Arva AI: Power Your Financial Crime Compliance with an Enterprise AI Workforce

What Arva AI Does

Arva AI streamlines manual financial crime operations at banks and fintechs with AI agents that handle document intelligence, online presence analysis, customer communication, and false positive alert reduction. Arva cuts review times by 80%, whilst strengthening compliance controls. We’re backed by Google AI and YC, and already work with top banks in the US and UK.

The Current Landscape of Financial Crime Compliance and Arva AI's Role

The financial crime compliance landscape is undergoing rapid change, yet many institutions remain weighed down by outdated approaches. Areas such as anti-money laundering (AML) checks and screening, customer onboarding, and transaction monitoring are still dominated by heavily manual processes. Banks, fintechs, and regulated businesses typically rely on large teams of human analysts who sift through alerts, documents, and news sources to make sense of potential risks.

Despite advancements in technology, the day-to-day reality inside many compliance departments still looks like this: analysts managing hundreds of cases simultaneously, copying and pasting data between spreadsheets, and manually reviewing adverse media hits or transaction anomalies. These old-school processes are slow, error-prone, and resource-intensive—making it increasingly difficult for financial institutions to scale effectively, adapt to evolving regulatory expectations, or respond to emerging threats.

At the same time, regulators continue to tighten scrutiny, issuing heavy penalties for non-compliance and demanding greater transparency around risk decisioning. The costs of failure are high—not just in fines, but also in reputational damage and loss of customer trust.

In this environment, a growing ecosystem of competitors and vendors has emerged. Some established players focus on data provision (e.g., sanctions lists, adverse media databases, corporate registries). Others offer transaction monitoring platforms or identity verification tools. However, most solutions remain siloed and still depend on large amounts of manual effort from compliance teams to interpret alerts, connect the dots across fragmented systems, and decide whether a risk is real or not.

The Arva AI Birth Story

Arva was born out of a pretty simple frustration: fighting financial crime is one of the most important problems in the world, but the tools that exist to do it are painfully outdated. Compliance teams today are drowning in manual work, juggling spreadsheets, PDFs, and endless alerts that rarely tell the full story. We knew there had to be a smarter way.

Our founding team comes from both sides of the problem: financial crime and cutting-edge machine learning. Rhim Shah, who previously led the Financial Crime product team at Revolut Business and earlier built multiple product teams at Jobandtalent, saw firsthand how compliance teams were stuck using slow, rigid systems while criminals kept getting more sophisticated. Oli Wales, who led product engineering at Opvia and before that worked at Iventis, Chimnie, and The Trade Desk, had been building scalable data platforms and knew how modern AI could transform messy, high-volume information into actionable intelligence.

We started Arva at Y Combinator, with the idea of reimagining compliance from the ground up. Instead of building “just another workflow tool” or a slightly faster version of the same old screening software, we wanted to create a system that actually thinks with you—bringing speed, context, and intelligence to resolving financial crime reviews.

That vision resonated. Arva is backed by Google’s AI startup fund as our lead investor, alongside some of the best operators and builders in the fintech and AI ecosystem. Today, we’re building the next generation of financial crime tools—ones that let compliance teams go faster, go deeper, and focus on the decisions that really matter.

The Arva AI Solution

Financial crime compliance is one of the most pressing challenges facing banks, fintechs, and trading platforms today. Burdened by expanding global regulations, massive volumes of alerts, and a reliance on large teams of analysts, traditional approaches are slow, reactive, and costly. Arva AI was founded to change that.

At its core, Arva is building an Agent OS — an enterprise-grade platform designed to power an AI workforce that can take on the heavy lifting of compliance. Instead of building one-off tools, Arva has created a modular system of intelligent agents that can be deployed across the compliance lifecycle, from screening sanctions and politically exposed persons (PEPs), to automating KYB/KYC reviews, to handling transaction monitoring alerts. These agents are powered by Arva Intel, the company’s deep web intelligence layer that crawls, categorises, and enriches entity data across 150 countries, enabling richer context and sharper decisioning.

What makes Arva stand out is its governance-first design. Every agent is built with explainability, auditability, and regulatory trust at its core. Compliance teams don’t just get automation — they get automation they can defend to regulators. The platform includes transparent audit trails, model benchmarking, drift detection, and human-in-the-loop oversight to ensure decisions are not only fast but also accountable. With SOC 2 Type II certification and alignment with ISO 42001 (AI governance), GDPR, and UK FCA/PRA guidance, Arva has made security and compliance a first-class product feature rather than an afterthought.

