RBI Emphasizes Human Touch in Digital Banking
Artificial intelligence (AI) is reshaping the way corporate and institutional customers engage with their banks, yet Raiffeisen Bank International (RBI) leaders assert that AI will augment, not supplant, relationship banking in future. Sabine Zucker, Head of Group Transaction Banking, and Elitza Kavrakova, Group Head Institutional Clients, examine AI’s influence on banking.
Elitza Kavrakova notes that the biggest challenge for organizations today is adopting AI responsibly and effectively. Financial institutions and corporates face multiple challenges, including striking the right balance between innovation, regulatory compliance, cybersecurity, and data governance.
While AI can significantly improve efficiency and decision making, Kavrakova emphasizes that it should remain a co-pilot rather than an autopilot. Human judgment, accountability, and critical thinking remain indispensable, especially in areas such as risk management and compliance. Clients also continue to value human interaction, with technology enhancing the client experience but trust-based relationships remaining at the core of banking.
Changing Client Expectations
Client expectations are changing, with clients increasingly expecting real-time access to information, faster execution, greater transparency, and more proactive services from their banking partners. They are also looking for actionable intelligence that helps them anticipate developments and make better decisions.
AI will change the role of relationship managers from being information providers to becoming strategic advisors. At RBI, data-driven insights are already used to support client engagement, and AI can help relationship managers better interpret and understand client needs.
Transforming Transaction Banking
Sabine Zucker notes that customers are increasingly interested in a smooth and seamless interaction with their bank, requiring strong connectivity between banking platforms and clients’ treasury or bookkeeping systems. APIs play a major role in providing the basis for straight-through connectivity and supporting tailored client experiences.
The integration of AI into transaction banking could drive a new wave of innovation, including smarter liquidity management, predictive cash-flow forecasting, and advanced fraud prevention capabilities. This will help banks meet rapidly changing client expectations, such as the increasing use of instant payments and the demand for instant information on liquidity positions.
As RBI looks to the future, executives believe that successful AI adoption will require robust governance frameworks that address transparency, accountability, data protection, model validation, and human oversight. The combination of innovation, trust, responsible leadership, and a strong understanding of clients’ needs will be key to success.
Elitza Kavrakova is excited about developments in generative AI, predictive analytics, ecosystem banking through APIs, and the continued digitization of trade finance and cross-border transactions. These technologies are helping institutions move from reactive to predictive service models, and the winning model will blend human judgment, trusted relationships, and AI-powered intelligence.
