Financial Technology: Cryptocurrency, Machine Learning & Digital Banking

Key information

Duration: 8 weeks (online, part time)
Programme dates:
Location:
Address
Study online, eight weeks
Fees: £1,280

Programme overview

Financial Technology: Cryptocurrency, Machine Learning & Digital Banking is designed to give you a foundation in fintech and its components, including digital finance tools, personal banking, Blockchain and cryptocurrency, and machine learning and artificial intelligence.

The eight week online programme draws on expertise from Imperial College Business School faculty, industry experts and case studies. You will also draw on the expertise of your peers and will gain the skills to lead your company into the fintech revolution.

You will experience live online teaching sessions, video lectures, interactive activities and assignments whilst receiving personal support from a dedicated Learning Team.

You will finish the programme prepared to implement your learnings, and with a verified Digital Certificate from Imperial College Business School Executive Education. 

Who should attend?

This global programme is designed to equip mid- to senior-level finance executives with insights and practical skills to harness financial technology strategies, particularly:

  • Finance professionals looking to fain insights on technologies that are changing banking and finance, and on disruptions taking place in financial services
  • CXOs and senior management of fintech startups looking to critically assess the future of the financial services industry through exploration of real world problems
  • Consultants who provide fintech services to clients and want to stay updated on trends to create cutting-edge solutions based on disruptions in the space
  • Risk compliance and regulatory professionals seeking to improve their professional knowledge of fintech and its regulatory frameworks

Learning objectives

  • Learn existing functions within banks to uncover potential inefficiencies
  • Compare and contrast how standard versus digital banks perform given functions in your country
  • Determine the best tactics to attract new customers for loans and identify the holes in the way customers are currently found
  • Consider which functions would be better utilised with machine learning or artificial intelligence
  • Understand the limitations of ML and AI and how to use them to analyse results and determine risk factors
  • Apply the concepts and applications of ML and AI to real-world scenarios
  • Determine situations that should utilise cryptocurrency versus digital fiat currency
  • Sort risks according to whether they apply to fintech or regular financial institutions
  • Predict which functionalities will remain in banks or switch to an outside entity
  • Develop a plan for integration of fintech within a financial organisation

What you will learn

Module 1: Digital Transformation and Financial Services

Module 2: Personal Banking

Module 3:  Lending Markets

Module 4: Applications of Machine Learning in Fintech; Risk Management and Credit Scoring

Module 5: Digital Distributed Ledger: Blockchain and Cryptocurrencies

Module 6: Regulations

Module 7: Fintech Capstone Project

Programme faculty 

Rajkamal Iyer

Rajkamal Iyer

Associate Professor of Finance

Rajkamal is an Associate Professor of Finance at Imperial College London. His research centres on the area of banking and financial intermediation, particularly on understanding the role of banks in society. Currently, he is focused on fintech and how it can reshape the intermediation landscape and improve access to credit. Raj also holds a research advisory role at the Bundesbank.

Become an Associate Alumni

Take your partnership with Imperial College Business School to the next level by becoming an Associate Alumni. Complete more than eight days of our programmes to claim 'Associate Alumni' status and join our active alumni community.

Key information

Duration: 8 weeks (online, part time)
Programme dates:
Location:
Address
Study online, eight weeks
Fees: £1,280