DataVisor Will Reduce City National Bank's Fraud by 10%, or Your Money Back

You deserve a fraud solution that moves the needle. If DataVisor doesn’t lower your fraud by at least 10%, we’ll refund your POC.

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No risk, no long-term commitment, just results.

Trusted by Leading Fraud & AML Teams

How It Works

We support teams making smooth transitions from legacy platforms like Nice Actimize, helping you cut fraud losses, reduce false losses, and boost operational efficiency. Our experience with FIS migrations means we support your team with clarity and confidence from day one.

STEP 1

Tell Us Your Goals and Challenges

Share your use cases, key challenges, and current performance baseline. Our experts will recommend a modeling approach calibrated to your success.

STEP 2

AccountShare Your Sample Data  Takeovers

Share your internal and third-party datasets. We’ll validate, cleanse, and normalize fields as needed. We’ll also recommend additional data points to improve detection and precision.

STEP 3

We Develop and Optimize Your Models

Our experts will engineer models using your data and success criteria. Throughout the process, we’ll share with you our key findings and notable patterns.

STEP 4

Review Final POC Results and Go Live

We evaluate the POC outcomes with you, validate performance uplift, and initiate the go-live transition.

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Why Choose DataVisor

AI for Features and Rules

AI for Features and Rules uses artificial intelligence to automatically analyze data, detect patterns, and generate the most relevant features and rules for decision-making. Instead of manually defining conditions, the system learns from historical and real-time data to create smarter logic that improves accuracy and efficiency. This helps teams respond faster, reduce manual work, and make more consistent, data-driven decisions.

Layered AI Approach

Our layered AI approach layers three AI defenses into one unified fraud detection strategy. It combines:
• Clarity of rules
• Pattern-finding strength of unsupervised machine learning (UML)
• Precision of supervised machine learning (SML)

Knowledge Graph

Knowledge Graph connects information from different sources and organizes it into a structured network, making relationships between data easy to understand. It helps users see how people, processes, events, and insights are linked, allowing faster and more accurate decision-making. By visualizing connections instead of isolated data points, the Knowledge Graph turns complex information into a clear, searchable, and intelligent map.

Interactive Review Checklist

Interactive Review Checklist streamlines and standardizes the investigation process for fraud and AML teams. It provides a step-by-step, AI-guided checklist that adapts to each case, ensuring investigations are consistently thorough and fully auditable.

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How We Helped Fraud Leaders in Leading Financial Institutions

DataVisor 🤝 NASA Federal Credit Union

DataVisor 🤝 Galileo

DataVisor 🤝 ONE

DataVisor 🤝 Beem Credit Union

Awards & Recognition

Unrivaled in Fraud & Risk Solutions

Thanks to our visionary customers, partners, and relentless team, together we’re turning bold ideas and innovation into real-world results and lasting impact—and earning some extraordinary recognition along the way.