Fraud is evolving at breakneck speed, accelerated by the wide-spread use of artificial intelligence (AI). For financial institutions (FIs), the rise of AI presents both a threat and an opportunity: fraudsters are using the technology to carry out more sophisticated scams, while banks and payment providers are deploying AI to strengthen defenses.
The reality? We’re in the middle of an AI cat and mouse game, which could put customers in harm’s way.
What is AI fraud?
AI fraud refers to the use of artificial intelligence to automate, scale, or enhance fraudulent activities. Examples include synthetic identities that can pass traditional checks, AI-generated voice clones used in scam calls, and deepfakes that trick onboarding or verification systems, or manipulate customers in scams like romance or impersonation scams.
Unlike older fraud schemes that relied on more skill and manual effort, AI-powered scams can be launched fast, with little skill required, and on a massive scale.
The rise of AI-enhanced threats in digital banking
Today, fraudsters are combining deepfakes, synthetic identities and video injection (an attack where manipulated video content is added to a video to bypass security measures) in their attack vectors. That means extremely convincing attacks that are more likely to fool and bypass a bank’s security measures.
Synthetic identity fraud: Fraudsters use AI to combine stolen and fabricated data into convincing new “identities,” making onboarding attacks harder to detect. A recent industry survey found that 72% of financial institutions encountered synthetic identity fraud at onboarding.
Deepfake and voice cloning scams: Criminals use AI voice generators to impersonate victims, bypassing phone-based authentication. Fraudsters also use voice cloning and deepfake video technology to manipulate their victims in social engineering scams, pretending to be a person’s relative, for instance. Some FIs are already reconsidering their use of voice biometrics after seeing how easily AI can mimic speech patterns.
Co-ordinated bot-driven fraud: Automated scripts powered by AI can overwhelm fraud systems with account-opening attempts or credential-stuffing attacks. These attacks often happen in bursts, making them difficult to contain without real-time detection.
Let’s examine why these advanced attacks are more powerful than past attack vectors.
Why AI fraud is often effective
The danger lies in its capabilities for scale and believability. AI reduces the cost and time it takes to launch an attack while making scams appear more authentic. Where a fraudster once needed hours to create a fake ID, AI can generate hundreds in seconds. Similarly, a single fraudster can now run bot networks capable of attacking thousands of accounts simultaneously.
In social engineering scams, the high-quality video and voice impersonation capabilities made possible through AI trick even tech-savvy individuals into becoming a victim.
The solution: Fighting AI fraud with AI
While criminals innovate, financial institutions cannot afford to stand still. Today, outdated authentication measures like one-time passcodes (OTPs) are ineffective in safeguarding banks from AI-enhanced fraud.
However, modern AI-driven defenses, like data-driven authentication, can turn the tide:
Real-time fraud detection: AI systems can act like fraud “radars” flagging coordinated fraud attempts within seconds, enabling teams to block suspicious activity before losses occur.
Behavioral analytics and adaptive risk scoring: By learning a user’s normal patterns — from their device to login behavior and transaction habits — AI and data-driven tools can identify anomalies that appear suspicious. These red flags may be a sign of fraud, so the risk engine determines a risk score and takes the appropriate action, such as blocking the transaction or requiring an additional confirmation from a customer.
These AI-enhanced fraud prevention tools not only reduce fraud but can also minimize friction for legitimate users, helping FIs strike the balance between security and customer experience.
Building synthetic resilience to evolving banking fraud
Defending against AI fraud isn’t just about deploying smarter tools — it’s about building resilience. For financial organizations, that means:
Integrated risk intelligence: Moving beyond siloed detection to fraud prevention systems that provide transparent, auditable results sharing vital contextual data points across all channels.
Collaboration across the industry: Fraud and fraud patterns are typically not unique to each bank. Intelligence-sharing and joint initiatives are key to anticipating and preventing new and ‘upgraded’ old fraud tactics .
A layered authentication approach: A layered approach to authentication reduces the risk of AI-enhanced fraud, like deepfake voice cloning being successful.
Keeping ahead of the fraud curve with modern authentication
As AI models become more advanced, they may pose more of a threat to financial institutions and their customers — in the wrong hands. From deepfakes to synthetic identities and AI agents or other bot-driven attacks, the more sophisticated, automated and scaled up these attacks become, the more vulnerable customers become. Yet the same technology that enables these threats can also equip banks with the tools to fight back.
By adopting AI and data-driven fraud detection and fostering collaboration, financial institutions can keep ahead of evolving fraud, like AI-fraud, safeguarding their customers today and in the future.