Machine Learning for Risk Managers

Dr, Ariane Chapelle, is Honorary Reader at University College London and is an internationally recognised trainer and consultant in Risk. She teaches at UCL 'Operational Risk Measurement for Financial Institutions’ and is a Fellow of the Institute of Operational Risk..

In 2019, the firm received the Risk.net Award for ‘Outstanding Achievement in the Year in Operational Risk’. She published at Wiley Finance Series the textbook Operational Risk Management: Best Practices in the Financial Services Industry, in December 2018 that rapidly became the No.1 best seller in its field and is now translated in French by Pearson France. In 2020, the book got elected “Book of the Year” by risk.net.

Dr. Chapelle founded and runs her adivsory and training practice in risk management, serving all sizes of financial organisations and international institutions, including central banks and UN agencies. She is a former holder of the Chair of International Finance at the University of Brussels with backgrounds in internal audit, credit risk and investment risk. She has been active in operational risk management since 2000 and was formerly head of operational risk management at ING Group and Lloyds Banking Group.

Natalie Gapp is a research consultant at Chapelle Consulting and co-founder of Chapelle Analytics, one of its subsidiaries. Natalie holds a Master degree in Computational Finance from University College London (UCL) where her study centered around data analysis, statistics, and operational risk.

She is currently working toward a PhD in machine learning applied to operational risk and reputation impact through UCL. Her current research focuses on building machine learning models for operational risk prediction and the measurement of reputation damage to firm following adverse news. Natalie previously built machine learning models for financial news analysis during work on her MSc dissertation. 

Alongside her research activity, she is developing ML online training courses for general managers and advanced courses on ML techniques and coding.

In her prior work she taught high school special education maths courses in New York City. As a teacher, she sought to create engaging curriculum that used real-world applications to make content relevant beyond the classroom.