Scam Detection 101: How to Spot Scam Schemes Before Customers Fall Victim

by Laura Burrows 5 min read August 25, 2026

At A Glance

Explore five common scam schemes, the signals to watch for and how fraud teams can identify scams earlier in the customer journey.

Scams have become one of the fastest-growing fraud threats facing financial institutions. In 2025 alone, U.S. consumers filed more than 3 million fraud reports, continuing a decade-long trend of increasing losses. As digital banking, real-time payments, and artificial intelligence reshape the financial landscape, scammers are evolving just as quickly, using sophisticated social engineering techniques to convince legitimate customers to willingly send money or share sensitive information.

For fraud teams, this represents a fundamental shift. Traditional fraud prevention strategies are designed to stop unauthorized access, but today’s scams often involve authorized customers making seemingly legitimate transactions. By the time an institution realizes a customer has been manipulated, the funds have often already left the account. The challenge is no longer simply identifying fraudulent transactions; it’s recognizing the subtle behavioral signals that indicate a customer is being deceived before a payment is made.

Fortunately, while scam tactics continue to evolve, they tend to follow a predictable pattern.

Every scam follows a familiar path

Whether it’s a phishing email, an imposter pretending to be a family member or a fake investment opportunity, most scams progress through the same lifecycle. Fraudsters first identify a target and establish contact before gradually building trust. Once credibility has been established, they create urgency and encourage the victim to act quickly, whether that’s sharing credentials, approving a payment or moving funds. Only after the transaction has been completed does the customer discover they’ve been scammed.

For financial institutions, the greatest opportunity lies in recognizing the signs of manipulation before the final transfer occurs. Although organizations can’t see the text messages, social media conversations or phone calls taking place outside their systems, they can identify the behavioral changes those interactions leave behind.

AI is making scams more convincing than ever

Artificial intelligence (AI) has dramatically lowered the barrier to entry for fraudsters. What were once poorly written phishing emails or obviously fake websites can now be personalized, grammatically correct and nearly indistinguishable from legitimate communications. Voice cloning and deepfake technology have also transformed imposter scams, allowing criminals to convincingly imitate family members, coworkers or financial institutions.

These tactics are becoming mainstream. Deepfake fraud attempts increased by over 2,000% in the last three years and now account for 6.5% of fraud attempts. Nearly one-third of scams originate on social media, and crypto-related scams generated more than $8.6 billion in losses during 2025. Rather than replacing traditional social engineering, AI has simply made it more scalable, more personalized and more difficult for consumers to recognize.

Five scams targeting financial institutions

While new scam variants appear regularly, five schemes continue to account for much of the fraud impacting financial institutions today.

Phishing scams

remain one of the most common entry points. Customers receive convincing emails, text messages or phone calls that appear to come from trusted organizations and are directed to cloned websites where credentials or one-time passcodes are collected. Institutions may never see the phishing message itself, but they can often detect unusual login activity, unfamiliar devices or sudden behavioral changes immediately afterward.

Imposter scams

have become significantly more sophisticated as fraudsters leverage AI-generated voices and deepfake technology. Rather than stealing credentials, these criminals manipulate customers into sending money directly by impersonating someone they know and trust. Because customers authenticate themselves and willingly initiate payments, behavioral analytics becomes increasingly important for identifying signs of coercion or unusual transaction patterns.

Investment scams

follow a slower timeline, often unfolding over weeks or months. Fraudsters establish credibility through fake trading platforms, fabricated investment returns and professional-looking websites before encouraging victims to make progressively larger investments. To a financial institution, these transactions may initially resemble legitimate investment activity until patterns begin to emerge, such as repeated transfers to unfamiliar recipients or significant movement of funds from savings into outbound payments.

Tech support scams

exploit customer concern by convincing victims that their device or account has been compromised. After persuading them to install remote-access software, fraudsters take control of authenticated sessions and initiate high-risk account activity themselves. In these situations, the institution may observe familiar credentials paired with entirely unfamiliar session behavior; a strong indication that a remote-access tool is being used.

Romance scams

often prove especially devastating because they rely on emotional manipulation rather than urgency. Fraudsters spend weeks or months building relationships before introducing financial requests, leading to repeated payments that gradually increase over time. Because victims genuinely believe they are helping someone they care about, these scams can be particularly difficult to interrupt without thoughtful customer interventions.

Building a smarter scam defense

As scam tactics continue to evolve, preventing fraud and identity verification requires a broader view of customer behavior. Rather than focusing solely on whether a transaction is authorized, financial institutions must understandwhya customer is behaving differently and whether those changes indicate external manipulation.

No single signal catches a scam, which is why organizations that combine multiple fraud signals across account opening, authentication, payment activity, and ongoing account monitoring will be better positioned to detect scams earlier, before customers become victims.

Ready to strengthen your scam prevention strategy?

Explore our fullwhite paperto learn how to recognize emerging scam tactics and the signals that can help stop them sooner.

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