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Sift: Overview
Updated over a week ago

Important: To check how you can enable Sift, please talk to your Lunchbox Customer Success Manager


Sift provides machine learning-based solutions to analyze data, detect anomalies, and make real-time decisions to mitigate potential risks. Sift offers fraud detection, content moderation, and insights to help businesses maintain a safe and secure online environment.

The Sift integration involves connecting Lunchbox's existing systems with Sift's APIs. This integration enables real-time analysis of Sift's user fraud rating and transactions, allowing Lunchbox Inc. to proactively identify and thwart fraudulent behaviors.


  • For Lunchbox 2.0, we compare email fraud scores and deny the transaction if the fraud score is above the configured threshold.

  • This is a global setting across the whole chain. We can not localize it per location.

Important Information

  • We cannot set up SIFT on the New 2.0 Adm Dashboard because the Menu category is unavailable. We MUST switch to "old adm."

  • Lunchbox can integrate with SIFT regardless of the processor.


Machine Learning: Sift leverages advanced machine learning algorithms to analyze vast amounts of data and detect patterns of fraudulent behavior. It continuously learns from new data to improve accuracy and adapt to evolving fraud tactics.

Data Collection: Sift collects and aggregates data from various sources, such as user actions, device fingerprints, and transaction information. This data is then processed to identify suspicious activities and potential risks.

User Behavior Analysis: Sift examines user behavior patterns to establish a baseline of normal activity. It detects anomalies, such as unusual login locations, atypical purchasing patterns, or abnormal browsing behavior, which could indicate fraudulent intent.

Fraud Detection: By correlating multiple data points and applying machine learning models, Sift accurately identifies fraudulent activities, including account takeovers, payment fraud, fake accounts, and content abuse. It assigns risk scores to each user or transaction, allowing businesses to make informed decisions.

Real-time Decisions: Sift provides real-time decisions, enabling businesses to automatically accept, deny, or flag suspicious activities based on risk scores. This minimizes manual reviews and streamlines the user experience, reducing false positives and preventing real-time fraud.

Customizable Rules and Policies: Sift allows businesses to define their own rules and policies to align with their unique requirements. This flexibility enables the customization of fraud prevention strategies and ensures that the platform adapts to each business's needs.

Content Moderation: Sift helps businesses moderate user-generated content, such as reviews, comments, and images, to identify and remove harmful or inappropriate content. This protects users from offensive or malicious material and maintains a safe online environment.

Global Network: Sift maintains a global network and shares insights across its customer base, enabling businesses to benefit from the collective knowledge and stay ahead of emerging fraud trends. This collaborative approach enhances the accuracy and effectiveness of fraud detection.

Insights and Reporting: Sift provides businesses with comprehensive insights and reporting, allowing them to monitor fraud trends, track key performance indicators, and make data-driven decisions. These insights help businesses optimize their fraud prevention strategies and improve operational efficiency.

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