AI Arms Race Is Radically Reshaping the Fraud Threat in EMEA, FICO Research Finds

Among EMEA institutions surveyed, 86% see a unified, enterprise-wide fraud strategy as essential.

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Global survey of financial institutions on fraud protection shows 25%+ rise in fraud attempts for one-third of EMEA financial institutions as fraud complexity increases

LONDON--(BUSINESS WIRE)-- New research from FICO (NYSE: FICO), a leading global analytics software firm, shows that fraud leaders across Europe, the Middle East and Africa (EMEA) are grappling with rising fraud complexity and AI-enabled threats, even as they accelerate investment in AI-driven detection and enterprise-wide fraud strategy. The findings, drawn from FICO's global survey of 202 senior fraud, risk and technology professionals at retail banks, neobanks and fintechs, show that 52% of EMEA institutions now cite increasing fraud complexity as their leading fraud prevention challenge, compared with just 40% of global firms. And nearly half ranked effective AI integration as a top challenge, underscoring that embedding AI into existing fraud controls remains as much an operational hurdle as a technological one.

More information: https://www.fico.com/en/latest-thinking/ebook/fraud-age-ai-insights-emea

Highlights

• More than one-third (36%) of EMEA institutions report fraud attempts rising by more than 25% over the past 24 months
• 28% reported that financial losses from fraud grew more than 25% over the past 2 years
• Effective AI integration ranks as a top challenge for 48% of EMEA respondents, closely mirroring the global response

“Fraud in EMEA is not accelerating out of control, but it is becoming far more sophisticated, and that shift matters just as much,” said Adam Davies, vice president, Product Management at FICO. “Fraudsters now have access to the same generative and agentic AI tools that banks are deploying to stop them, and they are using them to scale social engineering, synthetic identities and deepfake-enabled attacks. The institutions pulling ahead are the ones connecting their fraud functions across the enterprise and orchestrating every intelligence source they have, rather than adding point solutions one at a time.”

Other highlights from the FICO research for EMEA:

• EMEA respondents rate AI-enhanced fraud (4.42 out of 5) and social engineering scams (4.36) as more significant threats than the global average (3.86 and 3.90 respectively), with synthetic identities (4.02) and deepfake fraud (3.96) also outpacing global concern levels
• 86% of EMEA institutions see a unified, enterprise-wide fraud strategy as essential, with 38% already treating it as a critical priority and 48% pursuing it as a longer-term focus
• Half (51%) of EMEA institutions report false positive rates above 15%, creating friction for legitimate customers even as fraud controls tighten
• Third-party vendor models now carry the greatest influence over EMEA fraud decisions (46%), far more than in-house models (24%), reflecting growing reliance on external expertise to keep pace with evolving threats

“The next 24 months will be defined by orchestration, not by any single piece of technology,” Davies added. “EMEA institutions have already built strong foundations in AI-driven detection, and confidence in agentic AI is particularly high in the region. What’s needed now is the connective tissue: bringing in-house models, vendor intelligence and consortium data together so fraud teams can act on a complete picture in real time, without pushing more friction onto legitimate customers.”

Davies points out four priorities for financial institutions in their fight against fraud:

1. Close the deployment gap by moving AI from pilot to production at enterprise scale. “You should prioritize what works within disciplined fraud control frameworks rather than launching yet more pilots,” he noted.
2. Invest in active orchestration across models, channels, products, and portfolios so that shared signals shape fraud management decisions in real time.
3. Apply risk-based, outcome-driven prioritization to balance competing investment demands, led by financial impact and regulatory exposure.
4. Treat fraud prevention and customer experience as a single, connected challenge. “The organizations that can do both will be the ones that define competitive advantage in this era,” Davies said.

FICO® Enterprise Fraud Solution, powered by FICO® Platform, addresses the full spectrum of fraud, from synthetic identity and application fraud to real-time payment scams and account takeover. Its composable, API-first architecture integrates with existing systems without requiring a rip-and-replace, while AI and ML models trained on billions of tagged transactions from a consortium of more than 10,000 financial institutions help drive detection accuracy while reducing false positives. Generative and agentic AI capabilities further accelerate investigation and decision-making, and digital simulation tools allow fraud teams to test and tune strategies before deployment.

About FICO

FICO (NYSE: FICO) powers decisions that help people and businesses around the world prosper. Founded in 1956, the company is a pioneer in the use of predictive analytics and data science to improve operational decisions. FICO holds more than 200 US and foreign patents on technologies that increase profitability, customer satisfaction and growth for businesses in financial services, insurance, telecommunications, health care, retail and many other industries. Using FICO solutions, businesses in more than 80 countries do everything from protecting 4 billion payment cards from fraud, to improving financial inclusion, to increasing supply chain resiliency. The FICO® Score, used by 90% of top US lenders, is the standard measure of consumer credit risk in the US and has been made available in over 40 other countries, improving risk management, credit access and transparency. Learn more at www.fico.com.

FICO is a registered trademark of Fair Isaac Corporation in the United States and other countries.

View source version on businesswire.com: https://www.businesswire.com/news/home/20261005046807/en/

For further press information please contact:
FICO UK PR Team
Wendy Harrison/Matthew Enderby
ficoteam@harrisonsadler.com
0208 977 9132

Source: FICO

Key Terms

agentic ai technical

Agentic AI refers to computer systems that can make their own decisions and take actions without needing someone to tell them what to do each time. It's like giving a robot a degree of independence to solve problems or achieve goals on its own, which matters because it could change how we work and interact with technology in everyday life.

synthetic identities technical

Synthetic identities are fake customer profiles created by combining real and fabricated personal details—like pieces of different IDs, Social Security numbers, or addresses—to open accounts, obtain credit, or hide transactions. For investors, they matter because this kind of fraud can inflate loan books, hide losses, trigger regulatory fines, and damage a lender’s trust and profitability; think of it as termites quietly weakening a building’s foundation until the damage becomes obvious.

false positive rates technical

The false positive rate is the share of cases that are actually negative but are incorrectly identified as positive by a test, screening tool, model, or detection system; numerically it is calculated as false positives divided by the sum of false positives and true negatives (FP / (FP + TN)). It measures how often a method cries wolf and is distinct from related measures such as the false discovery rate (which conditions on positive test results) and sensitivity; it does not depend on how common the condition is but does depend on the test's decision threshold and operating characteristics.

api-first architecture technical

An api-first architecture is a way of designing software where the programmable interfaces that let different apps talk to each other are planned and built before the rest of the product. Like designing standardized doorways in a building so future rooms and tenants can plug in easily, it makes a company’s technology faster to expand, easier to sell or partner with others, and simpler to maintain—factors that can speed product launches, reduce costs, and lower operational risk, all important to investors.