Safeguarding Your
Transactions
with AI-Powered Fraud Detection
That Stops Threats in Real-Time
At Mastropay Technology, our fraud detection services represent the pinnacle of proactive cybersecurity in fintech, harnessing advanced machine learning, behavioral analytics, and graph-based anomaly detection to identify and neutralize fraudulent activities before they impact your bottom line. In an era where sophisticated attacks like account takeovers, synthetic identity fraud, and money mule schemes evolve daily, we deploy multi-layered defenses that analyze over 300 data points per transaction—including device fingerprinting, geolocation velocity, and network behavior—to achieve false positive rates under 0.5% and detection accuracy exceeding 98%. Integrated seamlessly with payment gateways, core banking systems, and CRM platforms, our solutions not only block fraud in real-time but also provide forensic-grade explanations for every alert, enabling rapid investigations and continuous model refinement. Compliant with global standards such as PCI DSS 4.0, GDPR, and PSD3, we empower businesses to foster trust, reduce chargeback losses by up to 90%, and unlock revenue opportunities through frictionless, secure customer experiences that prioritize both protection and usability.
Our Multi-Layered Fraud Detection Lifecycle
We implement a continuous, adaptive lifecycle that combines rule-based heuristics, supervised ML models, and unsupervised learning to create a dynamic defense system. This approach not only reacts to known threats but proactively evolves through feedback loops, ensuring resilience against zero-day exploits and adaptive adversaries while maintaining high throughput for legitimate transactions.
Data Collection & Enrichment
Gather comprehensive signals
Initiating the detection pipeline with exhaustive data ingestion, we capture transaction metadata from multiple vectors: user behavior (session duration, navigation paths), device signals (browser fingerprints, IP geolocation), and external enrichments (velocity checks against blacklists, credit bureau pulls). This phase employs privacy-preserving techniques like differential privacy to aggregate signals without compromising PII, feeding into a unified feature store that contextualizes each event. By correlating historical patterns with real-time feeds from threat intelligence platforms (e.g., Recorded Future, ThreatConnect), we build a 360-degree risk profile, enabling nuanced scoring that distinguishes benign anomalies from malicious intent, all while adhering to data minimization principles under CCPA and LGPD.
- 300+ feature engineering points per txn
- Real-time API integrations for external validation
- Graph databases for relationship mapping
- Consent management for data usage
Risk Scoring & Rule Engine
Apply layered risk assessment
Deploying a hybrid engine that combines deterministic rules (e.g., velocity limits, blacklisted IPs) with probabilistic ML classifiers (XGBoost, neural nets), we assign dynamic risk scores from 0-1000, calibrated per transaction type. Rules are configurable via low-code interfaces, allowing business users to adjust thresholds for high-value scenarios like wire transfers, while ML components learn from labeled data to score novel attacks. This dual approach minimizes evasion tactics, with ensemble methods fusing outputs for a composite verdict, triggering holds, challenges, or blocks based on score bands, all executed in under 50ms to preserve user flow.
- Rule chaining & decision trees
- Model ensembles for robustness
- Adaptive scoring via online learning
- Explainability layers (SHAP values)
Anomaly & Behavioral Analysis
Uncover hidden patterns
Utilizing unsupervised algorithms like isolation forests and autoencoders, we detect deviations from baseline behaviors—such as unusual login locations or spending spikes—across user cohorts. Graph analytics reveal collusion networks (e.g., shared devices in ATO rings), while time-series models forecast fraud propensity based on seasonal trends. Integrated with SIEM systems, alerts feed into SOAR playbooks for automated responses, like temporary holds or OTP challenges, ensuring proactive containment without overreach.
- Unsupervised clustering for outliers
- Behavioral baselines per user segment
- Network analysis for fraud rings
- Time-series anomaly forecasting
Response & Remediation
Act and learn from incidents
Upon detection, orchestrated responses deploy via API calls: freezing accounts, notifying users via multi-channel alerts, or escalating to investigators with enriched case files. Post-event, root cause analysis feeds back into model retraining, with A/B testing for new rules to validate efficacy. This closed-loop system continuously hardens defenses, incorporating lessons from global threat feeds to preempt similar attacks across your ecosystem.
