Key Takeaways
Artificial intelligence (AI) will continue shaping fintech in 2025, driving efficiency in trading and compliance. The EU’s AI Act, effective in 2025, will impose strict rules on high-risk AI applications, creating both opportunities and challenges for financial institutions.
While the U.S. adopts a more relaxed approach, the EU’s regulations may push innovation to more flexible regions. How institutions navigate these changes will impact AI adoption in the sector.
AI will remain a key focus in fintech throughout 2025. As the initial hype around Gen-AI settles, financial institutions are gaining a clearer view of AI’s viability across operations.
However, according to Taylor Wessing analysts, interest in AI-driven solutions will persist wherever they enhance efficiency— from front-office functions, like securities trading and investment research, to back-office compliance, fraud prevention and internal monitoring.
“Fintech firms demonstrating strong AI capabilities will continue to attract venture capital and strategic partnerships or acquisitions from incumbents,” the experts said.
The EU regulatory environment is also evolving. The first rules under the EU AI Act will become operational on Aug. 2, 2025, but they will be fully implemented next year.
“This will make the EU the largest jurisdiction with a comprehensive AI regulatory framework, impacting financial institutions both as AI providers and users. The Act imposes strict requirements on high-risk AI applications, such as credit scoring and creditworthiness assessments, and transparency obligations for AI interacting with consumers, like chatbots,” according to the analysts.
Financial institutions will likely face significant compliance challenges , particularly where AI is used for lending decisions, recruitment and staff performance monitoring.
The open finance framework is set to drive the development of more efficient and personalized financial services in the EU. Additionally, it will likely encourage the expansion of fintech by enhancing embedded finance, API infrastructure and the development of innovative superapps.
According to Moody’s, banking leaders, like JPMorgan Chase, are already integrating AI across operations.
These integrations include AI assistants for fraud detection and claims processing in insurance. Asset managers also use AI to automate tasks and enhance efficiency. Though high implementation costs mean full benefits will take time to materialize.
Giovanni Cattani, an AI expert and investor, told CCN, “AI will deeply transform legacy industries worldwide over the next decade. Its impact on financial institutions will be massive, offering significant benefits to both consumers and corporate clients.”
Diverging AI regulations could deepen global disparities in adoption and competitiveness. A Donald Trump presidency that prioritizes U.S. competitiveness is likely to maintain a hands-off AI oversight approach. This is expected to benefit tech firms by reducing constraints.
Meanwhile, the EU AI Act imposes strict compliance costs, raising concerns that it could stifle innovation and push investment toward more flexible markets. Smaller firms may struggle with regulatory demands, consolidating the AI sector around larger players, as warned in the Draghi report.
“With the EU AI Act, financial institutions in the EU now have a legal framework to develop AI-powered products and internal AI solutions. For entrepreneurs, this regulatory clarity brings the hope of leveraging the EU’s large single market to scale their companies rapidly across the continent,” Cattani added.
China has taken a more balanced approach, combining targeted regulations with pro-innovation policies. The Cyberspace Administration of China (CAC) enforces algorithmic transparency and content moderation. At the same time, it promotes domestic AI leadership, maintaining oversight without hindering growth.
The U.K., by contrast, follows a flexible, sector-specific approach, with ongoing consultations on AI governance. Similarly, Hong Kong’s SFC issued guidelines on large AI models and launched an AI sandbox for banking sector experimentation.