Rafal Pasierbek
Data & Ai Governance Lead, Enterprise Data Office @Citi
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WORK HISTORY
Data & Ai Governance Lead, Enterprise Data Office @Citi
London, GB
Building on my previous leadership in Model Risk and AI governance at HSBC, I was headhunted to Citi to focus on Data & AI Governance within the Enterprise Data Office, working horizontally across Markets, Banking, and Client data domains. In this role, I translate enterprise data standards into practical, scalable governance and control frameworks, with a strong emphasis on data quality, lineage, and preventive and detective controls for Critical Data Elements. I partner closely with Business, Technology, and Data Architecture teams to support target-state data architecture and migration from legacy platforms, while ensuring data remains fit for regulatory, risk, accounting, and business use. A key driver of this work is the regulatory environment, where models, regulatory reporting, analytics, and AI tools depend on consistently high-quality, well-controlled data. As part of this mandate, I shape AI data governance from a data perspective, defining standards for training, validation, and inference datasets, governing data provenance and access, and working closely with data science teams to ensure AI solutions are built on well-governed, representative data. I enjoy working hands-on with Product, Operations, Technology, Risk, and Control partners to embed sustainable data management practices and enable analytics and AI innovation in a responsible, pragmatic way.
EDUCATION
City St George’s, University of London
Master of Science - MSc, Financial Economics, Specialisation Financial Engineering
Wyższa Szkoła Biznesu - National Louis University w Nowym Sączu
BA, Business Administration
IESE Business School
Programme for Management Development
HEC Lausanne - The Faculty of Business and Economics of the University of Lausanne
Financial Engineering & Risk Management
ABOUT RAFAL PASIERBEK
I am a senior leader working at the intersection of data, AI, regulation, and risk governance within global financial institutions. My career has evolved through advisory, risk, and transformation roles into my current position within a Group Enterprise Data Office, where I lead Data & AI Governance across Markets, Banking, and Client domains in a highly regulated environment.I started my career in professional services, advising financial institutions on risk, valuation, and regulatory-driven modelling, before moving into increasingly senior in-house roles at Deutsche Bank and HSBC. Across these roles, I have led and delivered regulatory change programmes, designed risk and data governance frameworks, and provided interpretation of secondary financial services legislation, translating regulatory intent into practical methodologies, controls, and operating models. My work has spanned market risk, model risk, climate and ESG models, and the early governance of AI tools, combining hands-on technical depth with delivery and leadership responsibility.At Citi, I now focus on enterprise Data & AI Governance, embedding data quality, lineage, and control standards that support regulatory reporting, risk management, analytics, and AI use cases. A key part of my work is ensuring that data used across models, reports, and AI tools is well-governed, reliable, and fit for purpose in a regulatory-driven environment, while enabling innovation in a responsible and sustainable way. I work closely with Business, Technology, Risk, Legal, and Control functions to bridge strategy and execution in complex, matrix organisations.Alongside my professional roles, I am actively engaged in leadership and community building. I am an alumnus of IESE Business School, having completed the Programme for Leadership Development, and I serve as a board member of the IESE Alumni Chapters in the UK and Poland. Through this work, I help bring together senior executives and entrepreneurs, fostering meaningful professional connections, knowledge exchange, and long-term community building across geographies.I am motivated by roles that sit between disciplines — where data, regulation, technology, and people meet — and by work that turns complex regulatory and data challenges into clear, durable solutions that stand the test of scrutiny and change.
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