Early Warning Tools for Financial System Distress: Current Drawbacks and Future Challenges

Early Warning Tools for Financial System Distress: Current Drawbacks and Future Challenges

Iustina Alina Boitan (Bucharest University of Economic Studies, Romania)
DOI: 10.4018/978-1-4666-9484-2.ch005
OnDemand PDF Download:
No Current Special Offers


In the last decade, economic literature has consistently and imperatively promoted the need to create and use early warning models to prevent the various types of crises, especially as the coverage of bank risks has widened, as a result of the financial liberalization process, innovation and cross border financial activity. Although several supervisory authorities and central banks have already in place different types of early warning systems (Austria, Czech Republic, France, Italy, Romania, UK), the recent global financial crisis has put into question the ability of these statistical tools to monitor financial or banking distress and make accurate predictions. The aim of the chapter is twofold: i) to review the existing typologies of EWSs, developed at micro prudential and macro prudential levels; and ii) to answer several questions related to the low predictive power recorded by early warning models with respect to the current financial crisis and to depict the main international approaches towards their future structural reconfiguration and role.
Chapter Preview

Typology Of Operational Early Warning Systems

Early warning systems are flexible, dynamic tools that have to be permanently connected and adjusted to the theory of systemic risk, the evolution of financial markets and the availability of information (Oet et al. 2014). Regardless of the purpose for which they are designed, each EWS is a combination of five dimensions: the set of candidate variables, sample period, sample of countries or individual financial institutions, the definition of a crisis or distress phenomena and the statistical method applied (Beckmann et al. 2006).

The core objective of EWSs is to provide a reliable and as accurate as possible estimation of the likelihood of a financial distress episode, over a given time horizon. The timing for issuing warning signals is an important feature, as it allows monetary decision makers to identify, monitor and mitigate potential risks or vulnerabilities in an incipient stage.

Recent studies (Candelon et al., 2012; Knedlik 2014) outline that EWSs have become a valuable and promising instrument in the monetary decision-making process, as the authorities might rely on their forecasts in order to decide if there is the case to initiate preventive actions or implement policies to alleviate the impact of a financial turmoil.

Key Terms in this Chapter

Problem Bank: A bank that depicts impaired liquidity or solvency.

Candidate Variables: Indicators that have the potential to predict a given financial distress episode.

Early Warning System: Statistically-based model that estimates the probability of failure or financial distress of an individual bank or banking system, over a fixed time horizon.

Financial Crisis: A severe disruption on financial markets, which may take the form of banking crises, currency crises or debt crises.

Macro Prudential Supervision: An approach that monitors financial and economic threats affecting the entire financial system.

Threshold: Critical, predefined benchmark introduced in the EWS model that delineates between issuing or non-issuing a warning signal.

Micro Prudential Supervision: An approach focused on monitoring the soundness and viability of individual financial institutions.

Complete Chapter List

Search this Book: