UCLIQ’s Fraud Prevention system is designed to fortify the integrity of its affiliate tracking platform. Using advanced technologies, UCLIQ’s Big-Data Tracker and machine learning algorithms work together to detect and prevent fraudulent activities, ensuring a secure and trustworthy environment for users.
Understanding the Mechanism
UCLIQ’s Fraud Prevention system starts by using the Big-Data Tracker. This tool gathers and examines all the data coming in, including details like device fingerprints and IP addresses.
By thoroughly reviewing this information, the system establishes a basis for spotting potential fraud patterns that could pose a risk to the authenticity of transactions.
Machine Learning Insights
Using advanced machine learning, UCLIQ’s fraud detection suite goes beyond traditional methods.
It can identify complex patterns in the data, adjusting and improving as new threats emerge. Every transaction undergoes a careful assessment, receiving a unique Fraud Risk Score. This score is a crucial measure of the potential risk linked to the transaction.
Conversion Control Options
UCLIQ provides users with flexible options to manage conversions based on the Fraud Risk Score.
Users have two options for managing suspicious transactions. First, they can manually review and reject questionable conversions one by one or in groups.
Second, there’s the Conversion Delay filter, a cool feature that lets users set specific Fraud Risk Score limits. If a conversion exceeds these limits, its approval is delayed, keeping it from being immediately shown to publishers.
Strategic Decision-Making
The Conversion Delay filter gives managers the power to check flagged conversions when they want. This extra control lets them carefully assess potentially fraudulent activities.
Managers can then decide whether to approve or reject delayed conversions, making sure only genuine transactions are shown to publishers.
Enhanced Transparency
UCLIQ’s Fraud Prevention system enhances transparency by providing a clear distinction between approved and delayed conversions.
Publishers are shielded from potentially fraudulent activities, as delayed conversions are not displayed to them until approved by the managerial team. This not only safeguards the interests of publishers but also fortifies the overall integrity of the affiliate tracking platform.
