Grzegorz Hałaj, PhD, is an Adjunct at the AI Lab SGH and an Adviser at ECB Banking Supervision, where he leads work on SSM thematic stress tests and elements of the EU-wide stress test. He was also a member of the steering body for the stress test activities run by the EBA. In addition, he is a visiting scholar at the International Monetary Fund.

He began his central banking career as an Economist at the National Bank of Poland in 2004, later moving to a risk management unit of the UniCredit Group. In 2011, he joined the ECB as a Financial Stability Expert and later became a member of the ECB stress testing team supporting the Troika programme for Cyprus. In 2018, he moved to the Bank of Canada, initially as a Principal Researcher focusing on enhancing stress testing tools, and was subsequently appointed to two managerial roles at the Bank before returning to the ECB in 2022.

He holds a PhD and a Master’s degree in Economics from SGH Warsaw School of Economics and a Master’s degree in Mathematics from the University of Warsaw.

Research interests:

Assessing the resilience of the financial system to extreme market conditions (in particular, using stress tests and taking into account the impact of the structure of financial system interconnections and entities' activity within business plans and risk management).

Research problems:

  1. Does the diversity of entities, in terms of business strategies or regulatory requirements and constraints, increase systemic risk? What is the impact of cross-sector interconnections, particularly with non-bank financial institutions and new technology sectors?
  2. How should the strategic interactions of diverse entities be modelled? In particular, how should an agent-based approach be used to ensure the interpretability of results and the identification of key model parameters, as well as to assess the sensitivity of the results?
  3. New risks - new methods for their assessment? The impact of new risk categories, i.e., those related to AI and other digital technologies.

Methods for selecting appropriate supervisory policies to minimize the risk of financial instability.

Research problems:

  1. Should models be built based on optimization techniques or on the reaction rules of an agent-based model approach, calibrating them based on empirical research and economic theory? 
  2. How do entities' responses to supervisory policy instruments affect the stability of the financial system?

Effective use of available large data sets, particularly supervisory data, and effective use of public data.

Research problems:

  1. How to reconstruct the network of connections in the financial system? What are the most important connections, particularly between different types of financial institutions, considering trends related to the evolution of the financial sector?
  2. Volatility or stability of the network? How can available data, particularly public and market data, be used to assess changes in the structure over time and the impact of volatility on the stability of the system?