How Do We Make Financial Advice Independent of the Advisor? | Abhishek Taneja
Lovely listener, share with us your thoughts! The most important data in wealth management is not in a database. It lives in advisors' heads and in their notebooks. Abhishek Taneja, an AI and machine learning practitioner who spent two decades across retail banking and wealth management, explains why that matters and what it would take to give every client a baseline of good advice, whichever advisor they get. In this episode, Abhishek compares retail banking, where every transaction is data and a model learns within months, with wealth, where the data is thin and the feedback loop runs for decades. He explains why wealth used machine learning for portfolio construction long before it touched advice, why the advice itself should still come from people rather than an LLM, and what hedge funds can do with data that a regulated manager of retail money cannot. He walks through how people in Asia actually get financial advice, through bank relationship managers, tied insurance agents and bancassurance, and why clients move from robo-advisors to human advisors once their savings grow. He closes on why tree-based models still beat tabular foundation models for decisions a regulator has to understand, and what an advisor's day looks like in five years. Key topics discussed: 0:00 Introduction 1:12 Moving from retail banking to wealth 4:13 Where wealth still runs on the advisor's judgement 6:33 Why wealth adopted machine learning later than banking 11:44 Why advice is where AI hesitancy is strongest 15:47 What hedge funds can do that asset managers can't 19:38 How people in Asia get financial advice 24:22 Making advisory independent of the advisor 28:08 Will people accept AI advice? 31:04 AI copilots vs human advisors 35:50 Tree models vs tabular foundation models 40:58 The advisor's job five years from now Abhishek Taneja is an AI and machine learning practitioner with over two decades of experience across retail banking and wealth management, focused on data, machine learning and business transformation. He has worked at institutions including Citibank and HSBC, and his work centres on scaling data capabilities, putting machine learning models into production and driving AI transformation in financial services. He appears on the podcast in a personal capacity. 🎙️ Subscribe for weekly episodes on fintech, AI, and innovation 🌐 Website: https://curiositycodepodcast.com/ 📱 Follow on LinkedIn: https://www.linkedin.com/in/alexkhomyakov/ 🎧 Listen on Spotify: https://open.spotify.com/show/4ePKf2qCLzcKATS7o6w2U5 🍎 Apple Podcasts: https://podcasts.apple.com/podcast/id1797349967 This conversation explores AI in wealth management, the future of financial advice, explainable machine learning and how wealth and asset managers in Asia reach their clients. For anyone building in wealthtech, advisory or AI for financial services who wants to understand where human advice ends and automation begins. 🎙️ Subscribe for weekly episodes on fintech, AI, and innovation 🌐 Website: https://curiositycodepodcast.com/ 📱 Follow on LinkedIn: https://www.linkedin.com/in/akhomyakov/ 🎧 Listen on Spotify: https://open.spotify.com/show/curiosity-code 🍎 Apple Podcasts: https://podcasts.apple.com/podcast/the-curiosity-code-podcast/id1748596092
