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      Deep Thomas

      Deep Thomas

      Chief Data & Analytics Officer

      JPMorgan Chase

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      Deep Thomas serves as the Managing Director and Chief Data and Analytics Officer for APAC. In this role, he is responsible for driving the data and AI strategy, governance, and solutions across the APAC franchise to enhance business outcomes, manage risks, and maximize the value derived from data.
      Prior to his current position, Deep was the Group Chief Data Officer at Nomura, where he spearheaded the firm's data and AI strategy. With over 28 years of experience, he has held senior roles such as Chief Data and Analytics Officer at Aditya Birla Group, CEO of Tata iQ—a data science company—and led global analytics initiatives across the U.S., Europe, and Asia at Citi, HSBC, and American Express.
      Deep holds a master’s and bachelor’s degree in computer science, an MBA in International Marketing, and has been awarded numerous patents in data management and analytics.

      Speaking At

      • 12:00–1:30pmMon 16 NovPublic-Private RoundtableRoundtable Room 2Invite-Only

        Accountability & Liability In Agentic Systems

        Financial AI Builders: Scaling Innovation in Regulated Markets

        Public-Private RoundtableRoundtable Room 2Invite-Only

        About this session

        The next phase of AI in finance will not be defined by better models alone, but by institutions that can successfully embed AI into regulated business processes at scale. From compliance and risk management to customer servicing and agentic finance, AI is creating new opportunities to transform how financial services are designed, delivered and supervised. As institutions explore frontier AI capabilities, the challenge is no longer just building AI solutions, but operationalising them responsibly while maintaining trust, resilience and accountability.
         
        Many financial institutions face similar challenges in developing, evaluating and deploying AI, yet often tackle them independently. Through BuildFin.ai, financial institutions, technology providers and research institutes are collaborating to develop and scale frontier AI capabilities within established regulatory and risk management frameworks. This includes the development of the MindForge AI Risk Management Toolkit, which provides practical guidance, industry case studies and implementation insights, as well as the SAFR (Safeguards for Agentic Finance at Runtime) framework, which explores safeguards for AI-enabled financial activities. This roundtable brings together members of the BuildFin.ai community and industry leaders to exchange lessons from the front lines of AI deployment and discuss how collaboration can help accelerate the responsible adoption of AI across financial services.