Get detailed, real-time fraud signals powered by machine learning, and take proactive steps to defeat even the most sophisticated fraud attacks.
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.
Get real-time protection for mobile and web applications by gathering extensive device information and accurately identifying manipulated devices.
Companies must make the leap successfully from the centralization of data to the centralization of intelligence.
Combine sophisticated out-of-box features and advanced AI and machine learning-enriched features to build powerful rulesets for comprehensive fraud detection.
Leveraging the power of machine learning to build intelligent solutions that empower organizations to proactively defend their businesses, their customers, and their data. There are many ways to understand AI and machine learning, and as…
Leverage the power of an end-to-end fraud modeling platform combining unparalleled control with enterprise capabilities.
dCube is the complete AI-powered fraud management solution that enables the proactive defeat of emerging fraud.
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.
Eliminate fraud losses and provide great experiences to loyal customers by proactively detecting and preventing promotion abuse, bot attacks, account takeover, and more.
Read this case study to learn how DataVisor detected hundreds of thousands of fake accounts with 99.5% accuracy.
Ensure platform safety, protect good customers, and reduce fraud losses.
When a top delivery services company that processes over 6 billion packages annually succumbs to mass registration attacks, it’s a complex problem that demands an advanced solution. Fortunately, using dVector from DataVisor, the company…
Prevent financial loss from fraudulent subscribers, protect against ATO, and stop spam and phishing attacks.
5 stories. 5 victories against fraud. See how organizations across industries are proactively defeating attacks.
Detect fraudulent claims and applications, spot collusion, and prevent dishonest agents from deceiving insurers.
First in a three-part series focusing on fraud modeling. The series covers pre-modeling, modeling, and post-modeling.
Uncover and block fraudulent reservations in real time, prevent losses from loyalty program fraud, and protect good customers.
As malicious bot attacks become more sophisticated, one airline is fighting back.
Leverage proprietary unsupervised machine learning technologies to proactively detect fast-changing attack patterns and capture entire fraud rings before financial loss occurs
Detect transaction fraud in real time to prevent financial loss, and allow legitimate transactions to go through with no friction.
Enhance detection and fluidly adapt to new and evolving money-laundering tactics. Maintain compliance with full transparency and explainable results.
Detect, deter, and defeat known and known money-laundering attacks.
Analyze context and linkages to discover fraudster activity early, at the registration stage. Create frictionless experiences for good customers, and purge damaging content.
In the United States, the USPS handles more than 500 million pieces of mail each day, while FedEx and UPS deliver a combined 34 million packages, not to mention the packages handled by smaller parcel services. With such a high volume of…
Predict and prevent suspicious activity, reduce overhead and boost review efficiency, and block fake accounts at the gate to protect good customers throughout the lifecycle of their journey.
This e-book describes how four e-commerce companies are using DataVisor’s fraud solutions to successfully fight modern fraud.
Consistently produce reliable results with high accuracy, capture fraudulent accounts at the point of registration, and implement scalable solutions for multiple regions and businesses. Ensure that valuable promotions reach real customers, and power ongoing business growth.
It’s no secret that flights can be expensive. So when airlines offer great deals, it’s a tough opportunity to pass up. This isn’t just a head-turner for travelers, however; fraudsters are also taking advantage of low airfare deals and…
Discover all the ways our customers are staying ahead of fraud by embracing AI-powered solutions that enable their organizations to know the unknown.
Get experts insights on how to deploy cutting-edge fraud solutions to defeat even the most sophisticated modern attacks.
This e-book explores the next generation of fraud prevention technology, which applies unsupervised machine learning to reduce false positives and risk.
Delve deep into proprietary research to ensure your organization stays ahead of malicious threats.
Can your business react in real time to a sophisticated digital threat attack? The scale will be massive, the speed unprecedented, and the potential damage incalculable. Will you be ready?
Learn from leading experts in the fields of AI, machine learning, and fraud prevention, as they provide rich insights on fraud trends and solutions.
Watch this webinar to learn about how faster payments have become the new reality in more than 40 countries, and how this innovation is benefiting consumers and businesses alike.
Capture new attacks fast. Detect incubating fraud early.
Proactively detect unknown and emerging threats with the power of proprietary unsupervised machine learning (UML). There’s no need for labeled data – DataVisor’s UML engine uses advanced clustering and graph analysis techniques to identify correlated groups of fraudulent activities and bot attacks in real time. It provides early detection by capturing incubation accounts before any damage occurs. By identifying fraudulent clusters – not just anomalies or outliers – dVector reduces false positives and delivers extremely accurate results.
Leverage unstructured data. Discover insightful patterns.
Integrate heterogeneous data from various channels and sources across the organization in real time, supporting SQL database, Amazon S3 and any local files. dVector dynamically derives hundreds of enriched features from unstructured and structured data, including IP addresses, emails, user names, timestamps, device information, transaction, user events and more. Using the power of digital data and enriched features, dVector uncovers hard-to-surface patterns and increases detection performance.
Make confident decisions. Boost review efficiency.
Analyze fraud techniques and monitor fraud trends over time, and gain valuable insights with detailed reason codes. dVector boosts operational efficiency by enabling you to take automatic actions with accurate results and make bulk decisions on hundreds of correlated cases. Investigate complex cases and uncover sophisticated patterns efficiently using Knowledge Graph to visualize multidimensional connections among entities, groups and money flow.
Get insights across the world. Enhance detection for business.
Improve fraud detection by leveraging actionable insights from DataVisor’s Global Intelligence Network (GIN). The GIN is powered by more than 4.2B protected accounts across various industries, regions and use cases. It contains rich information on digital data such as IP address subnets, prefixes, proxies and data centers, user agent strings, device types and OS, email address domains and more. Information from the GIN feeds into machine learning algorithms to optimize overall detection.
Capture significantly more fraud to increase security and power growth.
Achieve high accuracy and low false positives for positive customer experiences.
Achieve high accuracy and low false positives to promote positive customer experiences.