The results speak for themselves. Arva’s agents now automate 80–92% of manual casework, depending on the task. Screening AI alone is capable of resolving the vast majority of alerts across sanctions, adverse media, and PEP checks. KYB/KYC AI has been shown to untangle ownership structures up to fifteen layers deep and resolve nearly 90% of due diligence cases without human escalation. Transaction Monitoring AI automates over 85% of alerts while still integrating with internal systems to preserve context. In practice, this has enabled banks and fintechs to cut compliance workloads dramatically, speed up onboarding by orders of magnitude, and deliver measurable improvements like a 21% increase in straight-through processing.

Backed by Google’s Gradient AI fund, Y Combinator, and a roster of leading fintech investors, Arva has already gained traction with top-tier financial institutions in the UK and US. The company processes tens of thousands of reviews each month and is quickly establishing itself as the go-to AI partner for compliance leaders who need scale without bloat.

“We’re on the forefront of advanced AI models for financial crime compliance, building agentic systems that don’t just surface alerts but actually help resolve them. Our vision is to give compliance teams superpowers—speed, accuracy, and explainability - so they can focus on judgment and strategy rather than manual grunt work.” - Rhim Shah, Co-founder of Arva AI

A Customer Story with Arva AI

Earlier this summer, a U.S.-based fintech using Arva began onboarding what appeared to be a straightforward new customer — a design services business incorporated in Florida. On paper, everything looked legitimate. The business had an active LLC registration, a matching legal name and address, and no flags from standard incorporation, sanctions, or ownership checks. Initial risk ratings came back as low across the board.

But something didn’t sit right.

A member of the compliance team, using Arva during routine onboarding review, decided to dig deeper. Within moments, Arva’s platform uncovered multiple red flags that would have been easy to miss in a traditional manual review.

First, Arva’s web presence analysis flagged the company’s website as suspicious. Although a landing page existed, it showed no real traffic or activity. There were no indicators of a functioning business—no team bios, no client logos, no service details beyond boilerplate buzzwords.

Next came a more serious issue. Arva’s adverse media engine identified that multiple individuals listed as officers of the company had been linked to prior scam-related activity. The platform didn’t just surface generic mentions—it accurately classified the results and surfaced the “Scam” tag, helping the reviewer distinguish signal from noise instantly.

Finally, when verifying the operating address, Arva noted that no proof had been submitted—no utility bill, no bank statement. This triggered an automated request for further documentation before the onboarding process could continue.

The compliance reviewer escalated the case internally and, using Arva’s audit logs and documentation trail, was able to block the business from being onboarded — all in under 10 minutes. A quick cross-check with another internal tool validated the same concerns. Without Arva, this application may well have slipped through, exposing the fintech to potential fraud and downstream risk.

The reviewer later shared: “At first glance, this looked like a clean case. But Arva surfaced all the deeper issues within moments — scam tags, weak web footprint, lack of address proof. We confirmed it with another tool, but Arva got us there first. Honestly, without it, this could’ve been a problem.”

This customer story is a clear reminder that in today’s complex risk landscape, a superficial “low-risk” score doesn’t always tell the full story. It’s the contextual signals — the media mentions, the website intelligence, the documentation gaps — that often reveal the truth.

The Team Culture at Arva AI

At Arva AI, there’s a palpable sense that speed and ownership isn’t just encouraged—it’s a core superpower. Team members are urged to act decisively, favouring momentum over perfection. At this early stage, the company values getting your hands dirty, experimenting, iterating fast, and taking full responsibility for outcomes.

This high‑octane drive is balanced by a deeply held belief in customer first, team second, self last. It’s a culture that prizes collective success: the team focuses relentlessly on delivering value to customers, often placing individual priorities behind broader team goals. The notion of shared responsibility and mutual accountability underpins how day‑to‑day work gets done.

Underpinning both agility and alignment is a commitment to radical transparency. At Arva AI, openness flows through all levels—decisions, wins, and missteps alike are shared openly. This ethos builds trust, enhances collaboration, and creates a feedback‑rich environment where everyone grows together.

What this all adds up to is a culture of purpose-driven urgency—a team united by a mission to transform financial crime compliance with AI, backed by deep expertise in anti‑fraud, machine learning, and product design. The result is a nimble, customer-obsessed environment where growth is social, rapid, and shared.

Find out more about Arva AI:www.arva.ai