Stripe Radar is designed to detect and block fraudulent transactions before they go through. But if you're seeing too many legit payments get flagged or declined, you're not alone. It’s a common complaint among merchants, especially in industries with high-ticket items, global customers, or unusual buyer behavior.
In this guide, let’s walk through the main reasons Stripe Radar blocks valid payments and what you can do to fix it without opening yourself up to fraud.
Why Stripe Radar Flags Legit Payments
Radar works by using machine learning models and customizable rules to decide whether a payment is risky. It assigns each transaction a fraud score and applies rules based on that score, along with other data like IP, card country, billing ZIP match, and user history.
Sometimes, this system is too cautious. Here’s what usually causes false positives:
- Default rules that are too strict
- Mismatches in address or ZIP code
- High fraud scores due to unusual customer behavior
- International payments with a limited history
- Repeated purchase attempts that trigger velocity rules
If you’ve ever lost a sale because a real customer’s payment got blocked, here’s how to make Stripe Radar less aggressive without turning it off.
1. Review and Adjust Radar Rules
Head to your Radar > Rules section in the Stripe Dashboard. Stripe includes a set of default rules, but many of them are blunt instruments.
For example:
- Blocking payments where AVS ZIP fails
- Declining all medium-risk payments
- Auto-blocking high-risk countries
You can modify these rules or add exceptions. Try changing "block" actions to "review" instead. This way, you’ll have the option to approve the payment manually.
To edit a rule, click the pencil icon next to it. Change the action from "block" to "review," save the rule, and monitor how it performs.
2. Use Radar for Teams (If You Have It)
If you’re on a plan that includes Radar for Teams, you get access to advanced tools like:
- Fine-tuned rules with AND/OR logic
- Webhook-based rule triggers
- Filtering by customer attributes
- Fraud score visibility thresholds
This lets you get more precise. For example, you could allow low-risk payments from customers who’ve ordered more than twice, or flag first-time orders over $500 for manual review.
It takes some time to configure, but it gives you better control than Radar’s basic setup.
3. Add Allow Lists for Trusted Customers
If you have regular customers, B2B clients, or test cards that keep getting flagged, add them to your Allow List.
You can allowlist by:
- Email address
- Card fingerprint
- IP address
- Billing details
Go to Radar > Lists > Allow List in your Dashboard to manage entries. Stripe will let payments from those sources through, even if they would normally trigger a rule.
4. Adjust the Fraud Score Threshold
Stripe assigns each payment a fraud score from 0 to 100. By default, anything over a certain number (often 75) might get blocked.
If you're seeing too many false positives, consider raising that threshold slightly. Some merchants find that moving it to 85 or even 90 reduces blocked payments without letting fraud through.
You can do this by editing rules like:
Change it to:
Then watch how many reviewed payments turn out to be valid or fraudulent. Tweak as needed.
5. Watch the False Positive Rate in Your Dashboard
You can check your false positive rate by going to Radar > Overview > Disputes and looking at metrics related to declined or blocked payments that were later confirmed as valid.
Stripe also shows you the Radar accuracy rate based on how often it correctly blocks fraud or incorrectly blocks good payments.
Use this data to justify rule changes or spot problem areas like:
- Frequent declines from certain IP ranges
- Issues with a specific payment method or gateway
- Rules that are triggered too often
6. Change Aggressive Rules to “Review” Instead of “Block”
If you’re not ready to fully trust Radar, the best middle ground is using "review" rules. These send the payment to your dashboard, where you or your team can manually approve or decline it.
This works well if:
- You have a small volume of daily orders
- You’re in a high-risk or gray-area industry
- You're getting hit with chargebacks, but also blocking real buyers
Manual review adds friction but gives you the final say.
Recover Lost Revenue Without Raising Risk
Stripe Radar is powerful, but it’s not perfect out of the box. The default settings can hurt sales if they’re too strict for your business model. Thankfully, you can tune it.
Start by reviewing the rules you have in place, then make careful changes based on fraud scores, customer history, and dispute data. Use manual reviews when needed and always watch your metrics.
The goal isn’t to eliminate all fraud but to strike the right balance—keeping your store secure without rejecting good customers.
Frequently Asked Questions About Stripe Radar
Why is Stripe Radar blocking good payments?
Stripe Radar might block legit payments due to overly strict rules, mismatched billing info, high fraud scores from first-time customers, or international purchases that look unusual to the algorithm.
How do I lower Stripe Radar's sensitivity?
Go to the Rules section and adjust or remove overly aggressive rules. Change actions from “block” to “review,” and raise the fraud score threshold slightly to let more payments through.
Can I whitelist certain customers in Stripe?
Yes. Use the Allow List feature in the Radar settings to whitelist trusted customers by email, card fingerprint, or IP address.
Will changing Radar rules increase fraud?
It can if you’re not careful. The key is to make small changes, monitor the fraud rate, and use the "review" action instead of "allow" when you're unsure.
Want Fewer Disputes and Less Manual Work?
If you're spending too much time managing false positives or reviewing payments manually, Chargeblast can help streamline your fraud strategy. We work with Stripe Radar setups, track dispute trends, and help you optimize rules for your business model. Less stress. Fewer chargebacks. More revenue recovered.
Book a demo today or try it out yourself.
