Leverage the power of unsupervised machine learning to defeat fraud with speed and agility.
dCube is the complete AI-powered fraud management solution that enables the proactive defeat of emerging fraud.
Get detailed fraud signals in real time, and take proactive steps to defeat both known and unknown fraud.
This is part one of a three-part blog post series highlighting some of the key things to look for when it comes to choosing a third-party fraud prevention solution. In this post, we go over topics such as multi-layer protection, target use cases, global reach and data, etc.
Stop application and transaction fraud, account takeover, money laundering, and more.
Learn how leading financial institutions are using ML to proactively detect card application fraud.
Build and maintain trust by stopping fraud before reputational damage occurs.
Every company is different, and every attack is different. When it comes to defeating fraud, success is determined organization by organization. From mass registrations and fake listings, to ATO and spam, to promo abuse and bot attacks,…
Keep your platform safe and secure by purging spam and harmful posts.
Understand the range of modern fraud attacks to ensure complete coverage for your organization.
Discover all the ways our clients are staying ahead of fraud by embracing AI-powered solutions that enable their organizations to know the unknown.
5 stories. 5 victories against fraud. See how organizations across industries are proactively defeating attacks.
Get experts insights on how to deploy cutting-edge fraud solutions to defeat even the most sophisticated modern attacks.
Discover advanced strategies for managing the rapidly-evolving fraud attacks plaguing the modern banking sector.
Delve deep into proprietary research to ensure your organization stays ahead of malicious threats.
Customers online want convenience, ease, and access. Fortunately, your business offers it all. Unfortunately, that’s what fraudsters want too. To a cyber criminal, those features means vulnerabilities. To bring you the very latest and most…
Learn from leading experts in the fields of AI, machine learning, and fraud prevention as they provide rich insights on fraud trends and solutions.
Draw on holistic data analysis to proactively detect malicious scripted logins from cloud IPs.
Put up defenses against attacks that come within two hours of registration.
Detect dormant accounts before they can be summoned for large-scale attacks.
Flag and disarm fraudulent accounts before damaging actions are taken.
Differentiate between legitimate and fraudulent accounts to protect good users.
Analyze user histories, behavior changes, and suspicious patterns to capture large-scale attacks.
DataVisor helped protect a large, mobile P2P Marketplace from fraud and abuse using Unsupervised Machine Learning.
A leading global social commerce platform with over 250 million monthly active users was losing the battle against ATO fraud. Attackers were taking over user accounts in bulk and spamming legitimate users. The brand’s reputation was…
Protect your marketplace from spam, fake reviews, and more, with comprehensive AI-powered fraud solutions.
In our digital era, online marketplaces must prioritize platform integrity, and embrace fraud management strategies that promote safety, security, and trust. Spam, fake reviews, promo abuse, mass registration, and more, work to undermine modern marketplaces, and these attack types can result in…
ThePaypers's annual report provides insightful perspectives from industry associations and leading market players on…
ThePaypers's annual report provides insightful perspectives from industry associations and leading market players on key aspects of the global ID, transactional, and web fraud detection space.
DataVisor CEO Yinglian Xie discusses her predictions for an active fraud ecosystem at online marketplaces and…
DataVisor CEO Yinglian Xie discusses her predictions for an active fraud ecosystem at online marketplaces and e-commerce sites during the 2018 Holiday Season with PYMNTS' Karen Webster in this podcast.
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