AI: Banks see the Potential
Blog
10/27/2026
Artificial intelligence is also making its way into the banking industry. However, there is a gap between interest in this technology and its actual implementation. A recent survey in the Finstar Community shows that while banks see opportunities for advisory services, innovation, and business models, they lack strategies, expertise, and a clear regulatory framework.
A Current and Important Topic
As part of the Finstar Community Event 2026, Finstar AG surveyed executives from its banking community on the role and potential of AI. The survey, conducted by the Lenzburg-based banking software company, targeted C-level executives and examined the topic across twelve areas—ranging from advisory services and organization to regulation, strategy, and employees. The high response rate of over 60% underscores the timeliness and importance of the topic within the industry. One key finding upfront: Overall, it is clear that there is no AI euphoria among the respondents; banks see potential but are still seeking answers to key questions.
Faster Pace of Innovation
This ambivalence is clearly evident in customer advisory services: The majority of respondents expect AI to contribute to better advice. It remains to be seen to what extent customers will trust AI recommendations. Bank advisors will continue to play an important role in the future, especially when it comes to complex issues. This points to a division of labor in which AI handles preparation, analysis, and routine tasks, while humans address complex issues, trust-intensive matters, and customized solutions. Banks do not see a sustainable competitive advantage in relying solely on AI, but expectations are high that AI will enable new business models and accelerate the pace of innovation.
Size Is Not an Advantage
According to the study’s findings, the ability to use AI efficiently and effectively is more important than the size of the bank. What matters most is how quickly institutions identify relevant, bank-specific use cases, how they make their data usable, and how they integrate AI into their processes. This is precisely where respondents identify shortcomings: The majority of banks lack a clear AI strategy and objectives, and the topic is not sufficiently embedded within the organization. At the same time, with few exceptions, there is a lack of both specific budgets and internal technical resources. On the one hand, employees’ AI knowledge is considered somewhat inadequate; on the other hand, training opportunities are insufficient. This is noteworthy, given that employees’ acceptance of AI tends to be viewed positively.
Digital Sovereignty
The latest AI survey in the Finstar Community provides a particularly clear picture regarding the technological foundation: Dependence on foreign, globally active AI providers is perceived as a risk, and there is interest in bank-proprietary models and strong digital sovereignty. However, according to the banks surveyed, high-quality data and the integration of AI into specific banking processes are more important than the choice of an AI model. This brings into focus aspects that go far beyond the question of whether to use AI or which provider to choose. Data quality, software architecture and flexibility, interfaces and process integration, governance, and compliance are becoming fundamental prerequisites for the targeted, productive use of artificial intelligence in banks.
No regulation
The regulatory environment is causing additional uncertainty and delays: The current legal requirements are almost unanimously deemed insufficient. At the same time, the relevant regulatory processes are considered too slow compared to technological developments. This uncertainty entails higher risks and delays in AI investments—increasing the danger of falling behind. Against this backdrop, the banks surveyed believe that the importance of technology partners will continue to grow in the future. On the one hand, AI is expected to support a large portion of software development and make banking software vendors more productive. On the other hand, the study confirms a key tenet of Finstar: sustainable banking is not created by technology alone, but through the convergence of software engineering expertise, banking know-how, regulatory expertise, and close collaboration with financial institutions.
AI, yes, but…
The survey shows that the Finstar community is largely positive about AI in banking. The technology is associated with new business models and a faster pace of innovation, though there are also uncertainties regarding regulation, risks, advisory services, and benefits. For banks, the next step is to define where AI creates real added value for them and what skills and data are required for the targeted implementation of their bank-specific strategy—these are precisely the aspects that Finstar will continue to explore with its community in the future.
Finstar with a Solid Foundation
The Finstar community agrees: Artificial intelligence is transforming banking. AI enables proactive, comprehensive advice, intelligent assistants, and customer- and context-specific financial products. With its early investments in open banking and an open, modular system architecture, Finstar has laid a solid foundation for targeted AI integration. The use of AI accelerates Finstar’s development cycles and enables the faster implementation of new, banking-specific business models. When implementing its solutions, the banking software provider consistently relies on new consent and delegation models to ensure that the defined AI agents can act securely, in the best interests of customers, and within defined internal banking and regulatory guidelines.
Integration Instead of Isolation
Finstar integrates AI solutions into existing IT infrastructures and connects its clients with the relevant AI entities in the industry. This enables the Lenzburg-based pioneer to accelerate the implementation of practical, regulatory-compliant solutions. As a result, banks that open their platforms to ecosystems and AI agents become the infrastructure for the next generation of financial service providers. Thanks to its openness, API-first approach, and forward-looking AI solutions, Finstar ensures participation in the agent-based AI financial sector and the success of its client banks—isolated financial institutions are transformed into an integrated ecosystem comprising banks, fintech companies, regulators, and technology platforms.
(Translation with deepl.com; the German version is authoritative).