Breaking the AI Deployment Barrier: How Leading Banks Are Succeeding Where Others Fail

In the latest event I hosted, we welcomed Simon Axon , Global Financial Services Specialist at Teradata , for a deep dive into why 80% of AI projects in financial services fail — and what leading banks are doing differently to succeed. From data readiness to deployment hurdles, Simon shared tactical insights, real-world case studies, and a vision for a more human-centric AI approach in banking.

Key Highlights to Feature :

• 80% of AI projects never reach production. Most of the time is spent preparing data, not delivering value.
• “Signal Banking” is the future. This model mimics human behavior to deliver personalized, timely customer experiences using AI.
• Banks are not scaling AI efficiently. A typical AI model can take 5–12 months to deploy — and many never see the light of day.
• Case Study: A European bank cut 5 days off regulatory reporting with a single AI model.
• Call center cost savings of $36M: AI-powered call wrap-up summaries are streamlining operations significantly.
• Mortgage innovation in Australia: AI is helping banks compete on service, not just interest rates, with hyper-personalized digital journeys.