Banks are managing a surge of documents and adhering to regulations, while meeting customer expectations. This is where generative AI (GenAI) for the financial sector comes in: It automates document analyses, creates precise summaries, and generates personalized customer communication. Supplemented by traditional AI for fraud detection and risk assessment, the result is a powerful combination.
Technology alone is not enough. If you want to use GenAI successfully, you also need to involve the people who work with it. This includes an introduction that not only works technically, but also culturally – including training, a new understanding of roles, and active participation.
Because AI – finance generative AI – cannot replace specialists, but it can help them to make better decisions, act faster, and communicate in a more targeted manner. Banks that recognize this early on not only create efficiency, but also internal acceptance and trust.
What distinguishes GenAI from traditional AI, and why is their combination in the financial sector so powerful for digital transformation in banks?
Finance GenAI:
Classic AI:
The combination makes all the difference: while traditional AI ensures secure processes, GenAI takes the customer experience and process automation to a new level. Banks are already using both technologies – from chatbots that answer customer queries in real time to AI-supported analyses that minimize financial risks. But the key lies in striking the right balance: innovation and safety must go hand in hand.
Many banks are asking themselves: “Is the use of AI really safe?” Strict data protection and compliance regulations apply in the financial sector in particular. However, modern AI technologies now offer solutions that combine security and innovation.
T-Systems provides GDPR-compliant AI infrastructures that protect sensitive customer data and meet regulatory requirements. The combination of GenAI and traditional AI not only enables efficient automation, but also better risk control – from fraud detection to automated compliance with regulatory requirements.
Banks that invest now will not only secure technological advantages, but also the trust of their customers and supervisory authorities. So the question is no longer “Should we use AI?”, but “How do we use AI safely and sensibly?”
How are banks using GenAI and traditional AI today?
GenAI in practice:
Traditional AI for greater security:
The combination of both technologies creates a highly efficient, secure, and customer-friendly financial system. Banks that rely on AI increase efficiency and security in equal measure – and therefore have a clear advantage.
Hyperautomation: What data does GenAI really need?
Financial institutions have real data capital – but is it actually usable? If you want to integrate GenAI into your processes, you need to ask yourself a crucial question: “Is our data clean, structured, and understandable for AI?”
The truth is that GenAI is not a miracle cure automatically extracting knowledge from every piece of information. It requires well-maintained, high-quality data in order to deliver precise analyses, and meaningful content.
Structured data – organized, easy to retrieve, perfect for AI:
Unstructured data – chaotic, difficult to use, but full of potential:
The challenge: How do banks use this data for real added value?
Banks cannot afford to work with insecure or non-compliant data. GDPR, BaFin regulations and industry-specific guidelines define exactly what AI may – and may not – do with financial data.
The typical pitfalls in AI-supported data processing are:
The solution: Banks need a smart AI data strategy that combines security and innovation.
Conclusion: Without a data strategy, GenAI remains just a concept.
Banks that are rethinking and optimizing their data structures now have a clear advantage: more precise analyses, better automation, and regulatory security.
The use of GenAI in the financial sector requires not only innovation, but also security, scalability, and regulatory compliance. T-Systems offers exactly that: a GDPR-compliant AI infrastructure, powerful cloud solutions, and in-depth industry expertise.
Our strengths for banks and financial service providers are:
T-Systems supports banks – from the initial idea through to successful implementation – with a strong technology ecosystem, in-depth industry knowledge, and proven best practices.
AI-as-a-Service (AIaaS) is bringing movement to the world of AI – and significantly lowering the barriers to entry. Instead of setting up complex in-house developments, companies are turning to cloud-based AI services that are flexibly scalable and ready for immediate use.
This is particularly important for banks: faster integration, less complexity, and clearly calculable costs. AIaaS makes it easier to access powerful models without overburdening your own IT infrastructure.
T-Systems and UiPath are pooling their expertise to make exactly these advantages available: With platforms that are not only technological leaders, but also satisfy the stringent requirements for data protection, compliance, and reliability in the financial sector.
In short: users of AIaaS don't compromise on quality; instead, they gain speed, flexibility, and future-proofing.
GenAI has long moved beyond being just an experiment; it is now a key driver of innovation in banks and financial institutions. However, its implementation requires clear strategies to address challenges at an early stage:
Ethical and regulatory responsibility
Technical integration and data strategy
Change management and acceptance
A proof of concept helps banks to test the feasibility and added value of AI. T-Systems not only offers scalable AI infrastructures, but also its experience gained from numerous successful financial projects.
The introduction of GenAI is not an isolated IT measure, but a part of a comprehensive, strategic transformation. Banks that rely on individual solutions quickly reach their limits: fragmented data flows, lack of scalability, and redundant systems.
That's why we need a strong ecosystem in terms of technology and partnership. The combination of GenAI, traditional AI, cloud infrastructure and process expertise only delivers its full potential when it works seamlessly together.
T-Systems has these precise strengths: industry knowledge, regulatory understanding, platform expertise, and long-standing partnerships with leading AI providers.
Together, we create scalable, secure and sustainable solutions – not only for quick success, but also for future-proofing financial IT. Those who think as a network today will have the advantage tomorrow.
GenAI will continue to gain importance in the coming years; but what are the next developments?
One thing is clear: investing early secures long-term competitive advantages.
But this future will not happen by itself. It needs strategic vision, technological expertise, and the courage to embrace change. Do you still have concerns about advanced AI? Work with it. GenAI is becoming an integral part of modern financial architectures – for all those who not only want to join in, but also want to help shape them. Now is the right time to position yourself in a targeted manner.
