How Macquarie Bank Uses AI and Data to Enhance Customer Experience

Prepare to see banking in a new light! Cindi Howson and Macquarie Bank's data trailblazer, Ashwin Sinha (Chief Data Officer), go deep into the AI revolution transforming financial services. Discover how one of Australia's most dynamic financial institutions, Macquarie Bank, is wielding the disruptive force of generative AI, not just for efficiency, but to combat high-stakes threats like fraud. Plus, discover the remarkable evolution of the data analyst from report-generator to AI-powered strategic powerhouse!Key Moments: Drivers of Digital Transformation (04:36): Ashwin outlines the key factors driving a digital transformation and early cloud adoption, emphasizing customer obsession, improving turnaround times, and ensuring technology reliability.  Leveraging Dual Cloud Providers (12:25): Ashwin discusses Macquarie Bank's use of AWS for infrastructure and core applications and Google Cloud (GCP) for its digital and data stack, including AI capabilities.  The Power of Gen AI in Analytics (14:16): Ashwin explores the role of generative AI in enhancing productivity for data analysts, particularly through prompt engineering and tools like ThoughtSpot.  Empowering Analysts Through Evolution (16:56): Ashwin details Macquarie Bank's successful strategy for evolving the data analyst role by proactively introducing self-service analytics, emphasizing upskilling, and enabling analysts to concentrate on higher-impact activitiesCombating Data Risk and Fraud Prevention (26:04): Ashwin discusses the increasing threat of scams and fraud and details Macquarie's two-pronged approach: educating customers and employing AI and machine learning to detect and prevent fraudulent activities.  Importance of Prompt Engineering (32:57): Ashwin stresses the significance of prompt engineering as a general-purpose technology that can drive productivity across various business functions, not just within technical roles.  Key Quotes:"There is always a big backlog in most organizations, which you cannot get done just because you do not have enough capacity. You cannot prioritize them. You cannot execute fast enough. And so, what prompt engineering and GenAI broadly does is take away the low-value tasks that you could just use AI and machine learning to do for you." - Ashwin Sinha"Prompt engineering—even though it has 'engineering' in it— I see that as a general-purpose technology. It's a bit like we've just got access to a super powerful search with a lot more analytical and reasoning capability. That's how I think of the usage of any of the foundational or large language models for, you know, the general population who are not in engineering or technical roles. Whether they're in business roles, sales and distribution, finance, marketing, or any of those functions, the use of prompt engineering just enables the next level of productivity for them. - Ashwin SinhaMentionsPrompt Engineering in the Age of AIAI Agent GovernanceThoughtSpot Spotter: Your AI AnalystScuba Diving and the History of the Liberty Shipwreck in BaliThe Importance of Child Education in IndiaGuest Bio Ashwin Sinha is the Chief Data Officer and Executive Director at Macquarie Bank, where he oversees the strategy and execution of Data and AI. Before joining Macquarie in 2019, Ashwin was a Partner at KPMG, leading the Data business. He has also held various global software engineering, start-up, and consulting roles over the past 22 years, focusing on data and digital transformations. Outside work, Ashwin is passionate about child education and macroeconomics Hear more from Cindi Howson here. Sponsored by ThoughtSpot.