10 Shopify Flow Workflows That Automate Fraud Response

Manual fraud review doesn't scale. A small merchant might be able to look at every flagged order; once order volume crosses a few hundred a day, manual review becomes the bottleneck that determines how well your fraud prevention works.

The merchants who scale fraud operations well don't have more staff — they have better automation.

Shopify Flow is the workflow engine inside Shopify that lets you connect events (new order, order paid, customer created, risk analysis completed) to actions (tag the order, send an email, cancel the order, fulfill from a specific location). Combined with a fraud app that exposes risk signals to Flow, it becomes a flexible automation layer.

This guide walks through 10 workflows that consistently earn their keep.

Why Flow specifically

Shopify Flow gets used for many things — promotions, fulfillment logic, customer segmentation — but it's particularly well-suited to fraud handling because of three properties:

Native triggers for risk events. Many fraud apps expose triggers like "risk analysis completed," "order flagged," and "order blocked" directly into Flow. Trigger fires the moment risk is identified; workflow runs in real time.

Access to the order, customer, and address. Flow has comprehensive access to the order's full context — workflows can make sophisticated decisions based on more than just the risk score.

Composability. Workflows can branch on conditions, call APIs, send notifications, and tag entities. Complex multi-step fraud responses are within reach without writing code.

For non-Plus stores, Flow's capabilities are narrower than on Plus, but the core triggers and actions for fraud handling are available on most plans.

Workflow 1: Auto-cancel high-risk fraud orders

The most basic and probably the most valuable.

Trigger: Risk analysis completed (or order created), risk classification "high"

Action: Cancel the order with reason "high risk." Notify customer. Optionally restock inventory.

Handles the bulk of obvious fraud automatically. Variations include adding conditions (only cancel if high-risk + specific indicators), and routing certain high-risk cases to manual review instead of auto-cancel for higher-AOV thresholds.

Workflow 2: Auto-flag medium-risk for manual review

Companion to auto-cancel.

Trigger: Risk analysis completed, classification "medium"

Action: Add tag "fraud-review" to the order. Email the fraud-review queue alias. Hold fulfillment.

Routes orders needing human judgment — too risky for auto-fulfill, not risky enough for auto-cancel — into a queue where a person decides. The "hold fulfillment" step (using fulfillment holds or unfulfilled status) prevents shipping before review.

Significantly reduces staff time required because the human only looks at orders that genuinely need judgment, not every flagged order.

Workflow 3: Tag fraudulent customers across future orders

For customers confirmed as fraudulent (manually identified, charged back, or confirmed bad actors), ensures their future orders get appropriate treatment.

Trigger: Manual action — staff member tags a customer as "blocked" via customer admin

Action: For all future orders from that customer (matching email, phone, or address), auto-cancel and notify team.

A refinement: rather than blocking outright, some merchants prefer "elevated review" — order doesn't auto-cancel but goes straight to manual review with customer's history surfaced. Both reasonable; choice depends on confidence in the blocked-customer identifier.

Workflow 4: Real-time fraud alerts to Slack

For fraud events that need immediate human awareness — high-value flagged orders, unusual patterns, sustained attacks.

Trigger: Risk analysis completed, classification "high" AND order value above threshold

Action: Post message to Slack channel with order details and direct link to order page.

Threshold matters. Alerting on every high-risk order is too much noise. Alerting on high-risk orders above $500 (or whatever your threshold is) keeps the signal valuable.

Workflow 5: Auto-add IP from chargeback to blocked list

When a chargeback fires, the originating IP of the original order is usually worth blocking.

Trigger: Order disputed (chargeback received)

Action: Extract IP from original order. Add to fraud app's blocked-IP list with note: "Auto-added from chargeback on order #{order_id}."

Builds your private blocklist over time, learning from your own loss data. Same fraudster won't typically come back from the same IP, but their network often does — and the IP that generated one chargeback frequently generates several before it gets fully rotated out.

Workflow 6: Sync flagged customers to Klaviyo segment

For merchants using Klaviyo (or similar ESPs), suppressing flagged customers from future campaigns is straightforward through Flow.

Trigger: Risk analysis completed, classification "high" OR confirmed fraud action

Action: Send customer's email to a "fraud-suppressed" segment in Klaviyo via webhook/API.

Once in the segment, customer is excluded from broadcast campaigns and high-spend automation. You're not blocking them from purchasing if they choose to come back legitimately, but you're not paying acquisition costs on them either.

