Miquel Noguer Alonso
Artificial Intelligence Finance Institute
Miquel is a co-founder at Artificial Intelligence Finance Institute. He is a financial markets practitioner with more than 20 years of experience in asset management. Additionally to his role at AIFI, he is currently Head of Development at Global AI (Big Data Artificial Intelligence in Finance company) and Head on Innovation and Technology at IEF.
He worked for UBS AG (Switzerland) as Executive Director for the last 10 years and previously worked as a Chief Investment Officer and CIO for Andbank from 2000 to 2006.
He is a professor of Big Data in Finance at ESADE and Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. He received an MBA and a Degree in business administration and economics in ESADE (1993).
In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain).
Dr Djamila Amimer
Mind Senses Global
Dr Djamila Amimer founded Mind Senses Global to help businesses and organisations apply Artificial Intelligence. She is an experienced business leader and an entrepreneur with a broad range of experiences across AI, machine learning, commercial deals, business strategy, energy, supply chain, shipping & trading, business resilience and climate change.
Djamila has a PhD in AI and Economics and has developed frameworks and novel AI techniques in the area of investment decisions, dealing with uncertainty in project evaluation. She has a track record in leading teams, delivering results and focusing on performance. In addition to helping organisations unlock AI potential, she spends significant amount of her time exploring the next wave of AI. Djamila is passionate about AI for good and would like to make AI accessible to everyone.
AI risk expert
formally TSB Business Banking
Janet Adams is a disruptive tech advocate with 20 years experience in Banking Risk and Technology, previously working at TSB Business Banking as Head of Strategic Projects & Performance. With previous experience gained in commercial and investment banking sectors at HSBC, RBS, and Barclays, Janet has recently completed a MSc in Artificial Intelligence at the University of Essex where she developed a path breaking dissertation on Explainability and Accountability of AI for global banking regulatory compliance, fair customer outcomes and market stability, in which she investigated and assessed different algorithmic approaches for 9 AI banking use cases across retail and wholesale sectors. Janet’s blend of technology, risk, conduct and AI gives her a unique perspective on the ethics of Artificial Intelligence in Banking, and she is committed to the principles of inclusivity and benefit for all through the AI revolution.
Sjoerd works in the Financial Risk team of Deloitte, with over 10 years of experience in the financial sector. He has worked on numerous assignments in the areas of model risk management, model development and validation within the financial services industry, including banks, insurers and investment managers.
His focus is on the development of model risk management frameworks, model risk management tooling and on the model development and validation of regulatory and non-regulatory market risk models.
Ozgur works in the Financial Risk team of Deloitte, with over 20 years of experience in the financial sector. He has worked on numerous engagements in the areas of direct marketing, customer segmentation, credit risk management and credit life cycle optimization for large financial institutions in North America and Western Europe. His focus is on the application of advanced algorithms for decision making in risk management and the development of model risk management frameworks for them.
Sebastiaan is a member of the Financial Risk team and the Risk AI Expert Group of Deloitte. His focus is on the risks originating from the use of AI and incorporating this in model risk management frameworks. He has supported various organizations with integrating the aspects of AI in their model risk management framework. He specializes in the field of explainable AI and algorithmic transparency where he integrates these two aspects in AI model development, validation and use.
Katherine Taylor is a quantitative analyst who specializes in machine learning applied to risk management. Katherine researches and implements machine learning models that improve traditional risk measurement and risk management. To help advance AI in financial services, Katherine is also active in the fields of AI model interpretability, model fairness, and model governance. Katherine holds degrees in economics, political science, and financial mathematics.