Geoconsistency down to the millimeter: How ZIP codes affect AVS and fraud score

[BadB]

Analyzing the relationship between IP, address, time zone and the likelihood of a transaction being approved

Introduction: The Age of Geographical Accuracy​

Previously, using a US proxy was enough to pass as an American user. Today, in 2026, geoconsistency is not just a country match, but the synchronization of dozens of parameters down to the zip code level.

Modern fraud engines (Forter, Riskified, Sift) and payment gateways (Stripe, Adyen) analyze three-dimensional geolocation:

• IP geolocation (city, ZIP),
• Billing address (street, ZIP),
• Device time zone,
• OS and browser language,
• History of behavior in the region.

Violation of even one element triggers the system to raise an alarm. In this article, we'll provide an in-depth technical analysis of how the ZIP code became a critical trigger, why an IP address from Miami ≠ an address in Miami, and how to achieve geoconsistency down to the millimeter.

Part 1: What is AVS and why it evolved​

Address Verification System (AVS)​

AVS is a protocol that verifies that the billing address specified during payment matches the address registered with the bank.

Initially, AVS only verified:

• Postal code (ZIP),
• House number and street.

But today, AVS is part of a multi-factor geo-assessment integrated into the AI models of fraud engines.

Evolution of AVS:​

Year	Verification level	Example
2010	ZIP only	Match 33101 = OK
2018	ZIP + street	123 Main St, 33101 = OK
2026	ZIP + IP + timezone + behavior	All parameters must match

The key shift is that
AVS no longer operates in isolation – it is part of the geographer.

Part 2: How ZIP Code Affects Fraud Score​

Why ZIP?​

• ZIP codes in the United States have a high granularity:
  • 33101 = Downtown Miami,
  • 33130 = Brickell,
  • 33131 = Edgewater.
• Banks and merchants use geo-clusters to analyze behavior.

Impact of ZIP mismatch:​

Scenario	Changing the fraud score	Probability of approval
IP: 33101, Address: 33101, TZ: EST	Basic (10)	95%
IP: 33101, Address: 10001 (NYC)	+35 points	40%
IP: 33101, Address: 33101, TZ: PST	+25 points	60%
IP: Datacenter, Address: 33101	+50 points	10%

Field data (2026):
ZIP and IP mismatch reduces success rate by 55–70%.

Part 3: The Four Pillars of Geoconsistency​

For maximum approval chances, all four parameters must be in sync:

1. IP geolocation​

• Use a static residential proxy with the exact city and ZIP,
• Example: For the address 123 Main St, Miami, FL 33101 → the IP must be physically located in 33101.

🛠 Tools: IPRoyal, Bright Data - allow you to select a city + ZIP.

2. Billing address​

• Must match the card details exactly,
• Use ZIP-specific address generators (such as FakeNameGenerator).

3. Device time zone​

• Windows/macOS must be set to the local time zone,
• For 33101 → America/New_York (UTC-5),
• Check: https://browserleaks.com/time

4. Language and locale​

• OS language: en-US,
• Browser language: en-US,
• Keyboard: US English.

Rookie mistake:
IP from Miami + time zone UTC+3 → instant increase in fraud score.

Part 4: How Fraud Engines Check Geo-Consistency​

Forter: Geo-graph​

Forter builds a graph of connections between:

• IP → ASN → city → ZIP,
• Device → Time Zone → Language,
• Address → bank → historical transactions.

If the IP and address are in different geo-clusters, the system requires Challenge Flow.

Sift: Behavioral Geography​

Sift analyzes:

• Time of day of purchase (purchase at 3 AM EST is normal, at 3 AM PST is suspicious),
• Session history (all previous sessions from one ZIP?).

Stripe Radar: Dynamic AVS​

Stripe doesn't just check ZIP — it compares it to fraud patterns:

• If 33101 is often used in fraud → even an exact match triggers a check.

Part 5: A Practical Guide to Setup​

Step 1: Select a ZIP code​

• Use real ZIP codeswith high population density:
  • 33101 (Miami),
  • 10001 (New York),
  • 90210 (Beverly Hills).

Step 2: Set up a proxy​

• In IPRoyal: select USA → Florida → Miami → ZIP 33101,
• Make sure the IP is not a datacenter (check on ipqualityscore.com).

Step 3: Set the system time​

• Windows:
  Settings → Time & Language → Time zone = (UTC-05:00) Eastern Time
• Disable automatic time synchronization.

Step 4: Generate an address​

• Use FakeNameGenerator:
  • Select the state of Florida,
  • Make sure ZIP = 33101.

Step 5: Check the consistency​

• BrowserLeaks.com:
  • IP Geolocation = Miami, FL 33101,
  • Timezone = America/New_York,
  • WebRTC IP = proxy IP.

Part 6: Mistakes That Kill Carding​

Error 1: Using the "closest" IP​

• IP from 33130 (Brickell) to address 33101 (Downtown) → distance 2 km, but different geo-clusters.

Mistake 2: Ignoring the time zone​

• Purchase at 2 PM EST, but the device is in UTC+3 → the fraud engine sees "night activity".

Error 3: IP Reuse​

• After refusal, the same IP → automatic increase in fraud score.

Conclusion: Geoconsistency is the foundation of trust​

In 2026, geography is not a backdrop, but a central element of trust. Fraud engines no longer ask, "Are you from the US?"
They ask, "Are you from 33101, making a purchase at 2 PM EST, on a device configured for en-US?"

Final thought:
The best geo-masking isn't fakery, but an accurate reproduction of reality down to the zip code level.
Because in the world of AI, a millimeter of discrepancy is a kilometer of suspicion.

Stay precise. Stay consistent.
And remember: in the geography of trust, details matter.

 

[Tyknerknerk]

So is it absolutely necessary for the ip of proxy to match the zip code of the billing adress of the card holder. My proxy provider only allows targeting by country, state and city. There isn't an option for zip code. So for eg the card holder's billing adress is miami, 33100 I use a proxy of miami with zip of 33200 will it be flagged by the anti fraud systems if everything else like timezone, timing of the day, web rtc , browser language , keyboard language matches. I cannot purchase bright data or ip royal as they now require KYC verification. Is there any other high quality proxy providers that allows for targeting by zip code

 

[Tyknerknerk]

So is it absolutely necessary for the ip of proxy to match the zip code of the billing adress of the card holder. My proxy provider only allows targeting by country, state and city. There isn't an option for zip code. So for eg the card holder's billing adress is miami, 33100 I use a proxy of miami with zip of 33200 will it be flagged by the anti fraud systems if everything else like timezone, timing of the day, web rtc , browser language , keyboard language matches. I cannot purchase bright data or ip royal as they now require KYC verification. Is there any other high quality proxy providers that allows for targeting by zip code

Also prioritising exact zip code will it not create false positives because the real card holder can make transactions while travelling or at work