Democratizing Fraud Prevention

Talking Trends

Technological progress in the electronics sector has historically followed cycles of invention, adoption, and maturity. Today, however, the pace of change is accelerated by digitalization, increased data flows, and the convergence of technologies such as artificial intelligence (AI), the Internet of Things (IoT), and advanced semiconductors.

Dr. John Mitchell, President & CEO of the Global Electronics Association, Paul Breitenbach, Founder & CEO of r4 Technologies, and Ian Tien, CEO of Mattermost, join Nasdaq TradeTalks to discuss reshaping the electronics industry and key initiatives around workforce, sustainability, and next-gen technologies. These changes have cascading effects across industries, influencing policy choices and redrawing the contours of international trade.

The electronics industry is being reshaped in real time by coordinated efforts in workforce development, sustainability, and technological innovation. This transformation is not confined to manufacturing plants or R&D labs. It reverberates through industries, prompts new policy frameworks, and reshapes international trade. Navigating this dynamic landscape requires agility, collaboration, and a commitment to inclusive, responsible progress. Those who anticipate and adapt to these shifts will not only thrive but also help define the contours of the next era of global innovation. By prioritizing resilience and proactive threat mitigation, organizations can ensure trust and safeguard the broader transition to a digital, connected future.

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From your perspective, what are the biggest trends shaping the future of artificial intelligence?

I see the biggest trend as a shift from AI hype to AI practicality. We're moving past the headlines and buzzwords toward tangible applications that actually solve real problems. The key distinction I'm watching is between informational AI and actionable AI. Too many solutions today can tell you something is wrong but leave you hanging with what to do about it. The future belongs to AI that completes the loop — identifying the risk, prescribing the action, and enabling you to execute that action seamlessly.

In your recent TradeTalks interview, you noted how bad actors are "using the same efficiency measures from AI to do all of their old tricks." How should companies think about using AI to combat financial crime? What are some of the best practices you’ve seen?

I push back on the narrative that AI is making fraud more sophisticated; rather, it's making fraudsters more efficient and effective at the same old tricks they've been doing for decades, such as identity theft, account takeover fraud, and social engineering scams. The good news is that financial institutions are also using AI to combat these types of fraud. The best practice I see is leveraging AI to get ahead of fraudsters rather than always playing catch-up — that means identifying fraudsters at onboarding, rather than after they’ve already infiltrated a product and stolen money. Mountain America Credit Union, for example, has implemented proactive policies to decrease potentially fraudulent applications by 30% while maintaining excellent member experiences.

What is needed to democratize fraud prevention across industries and geographies?

To democratize fraud prevention, we need to stop treating it as a cost center and start seeing it as a growth driver. When banks and fintechs can automate most manual reviews while actually increasing approval rates for good customers, everyone wins — institutions grow faster, and good customers get the financial products they need without friction. The technology exists today to make this accessible to any financial institution, regardless of size or location, turning fraud prevention into a powerful tool for business growth.

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