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How to Use Fraud Holds on Orders

Fraudulent orders are a major headache for any e-commerce business, leading to lost money and frustrating chargebacks. Fraud Holds allow users to flag potentially fraudulent orders. When enabled, the order will not appear in the picking queue until the hold is removed.

Managing Fraud Holds

There are multiple ways to update a Fraud Hold on an order. For specific instructions, please visit our article: Managing Order Holds in ShipHero.

Method Description
Dashboard Manually apply or remove holds directly through the ShipHero user interface.
Automation Rules Set up rules to automatically apply a hold using the Set Fraud Hold action, triggered by specific order conditions.
Store Integration Certain e-commerce platforms, like BigCommerce, can automatically set a fraud hold when orders are imported using the Map Statuses setting on the store connection in ShipHero. See below for more information.
API Use GraphQL mutations to programmatically control fraud holds. Visit the Developer Site for more information.

Store Integrations - Map Statuses

For supported stores, an order can automatically be assigned a fraud hold based on its status in the e-commerce platform. For unsupported stores, holds must be managed manually.

How to Map Statuses

  1. Go to My Account > Stores and click Map Statuses on the store.
  2. Select Fraud Hold from the appropriate dropdown in the Order Hold column.
  3. Click Save.

The table below provides a quick reference for e-commerce platforms and their support for automatic fraud holds.

Supported Stores (Automatic Mapping) Unsupported Stores (Manual Management)
BigCommerce Shopify*
WooCommerce Amazon
Magento v2 eBay
Mystoreno Walmart
Etsy
Google

NOTE

While Shopify is not a supported store for the Map Statuses feature, it has its own dedicated Fraud Hold settings explained in the next section.

Fraud Holds from Shopify

Shopify and ShipHero work together to help you catch fraudulent orders. This section breaks down how the fraud prevention systems work so you can protect your business.

How Shopify's Fraud Score Works

Every order placed on a Shopify store is automatically analyzed for risk. Shopify's Risk Analysis system gives each order a Fraud Recommendation, which is sent to ShipHero. This recommendation can be one of three values:

Recommendation Meaning
Investigate The order has some suspicious signals and should be reviewed more closely.
Cancel The order has a high risk of being fraudulent and should likely be canceled.
Accept The order appears legitimate and has a low risk of fraud.

ShipHero Order Risk Levels

ShipHero takes Shopify's recommendation and applies its own rules to place a Fraud Hold on an order. You can configure your Order Risk Level from your store's settings page.

  1. Go to My Account > Stores and click the Settings button for your Shopify store.
  2. Scroll to the Fraud Settings section at the bottom left of the page.
  3. Select a risk level from the Order Risk Levels dropdown.
  4. Click Save.
Risk Setting Definition
Investigate or Cancel The most cautious setting. ShipHero will place a fraud hold on any order Shopify flags as "Investigate" or "Cancel."
Cancel A more moderate setting. A fraud hold will only be placed on orders that Shopify recommends you "Cancel."
Never Bypasses the fraud hold system entirely. No orders will be automatically flagged for fraud by ShipHero, regardless of Shopify's recommendation.

Order Risk Settings Defined

fraudsettings.jpg 

Notification Settings

To receive email notifications when an order imports with a fraud hold, add the contact email to the Notify Fraud Hold field on the My Account Settings page. More information about other notification settings can be found here.

  1. Go to the My Account > Settings page.
  2. Type the email address and press Enter in the Notify Fraud Hold Email field. The email will be highlighted with a green box to confirm it was added correctly.
  3. Click Save Changes.

NOTE

Fraud hold notifications are only sent when an order is first placed on hold during the import process.

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