Segment Challenges
PSPs and PayFacs process millions of transactions daily against fraud patterns that continuously evolve - outpacing rules-based detection models that require manual tuning to stay current.
Merchant risk does not end at onboarding. PSPs and PayFacs must monitor merchant behaviour continuously - across transaction patterns, chargeback rates, and payout activity - throughout the full merchant lifecycle.
Overly aggressive fraud controls generate false positives that decline legitimate transactions - directly impacting approval rates, merchant satisfaction, and revenue for PSPs and PayFacs operating on thin margins.
Fraud scoring, merchant risk management, device intelligence, and investigation tools typically operate as separate systems - creating integration overhead, data gaps, and operational inefficiency across risk teams. As payment scheme fraud liability requirements and PCI DSS v4.0 obligations raise the bar for risk infrastructure, fragmented tooling creates increasing exposure.
When fraud alerts require manual triage and context gathering before investigation can begin, response times extend - allowing fraud to continue while analysts work to assemble the picture needed to act.
Cross-border transaction flows and multi-merchant fraud rings create risk patterns that span jurisdictions, payment rails, and institution types - requiring connected intelligence across accounts, merchants, and transaction networks that individual-event monitoring cannot provide.
Why Legacy Fails
Point-in-time transaction scoring cannot see coordinated fraud networks operating across merchants, devices, and accounts. Organised fraud rings deliberately structure activity to stay below individual transaction thresholds - invisible to event-level models.
Merchant risk management and transaction fraud tools operate in separate systems with separate teams - preventing the cross-domain analysis that reveals when merchant-level risk patterns connect to individual transaction fraud.
Device intelligence, behavioural signals, transaction data, and merchant attributes are rarely connected into a shared intelligence layer - leaving cross-signal patterns that indicate coordinated fraud undetected across the stack.
As transaction volumes grow, alert volumes grow proportionally - and traditional stacks respond by adding analyst headcount rather than improving the intelligence that would reduce alert noise and accelerate investigation.
How Verafye Fits
Verafye connects merchant, transaction, device, and behavioural signals into a single intelligence layer - delivering graph-based detection and investigation-centric workflows that cover the full merchant lifecycle without adding operational overhead.
Verafye unifies merchant risk signals, transaction data, device intelligence, and behavioural patterns into one connected layer - enabling cross-domain detection that individual point solutions cannot provide.
A graph-native intelligence layer connects entities across merchants, devices, accounts, and transactions - surfacing coordinated fraud rings, card testing networks, and synthetic merchant schemes that transaction-level scoring misses.
See Graph IntelligenceFraud alerts are clustered and enriched with relationship context before reaching the analyst - reducing manual context gathering, accelerating triage, and enabling faster, higher-confidence decisions across the risk operations team.
See Investigation IntelligenceVerafye supports merchant risk management across the full lifecycle - from onboarding and KYB through ongoing transaction monitoring to payout risk assessment - providing continuous connected intelligence aligned with evolving regulatory expectations, including the fraud prevention and documentation requirements that payment scheme rules and PCI DSS v4.0 increasingly demand.
Relevant Capabilities
Bring together payment, merchant, sub-merchant, user, counterparty, fraud, and AML signals in one investigation layer.
View PlatformGroup related alerts and activities across programs, merchants, entities, and payment flows.
Explore Investigation IntelligenceReveal hidden links across merchants, devices, accounts, transactions, counterparties, and suspicious networks.
Explore Graph IntelligenceHelp teams prioritize cases, review evidence, record decisions, and maintain audit-ready investigation trails.
Explore Investigation IntelligenceBusiness Impact
Graph-native detection surfaces coordinated fraud networks, card testing rings, and synthetic merchant schemes that transaction-level models miss - improving detection coverage without increasing false positive rates.
Smarter risk scoring grounded in network context and cross-system signals reduces false positive rates - improving approval rates, protecting merchant revenue, and reducing friction for legitimate customers.
Pre-assembled case context and alert clustering reduce the time from fraud alert to analyst decision - enabling faster account action, dispute resolution, and merchant intervention across the risk operations team.
Connected intelligence and structured investigation workflows reduce the manual effort per case - enabling risk operations teams to manage growing transaction volumes without proportional growth in analyst headcount.
Continuous merchant monitoring connected to transaction and network intelligence gives PSPs and PayFacs a complete, real-time picture of merchant risk - enabling proactive intervention before exposure escalates.
A unified intelligence layer connecting merchant profiles, transaction signals, and account behaviour gives risk operations a complete, real-time picture of exposure - enabling more informed decisions on merchant intervention, account action, and escalation across the PSP and PayFac risk stack.
See how Verafye helps PSPs, PayFacs, MSBs, processors, and fintechs investigate faster with connected risk intelligence.
No commitment required. Speak directly with our solutions team.
