The Challenge

A Tier-1 US bank with a global footprint was facing escalating pressure across its financial crime operations. Rapid growth in customer volumes, expanding regulatory expectations, and increasingly complex sanctions and adverse media requirements had driven a surge in screening alerts—the vast majority of which were false positives.

Despite a well-resourced compliance function, the bank’s sanctions and adverse media teams were spending thousands of analyst hours each month manually reviewing low-risk alerts. This created several compounding challenges:

• Operational strain: Highly skilled analysts were tied up with repetitive, low-value reviews instead of focusing on genuinely high-risk investigations.

• Rising costs: Alert volumes continued to grow year-over-year, driving headcount expansion without corresponding gains in effectiveness.

• Scalability limits: Existing rules-based systems and vendor tools lacked the intelligence needed to materially reduce false positives without lengthy tuning cycles.

• Technology constraints: Traditional solutions required complex integrations, multi-month implementations, and heavy internal engineering involvement—posing delivery and change-management risk in a tightly controlled environment.

The bank needed a solution that could deliver immediate impact, integrate safely into an enterprise compliance stack, and stand up to regulatory and model-risk scrutiny—without adding further operational burden.

The Solution

The bank deployed Arva AI to automate sanctions, PEP, and adverse media alert review across multiple screening workflows.

A key differentiator was Arva’s single-click deployment, enabling the bank to integrate Arva alongside existing screening systems with no custom engineering work and minimal operational disruption.

Once live, Arva’s AI agents began performing end-to-end alert investigations in line with senior-analyst decisioning:

• Automatically gathering and contextualising data from internal systems and external intelligence sources

• Assessing name matches, entity relationships, geographic risk, and adverse media relevance

• Producing clear, auditable rationales for alert disposition

• Confidently resolving low-risk false positives while escalating only genuinely high-risk cases to human reviewers

Unlike legacy automation tools, Arva did not rely on static rules or keyword suppression. Instead, its agents continuously learned from outcomes, enabling progressive accuracy improvements over time—without requiring ongoing tuning by the bank’s teams.

Crucially, the platform was designed with enterprise governance and auditability in mind, supporting internal model risk management, compliance oversight, and regulatory examination requirements.

The Results

The impact was immediate, measurable, and sustained:

84% Reduction in False Positives
Within weeks of deployment, the bank reduced sanctions and adverse media false positives by 84%, with performance continuing to improve as the system learned from additional alerts.

5× Increase in Operational Capacity
By automating the majority of low-risk alert reviews, the bank effectively multiplied the capacity of its compliance team—allowing existing staff to handle significantly higher volumes without additional headcount.

Material Cost Reduction
Automation of manual reviews delivered substantial Opex savings while improving consistency and decision quality across alert handling.

Zero Engineering or Change-Management Burden
Deployment required no internal engineering resources and no re-architecture of existing screening infrastructure—dramatically reducing implementation risk compared to traditional solutions.

Regulatory-Ready Automation
Every automated decision was supported by clear, human-readable reasoning, enabling transparent audit trails and confident regulatory engagement.

From Experimentation to Enterprise-Grade ROI

For this Tier-1 US bank, Arva AI proved that AI-driven financial crime automation is no longer experimental or aspirational—it is production-ready, auditable, and delivering real ROI at scale.

By removing manual drag from sanctions and adverse media screening, the bank unlocked a more resilient, scalable, and future-proof compliance operating model—one where human expertise is reserved for the risks that truly matter.