Machine Learning in Finance, London

This training course will address in-depth the opportunities and limitations of machine learning in quantitative finance with practical guidance from a variety of expert tutors.


Machine Learning in Finance

November 27–28, 2019


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This two-day training course will provide attendees with a deep understanding of machine learning applications within finance.

The sessions offer a technical look at machine learning and provide suggestions and strategies for integrating it within your organisation. You will learn about key theories, models and more advanced tools in machine learning, using a quantitative approach presented by top practitioners from leading firms in the financial industry. Further sessions will delve into portfolio construction, trading, risk management and other business areas.

What will you learn?
  • How to properly and efficiently manage data for machine learning

  • A new or improved understanding of the relationship between machine learning and risk management

  • Methods for portfolio construction with machine learning

  • Insight into machine learning models and their application

  • How to address the human element in machine learning and banking

  • Best practice approaches to applying machine learning models 

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Who should attend

Relevant departments may include but are not limited to: 

  • Machine learning

  • Portfolio management

  • Asset allocation

  • Data science

  • Financial engineering

  • Quantitative analytics

  • Quantitative modelling

  • Infrastructure and technology

view pricing options

Course highlights
  • Machine learning in finance: opportunities and limitations

  • Data management for machine learning 

  • Machine learning in risk management

  • Machine learning for portfolio construction

  • Machine learning models 

  • Natural language processing: a deep dive 

  • Managing the human factor and biases in machine learning

  • Applying machine learning in practice

View agenda topics

Past attendees include
  • ABN Amro Clearing Bank
  • Accenture
  • Banca IMI
  • BBVA
  • Citibank
  • Credit Suisse Banking 
  • ING Bank
  • Intermediate Capital Group
  • Investec UK
  • JHL Quantitative Analysis
  • Rabobank London
  • RBS
  • Swift
  • UK Pension Fund

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Dr Richard Saldanha

Founder & Co-Head


Dr Richard Saldanha is Founder and Co-Head of Oxquant, a consultancy firm that provides expertise and advice on risk management, investments and the impact of artificial intelligence. He is also an Independent Adviser to Oxford Portfolio Advisers.

Richard has over 20 years’ experience in asset management and investment banking in the areas of risk, trading and investments. In particular, he was Global Head of Risk at Investec Asset Management (2010–15), headed a quantitative global macro initiative for the same firm (2006–09) and founded and ran his own hedge fund Oxquant Capital Partners (2004–06).

In addition to his consulting and advisory activities, Richard lectures on statistical machine learning and its applications in finance at Queen Mary University of London. He attended Oriel College, University of Oxford, and holds a doctorate (DPhil) in statistics.

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CPD / CPE Accreditation


CPD Accreditation

This course is CPD (Continued Professional Development) accredited and will allow you to earn up to 12 credits. One credit is awarded for every hour of learning at the event.

CPE Member

CPE Accreditation

This course is CPE (Continuing Professional Education) accredited and will allow you to earn up to 12 credits. One credit is awarded for every hour of learning at the event in accordance with the standards of the National Registry of CPE Sponsors.

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