FinTech in Economic Analysis for Macro-prudential and Monetary Policy Making

FinTech in Economic Analysis for Macro-prudential and Monetary Policy Making

FinTech in Economic Analysis for Macro-prudential and Monetary Policy Making

Course Chair: Daniel Heller, FinTech Specialist and former Head of Financial Stability, Swiss National Bank


Day 1, 17th September - Economic Analysis in the Era of Disruptive Innovation 

FinTech revolution: digital transformation in finance and economics 
Bruno Tissot
, Head of Statistics and Research Support and Head of the Irving Fisher Committee’s Secretariat, Bank for International Settlements

  • Overview of recent trends and developments in disruptive technological innovation
  • State of the art of key statistical and computational technology
  • Impact of FinTech on financial services industry and the world of economics
  • Implications for information architecture and statistical methodology in central banks

Rethinking economic analysis: new frameworks, approaches and techniques
Doyne Farmer, Director, Institute for New Economic Thinking, University of Oxford and External Advisor, Bank of England (invited)

  • Key forces and dynamics shaping the work of economists, statisticians and data analysts in central banks
  • Evolution of data needs for monetary and macro-prudential policy making
  • Opportunities and challenges related to new international standards and initiatives 
  • Discussion: what are the key features of effective analytical frameworks and techniques applied in the delegates’ home institutions?

Making the most of innovation: a user’s guide
Workshop with Daniel Heller
, FinTech Specialist and former Head of Financial Stability, Swiss National Bank

  • Examples of key FinTech driven disruptions to central banking and supervision
  • Overview of new challenges and responsibilities that central bankers and supervisors need to deal with
  • Tips for effective integration of FinTech opportunities such Big Data Analytics or Blockchain applications
  • Discussion: how do central banks need to change to make the most of FinTech? 


Day 2, 18th September - The New Toolkit for Macro-prudential and Monetary Policy Making

Big Data analytics: finding hidden patterns and identifying risks
Stefan Bender
, Head, Research Data and Service Centre, Deutsche Bundesbank

  • The state of the art of Big Data analytics in 2019
  • Overview of building blocks in the fields of data creation, storage, retrieval and analysis
  • Examples of frameworks, approaches and techniques for successful application in the central banking and supervisory environment 
  • Discussion: how to effectively manage issues preventing a development of a coherent and sustainable Big Data strategy? 

Artificial Intelligence and Machine Learning: applications in stress testing
Mario Quagliariello, Head of Unit, Risk Analysis, European Banking Authority (invited)

  • The evolving role of systemic stress-testing in financial stability
  • Key features of effective stress-testing models and frameworks
  • Opportunities and challenges of disruptive technological innovation
  • Case study: applications of Machine Learning in European Banking Authority’s stress-testing models

Distributed Ledger and Blockchain: emerging opportunities in risk-based supervision
Allan Kearns
, Head of Prudential Analytics, Central Bank of Ireland

  • Key features of effective risk-based supervision frameworks and strategies
  • The impact of APIs (Application Programming Interface) and software platforms on regulatory value chain
  • Applications of DLT and Blockchain in effective collection, management and analysis of supervisory data
  • Discussion: what does it take to manage sensitive issues in the areas of security standards and confidentiality?

Making the most of Cloud: capacity vs security
Pieralberto Deganello
, Vice President, Customer Relations and Support Office (CRSO), Security and Risk Management Team, Federal Reserve Bank of Chicago

  • The state of the art of cloud computing
  • Overview of the technological foundations and building blocks
  • Examples of uses and applications in the central banking and supervisory environment
  • Tips for effective management of limitations and potential legal and security risks

FinTech governance: operational arrangements and institutional organisation
Johannes Turner
, Director of Statistics, National Bank of Austria

  • Examples of frameworks and indicators to assess suitability and needs for the effective governance of FinTech
  • Implications for institutional strategies and inter-departmental cooperation
  • Tips for selection and coordination of in-house technology solutions with the outsourced ones
  • Discussion: what does it take to attract, train and maintain the best FinTech talent?

Day 3, 19th September - Modelling in Focus

The use of Google Search data for nowcasting macro-economic indicators
Per Nymand Andersen
, Adviser, European Central Bank

  • Overview of emerging trends in regulatory Big Data
  • Opportunities and challenges of Big Data applications for financial stability and systemic risk analysis
  • Examples of good practice in combining Big Data from the internet, administrative and commercial sources
  • Case study: European Central Bank’s use of Google search data in autoregressive now-casting models

Modelling systemic risk with network analytics
Rodrigo Cifuentes
, Head of Financial Research, Central Bank of Chile

  • Methods and practices for combining available technologies and digital platforms for visualising different types of systemic risk
  • Tips to effectively analyse complex financial data and filter signal from noise
  • Management of key operational and ethical risks and challenges
  • Hands-on exercise: mapping of cross-holdings between financial institutions and identification of early warning indicators

Agent-based modelling in practice: housing market in the UK
David Bholat
, Senior Analyst, Advanced Analytics, Bank of England

  • State of the art of agent-based modelling
  • Differences and overlaps with DSGE approaches
  • Methods and practices for combining agent-based modelling with other technologies and digital platforms
  • Case study: using agent-based approaches to model housing market in the UK


Day 4, 20th September -Wider Implications and Opportunities

Using advanced analytics to measure (and so improve) central bank communication
Piet J.H. Daas
, Senior Methodologist and Data Scientist, Central Bureau of Statistics, the Netherlands

  • Implications and opportunities of disruptive technological innovation for central bank communication
  • Examples of applications in the areas of design, execution and evaluation of different communication strategies and frameworks
  • Assessment of the analytical value of new tools – such as text-mining – based on Big Data and Machine Learning
  • Case study: analysis of social media response to a monetary policy announcement

Financial stability and monetary policy implications of Central Bank Digital Currencies
Alexander Berentsen, Dean of the Faculty of Business and Economics, University of Basel and Senior Research Fellow, Federal Reserve Bank of St. Louis (invited)

  • Differences and overlaps between privately issued crypto assets and central bank digital currencies (CBDC)
  • Opportunities and risks of CBDC for monetary policy implementation
  • Impact of CBDC on financial services providers and systemic stability
  • Discussion: how to manage cross-country flows of digital money?

Lessons learnt and key takeaways
Led by the chair, Daniel Heller

  • Summary of the training course
  • Discussion of the observed trends and case studies 
  • Application of learning points in the delegates’ home organisations
  • Preparation of action points