Modelling Deposit Insurance Scheme Losses in a Basel 2 Framework

Abstract

This paper extends the existing literature on deposit insurance by proposing a new approach for the estimation of the loss distribution of a Deposit Insurance Scheme (DIS) that is based on the Basel 2 regulatory framework. In particular, we generate the distribution of banks' losses following the Basel 2 theoretical approach and focus on the part of this distribution that is not covered by capital (tail risk). We also refine our approach by considering two major sources of systemic risks: the correlation between banks' assets and interbank lending contagion. The application of our model to 2007 data for a sample of Italian banks shows that the target size of the Italian deposit insurance system covers up to 98.96% of its potential losses. Furthermore, it emerges that the introduction of bank contagion via the interbank lending market could lead to the collapse of the entire Italian banking system. Our analysis points out that the existing Italian deposit insurance system can be assessed as adequate only in normal times and not in bad market conditions with substantial contagion between banks. Overall, we argue that policy makers should explicitly consider the following when estimating DIS loss distributions: first, the regulatory framework within which banks operate such as (Basel 2) capital requirements; and, second, potential sources of systemic risk such as the correlation between banks' assets and the risk of interbank contagion.

Analysis of China Commercial Banks’ Systemic Risk Sustainability through the Leave-One-Out Approach

“…The leave-one-out model allows measuring the systemic risk of commercial banks on the basis of the subjacent SYMBOL model, proposed by De Lisa et al [38], initially used to simulate the loss distribution of the deposit insurance scheme, and later adopted by the European Commission to evaluate bank-related policies [43][44][45] and for assessing the possible effects of banking crises on public finances stability [46][47][48][49][50].…”

“…Other studies developed the simulation approach by Allen and Gale (2000) [22] to have more realistic estimations. In this line, De Lisa et al [38] developed a Monte Carlo simulation model for estimating the loss distribution of a deposit insurance scheme (DIS), showing that the Italian DIS can cover 98.96% of potential losses. Due to the model flexibility (then identified as systemic model of banking originated losses, or SYMBOL), it was subsequently adopted by the European Commission as a standard tool for testing and back testing the banking regulation proposals and directives.…”

Banks, Debt and Risk: Assessing the Spillovers of Corporate Taxes

“…To evaluate the systemic risk implications of tax reforms that eliminate the favorable tax treatment of debt over equity we use a microsimulation model for banking losses, which is referred to as SYstemic Model of Bank Originated Losses (SYMBOL). The model, which fits within the Basel framework for banks' MCR, been recently used to quantitatively assess the impacts of regulatory reforms in Europe, including the complete safety‐net set up after the crisis, that is enhanced Basel III capital rules, the bail‐in tool and the resolution funds (Benczur et al ; De Lisa et al ). In the model framework, financial stability is evaluated in terms of the losses materializing in the event of a severe financial crisis.…”

Risk Profile Indicators and Spanish Banks’ Probability of Default from a Regulatory Approach

“…SYMBOL is a model of micro-simulation based on the Basel risk assessment framework that estimates the distribution of bank losses originating in the system beginning with the balance and regulatory capital of individual banks. The methodological basis of the model was developed by the Commission's Joint Research Centre (JRC), the Directorate General Internal Market and Services and banking regulation experts (the original methodology was developed by De Lisa et al [4], but, in this paper, the abbreviation SYMBOL was not employed).…”

“…While the SYMBOL model has been used to quantify systemic losses, it also provides a proxy for a bank's default probability as a tail risk [5] that reflects bank capital strength and asset quality [4]. The probability of default of a bank is estimated as the probability that its obligor's loss exceeds actual capital, given by the sum of its minimum capital requirement plus the bank's excess capital.…”