GenAI Moves from Experimentation to Enterprise Banking
Scaling generative AI across a bank takes more than a successful pilot. It requires trusted data, integration with existing platforms and governance embedded into business workflows. As financial institutions move towards enterprise deployment, the challenge is to translate AI capabilities into better decisions, faster customer responses and greater employee productivity, while maintaining security, explainability and human oversight.
In this IBS Intelligence podcast, Fanis Mesologitis, MD in Banking at Profile Software, explores what it takes to move generative AI from experimentation to enterprise-wide adoption across banking and wealth management. The discussion covers data quality and context, audit trails and policy controls, change management, and practical applications spanning customer service, relationship manager copilots, lending and document processing. It also considers how AI can support personalised advice at scale and connect enterprise workflows.
The central message: competitive advantage comes from combining trusted data, strong governance and integration into business processes, with AI augmenting people and their expertise.
Τεχνητή Νοημοσύνη 
Τραπεζική 
Διαχείριση Επενδύσεων 
Λύσεις Ευρείας Κλίμακας 
