Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Pedro Bizarro, Chief Science Officer at Feedzai
Where there is money – or even pseudo-money – there is fraud risk. The rise of artificial intelligence and digital currencies is exacerbating this risk. Today fraudsters are using generative AI tools to craft tailored phishing messages, clone voices, and design synthetic identities that mimic legitimate behavior. Automation is enabling them to quickly scale by producing thousands of scam variations at once, learning from each attempt to refine the next. What once required hours of manual effort can now be assembled in minutes, allowing attackers to outpace defenders bound by traditional review processes and systems. Combined with real-time payments and digital currencies, deception is unfolding at machine speed.
The impact is significant. Feedzai’s Global State of Scams 2025 Report reported that 57% of adults worldwide encountered a scam in the past year and 23% of them lost money. The same report found that scam losses reached an estimated $442 billion globally.
While data suggests that attackers prefer common and familiar channels where trust is already established – bank transfers accounted for 29% and credit cards for 18% of scam payments in 2025 – fraud techniques will increasingly mimic real customer behavior in the coming year, making static rules ineffective. This puts many consumer-facing businesses in a challenging position, as delays and friction can negatively impact customer experience.
To make quick and confident decisions that protect consumers, financial organizations need to adopt trusted, continuous intelligence tools that learn and adapt as quickly as criminals do.
Real-Time AI Will Become Mandatory in Payments
In a world where instant payments are growing globally for both personal and professional use – J.P. Morgan projects a 289% increase in transaction value processed by 2030 – fraud prevention must move beyond the transaction itself. Financial institutions must continue to adopt models that assess behavioral patterns, device intelligence, and transaction context in real time. These systems operate within fractions of a second, allowing institutions to intervene before funds move irreversibly.
Real-time AI alone is not enough, though. Humans are crucial for contextual interpretation, ethical judgment, and an instinctual understanding of suspicious dynamics that data alone cannot capture. Blended intelligence needs to be the operational norm, with analysts and data scientists working in lockstep to solve their shared challenges.
AI Progress Will Favor Practitioners
As the AI buildout doubles down on ROI, real value will not come from hype, but instead from a combination of deep industry expertise and responsible innovation. Success will belong to practitioners who pair strong infrastructure with rapid model iteration and clear governance. Organizations that have invested in strong data foundations and the ability to innovate responsibly and quickly will be best positioned to respond to evolving threats in 2026.
Collaboration Will Define the Next Stage of Defense
Fraud moves across institutions, geographies, and ecosystems. No single organization can combat AI-enhanced scams alone. Collaboration needs to accelerate as banks, fintechs, and payment networks expand intelligence-sharing to detect mule networks and identify emerging scam patterns. Shared signals and coordinated analytics will go a long way in strengthening defenses across the entire ecosystem.
AI will continue to power fraud in 2026, but it will also enable strong industry defenses. The institutions that lead will be those that invest in resilient infrastructure and pair human judgment with machine speed.
##
ABOUT THE AUTHOR
Pedro Bizarro is co-founder and Chief Science Officer of Feedzai, where he leads the Research department. Drawing on a history in academia and research, Pedro helped to develop Feedzai’s industry-leading RiskOps platform to fight financial fraud using innovations from the Research team. Pedro is also an invited Visiting Professor at Universidade de Lisboa – IST, Member of the Global Innovator Programme at the World Economic Forum, has been a visiting professor at Carnegie Mellon University, a Fulbright Fellow, and holds a Computer Science PhD from the University of Wisconsin-Madison. Pedro is co-author of more than 100 scientific publications and more than 90 patent applications. Pedro’s main interests are high-performance systems for data processing, machine learning, responsible AI, and data visualization. Pedro is also an avid runner and an Ironman.
