Fraud Management for Financial Services

Stop application and transaction fraud, account takeover, money laundering, and more, before they result in financial and reputational damage.

Request Demo

Advanced Capabilities, Outstanding Performance.

Achieve quick and quantifiable ROI with easy-to-integrate, highly scalable fraud solutions. Deploy advanced fraud models informed by deep domain expertise, and receive actionable fraud signals in real time, without the need of labels, large data sets, or manual retuning. Go beyond simple anomaly detection to expose and deter known and unknown attacks.

Request Demo
Image for Data-Driven Insights
Data-Driven Insights

Process structured and unstructured data with feature engineering to identify common fraud patterns and correlations.

Image for Real-Time Production Readiness
Real-Time Production Readiness

Deploy machine learning models to directly operate on production data. Detect new fraud attacks with no need for labels or historic data.

Image for Minimal Training and Retuning
Minimal Training and Retuning

Benefit from consistent model performance over time, and bypass the need for extensive training and frequent retuning.

Product Suite

to manage the complete risk cycle

Total Control and Transparency

Prevent known and unknown fraud with the comprehensive fraud management platform that combines advanced unsupervised machine learning algorithms with an enterprise workflow to give full control to your fraud and data science teams. Build and deploy high-performance models to proactively defeat known and unknown fraud with speed and agility.

Real-Time Fraud Detection

Protect your organization with a robust fraud detection solution that combines adaptive machine learning technology and powerful investigative workflows to deliver real-time fraud signals. Rely with confidence on holistic data analysis and accurate risk scores to proactively detect and defuse emerging fraud attacks.

Client Success Stories

Application Fraud Case Study with Leading U.S. Card Issuer

DataVisor partnered with a top U.S. credit card issuer to deliver a scalable solution to fight application fraud.

Learn More

Fighting Fraud with Machine Learning: Stories from the Frontline

5 stories. 5 victories against fraud. See how organizations across industries are proactively defeating attacks.

Learn More

Top Financial Institution Uses DataVisor UML Solution to Fight Fraudulent Transactions

Learn how financial institutions are successfully saving millions in the fight against fraud.

Learn More


Intelligent solutions. Informed decisions. Unrivaled results.

Keeping Up with Fraud in Digital Banking

Learn More

Discover advanced strategies for managing the rapidly-evolving fraud attacks plaguing the modern banking sector.

Innovation is a hallmark of modern finance, and as banking expands online, organizations face intense pressure to defend against massive and rapidly-evolving attacks, while simultaneously preserving frictionless customers experiences, and meeting regulatory requirements. Discover the AI-powered…

DataVisor Fraud Index Report: Q1 2019

Learn More

Access proprietary data and research results to discover the latest attack techniques and prevention strategies.

Download the Q1 2019 Fraud Index Report from DataVisor to receive unparalleled data-driven insights into the latest attack trends, and the most effective prevention strategies, based on analysis of over 44 billion events, 800 million users, 396 million IP addresses, and more.

A Few Key Differences Between Supervised and Unsupervised Machine Learning

Learn More

An overview of how to choose between supervised and unsupervised ML.

In this guide, we will explain a few high level differences when it comes to choosing between supervised and unsupervised machine learning.

Protect your organization.

Request Demo