Maran Chandrasekaran

Maran Chandrasekaran

Solutions Architecture Leader - Banking and Lending

Amazon (AWS)

Maran Chandrasekaran architects enterprise-scale technology transformations that enable financial institutions to modernize legacy systems while maintaining operational excellence in highly regulated environments. With over 15 years leading platform engineering and AI adoption across banking, payments, and investment management (Capital One, USAA), he has delivered multimillion-dollar modernization initiatives that replaced hours-long batch processes with real-time decision intelligence.
He established a Machine Learning Center of Excellence that formalized responsible AI governance and accelerated production adoption of over 200 models processing more than 10 billion records daily. These enterprise-scale AI capabilities deliver award-winning solutions while maintaining strict compliance, auditability, and risk controls in regulated financial services environments.
Maran led global engineering organizations through strategic cloud migrations, building self-service data platforms that improved operational efficiency and resiliency across core banking systems, enterprise data ecosystems, and payment processing infrastructure. He established architectural governance standards and secure-by-design practices that enabled rapid deployment at a scale.
Beyond financial services, he architected next-generation analytics platforms for major sports organizations, implementing predictive modeling that contributed to championship-level performance optimization.
As a recognized thought leader in banking technology, Maran authors technical publications on enterprise AI implementation and leads industry workshops on generative AI adoption at scale. He holds advanced AWS certifications in Solutions Architecture, Machine Learning, and Security, positioning him as a trusted advisor for institutions navigating technology-driven business transformation.

Featured Sessions

Tuesday, June 16, 2026
3:10 pm
AI and Data Analytics

Automation isn’t autonomy. Agentic AI systems reason across domains, plan workflows, and execute decisions autonomously—a shift from scripted tasks. This session explores autonomous AI applications including loan processing, payments, customer service, and treasury operations. Panelists share how they’re building AI agent “fleets,” infrastructure across legacy systems, and governance for independent AI. Learn what separates proof-of-concept from production and why the limiting factor isn’t the models—it’s the discipline to trust them at scale.