The Puzzle That Fraudsters Don’t Want You to Solve
Fraudsters aren’t using completely fake information, they’re using bits and pieces of real data, stitched together to pass basic security checks. An email from one stolen record. A phone number from another. A new address that doesn’t match past transactions.
On their own, each data point looks fine. But put them together, and the pieces don’t fit.
That’s where identity correlation and anomaly detection makes a difference. AtData connects the dots, analyzing the data to find subtle mismatches that indicate fraud. Because a synthetic identity might look real, until you see the whole picture.
How Fraudsters Exploit Identity Gaps
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They Borrow Just Enough Real Data to Look Legitimate
Fraudsters mix legitimate and fake details to build synthetic identities that bypass security. A real address with a newly created email? A phone number that doesn’t match any past records? These differences are red flags.
AtData Detects: Cross-references identity markers to spot mismatched or suspicious combinations.
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They Change Small Details to Evade Detection
A single identity can be stretched across multiple fraud attempts. Fraudsters slightly alter names, tweak email variations, or use multiple phone numbers to fly under the radar.
AtData Detects: Flags suspicious variations that suggest an identity is being manipulated.
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They Use Dormant or Recycled Identities for Future Fraud
Some fraudsters don’t attack right away. Instead, they create accounts with minor anomalies, let them sit for months, and then strike when they’ve built enough “credibility.”
AtData Detects: Monitors identity behavior over time, catching incongruent, fraudulent patterns before they escalate.
Fraud Prevention Beyond a Single Data Point
Most fraud prevention systems look at one piece of information at a time. But fraud isn’t one-dimensional. It’s built from a patchwork of details that, when viewed separately, might not raise alarms.
- Email & Phone Linkages: Does this email match past records for this phone number?
- Address & Name History: Has this name ever been used at this address before?
- Behavioral Patterns: Is this a one-time mismatch, or part of a larger fraud scheme?
Real fraud detection happens when you connect the dots. AtData’s ID correlation & anomalies feature links email addresses, names, postal data, and other identifiers to reveal hidden fraud patterns.
By analyzing billions of email activity signals and historical data, AtData helps you detect inconsistencies early, exposing synthetic identities, fake accounts, and mismatched details that fraudsters use to slip through security.
Fraudsters Count on Businesses Missing the Details. AtData Catches Them.
Mismatched identity details might seem small, but they’re the foundation of synthetic fraud. AtData’s ID correlation & anomalies detection helps you:
- Uncover hidden inconsistencies that signal fraud.
- Stop synthetic identities before they gain access.
- Protect revenue and customer trust with seamless fraud detection.
Don’t Let Fraudsters Slip Through the Cracks in Your Defenses
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