Fraud Filter
Fraud Filter on the Shopify App Store provides robust protection against fraudulent orders, allowing merchants to safeguard their business effectively. This app helps in creating custom filters to flag and potentially block suspicious orders, thereby reducing chargebacks and maintaining profitability.
Fraud Filter offers customizable filters that let merchants set up specific rules based on order attributes like IP address, billing, and shipping information. These filters can flag or automatically cancel orders that meet the defined criteria. Additionally, the app tags suspicious orders for easy identification, providing a clear view of flagged orders within the Shopify admin panel.
The app also automates the cancellation of high-risk orders, saving time and preventing potential losses. Merchants can choose to review flagged orders before taking action, ensuring control over their processes. Fraud Filter sends instant email notifications when an order is flagged, keeping merchants informed in real time.
Integration with Shopify is seamless, making it easy to implement and use. The user interface is intuitive, designed for quick setup and efficient monitoring of orders. The app’s support team is responsive, providing quality assistance when needed. Fraud Filter’s distinct features and reliable protection set it apart from other fraud prevention tools on the market.
- Free plan is available
- Creates customizable filters based on specific business needs
- Automatically flags orders that match filter criteria as suspicious
- Blocks orders from known problematic customers
- Aids in reducing chargeback risks by preemptively flagging risky orders
- Alerts users about orders that trigger custom filters
- Allows blocking based on specific payment details or addresses
- Offers options for automatic cancellation or manual review of suspicious orders
- Integrates directly within the Shopify admin for ease of use
- No free trial of paid plan is available
- Specific customers continue to order despite being blocked
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