FraudCentral Industry
Industry-specific fraud detection powered by AI, behavioural analytics, and real-time intelligence.
Banking
Vericent's FraudCentral is an AI-powered fraud detection platform designed to enhance existing fraud prevention infrastructure across all transaction channels.
Comprehensive Transaction Monitoring
Real-time risk assessment across card payments, digital wallets, wire transfers, ATM withdrawals, and mobile banking, providing unified fraud detection across bank's entire transaction ecosystem.
Enhanced Real-Time Decisioning
Advanced behavioural analytics and pattern recognition that identifies suspicious activity before funds move, protecting customers across all transaction types and channels.
Cross-Channel Fraud Detection
Identifies coordinated fraud attacks across multiple channels, detecting when criminals test stolen credentials on one platform before executing larger frauds elsewhere, critical for protecting millions of digital banking customers.
Adaptive Learning Models
Machine learning that continuously evolves with new fraud tactics, combining rule-based detection with anomaly identification to catch novel attack patterns before they become widespread threats.
Key Capabilities
- Real-Time Behavioural Analytics: The system analyses device fingerprinting, session behaviour, transaction velocity, geolocation anomalies, and historical patterns to detect suspicious activity milliseconds before authorisation.
- Multi-Vector Risk Scoring: Combines supervised learning (known fraud patterns) with unsupervised learning (anomaly detection) to identify both familiar scams and emerging threats including synthetic identity fraud, account enumeration attacks, and credential stuffing.
- Seamless API Integration: The platform connects with core banking systems, NPP infrastructure, card networks, and mobile banking applications without disrupting customer experience or existing workflows, working alongside current fraud prevention technologies.
- Intelligent Alert Management: Machine learning prioritises alerts to reduce false positives by 60-70%, addressing the industry challenge where legitimate transactions are mistakenly blocked, frustrating customers and reducing revenue.
Strategic Benefits
- Accelerated Fraud Loss Reduction: Earlier detection of sophisticated fraud across all transaction channels can reduce fraud losses by an additional 15-25% beyond existing prevention measures.
- Operational Efficiency: Reduces manual review burden on fraud teams by 60-70%, allowing specialists to focus on high-risk cases while AI handles routine risk assessment.
- Enhanced Customer Experience: Minimises false declines that frustrate legitimate customers, preserving revenue and maintaining customer satisfaction.
- Competitive Differentiation: Positions institutions as innovation leaders in fraud prevention through comprehensive behavioural AI deployment.
- Regulatory Alignment: Enhanced monitoring and audit capabilities support compliance with evolving AML/CTF requirements and anticipated scam liability regulations.
Insurance
FraudCentral helps insurers detect fraudulent activity during policy underwriting and claims processing, uncover organised fraud networks, and validate policyholder, provider, and third-party behaviour across all insurance products including motor, home, health, life, and commercial lines.
Comprehensive Underwriting & Claims Monitoring
Analyses policy applications, KYC information, telematics inputs, historical claims data, supporting documents, and provider interactions to identify inconsistencies from the moment a policy is created through to claim settlement.
Real-Time Risk Assessment
Flags suspicious applications and claims by identifying behavioural deviations, abnormal timelines, inconsistent customer information, inflated estimates, and irregular provider patterns before policies are issued or payouts occur.
Cross-Entity and Cross-Policy Detection
Links policyholders, claimants, vehicles, addresses, repair shops, medical providers, and past claim histories to expose staged accidents, recycled claims, ghost policies, and organised fraud rings spanning multiple insurers.
Adaptive Fraud Models
Continuously learns from emerging fraud behaviours such as manipulated telematics data, synthetic identities, overstated losses, identity-misuse in health claims, and cross-insurer claim recycling.
Key Capabilities
- Underwriting Fraud Detection: Detects fabricated identities, false disclosures, manipulated documents, inconsistent risk information, ghost broking activity, and policy shopping behaviour used to obtain unfair premium advantages.
- Behavioural & Pattern Analytics: Identifies inflated claims, duplicate submissions, excessive repair estimates, suspicious medical billing, unusual accident conditions, and mismatches between reported damage and historical behaviour.
- Entity Linking & Network Analysis: Combines multi-entity relationships across policyholders, providers, vehicles, addresses, and historical claims to uncover fraud rings and high-risk networks across insurers.
- API-Based Integration: Integrates seamlessly with policy admin systems, claims platforms, underwriting engines, telematics devices, loss-adjuster tools, medical billing systems, and third-party assessors.
- Intelligent Alert Prioritisation: Ranks risk signals based on fraud probability to reduce manual review workload, helping investigators focus on high-impact cases while minimising false positives.
Strategic Benefits
- • Reduced underwriting risk, claims leakage, and payout losses
- • Improved accuracy and efficiency in underwriting decisions
- • Faster processing times for genuine policyholders
- • Enhanced fraud investigations and defensible audit trails
- • Stronger compliance with insurance regulatory requirements
Telecommunications
FraudCentral safeguards telecom operators by detecting high-frequency, multi-channel fraud across SIM lifecycle events, billing systems, mobile networks, and digital self-service portals.
