Banking.Vision
Until now, internal auditing has looked in the rear-view mirror to determine whether traffic rules have been followed. But in a world where autonomous AI agents make decisions about loans, investments and market entries in milliseconds, the classic audit cycle is no longer appropriate. We are facing a ‘zero moment’: Audit must decide whether it will remain a footnote to digitalisation or become the central navigation system for management.
Banking.Vision
AI in trading optimizes speed. AI in treasury controls stability. Both worlds use similar technologies but pursue completely different goals. Anyone who thinks of treasury in the same way as trading underestimates the complexity of bank management. This is precisely where the actual AI transformation begins.
Banking.Vision
Internal auditing has evolved considerably in recent years – and AI will continue to change it. AI can relieve, deepen and sharpen it. But only if the data quality, methodology and processes are right and there is clear AI governance.
Banking.Vision
AI governance is a comprehensive framework that defines responsibilities for the use of artificial intelligence in a company and ensures the safe, ethical, transparent and legally compliant use of AI. The new BaFin guidance clearly classifies artificial intelligence as an ICT risk under DORA. With the help of the three-pillar model and robust AI governance, banks are able to meet strategic and operational requirements.