The Role of AI in Fraud and Cybersecurity

The current state of AI in cybersecurity

AI has existed for decades, but recent advances have pushed it into the spotlight. Why is it dominating headlines now, and what does today’s AI landscape really look like?

Over the past decade, AI innovation has seen explosive growth thanks to breakthroughs in big data, machine learning and computing power. The landmark 2017 paper, Attention Is All You Need, paved the way for advanced models like ChatGPT, making powerful AI tools widely accessible.

Jaime Dickerson of Fiserv described AI as a “super brain” able to process massive volumes of data far faster than any individual while recognizing patterns in human-like ways. Its strength lies in efficiency, scalability and prediction. Still, she noted that it’s a force multiplier, not a replacement for human insight.

Understanding types of AI is essential for businesses adopting these tools. Traditional AI focuses on predictive analytics and forecasting outcomes. Generative AI creates new content—voices, videos, images and text. While innovative, generative AI fraud risks are significant when these tools fall into the wrong hands.

Another important distinction is open versus closed AI systems. Open systems, like ChatGPT, are accessible and affordable but vulnerable to misuse. Closed systems offer greater control and privacy, though they may introduce cost, bias or transparency concerns. If your business is implementing AI for daily operations, consider carefully whether an open or closed system is a better fit. Choosing the right model is a foundational business fraud prevention strategy.

An interconnected world where efficiency meets exposure

Modern businesses depend on interconnected systems—cloud platforms, collaboration tools, IoT (internet of things) devices and third-party vendors—to operate efficiently. This connectivity drives growth, but it also creates cybersecurity vulnerabilities by expanding the digital attack surface.

Each new integration creates another potential entry point for bad actors. The risk is real and the data proves it:

• 59% of organizations have experienced a third party-related data breach.
• The average enterprise shares sensitive data with an average of 583 external companies (per a 2018 data risk study conducted by Ponemon Institute).
• In 2024, 35% of breaches involved third-party vendors.

As Fiserv’s Dickerson summarized in the webinar, “Connectivity gives us incredible efficiency and real-time insight, but it also introduces new, often hidden risks.” And that modern reality makes managing third-party exposure a core pillar of cybersecurity best practices for businesses today.

AI-powered and AI-driven fraud detection threats

Fraudsters are now using AI to scale attacks faster, cheaper and more convincingly than ever. Sophisticated, industrial-sized scams no longer require technical skill or weeks to coordinate—just access to the dark web.

Losses tied to generative AI fraud are projected to reach $40 billion by 2027, with voice-cloning scams alone expected to cause $25.6 billion in losses by 2033. These numbers underscore the urgency of modern financial fraud detection technology.

Key AI-driven fraud trends include:

• Generative AI Malware: Tools like WormGPT and FraudGPT generate phishing emails, fake websites and malicious code with minimal effort.
• Mass-Produced Content: AI personalizes thousands of phishing emails and smishing text messages targeting victims simultaneously, using personal details mined from social media.
• Fraud-as-a-Service: Ready-made scam kits sold to fraudsters online include phishing templates and fake ID generators.
• Bot-as-a-Service: Rentable AI bots mimic human behavior by completing tasks like filling out online forms and bypassing authentication systems.
• Deepfake Fraud: Synthetic, legitimate sounding video or audio impersonations of executives contact victims requesting urgent payments.

Despite their sophistication, these scams aren’t unbeatable. Human instinct remains the most powerful tool—if something feels off, it’s probably good to be suspicious. Deepfake fraud prevention starts with skepticism and verification.

Organizational challenges in AI security and fraud prevention

While AI-driven fraud detection is advancing, many organizations struggle with implementing strong security measures. Limits to technology, resources and operational processes can hinder fraud detection with obstacles including:

• Incomplete or poorly managed datasets
• Legacy systems and siloed data environments
• Budget, resource and staffing constraints
• Competing IT and security priorities
• Limited cross-departmental visibility

Strong AI fraud prevention is dependent on collaboration, shared ownership and consistent communication across teams. Silos don’t just slow response—they create blind spots fraudsters can exploit.

Best practices for AI-driven fraud prevention and cybersecurity

There is no single tool that eliminates all fraud. As Dickerson noted, “The strongest defense is a layered approach, combining technology, process and people to stay resilient against AI-driven threats.”

These foundational tools and best practices can reinforce each other:

• Ongoing employee training and attestations (your people are your first line of defense)
• Cross-functional collaboration to eliminate silos and prevent blind spots
• Keystroke encryption to protect data at entry
• Secure protocols like HTTPS, TLS and MFA (multifactor authentication)
• Network segmentation to limit breach impact
• Encryption and tokenization of sensitive data
• Regulatory compliance (PII, PHI, PCI, GDPR, etc.)
• Reporting suspicious activity to the FBI or other relevant authorities

Many organizations also benefit from AI-driven fraud detection tools that identify anomalies, prevent impersonation and flag abnormal transactions in real time. Your financial institution can help determine the right fit.

As Associated Bank, we offer a full suite of fraud protection solutions, including Positive Pay for checks and electronic payments, Check Block and ACH Block—all designed to prevent unauthorized transactions before funds leave your account.

If you choose to implement AI tools at your organization, keep your data clean, your defenses fast, your oversight strong and your compliance in check.

Secure your company’s future with smarter defenses

AI has rewritten the rules of fraud and cybersecurity. Threats are faster, more scalable and more convincing—but businesses can still hold the power.

With layered defenses, ethical oversight and the right partnerships, organizations can stay ahead of evolving AI security threats. Understanding AI—its promise and its risks—is the first step toward building smarter, more resilient defenses.

To further strengthen your protection, explore our comprehensive fraud prevention services. Contact us today at Treasury@AssociatedBank.com to learn how we help safeguard your funds—and your future.