Common Forms of Online Identity Fraud: Cases and Countermeasures
According to the Federal Trade Commission (FTC), consumers in the US lost more than $12.5 billion to identity fraud in 2024. A big part of that comes down to how easily identity signals—like passwords, phone numbers, or emails—can be copied, stolen, or manipulated.
While that statistic focuses on consumers, the reality is the same for businesses. Whether you’re running a fintech app, an e-commerce platform, or a B2B service, you’re dealing with the same pressure points every day: account creation, payments, refunds, disputes, and account recovery.
In this guide, we’ll walk through five common types of identity fraud that show up again and again in digital systems. For each one, you’ll see a real-world example, why it matters, and what can actually help reduce the risk.
Account takeover
Account takeover happens when someone gets access to a legitimate user account and starts using it as their own.
One of the most common methods is credential stuffing. Attackers take leaked username-password combinations and run them across different platforms, hoping people reused the same credentials. Since many still do, this remains a low-cost, high-reward tactic.
A real-world example
In 2023, 23andMe disclosed that attackers used credential stuffing to access some user accounts. From there, they were able to pull additional data through the platform’s DNA Relatives feature.
The impact went beyond just those accounts—about 6.9 million users were affected through that secondary exposure. The fallout included investigations, reputational damage, and regulatory fines.
Why it’s a problem
A correct password doesn’t always mean a legitimate user. Without additional context—like device, location, or behavior—it’s hard to tell the difference.
Even worse, attackers don’t always act immediately. They may sit on an account until the right moment, such as when they can change payout details or extract valuable data.
In B2B environments, the damage can spread quickly. One compromised account can expose invoices, contacts, and financial workflows.
What helps
Don’t rely on passwords alone—add multi-factor authentication, ideally phishing-resistant options
Treat changes to account details (email, phone, payout info) as high-risk events
Strengthen account recovery flows so they can’t be easily abused
Add delays or additional checks after sensitive actions
SIM swap fraud
SIM swap fraud is essentially phone number hijacking. An attacker convinces a mobile carrier to transfer a victim’s number to a new SIM card. Once that happens, they can receive SMS codes and bypass phone-based security.
A real-world example
In early 2024, attackers used a SIM swap to take over the SEC’s official X (Twitter) account. By gaining control of the phone number tied to the account, they intercepted verification codes and posted false information about Bitcoin ETFs.
The breach didn’t happen because of weak internal systems—it happened because control over the phone number was enough.
Why it’s a problem
SMS-based security assumes that whoever controls the phone number is the legitimate user. SIM swapping breaks that assumption.
It also introduces a dependency on third parties—like carrier employees or call centers—who can unknowingly override your security.
What helps
Use stronger authentication for sensitive actions like account recovery or payouts
Treat phone number changes as high-risk signals
Offer alternatives like authenticator apps or passkeys
Require additional identity proof for account recovery
Bonus abuse
Bonus abuse is less dramatic but often just as costly. It happens when users repeatedly exploit sign-up offers, referral programs, or promotional credits.
Usually, this involves creating multiple accounts under different identities—real or fake.
A real-world example
In 2026, US prosecutors charged two individuals who allegedly used the personal data of around 3,000 victims to create accounts on gambling platforms and exploit promotional bonuses.
The scheme reportedly generated about $3 million.
Why it’s a problem
These losses often go unnoticed because they’re spread across many small transactions. But at scale, they add up quickly.
Referral programs can make things worse, as fraudsters recruit others or rotate identities to maximize rewards.
What helps
Delay withdrawals or rewards until identity is verified
Enforce “one person, one account” rules using stronger checks
Monitor for patterns like repeated sign-ups or unusual activity
Treat payout changes as risk events
Refund fraud
Refund fraud involves manipulating return or refund processes to get money back unfairly.
This can look like false “item not received” claims, returning empty boxes, or disputing legitimate transactions after using a service.
A real-world example
In 2025, reports highlighted organized refund fraud rings targeting major retailers. One operation used social engineering, fake return tracking, and even insider access to trigger refunds without returning goods.
Why it’s a problem
Refund systems are designed to be customer-friendly—which makes them easier to exploit.
Fraudsters often follow scripts and reuse proven tactics across multiple companies, turning it into a scalable operation.
What helps
Recheck identity for high-value or suspicious refunds
Add extra verification for exceptions or unusual claims
Monitor support interactions for patterns or inconsistencies
Validate shipping and return data carefully
Chargeback fraud
Chargeback fraud—sometimes called “friendly fraud”—happens when someone disputes a legitimate transaction to get their money back.
Sometimes it’s intentional, sometimes it’s confusion—but either way, the business loses.
A real-world example
In 2025, small businesses reported losing significant revenue to chargebacks, even when they had proof of delivery. In one case, a seller discovered that disputed items were later resold by the same buyer.
Why it’s a problem
The dispute process often leans toward the customer, making it hard for businesses to win—even with evidence.
On top of that, high chargeback rates can lead to penalties from payment providers.
What helps
Prevent confusion with clear billing descriptors and notifications
Add extra checks for risky or high-value transactions
Keep strong evidence linking the buyer to the purchase
Use early alerts to resolve disputes before they escalate
A final thought
If you look closely, these fraud types follow a similar pattern. Attackers find weak points—moments where identity is accepted with minimal proof—and exploit them repeatedly.
The good news is that the defenses also overlap.
Adding stronger verification at key moments—like account recovery, payouts, or unusual activity—can significantly reduce risk. So can combining different signals: device data, behavior, and, when needed, identity verification.
There’s no single solution that stops everything. But a layered approach, applied thoughtfully across the user journey, makes it much harder for fraud to scale.