Antifraud services are essential tools in digital advertising. But the marketing around them often oversells capabilities while hiding limitations. Lets look honestly at what these services actually do - and what remains beyond their reach.

What Antifraud Services Can Detect

Known Bot Signatures

The easiest fraud to catch:

WebDriver flags - Selenium, Puppeteer, automation tools
Headless browser markers - PhantomJS, HeadlessChrome
Known bot user agents - Scrapers, crawlers, monitoring tools
Automation framework artifacts - window._phantom, callPhantom

Detection rate: Very high for known signatures. But sophisticated fraudsters avoid these obvious markers.

Datacenter and Proxy Traffic

IP-based detection catches:

Datacenter IPs - AWS, Google Cloud, DigitalOcean ranges
Known VPN providers - NordVPN, ExpressVPN exit nodes
Public proxy lists - Regularly updated blacklists
TOR exit nodes - Published and trackable

Detection rate: Good for commercial services. Residential proxies are much harder.

Behavioral Anomalies

Pattern analysis catches:

Impossible speeds - Clicks faster than human reaction time
No mouse movement - Real users move mice; bots often dont
Linear patterns - Robotic, predictable behavior
Session anomalies - No scroll, no interaction, instant bounce

Detection rate: Moderate. Sophisticated bots simulate human behavior.

Device Fingerprint Inconsistencies

Technical checks catch:

Mismatched data - User agent says iPhone but screen size is desktop
Impossible configurations - Hardware combinations that dont exist
Spoofing artifacts - Signs of fingerprint manipulation

Detection rate: Good for lazy spoofing. Better tools produce consistent fingerprints.

What Antifraud Services Cannot Detect

Residential Proxy Traffic

The hardest problem in fraud detection:

Traffic routed through real residential IPs
Appears identical to legitimate home users
IP reputation services have limited coverage
New residential IPs constantly entering rotation

This is how sophisticated fraud operations evade IP-based detection entirely.

Human Click Farms

Real humans doing fake actions:

Actual people clicking ads for payment
Real devices, real behavior patterns
Indistinguishable from legitimate users technically
Only detectable through conversion quality analysis

No antifraud technology can detect a real human doing real clicks. Only post-conversion analysis reveals the fraud.

Sophisticated Bot Networks

Advanced bots that:

Run on compromised residential devices
Simulate realistic human behavior patterns
Vary timing, movement, and interaction naturally
Use real browser instances with real fingerprints

When bots use real devices with real browsers, the technical signals are legitimate.

Incentivized Traffic

Users completing actions for rewards:

Real users, real devices, real intent to complete action
Technically indistinguishable from organic users
Intent is wrong, but signals are legitimate
Only conversion quality reveals the problem

Attribution Fraud

Claiming credit for organic conversions:

Click injection on mobile
Cookie stuffing on web
Last-click theft

The user and conversion are real - only the attribution is fraudulent. Requires different detection methods.

The Detection Gap

Heres the uncomfortable reality:

Fraud Type	Detection Capability
Basic bots	90%+ detectable
Datacenter traffic	80%+ detectable
Commercial VPNs	70%+ detectable
Behavioral anomalies	50-70% detectable
Residential proxies	20-40% detectable
Sophisticated bots	10-30% detectable
Human click farms	<10% detectable

Antifraud services are excellent at catching lazy fraud. Theyre limited against motivated, well-resourced attackers.

What This Means Practically

Antifraud Is Necessary But Not Sufficient

You need antifraud tools, but dont expect them to catch everything. Layer them with:

Conversion quality monitoring
Source-level performance analysis
Post-conversion verification

Claims of 99% Detection Are Marketing

When a vendor claims near-perfect detection, theyre either:

Only counting easily detectable fraud
Not facing sophisticated attackers
Exaggerating for sales purposes

Multiple Providers Catch More

Different services have different strengths:

IP reputation specialists
Behavioral analysis experts
Device fingerprinting focus

Layering catches what individual providers miss.

Your Own Data Is Essential

No external service knows your business like you do:

Track conversion quality by source
Monitor downstream metrics (LTV, chargebacks)
Build your own fraud indicators

The Honest Expectation

Good antifraud services catch 60-80% of fraud in typical traffic. Thats valuable - its the difference between losing 20% to fraud versus losing 5-8%.

But if someone promises to eliminate fraud entirely, theyre selling fantasy. The goal is reducing fraud to manageable levels, not achieving perfection that doesnt exist.

Use antifraud tools. Just understand what theyre actually doing - and plan for what they cant catch.

What Antifraud Services Actually Detect (And What They Can't)