Introduction to AI in Fintech Operations
The implementation of Artificial Intelligence (AI) in financial technology (fintech) operations remains largely superficial, focusing mainly on automating secondary tasks, especially those related to customer service. According to Andrés Fontao, CEO of Finnosummit, a firm specializing in fintech innovation and research:
- Short-term impact: AI’s influence on financial services is currently shallow, primarily applied in areas like customer support, automating conversations or simple request responses.
- Long-term expectations: Fontao anticipates AI playing a more significant role in the medium to long term, making it crucial to start developing appropriate regulatory frameworks for its integration.
AI Adoption in Fintech Sectors
According to Finnosummit’s Fintech Radar 2025, wealth management leads AI adoption, with 81% of companies reporting its use. Digital banking follows closely at 73%, and technology infrastructure for banks and fintech accounts for 69%.
A key finding in the report is the high level of outsourcing in areas like user experience and general process automation. However, when it comes to more strategic functions such as predicting user behavior, developing machine learning algorithms, or fraud prevention, fintech companies tend to build internal solutions.
Regulatory Challenges Ahead
Fontao warns that as AI takes on increasingly critical roles in financial operations, regulatory advancement becomes essential:
“One of the main challenges will be adapting AI regulation, similar to what happened with cloud computing, mobile technology, or fintech itself. It’s crucial to ensure its ethical and responsible use.”
AI as a Driver of Financial Inclusion
On the positive side, Fontao highlights that AI adoption in the fintech ecosystem has increased user motivation. A survey of investors revealed that 31% felt more motivated due to new capabilities, partly enabled by AI technology.
The Fintech Radar 2025 report shows that AI has been a crucial tool for addressing traditionally excluded segments from the financial system, primarily those with low levels of banking access—a significant challenge due to limited information on their financial behavior.
- AI implementation in fintech: Of the fintech companies that reported using AI or machine learning solutions, 75% applied them to users with only one financial product, and 68% targeted non-banked users.
- AI’s potential for financial inclusion: Fontao suggests that AI integration into fintech software platforms will enhance operational capabilities and reach a larger user base more efficiently, making AI a key enabler for achieving these goals.
Key Questions and Answers
- Q: What is the current state of AI implementation in fintech?
- Q: Which fintech sectors are leading AI adoption?
- Q: What are the regulatory challenges posed by AI in fintech?
- Q: How can AI contribute to financial inclusion?
A: AI’s impact on fintech operations is currently limited, primarily automating secondary tasks like customer service.
A: Wealth management leads AI adoption, followed by digital banking and technology infrastructure for banks and fintech.
A: Ensuring ethical and responsible use of AI in fintech operations is a significant regulatory challenge.
A: AI has the potential to enhance fintech capabilities and reach a larger, more diverse user base, promoting financial inclusion.
