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Machine Learning & AI in Finance Training Course

Training Course Overview

Machine Learning and AI have been with us for longer than most of us would imagine – and well before banking apps, PFMs and chat bots were in all the news, but it’s only recently that their application and importance to banking and financial services has come to the fore.

Machine learning and artificial intelligence are going to radically change the decision making processes in financial institutions. They will impact investment signals in asset and wealth management. They will influence how people analyse concentration, scenario and operational risks. In addition, we will know clients much better than we currently do, leading to a more bespoke, though industrialised service.

We’ll explore these technologies, business use cases, case studies and key learnings in order to give you a solid grounding in AI, big data, and machine learning as well as help you understand the potential to apply them in your own organisation.

Some of the areas we’ll cover include:

  • Portfolio management
  • Algo trading/Robo advisory
  • Loan underwriting
  • Risk management
  • Fraud detection
  • Regulatory

Who should attend this course?

  • Decision makers
  • Portfolio managers
  • Risk managers
  • Wealth management
  • Pension fund managers
  • Insurance companies

Machine Learning & AI in Finance Content

Morning – Investors

Behavioural finance: understanding financial agents  based on their (ir)rationality & emotions

  • A description of the individuals’ behaviour as investors: theories & case studies
  • How to use data in order to help individuals make decisions
  • Case study: transposing the findings on Tesco to the financial industry

Afternoon – Investment

Understanding the new trends to generate performance

  • Making decisions of qualitative and quantitative signals
  • Techniques that improve performance and can help portfolio managers
  • From a classical to a big-data approach.
  • Case study

Morning – Risk Management

  • A new approach on counterparty risk
  • Case study: the CDS market & contagion
  • Other applications of financial analytics to other risk management topics

Afternoon – The IT organisation required to handle projects efficiently

  • Data security and interaction with the cloud
  • Bespoke programming versus open architecture code
  • Different challenges in the financial world as opposed to elsewhere


Using the KPMG Global Data Observatory for investment projects

Case study: visualisation of index based investment strategies


Using the KPMG Global Data Observatory for investment projects

Case study: visualisation of participants big data challenges

Open panel discussion – with representatives from industry and academia

Key course info

3 days
Imperial College Business School

Watch: An Intro to Machine Learning in Finance

Previous Exec-Ed participants

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