops costs
Core team: 3 ML engineers, 2 full-stack devs, 1 CX specialist, 2 sales reps
Market positioning and competitors
Market size: €5.8B global fraud detection (2025)
Competitors: Signifyd (enterprise), Riskified (chargeback guarantee), Kount (mid-market)
Differentiation: Behavioral biometrics specialization with lower false-positive rate
Sales strategy: Platform marketplaces for SMBs + direct enterprise sales
