Temenos’ Barb Morgan Shares How AI Is Reshaping Banking - Ep. 246
Episode
30 min
Read time
2 min
Topics
Artificial Intelligence
AI-Generated Summary
Key Takeaways
- ✓AI adoption shift: Banks now view GenAI as enabling hyper-personalization and smarter customer interactions rather than just cost efficiency, moving beyond frustrating chatbots to human-centered approaches that pull customer data instantly for meaningful conversations.
- ✓Data readiness challenge: Many banks can only leverage analytics on 25% of their data landscape due to legacy systems from mergers and acquisitions. Banks need proper data management before implementing responsible AI with full explainability and compliance standards.
- ✓Co-design methodology: Temenos works with banks to co-develop AI solutions by presenting five to six use cases, selecting one or two collaboratively, and building together. This approach includes AI-powered tools for product managers to create financial products using predictive analytics.
- ✓Leadership determines success: Organizations where C-suite leaders discuss AI as augmented intelligence and use tools themselves see higher adoption rates. When leadership frames AI as amplifying human potential rather than replacement, employees embrace it as a collaborative plus-one tool.
What It Covers
Barb Morgan, Chief Product and Technology Officer at Temenos, explains how generative AI transforms banking from efficiency-focused automation to hyper-personalized customer experiences, data challenges banks face, and sustainability initiatives across global financial institutions.
Key Questions Answered
- •AI adoption shift: Banks now view GenAI as enabling hyper-personalization and smarter customer interactions rather than just cost efficiency, moving beyond frustrating chatbots to human-centered approaches that pull customer data instantly for meaningful conversations.
- •Data readiness challenge: Many banks can only leverage analytics on 25% of their data landscape due to legacy systems from mergers and acquisitions. Banks need proper data management before implementing responsible AI with full explainability and compliance standards.
- •Co-design methodology: Temenos works with banks to co-develop AI solutions by presenting five to six use cases, selecting one or two collaboratively, and building together. This approach includes AI-powered tools for product managers to create financial products using predictive analytics.
- •Leadership determines success: Organizations where C-suite leaders discuss AI as augmented intelligence and use tools themselves see higher adoption rates. When leadership frames AI as amplifying human potential rather than replacement, employees embrace it as a collaborative plus-one tool.
Notable Moment
Morgan reframes artificial intelligence as augmented intelligence to eliminate negative connotations. She demonstrates how AI enables bankers to instantly access complete customer histories and family relationships, allowing personalized service without making clients wait while bankers manually research files and accounts.
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