Banking

Clear KYB remediation backlogs and stay audit-ready

Strise resolves fragmented AML data into a single, trusted customer record for onboarding, remediation, and monitoring.

Fragmented data

One AML source of truth across legacy systems

Data lives across systems, registries, and documents. Analysts reconcile records by hand, remediation backlogs grow, and material risk changes get missed. Strise unifies internal records, live registries, and screening into one governed customer record

Reduce false positives

Up to 40% fewer false positives

Remediation backlogs grow because low-risk cases still require manual review. Strise applies policy-driven, AI-assisted risk scoring to auto-clear low-risk cases and route only true exceptions to analysts.

Monitoring

Move from point-in-time reviews

Periodic reviews create blind spots. Ownership, sanctions exposure, and company status change between cycles. Strise monitors registries and risk signals continuously. When a material change occurs, alerts trigger immediately and route into your existing workflows.

Why Strise?

No rip andreplace for IT teams

Strise sits between CLMs and internal systems, integrating via API

Clear low-risk KYBcases automatically

Low-risk clients clear automatically. Manual effort focuses on exceptions

Audit-readyby design

Every data point, change, and decision is traceable to its original source

#1 choice for leading regulated businesses

Success stories
How fintech giant Vipps MobilePay made AML Automation a winning strategy
How Sparebanken Vest cuts manual AML data sourcing and speeds up case handling
How BN Bank reduces false positives by 30% and speeds up onboarding by 70%
How SpareBank 1 gets full client insight: pre-linked, analyst-ready data

Goodbye, backlogs
Hello, AML automation

Banks are moving from manual remediation cycles to continuous, event-driven AML. Backlogs shrink, low-risk cases clear automatically, and teams stay audit-ready as data changes. AML becomes a controlled, scalable operation instead of a recurring remediation exercise.

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Fredrik Riiser