Hariom Tatsat

Hariom Tatsat is an artificial intelligence researcher, financial AI specialist and keynote speaker who helps organisations understand, evaluate and safely deploy advanced AI systems. As Director, AI Quant at Barclays Investment Bank, he leads the design, fine-tuning and implementation of artificial intelligence models and agentic AI solutions for complex financial applications. His work focuses particularly on AI interpretability, explainability and trust, addressing one of the most pressing questions facing organisations today, how can leaders confidently use AI when they cannot clearly understand how it reaches decisions? By combining technical research with extensive commercial experience, Hariom provides organisations with practical approaches to making AI systems more transparent, auditable and reliable.

Hariom has spent more than 15 years working across quantitative finance, machine learning, risk management and artificial intelligence. Before joining Barclays, he held quantitative positions at First Abu Dhabi Bank, Royal Bank of Scotland, Nomura and Nykredit, where he worked on pricing, hedging, credit risk and complex financial models. He holds a Master’s Degree in Financial Engineering from the University of California, Berkeley, alongside a Bachelor’s Degree from the Indian Institute of Technology, Kharagpur. Hariom is also an Advisor and Mentor at Berkeley SkyDeck, where he supports emerging companies within the fintech sector, helping founders develop and apply innovative technologies to real-world financial challenges.

As a published researcher, Hariom has made important contributions to the understanding of trustworthy artificial intelligence. His paper, ‘Beyond the Black Box: Interpretability of LLMs in Finance’, explores how neuroscience-inspired mechanistic interpretability techniques can reveal the internal decision-making processes of large language models. His wider research includes risk-aware reinforcement learning, interpretable deep Q-networks and AI applications within trading, portfolio management and financial risk. Hariom is also the author of ‘Machine Learning & Data Science Blueprints for Finance’, published by O’Reilly Media, which became a No.1 new release in Amazon’s AI category. His contributions to the field have also earned him the Indian Achievers’ Award in Machine Learning.

As a keynote speaker, Hariom makes complex artificial intelligence concepts accessible to executives, regulators, investors and technology professionals. He has delivered talks for the Federal Reserve Bank of Atlanta, NVIDIA GTC, AI4, Reuters Momentum AI Finance, The AI Summit New York and the NexGen Banking Summit. His keynote topics explore trustworthy AI, financial AI, large language model interpretability, AI safety and agentic systems. Drawing on his experience implementing AI within global financial institutions, Hariom explains where artificial intelligence can create genuine value, why many AI projects struggle to reach production and how organisations can build systems that meet demanding standards for accuracy, governance and compliance.