Screening, monitoring, risk scoring and case management that pull from the same data
Plus Salv Bridge, for cases that involve another bank.
Trusted by 130+ financial institutions across 30 jurisdictions
Four tools and a network from Salv, for fraud and AML teams at banks and fintechs. Because Screening, Monitoring, Risk scoring and Cases all read each other, what one finds changes what the others do: a confirmed screening match moves a customer's risk score, and a higher score tightens the scenarios they fall under. For cases that need another bank, Salv Bridge connects financial crime teams into a network.
Salv tools that work together
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ScreeningScreen customers and payments against sanctions, PEP and adverse-media lists, with matching you configure and lists Salv keeps current.
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MonitoringScenarios you can read, test on your own data and change yourself. Watch payments, customers and counterparties, for AML and fraud.
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Risk scoringCustomer risk rating on weighted rules built around your framework. Kept current as the facts change, feeding the monitoring and screening that act on it.
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Intelligence sharingThe secure network where fraud, AML and sanctions teams settle a case directly with other institutions. Send structured requests, answered in minutes, under rules your network agrees.
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Alert and case managementWhen an investigation grows, it becomes a case. Bring the related alerts, customers and payments together and work it from one place as a team.
How the tools connect
Risk scoring is the hub. Screening and Monitoring feed what they find into Risk, and Risk sets how strict screening and monitoring should be for each customer. Screening also feeds Monitoring directly; Monitoring sends nothing back to Screening.
A scenario can read a payment's screening alerts before it decides, firing only when both coincide or only when screening is clear. It can also read screening tags, such as a PEP tag set on a confirmed match.
A confirmed PEP, sanctions or adverse-media match updates the customer's risk score.
A customer's alerts, and their outcomes, feed the risk score.
Risk level decides which screening flow a customer falls under and how they're re-screened.
Scenarios can use risk level and score, so a customer whose risk climbs falls under tighter scenarios without anyone moving them.
See it on your own data
Start from your challenge
- You can spot the fraud, but it moves faster than you can stop it. Salv covers account-to-account payments, instant payments and card payments, with experience across all three. Fraud overview
- Scams you can't stop fast enough Fraud, scam and mule detection with real-time payment blocking
- Detection you can't change yourself Configurable fraud detection and scenario building
- Cross-bank fraud cases take too long Joint investigations and stolen fund recovery
- Onboarding fraudsters other banks know Joint screening of new customers against a shared pool
- Too many alerts, a book growing faster than the team, and every decision to show the supervisor. AML overview
- Too many false positive alerts Screening and auto-clearance
- Thresholds and rules you can't tune easily Configurable AML rules, thresholds and segments
- Customer risk scores go stale between reviews Dynamic customer risk scoring
- AML screening and monitoring are often a step behind Real-time AML monitoring and screening
- Sanctions RFIs take too long Bank-to-bank sanctions clearance