Nimish Panchmatia is DBS Bank's Chief Data & Transformation Officer, leading the bank's digital, data, and cultural transformation. With over 20 years of experience, he spearheads strategic initiatives that drive customer and employee value from AI and Data, Innovation, Agile at Scale or Managing through Journeys, Customer Experience, Future of Work, amongst others.
Most recently, one of his key mandates has been to helm the bank-wide implementation of Generative AI. Leading to the launch of over 20 use cases, including ‘DBS-GPT’, an employee-facing version of ChatGPT & CSO Assistant, a Gen AI-powered virtual assistant to support DBS Customer Service Officers.
Prior to this, Nimish has also served as the Head of GTS Hong Kong where he was responsible for the bank’s Corporate Cash, Trade and Custody business, as well the CIO and Head of T&O for Hong Kong and China, where he oversaw Technology, Operations and Corporate functions.
Prior to joining DBS in 2010, Nimish worked for DHL Express for 10 years in various roles, including VP of Customer Service & Experience for Asia Pacific.
He chairs the Institute of Banking and Finance (IBF) Future-Enabled Skills Work Group.
Roundtable Room 4, Sands Expo & Convention Centre, Level 4
Invite-Only
BCG estimates that (Gen) AI can bring 30-50% efficiency improvement, impacting all the key elements of financial services value chain. Fintechs, Banks, Insurers are announcing great value delivered with Pilots, POCs, experiments but acknowledge that scaling is not straightforward.
In the 2023 (Gen) AI roundtable we covered the potential for Financial Institutions, prominent use cases, discussed challenges and aligned on key imperatives required to scale and achieve value.
12 months later it's time to count the chickens. This roundtable aims to bring together AI practitioners, FI executives, policy makers and thought leaders to discuss the proof of value, Gen (AI) at scale and what it takes to achieve it.
Key discussion points:
1. Proof of value in FIs - where's the promised transformative impact?
2. What are the lessons learned from transformative implementations
3. How do we solve the remaining challenges of scaling from business, tech and risk angle?
4. What role can regulator and ecosystem play in accelerating transformation?
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