Former Goldman Sachs CIO Damian Sutcliffe joins illumr Advisory Board

Posted by Jason Lee on Jul 29, 2021 8:30:00 AM


illumr removes bias in AI for Financial Services organisations

Damian Sutcliffe, the former EMEA CIO for Goldman Sachs has joined illumr’s advisory board.

Damian retired from a 20-plus year technology career at Goldman Sachs Group Inc., including the last five years as Chief Information Officer for EMEA. Over the course of his career, Damian held a range of senior management roles in London, Tokyo & New York delivering large-scale digital and data transformation initiatives. He is an external advisor at McKinsey and is currently completing a PhD at Cambridge University.

Jason Lee, CEO and Co-Founder of illumr comments:

“We are thrilled to have Damian join our Advisory Board. His guidance and input will be invaluable in the development of Rosa, illumr’s AI de-biasing solution.

“Algorithms affect our daily lives more and more. However, instead of being an objective arbiter, these algorithms replicate human biases because they are trained on biased data. What should be impartial algorithms become skewed in respect to race, age and other factors. Our goal is to help organisations understand and correct biased data, comply with regulations and make better decisions.

“Rosa has been applied successfully in life sciences, healthcare and public services. Damian’s experience as Global Head of Regulatory Architecture & Global Head of Enterprise Data Governance at Goldman Sachs will help us take these benefits to Financial services. His expertise will also help streamline integration into banking technology.”

Damian Sutcliffe, comments:

“illumr is an exciting fintech start-up addressing one of the emergent issues in the field of AI. Removing bias has quickly become a major concern, for both accuracy and compliance. I am excited about solving these challenges in banking, financial services and beyond.”

Topics: ai, bias, discrimination, machine learning

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illumr helps organisations better understand and predict patterns of behaviour that affect them.

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