Workflow 7: Auto-tag VIP customers for fraud-prevention exemption

Opposite problem: making sure highest-value customers don't get caught in fraud rules.

Trigger: Customer created with specific tag, or customer crosses LTV threshold

Action: Add tag "fraud-exempt" to customer. Fraud app respects the tag and elevates the order's safety classification.

Economics work: a $50K-LTV customer caught in a fraud rule represents tens of thousands of dollars of potential loss. Friction cost of explicitly exempting them is essentially zero.

Workflow 8: Auto-route high-risk orders to manual fulfillment

For stores with multiple fulfillment locations or providers, high-risk orders sometimes deserve different handling.

Trigger: Order created with classification "medium" or "high"

Action: Override standard fulfillment routing. Send order to manual-review fulfillment location instead of automated 3PL.

Most useful for stores using 3PL warehouses that ship within hours of receipt. Routing risky orders to a slower, manual location buys time for fraud review before shipment leaves.

Workflow 9: Auto-cancel COD orders matching non-acceptance patterns

For COD-heavy stores, automating the response to risky COD orders is a major lever.

Trigger: Order created with payment method "cash on delivery" AND (shipping address matches blocklist OR phone matches blocklist OR customer has prior non-acceptance)

Action: Auto-cancel with configurable message, OR auto-hide COD on subsequent attempts.

More nuanced version: rather than auto-cancelling, the workflow triggers a verification flow (automated phone call or SMS to confirm the order before shipping). Customers who verify proceed; those who don't get cancelled.

Workflow 10: Daily fraud report to operations team

Meta-workflow: rather than reacting to individual events, summarize the day's fraud activity for the team.

Trigger: Scheduled daily at end-of-business

Action: Query the day's fraud-related orders (flagged, cancelled, blocked, chargebacks received). Generate summary report. Email to operations team or post in dedicated Slack channel.

Pattern doesn't directly prevent fraud, but surfaces patterns individual-order workflows miss — a sudden spike in flags, a new fraud pattern emerging, a specific product being targeted.

Operations teams who see the daily summary catch developing issues much faster than teams who only see individual flagged orders.

Common Flow patterns to avoid

A few patterns that consistently underperform:

Auto-actions without monitoring. Workflows that fire and forget without visibility into how often they're firing or what they're doing. Build monitoring into your fraud workflows from day one.

Cascading cancellations. Workflows that trigger other workflows in complex chains. Hard to debug, hard to verify, easy for unintended consequences to compound. Keep each workflow focused on a specific decision.

Auto-blocking without exception paths. Workflows that block customers without any way for them to recover. Always pair auto-block workflows with a manual override path.

Notification overload. Workflows that ping the team on every flagged order. The team learns to ignore notifications. Tune thresholds so alerts are rare enough to maintain attention.

Single points of failure. Workflows that depend on specific third-party services without fallback. When the service is down, your fraud prevention is too.

How Shieldy integrates with Flow

Shieldy Fraud Filter exposes three Shopify Flow triggers:

1. Risk Analysis Completed — fires after Shieldy evaluates an order; provides risk classification + indicator breakdown
2. Order Flagged for Review — fires when an order matches review criteria; useful for tagging and team notification workflows
3. Order Blocked — fires when an order is auto-cancelled; useful for downstream sync (Klaviyo suppression, IP blocklist addition, etc.)

Combined with Shopify's native triggers (order created, order paid, customer created, order disputed), these support all 10 workflows above without writing code.

A practical first-month setup

For a store starting from no automated fraud workflows:

1. Set up Workflow 1 (auto-cancel high-risk) with conservative threshold
2. Set up Workflow 2 (auto-flag medium-risk) with tag and email notification
3. Set up Workflow 10 (daily fraud report) so you can see what's happening
4. Monitor for 30 days. Tune thresholds based on actual data.
5. Add Workflows 5, 6, and 7 as you accumulate evidence about which patterns matter most.

Within a quarter, most stores have a fraud-automation layer that handles 80% of cases without human intervention, freeing the team for the 20% that needs judgment.

A practical close

Manual fraud review is a stage, not a permanent state. Past a certain volume, automation pays for itself. Shopify Flow + Shieldy's risk triggers cover the typical workflows; custom workflows fill gaps.

Start simple. Tune over time. Build the daily report habit so you see patterns, not just individual events.