Financial Disruption

Understand the impact of automation and AI on finance and learn how to profit

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Next available date: 18 September

The biggest factor in human progress is our ability to coordinate. Economists have been discussing how humans coordinate since Adam Smith’s “the invisible hand” of the market. Markets are one way to coordinate; a decentralized way that reduces all our preference choices to one number: Price. But markets are not the only way. The second way is a completely centralized hierarchical structure: The firm. Markets and firms coexist and coordination mechanisms shift back and forth depending on what is more effective at any time or in any country. For example, Amazon, one of the biggest disrupters across a huge number of industries is almost completely centralized with all information flowing up to Jeff Bezos.

There are three major problems of coordination:

1. Matching (borrowers to lenders; employees to employers, workers to managers)
2. Solving asymmetric information issues
3. Adjusting for behavioral biases

Read the interview   ‘Upskill to stay competitive’ with disruption Professor Raghavendra Rau.

The Financial Disruption course argues that technology is changing the way we coordinate. It documents how boundaries between firms and markets are shifting, disrupting entire industries in the process.

How you will benefit

  • Understand why finance is being disrupted by technology
  • Understand what areas of your own firm might be at risk from automation
  • Brainstorm on ways to effectively implement the disruptive effects of technology into your own firm
  • Understand when and why you might need blockchains
  • Understand when AI is most likely to be effective

Program length
3 days

Day 1 09:00 – 17:00
Day 2 09:00 – 17:00
Day 3 09:00 – 17:00

Day 1: Automation and Transformation

Morning:
Information problems in firms

  • Imperfect information, asymmetric information, and behavioral biases
  • Digitalization and information flows within firms and markets
  • Organizing data in firms
  • Developing ontologies to compare preferences
  • Matching preferences across multiple dimensions
  • Capturing multi-dimensional preferences

Case study: AccorHotels – A digital transformation

The case discusses the strategic response of industry incumbents to the challenges coming from digital disruptors. It serves as a basis to discuss the opportunities and challenges of industry incumbents to transform themselves and better compete in an increasingly digital business environment.

Afternoon:
Case study: Transformation at ING (A): Agile

This case discusses the “agile” transformation of ING bank in the Netherlands, a reorganization of work which had been critical to respond to and exceed rapidly changing customer expectations. The case provides an opportunity to discuss when agile organizations are successful across countries. How fast should organizations roll out the transformation? How could they build on the experience acquired so far to improve their methodology?

Brainstorming: Threat and Opportunity Analysis

  • Is your firm likely to face disruption? Should you automate processes? If so, which processes are ripe to be automated?
  • Case studies from the audience


Day 2: Distributed Ledgers and Blockchains

Morning:
Distributed Ledgers: Bitcoin, Blockchain and Beyond

  • What is bitcoin?
  • What is a distributed ledger? When is it useful?
  • When are blockchains useful?
  • Mining blocks in class
  • Understanding smart contracts
  • The problems with poor smart contracting

Afternoon:
Case study: Maersk: Betting on blockchain

In March 2018, international shipping giant Maersk is getting ready to debut a trade digitization platform. Maersk hopes the platform will help streamline global trade since shipping goods internationally is an extraordinarily complicated and inefficient process. Executives at Maersk believe that Blockchain technology can provide much needed transparency to the global supply chain. The objective of the case is to discuss what challenges an organization will face in implementing blockchain technology.

Brainstorming: Threat and Opportunity Analysis

  • When should you implement blockchain technology in your own firms? What are the advantages and disadvantages?
  • Case studies from the audience


Day 3: AI and Machine Learning

Morning:

  • How are AI systems created?
  • Do AI systems help understanding employees and customers better?
  • Can deep learning help detect fraud?
  • The problems of AI systems
  • The dark side of technology

Afternoon:
Case study: Vodafone: Managing Advanced Technologies and Artificial Intelligence

Vodafone is operating in the fast-moving telecommunications market where innovation and scale are key. Faced with an onslaught of technological advances – big data, automation and artificial intelligence – the objective of the case is to discuss how to change the organization to incorporate these advancements to improve the way the functions work, and how to incorporate machine learning and artificial intelligence.

Brainstorming: Threat and Opportunity Analysis

  • Does your organization face a threat from AI? How can we implement machine learning or artificial intelligence in our own organizations?
  • Case studies from the audience

This training will be beneficial to any mid- to senior level managers who would like to develop an integrated view of how technology is disrupting different industries. 


Faculty

Raghavendra Rau

Raghu Rau is the Sir Evelyn de Rothschild Professor of Finance at the Cambridge Judge Business School. He is also a founder and director of the Cambridge Centre for Alternative Finance (CCAF), and a member of the Cambridge Corporate Governance Network (CCGN). His research interests include empirical corporate finance, information economics, behavioral finance, and game theory. Raghu’s papers focus…

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  • 3 days
  • € 3600
  • Strategy & Growth
  • English
  • NEW

Available dates

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