Outpacing Security: A Cyber Resilience Mandate For Modern Leaders

Forbes

02-05-2025

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Fraud is as old as commerce itself. From Ponzi schemes to phishing scams, bad actors have always exploited moments of technological or systemic transition. But with the rapid emergence of artificial intelligence, we've entered a new era—one where the tools used to enhance performance, automate workflows, and elevate customer experience are also being weaponized in real time.
At EXCELR8, we've work closely with global banks and enterprise institutions for years - often with their digital and IT divisions. What we're seeing firsthand is that AI's transformative promise is accompanied by an equally urgent need for robust, adaptive cybersecurity strategies. In other words, when the way we work and interact changes this fast—so too do the threats.
According to Team8, AI-powered impersonation attacks increased by over 300% year-over-year—making financial scams the fastest-growing category of fraud in banking. What was once limited to clever emails and forged documents is now a world of deepfakes, synthetic identities, voice clones, and hyper-personalized scam attempts that can be deployed at scale.
In efforts to dig deeper, I reached out to some experts. As fellow tech founder and entrepreneur Roy Zur - CEO of Charm Security - puts it, 'Generative AI has dramatically amplified scam risks for financial institutions by enabling highly convincing scams at scale. Financial losses are only part of the story—it's also about reputational damage, trust erosion, and regulatory exposure.'
For many of today's leadership teams - depending upon the industry, fraud prevention can no longer be confined to the domain of cybersecurity or compliance alone—it has become a core business imperative, demanding organization-wide alignment. As generative AI accelerates both the sophistication and scale of fraudulent activity, executive accountability has expanded accordingly.
Encouragingly, 84% of senior bank executives and board members now identify scams and cyber-enabled fraud as top-tier threats, according to Bank Director's 2025 Risk Survey. Yet despite this heightened awareness, most institutions still lack a comprehensive, cross-functional strategy—particularly one that addresses the human element of fraud: behavioral vulnerability, organizational blind spots, and the cultural norms that shape how risk is recognized and escalated.
Financial institutions are leading the way in this area. Banks like JPMorgan Chase, which suffered $500 million in losses due to fraud last year, are now using AI models that continuously learn from new data to detect and block suspicious activity, resulting in lower levels of fraud and a better customer experience, with account validation rejection rates cut by 15-20 percent.
Ironically, the very technologies that introduce new risks also represent our best defense. From machine learning that monitors behavioral anomalies to generative AI agents that model fraud scenarios before they occur, cybersecurity is evolving into a predictive discipline.
Global banks are now deploying AI tools to:
Even more advanced institutions are running AI-powered red-team (a process we used in the Navy SEAL teams to poke holes on our mission plans) simulations to proactively train fraud teams in real-time scam defense—ensuring organizations are prepared for evolving threat vectors before they materialize.
At EXCELR8, we've observed how these security advancements must be embedded not just into tech stacks, but also into leadership thinking, culture, and execution platforms.
Gone are the days when fraud prevention was relegated to a risk department or IT function. In today's landscape, cybersecurity must be a cross-functional priority that spans operations, leadership, product, and workforce enablement.
What we're seeing in our work with enterprise organizations is a shift toward shared ownership models:
This is where organizations often fall short—not in tools, but in coordination. And that's what separates the reactive from the resilient.
Despite advancements in AI-driven security, human error remains one of the most vulnerable entry points. Social engineering, phishing, and manipulation still succeed because systems are fallible—but so are people.
Leading institutions are changing that. We've seen them go beyond standard compliance training and implement:
Cybersecurity awareness is becoming less of a task and more of a team trait. It's about creating a workforce that doesn't just follow security protocols—but thinks in terms of security instinctively.
The next era of organizational growth will not be shaped solely by AI innovation—but by how confidently and securely that innovation is deployed. It's about building environments where velocity and vigilance coexist.
Enterprise AI must be built on trustworthy, transparent systems that support secure collaboration, role-specific visibility, and AI-driven decision support—without ever compromising data privacy, regulatory integrity, or user autonomy.
In our work with financial institutions, we've seen that the most successful leaders don't just prepare for cyber threats—they engineer resilience into the organization itself. They combine advanced technology with governance. They pair performance acceleration with risk mitigation. They understand that if speed is the strategy, security is the foundation.
AI will continue to redefine how we operate, compete, and collaborate. But it's not neutral. It amplifies whatever systems, behaviors, and risks we've already built. Which is why every conversation about innovation must be matched by a conversation about integrity, security, and trust.
Because in the age of intelligent systems, fraud prevention isn't just a function—it's a leadership mandate.