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Introducing Arva Research: building the models that move banking's highest-risk decisions beyond human-in-the-loop

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Introducing Arva Research: building the models that move banking's highest-risk decisions beyond human-in-the-loop

Book a demo

Introducing Arva Research: building the models that move banking's highest-risk decisions beyond human-in-the-loop

Book a demo

AI you can trust — built with regulators in mind

Arva combines enterprise-grade security with rigorous AI governance—so every recommendation is tested, explainable, auditable, and ready for regulated financial institutions.

Trusted BY LEADING
regulated institutions

Trusts

Trusted by authorities worldwide

Arva AI meets rigorous standards set by leading regulatory bodies including FATF, FCA, MAS, OFAC, OCC, AUSTRAC and more. Our commitment to transparency and security enables institutions to scale with confidence.

Benchmarking

Robust benchmarking to measure AI performance

In high-stakes domains like AML, responsible AI deployment is not optional—it’s foundational. Arva has built its platform from the ground up to embed rigorous controls and auditability into every AI-powered decision. Here's how we ensure safe, transparent, and reliable AI operations:

Strict AI model risk governance

Every agent is evaluated before deployment using benchmark-based validation, documented testing, and version-controlled releases aligned to each institution’s risk standards.

Strict AI model risk governance

Every agent is evaluated before deployment using benchmark-based validation, documented testing, and version-controlled releases aligned to each institution’s risk standards.

Transparency & explainability

All AI-generated verdicts come with clear, traceable rationale. Analysts can see exactly why a decision was made, including contributing sources, relevance scoring, and narrative cues. This ensures auditability and supports regulatory defensibility.

Transparency & explainability

Human-in-the-loop controls

Arva maintains robust human oversight through analyst-in-the-loop workflows. Analysts can override or adjust AI recommendations, and every override feeds back into the model's learning cycle. No critical compliance decisions are made without human review where ambiguity exists.

Human-in-the-loop controls

Conservative decision-making philosophy

Arva’s AI errs on the side of caution. In cases where the signal is weak, ambiguous, or multi-interpretable, the system flags the case for manual review with an “AI Recommended Verdict,” rather than making an autonomous decision.

Conservative decision-making philosophy

Multi-source validation

Arva validates risk and relevance across multiple independent sources to reduce false positives and avoid conclusions based on unreliable data.

Multi-source validation

Arva validates risk and relevance across multiple independent sources to reduce false positives and avoid conclusions based on unreliable data.

Continuous monitoring & improvement

Performance is monitored against curated datasets so drift is caught early and analyst feedback continuously strengthens model quality.

Continuous monitoring & improvement

Performance is monitored against curated datasets so drift is caught early and analyst feedback continuously strengthens model quality.

Our promise

SOC2 Type II Certified

Ensures secure, available, and confidential handling of customer data across systems.

Our promise

ISO42001 Compliant (AI Standards)

Aligns with international standards for safe, transparent, and responsible AI governance.

Our promise

Built for Compliance

All systems are designed with strict regulatory frameworks in mind.

Our promise

Transparent audit trails

Every result is logged and traceable, making compliance reviews faster and easier.

Visit the Trust Centre

"Our CDD and EDD processes are powered by Arva, the quality of analysis across entity type, ownership and business activities is consistently high, and our team is onboarding clients considerably faster than before."

Marvin Hurlston

Senior Director Client Onboarding & TM