# **Predicting Bank Insolvency in the Middle East and North Africa**

## **1. Introduction**

The financial crises experienced in recent decades prompted efforts to develop early warning systems (EWSs) which could help identify the factors underlying the occurrence of a crisis (Bell and Pain, 2000; Gaytán and Johnson, 2002; Berg et al., 2004; Demirgüç-Kunt and Detragiache, 2005). The recent global financial crisis has intensified these efforts, with academics and policy makers increasingly focusing attention on developing indicators and methodologies which can assist in the timely identification of signs of distress (Ghosh et al., 2009; Barrell et al., 2010; Babecký et al.; 2013). This paper attempts to identify the factors that affect the risk of bank insolvency in the Middle East and North Africa (MENA) as a way to provide a fundamentalsbased surveillance tool which can serve as an early warning device.

The impact of the global financial crisis on banking systems and banks in MENA has highlighted the importance of differentiating across countries and among financial institutions. While the region avoided systemic banking distress, the crisis had a stronger impact on countries in the Gulf Cooperation Council (GCC), where financial systems were more globally integrated and banks more overextended (Rocha et al., 2011). Most importantly, the global financial crisis revealed significant differences in the resilience of individual banks. This is largely the result of the quality of management, corporate governance arrangements and banks’ business models, sometimes mitigated by preemptive policy actions taken by country authorities. In many cases, knowledge about the specific features underpinning individual financial institutions’ health has been crucial for identifying problems and informing policy action. This suggests that an EWS model built on bank-specific fundamentals can provide a useful monitoring tool, helping supervisors detect vulnerable financial institutions and take preemptive steps to aid ailing financial institutions.

This paper builds on and expands the extant literature on bank default. The latter mostly focuses on testing a wide variety of accounting-based variables on the probability of bank default in discriminant analyses and logistic regression frameworks. The assumption is that insolvent banks present _ex ante_ weaker fundamentals than solvent banks. The literature on individual bank default draws heavily on the CAMEL rating system, a widely used microprudential supervisory tool to monitor the performance and soundness of financial institutions based on five categories: Capital adequacy, Asset quality, Management capacity, Earnings power, and Liquidity position.

Most of these studies focus on the US, where the data are most readily available (e.g. Thompson, 1991; Whalen, 1991; Cole and Gunther, 1995, 1998; Estrella et al., 2000; Wheelock and Wilson, 2000; and most recently Torna, 2010; Jin et al., 2011; Cole and White, 2012). Other studies take a cross-country perspective and analyze bank fragility in the context of the European Union (e.g., Poghosyan and Čihák, 2011; Betz et al., 2013), Latin America (e.g., Gonzalez-Hermosillo et al., 1997; 1999; Arena, 2008) or Eastern Europe (e.g., Maechler et al., 2007; Männasoo and Mayes, 2009). While there emerges a great deal of heterogeneity in terms of consistency of the predictive power of CAMEL variables, mainly due to the different definitions of bank distress employed and to the difficulty of comparing accounting rules across countries, bank-level indicators are in general found to be significant determinants of bank fragility. To the best of our 2