Sift Features

Rates each transaction's risk based on specific factors and their benchmarked scores.

Flags suspicious transactions and either alerts administrators or declines transaction.

Actively gathers data on suspicious purchasing sources and characteristics of common committers of fraud.

Stores data from external or internal sources related to fake accounts, evaluating users for risk.

Finds patterns in common occurrences of fraud to use when evaluating risk of purchasers.

Alerts administrators when fraud is suspected or transactions have been declined.

Constantly monitors system to detect anomalies in real time.

Constantly monitors system to detect anomalies in real time.

Alerts administrators when fraud is suspected or transactions have been declined.

Keeps records of geographic location and IP addresses of fraud suspects.

Tags users suspected of committing fraud and identifies them upon return.

Prevents previous committers of fraud from future transactions.

Monitors for and rids systems of bots suspected of committing fraud.

Stores data from external or internal sources related to fake accounts, evaluating users for risk.

Actively gathers data on suspicious purchasing sources and characteristics of common committers of fraud.

Produces reports detailing trends and vulnerabilities related to payments and fraud.

Tags users suspected of committing fraud and identifies them upon return.

Rates each transaction's risk based on specific factors and their benchmarked scores.

Prevents previous committers of fraud from future transactions.

Enables administrators to create access policies and applies policy controls throughout request and provisioning processes.

Integrates with common applications such as service desk tools.

Works across multiple software systems or databases

Improves performance based on feedback and experience

Makes informed choices based on available data and objectives

Monitors both incoming and outgoing payments to detect fraud, such as fake payees, bank accounts, or unathorized users.

Reviews every transaction in real‑time using rules, pre-defined criteria or a combination of signals to block, flag, or allow transactions.

Allows configuring custom rules/thresholds and adjusting sensitivity for different types of transactions.

Uses documents, biometrics, or device fingerprinting to verify that a user is who they claim to be.

Detects unusual login or credential usage and requires additional authentication when a risk is present.

Builds behavioral baselines to detect deviations in transactions and device usage.

Monitors and blocks automated fraud bots, such as creating fake accounts.

Tracks actions of users, rule changes, and other system events in secure logs

Generates customlizable reports for regulatory requirements and ongoing compliance.