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.
Discover advanced strategies for managing the rapidly-evolving fraud attacks plaguing the modern banking sector.
Build and maintain trust by stopping fraud before reputational damage occurs.
Discover AI-powered fraud strategies for preventing financial and reputational damage in this powerful eBook.
Keep your platform safe and secure by purging spam and harmful posts.
DataVisor has partnered with Momo for more than two years to help them take on fraudulent account creations and compromised accounts.
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.
Delve deep into proprietary research to ensure your organization stays ahead of malicious threats.
Access proprietary data and research results to discover the latest attack techniques and prevention strategies.
Learn from leading experts in the fields of AI, machine learning, and fraud prevention as they provide rich insights on fraud trends and solutions.
Understand the range of modern fraud attacks to ensure complete coverage for your organization.
Prevent malicious transactions conducted by new fake accounts or compromised existing accounts.
Block scripted bots from performing blunt force login attempts using hacked credentials.
Accurately and quickly detect the massive-scale use of bots to hijack legitimate accounts.
By holistically analyzing profile information, cross-account linkages, behavioral data, and digital footprints such as device IDs, datacenter IP subnets, email addresses, and browsers, DataVisor’s fraud solutions are able to capture significantly more fraud than less sophisticated systems, resulting in significant reductions in fraud losses.
By combining the adaptive power of proprietary unsupervised machine learning algorithms with aggregated intelligence from DataVisor’s Global Intelligence Network, organizations can achieve high detection accuracy and low false positive rates at scale, ensuring frictionless experiences for good customers.
DataVisor’s fraud solutions can identify clusters of linked accounts and group them by fraud pattern. Analysts then need only to review a handful of sample cases before confidently applying bulk decisions to all applications within a single fraud ring.
Learn how Yelp stops fake users with DataVisor’s fraud solutions, and connects real users with great businesses.
DataVisor helped protect a large, mobile P2P Marketplace from fraud and abuse using Unsupervised Machine Learning.
As malicious bot attacks become more sophisticated, one airline is fighting back.
Organizations across industries are preserving online trust and defeating fraud with advanced machine learning solutions from DataVisor. This collection of case studies shows how clients in e-commerce, social, and financial services are defending their platforms against reputational and financial…
Discover how your organization can benefit from BBVA’s unconventionally successful approach to fraud management.
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.
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