End-to-End Subscriber Monitoring
Monitors SIM activations, port-out requests, prepaid top-ups, roaming activities, device changes, and billing anomalies to detect unusual behaviour across the subscriber lifecycle.
Real-Time Telecom Decisioning
Identifies suspicious call sequences, sudden data spikes, premium-rate fraud, subscription misuse, and high-risk account interactions before revenue is lost.
Cross-Channel Telecom Fraud Detection
Links risk patterns across OSS/BSS systems, KYC onboarding, mobile apps, digital wallets, customer support channels, and billing events to stop coordinated fraud networks.
Adaptive Models for Telecom Fraud
Learns patterns of SIM-swap attacks, identity misuse, fake documentation, IMSI/IMEI fraud, and digital service abuse, enabling rapid mitigation of emerging risks.
Key Capabilities
- Network Behavioural Analytics: Flags anomalies in call, SMS, and data usage; identifies abnormal roaming; detects suspicious device or SIM activity.
- Identity & Usage Scoring: Combines device fingerprinting, KYC risk scores, location mismatches, and velocity patterns.
- Seamless Telecom Stack Integration: Works across provisioning systems, CRM, billing engines, top-up platforms, and mobility apps.
- AI-Driven Alert Prioritisation: Reduces noise for fraud operations teams by focusing on high-risk activities.
Strategic Benefits
- • Reduced subscription fraud, SIM fraud, and port-out attacks
- • Lower revenue leakage across prepaid and postpaid services
- • Improved detection of account takeover and device-level fraud
- • Reduced chargebacks for carrier billing
- • Stronger adherence to telecom security and consumer regulations
Retail
Vericent’s FraudCentral strengthens fraud prevention across modern retail ecosystems by delivering real-time risk intelligence across both in-store and digital channels.
Comprehensive Retail Fraud Monitoring
Tracks and assesses activity across POS systems, loyalty programs, returns, refunds, gift card activations, and e-commerce checkouts to detect suspicious transactions across the entire retail environment.
Real-Time Behavioural Decisioning
Analyses device behaviour, purchase patterns, return velocity, and irregular transaction sequences to identify fraudulent activity before orders are completed or refunds are processed.
Cross-Channel Fraud Detection
Links signals across physical stores, e-commerce sites, mobile apps, loyalty platforms, and customer service interactions to reveal coordinated abuse patterns early.
Adaptive Learning Models
Learns evolving retail fraud patterns, from serial return fraud and coupon abuse to gift-card draining, ensuring protection during peak sale periods and promotional campaigns.
Key Capabilities
- Behavioural Analytics: Detects abnormal shopping behaviour, suspicious return timing, device spoofing, and loyalty manipulation.
- Multi-Vector Risk Scoring: Identifies synthetic customers, bot-driven checkouts, and repeat abuse patterns using combined rule-based and anomaly detection models.
- Seamless Integration: Works with POS, ERP, OMS, CRM, and e-commerce platforms without slowing checkout or fulfilment.
- Intelligent Alert Management: Reduces false positives to protect customer experience while escalating high-risk retail fraud incidents.
Strategic Benefits
- • Reduced retail shrinkage and fraudulent returns
- • Lower chargebacks from payment fraud
- • Stronger customer trust and loyalty
- • Reduced operational load on fraud and store teams
- • Alignment with consumer protection and retail compliance standards
E-commerce
FraudCentral provides end-to-end protection for digital stores, online marketplaces, and D2C brands by securing user accounts, payments, order flows, and returns.
Full Customer Journey Monitoring
Observes browsing patterns, login attempts, cart activity, payment retries, shipping patterns, device behaviour, and fulfilment events to identify risk across the entire online journey.
Real-Time Payment Fraud Prevention
Detects card-not-present (CNP) fraud, velocity attacks, mismatched payment data, bot-driven checkouts, coupon-stacking, and compromised account behaviour before orders are placed.
Cross-Channel E-commerce Fraud Detection
Links signals across web, mobile apps, marketplaces, support tickets, return flows, and warehouse operations to identify coordinated abuse.
Adaptive E-commerce Fraud Models
Learns new fraud behaviours such as loyalty point theft, refund exploitation, promo misuse, account enumeration, and synthetic identity creation.
Key Capabilities
- Behavioural Analytics at Checkout: Uses device fingerprinting, IP risk scoring, behavioural biometrics, and transaction anomalies to detect fraud in milliseconds.
- Multi-Layer Risk Scoring: Spots synthetic accounts, repeat offenders, bot networks, and abnormal purchase/return patterns.
- Flexible Integration: Connects with payment gateways, order management systems, shipping APIs, and marketplace portals.
- Optimised Alert Handling: Reduces false declines, improving conversion without compromising security.
Strategic Benefits
- • Lower chargeback losses and CNP payment fraud
- • Increased approval rates and revenue protection
- • Reduced return/refund abuse and coupon manipulation
- • Frictionless shopping for genuine customers
- • Scalability during high-traffic sale events
Ready to Strengthen Your Fraud Defenses?
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