- Automated blocking & recovery workflows
- Case management & escalation tiers
- Feedback loops for model improvement
- Simulation testing for response efficacy
Monitoring & Optimization
Evolve defenses continuously
Ongoing surveillance through dashboards tracks KPIs like detection latency and false positive trends, with AI-driven hyperparameter tuning to optimize performance. Quarterly audits and red-team exercises validate resilience, while integration with compliance tools ensures alignment with evolving regs like the Digital Operational Resilience Act (DORA). This iterative refinement keeps your fraud defenses ahead of adversaries, adapting to new tactics without manual reconfiguration.
- Performance dashboards & alerting
- Model drift detection & retraining
- Regulatory alignment checks
- Cost-benefit analysis for controls
Sophisticated Fraud Detection Features from Mastropay Technology
Our platform delivers a comprehensive arsenal of tools, from velocity monitoring to deepfake detection, designed to counter diverse fraud vectors while integrating effortlessly into your transaction pipeline for minimal latency.
Velocity & Pattern Monitoring
Track transaction frequencies, amounts, and sequences to flag bursts indicative of card testing or laundering, with adaptive thresholds based on user history and peer benchmarks.
- Multi-dimensional velocity rules
- Historical baseline deviations
- Peer group comparisons
Device & Network Fingerprinting
Generate unique device signatures from canvas rendering, font enumeration, and hardware sensors, cross-referenced with VPN/proxy detection to unmask spoofed identities.
- Passive fingerprint collection
- Tor/VPN evasion flags
- Session continuity scoring
Synthetic Identity Detection
Identify fabricated personas through cross-validation of PII against public records, social graphs, and velocity patterns, flagging mule accounts before activation.
- Graph-based entity resolution
- OSINT enrichment
- Age-of-account scoring
Account Takeover Prevention
Monitor login anomalies with continuous authentication, combining biometrics, keystroke dynamics, and session hijack detection to secure sessions post-login.
- Continuous behavioral auth
- Session anomaly alerts
- MFA fatigue mitigation
Deepfake & Biometric Fraud
Advanced liveness detection and voice biometrics to counter AI-generated fakes, integrated with facial recognition APIs for multi-modal verification during high-risk actions.
- Liveness challenges & 3D mapping
- Voiceprint analysis
- Deepfake probability scoring
Orchestrated Response Engine
SOAR-integrated automation for tiered responses, from silent monitoring to full blocks, with human-in-the-loop for edge cases and post-event simulations to refine playbooks.
- Playbook orchestration
- Multi-channel notifications
- Simulation & backtesting
Why Mastropay Technology for Fraud Detection?
Powered by a team of 50+ certified fraud analysts and ML engineers with experience at leading payment processors, we deliver solutions that have prevented â‚ą2B+ in losses. Our commitment to explainable AI and seamless integration sets us apart, turning fraud prevention into a value driver for your business.
Proven Efficacy
Deployed in 100+ live environments, our systems block 98% of fraud attempts at source, with adaptive learning that outperforms static rules by 3x in dynamic threat landscapes.
Seamless Scalability
Cloud-native architecture handles petabyte-scale data with auto-scaling, ensuring sub-millisecond latencies even during peak fraud waves like holiday shopping surges.
Regulatory Alignment
Embedded compliance controls for PCI 4.0, SCA, and AI ethics guidelines, with audit-ready logs that streamline certifications and reduce legal exposure.
Intuitive UI/UX Design That Enhances Detection
Tailored for fraud management consoles, our UI/UX packages focus on visual analytics, workflow efficiency, and role-specific dashboards to empower teams without overwhelming complexity.
Starter UI/UX
Basic alert interfaces
- 5 screen wireframes
- Simple mockups
- 2 revisions
- Advanced dashboards
Business UI/UX
Workflow dashboards
- 15 interactive screens
- Prototypes & testing
- 5 user sessions
- Basic design system
Enterprise UI/UX
Full ecosystem design
- Unlimited screens
- Advanced prototypes
- Extensive testing
- Custom design system
All packages include Figma prototypes, accessibility compliance, and 45 days support. Retainers provide iterative updates for evolving fraud interfaces.
Request UI/UX ProposalPrepared to Neutralize Fraud Risks?
Join forces with Mastropay Technology to deploy fraud detection that anticipates and defeats threats. Begin with a complimentary risk assessment to map your vulnerabilities and chart a secure course forward.
Mastropay Technology | Detecting Fraud, Protecting Futures