Utilize K-Protect in E-commerce to thwart fraudsters at any point of the customer journey
Offering e-commerce solutions for sensing various types of account and payment fraud
The Worldwide Intelligence Network
Leverage our fraud library of
millions and billions of devices and user accounts to detect previously unseen attacks
Persistent Device Recognition
K-protect generates device IDs that are both unique and extreme- ly persistent, identifying which users should and should not be trusted
Flags all methods and tools that are frequently used in fraudu- lent activities
Well, what sorts of fraud are faced by e-commerce businesses?
Fraudulent chargebacks can happen on purpose or by accident. The fundamental tenet is that a user will pay for a service or good that they assert was never delivered or was damaged in transit. Chargebacks are a frequent point of contention for e-commerce platforms.
Return to Origin fraud is the one by which an order is sent back to the warehouse but never gets to the customer for a no. of rea- sons. With more orders coming in and sellers expanding to Tier 2 and Tier 3 cities, RTO orders start to matter more.
Triangulation fraud is an act of obtaining credit card information and using it to make unauthorized purchases. The name refers to the three-step process of luring customers, acquiring their personal information, and utilizing them in a bigger scheme.
Complete assistance for e-commerce platforms to build trust and safety
01.Rapid and precise detection of potential f rauds
AI-powered systems weigh risk exposures against cus- tomer value without jeopardizing business policies. K-protect also provides analysis that helps brands identify anomalies and patterns much more quickly and precisely.
02. Reduces the costs f raudulent activity
Providing guidance on how to handle risks associated with new products and elongated offers without having to deal with stick shift reviews and chargebacks.
03. Effective Real-time data processing
With an AI system detects anomalies in real-time and inter- venes in fraudulent activity even before the attack.
Real-time machine learning data enrichment to lessen fraud scores
- Allows you to skim through all of your customers’ data to identify poten- tially fraudulent patterns. That data is fed through risk rules using basic tools.
- Foresees new vulnerabilities before they harm your ecommerce.
- Analyses hundreds of data points to identify fraud connections. It will then recommend rules that you can use as quickly as possible to prevent online payment fraud, friendly fraud, and other attacks.