In 2024, identity fraud and scam-related losses totaled $47 billion, including $27 billion in traditional identity fraud and $20 billion from scams orchestrated by criminals, according to Javelin Strategy & Research. While many consumers believe a credit freeze is a sufficient line of defense, scammers have evolved well beyond tactics that merely target credit reports. From imposter calls and phishing texts to real-time social engineering during transactions, modern fraud schemes bypass credit files altogether.
For banks, credit unions, and credit card issuers, this trend presents a critical challenge: traditional fraud defenses—especially those reliant on credit bureau interventions—can’t keep pace with dynamic, real-time scams. Protecting customers requires a broader, more adaptive approach to scam prevention, one that understands how deception works across multiple channels and touchpoints.
How Modern Scams Work Around Credit Freezes
Credit freezes were designed to stop criminals from opening new lines of credit in someone’s name. But most scams today don’t require opening an account—they exploit existing ones. A few common tactics include:
- Bank impersonation scams: Criminals pose as financial institution representatives and convince customers to transfer money out of their own accounts.
- Zelle and peer-to-peer (P2P) fraud: Scammers trick victims into authorizing transactions under false pretenses—once sent, those funds are typically unrecoverable.
- Synthetic identity fraud: Fraudsters mix real and fake information to create new identities that pass basic checks.
- Account takeover (ATO): By harvesting credentials or tricking victims into sharing login data, criminals gain direct access to funds.
In each of these cases, a credit freeze offers no protection. There’s no credit report involved, and no new line of credit is being requested. These are scams based on manipulation, not application.
Why Traditional Prevention Falls Short
The financial sector has long relied on tools like multi-factor authentication (MFA), fraud scoring, and transaction monitoring. While these remain important, they’re increasingly reactive rather than preventative. Many customers approve transactions while actively being scammed—often because they’ve been manipulated into believing they’re protecting their own money.
Compounding the issue is consumer overconfidence. According to a 2024 Federal Trade Commission report, many victims don’t recognize they’re in a scam until it’s too late, especially when scammers create false urgency or impersonate trusted institutions. And while financial institutions refund unauthorized fraud, they’re under less obligation when a transaction is “authorized,” even if under false pretenses.
This is where prevention efforts falter—fraud controls may detect unusual patterns, but they don’t always catch why a transaction is happening. Without context, it’s hard to tell the difference between a legitimate wire and one coerced through social engineering.
Adaptive Threats Require Adaptive Solutions
To effectively protect customers, financial institutions need tools that understand behavior and language, not just transactions. Newer strategies gaining traction include:
- Real-time scam detection using natural language analysis: AI models can analyze voice calls, texts, and chat interactions to detect common scam patterns—such as urgency, coercion, or impersonation language—before a transaction occurs.
- Context-aware transaction interventions: Rather than flagging transactions solely based on size or frequency, smart systems can assess metadata (like call history or message content) to determine whether a transaction appears coerced.
- Consumer education through just-in-time nudges: Instead of relying on customers to spot scams, banks can use interactive warnings during transactions that prompt users to slow down, verify the identity of a sender, or review potential risks.
- Multi-channel fraud signal integration: Fraud doesn’t occur in silos. Institutions that connect phone, email, and transaction data are better positioned to recognize and intercept scams that span multiple channels.
Financial institutions that invest in these kinds of preventative frameworks—especially those that incorporate AI—can reduce not only financial losses but also reputational risk. Customers increasingly expect their banks and credit providers to understand and anticipate scam threats, even those rooted in human psychology rather than technical intrusion.
Shifting the Narrative from Freeze to Foresight
Credit freezes still have value, especially in protecting against certain forms of identity theft. But relying on them alone is like locking your front door while leaving your windows wide open. They represent a static solution to an increasingly fluid threat environment.
For financial institutions, the imperative is clear: proactive scam prevention must go beyond account security and into behavioral analysis, cross-channel intelligence, and consumer empowerment. Fraudsters are innovating in real-time—and so must we.
Ultimately, scam prevention is no longer just a cybersecurity issue. It’s a trust issue. And trust, once lost, is far harder to restore than it is to protect.
Discover how KnowScam helps identify scams beyond credit freezes.
