The use of agentic AI in fraud schemes is increasing the sophistication of attacks and making traditional pattern-based detection more difficult. This evolution of AI enables the automation of complex, multi-step attacks, dynamically adapts to victims’ responses, and hyper-personalizes scams at scale.
As a result, cybersecurity is becoming increasingly complex in the age of AI. Autonomous agents can reason, plan, and execute social engineering attacks without human supervision, and can even change tactics instantly based on what a target says or does. Their deception is highly convincing: they can generate natural-sounding text and imitate people’s voices or video styles without the typical errors that once made fraudulent content easier to identify. In this way, synthetic fraud can combine real and fabricated data to create false yet highly credible identities. In addition, attacks can quickly move across multiple channels, including email, text messages, and phone calls.
AI’s ability to modify recognizable elements of an attack on the fly also weakens defenses based on repetitive patterns, requiring organizations to place greater emphasis on detecting unusual behavior.
Boston Consulting Group predicts that, in the financial sector, agentic AI will drive the industrialization of financial scams. “This technology could reduce the cost of carrying out a scam or fraud by 90% over the next two years, potentially leading to a twofold—or even greater—increase in case volumes”, the analysts say.
Automation also removes one of the main constraints of traditional digital fraud: the number of people required to research targets, maintain conversations, and adapt strategies. AI agents can perform these tasks simultaneously at a scale that is no longer limited by the operational capacity of a human team.
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Because AI is also a powerful tool for preventing, detecting, and rapidly responding to scams and fraud, BCG argues that banks should use it “to strengthen their defenses, detect suspicious activity, help customers exit scams and fraud quickly, and preserve trust when incidents occur”.
Financial organizations need to incorporate automated intelligence to analyze signals that traditional controls cannot detect.
The acceleration of digital fraud described by multiple studies is already taking place. In the United States, identity theft reports filed with the FTC increased by nearly 20% year over year. AI is making fraud easier to execute, faster to scale, and harder to detect.
Today, it is no longer enough to confirm that a document exists or that an individual can provide a specific piece of information. Organizations must verify that the person’s behavior and the signals associated with that identity are consistent.
In this environment, identity verification evolves from a one-time control—for example, during registration or account opening—into a continuous process capable of analyzing signals throughout the user’s interactions. Companies are moving beyond validating isolated documents or attributes and toward combining identity, behavioral, device, contextual, and other signals.
To help prevent digital fraud, organizations can rely on mobile identity APIs that strengthen authentication and identity security. At Plusmo, we have developed a comprehensive set of tools designed to help protect transactions against fraudulent activity.
