AI-Powered Fraud Detection System for a FinTech Startup

As the startup scaled, so did the number of fraudulent attempts—from identity theft and account takeovers to card testing and synthetic fraud. Their legacy rule-based system couldn’t adapt to evolving fraud patterns, leading to:

• High false-positive rates blocking legitimate transactions
• Delays in transaction processing due to manual review
• Reputational and financial risks
• Inability to meet tightening EU regulatory compliance standards (PSD2, AML, KYC)

The client urgently needed an AI-powered fraud detection system for a FinTech startup that could provide accurate, real-time decisioning without compromising customer experience.

Plavno designed and implemented a robust AI-Powered fraud detection system for a FinTech startup, combining machine learning models, behavioral analytics, and real-time transaction monitoring to identify and prevent fraud with high accuracy.



Key Objectives

We aimed to deliver a scalable, real-time AI-powered fraud detection system with the following goals:

• Instantly detect and block fraudulent transactions (<300ms latency)
• Minimize false positives using adaptive machine learning
• Ensure full compliance with PSD2, AML, and KYC regulations
• Seamlessly integrate with existing FinTech infrastructure
• Automate manual reviews and improve fraud team efficiency
• Cover all channels: payments, logins, account creation

Rollout Strategy
Plavno executed a phased rollout strategy for the AI-powered fraud detection system for a FinTech startup, starting with a detailed discovery and risk assessment phase, followed by data preprocessing and model training using historical fraud patterns. An MVP was deployed in shadow mode to benchmark performance, then A/B tested in a live environment to fine-tune accuracy and reduce false positives.

Once validated, the system was fully integrated across all transaction channels with real-time APIs, automated workflows, and compliance dashboards. Post-launch, continuous monitoring and model retraining ensured the system remained adaptive, scalable, and regulation-ready.



Results
The AI-Powered fraud detection system for a FinTech startup delivered immediate and long-term impact:

• 92% reduction in successful fraud attempts
• 73% drop in false positives
• <300ms decision latency for real-time scoring
• Full compliance with EU financial regulations
• 42% cost savings in fraud team operations

By leveraging advanced AI and behavioral analytics, Plavno helped the FinTech client shift from reactive fraud management to a proactive, automated fraud prevention strategy that scales with their growth.

• Real-Time Fraud Scoring: Instantaneous decision-making using AI/ML
• Adaptive Machine Learning Models: Constantly improving fraud detection accuracy
• Multi-Channel Monitoring: Supports payments, logins, account creation, and more
• Explainable AI: Transparent scoring for regulatory compliance
• Behavioral Analytics: User patterns enhance fraud detection
• Custom Rule Engine: Combine AI with business-specific logic
• Alerts & Dashboards: Real-time fraud analytics for risk teams