PANEL DISCUSSION: CHAT AI IN BFSI - BALANCING INNOVATION, COMPLIANCE AND CUSTOMER TRUST

In the BFSI (banking, financial services & insurance) sector, Chat AI is evolving from a front-end customer interaction tool to a core component of enterprise automation. Today’s financial institutions are deploying intelligent conversational systems that not only communicate - but connect securely to back-end platforms to access customer data, execute transactions, and deliver real-time, personalized insights.

Achieving this end-to-end integration requires more than APIs and models - it demands a tightly governed data and automation architecture. BFSI organizations must ensure every interaction is accurate, explainable, and compliant with evolving regulations around privacy, security, and auditability. Chat AI systems must retrieve and act on sensitive data only within approved controls, maintaining full traceability across data lineage, identity management, and risk frameworks.

Topics of discussion will include, yet will not be limited to:

• Designing Chat AI architectures that integrate securely with core banking, CRM, and data platforms
• Ensuring data privacy, lineage tracking, and regulatory compliance across all conversational interactions
• Automating end-to-end workflows - from inquiry to resolution - without compromising oversight or accuracy
• Building governance models that balance innovation with transparency, auditability, and customer trust

Srinivas Akella, Head of Contact Center Technology & Director of Engineering & Gen AI & Agentic AI Enablement, U.S. BANK

Nitin Sharma, Senior Manager, Digital Product Solution Design, AMERICAN EXPRESS

Mostafa Rafaie, Director, Data Science - Aligned Assurance, MUTUAL OF OMAHA

Moderator/Speaker: Suzanne LaLena, Senior Vice President, Automation Engineering, BNY