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"BANKING NETWORK"
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Evaluation of the post-crisis EU banking network connectedness in the global context
Research background: The global banking network has been undergoing structural changes since the recent financial crisis. Previous studies on connectedness of global banking network during post-crisis period revealed the trends of regionalization and segmentation. Our previous research has also shown that during post-crisis period the level of regionalization within the EU banking network has increased; the network became more clustered and more decentralized. This paper continues our research of structural changes of EU banking network during post-crisis period by adding a global context and questioning the connectedness of EU banking network within global banking system. Purpose of the article: The aim of the paper is to evaluate the EU banking network?s connectedness in the global context during the post-crisis period. Methods: network analysis method and data on yearly flows of BIS bilateral interbank cross-border claim were used to evaluate the connectedness of global and EU banking systems. Findings & Value added: Evaluation of the global banking network?s connected-ness revealed that global banking network density decreased by 4.50 %, suggesting that connectedness is decreasing, but it is happening slowly. Structural changes in the global banking network did happen during post-crisis period with regards to out-degree, betweenness and closeness centrality indicators. In the global context, the EU banking network became more connected during post-crisis period. The EU banking network was regionalized in 2011, but this regionalization disappeared in 2015, as the level of intraregional density decreased in 2015 and became lower than the interregional density. This research contributes to previous research in a way that it applies intraregional and interregional network density measures for evaluation of the EU banking network?s connectedness, and analyses it as a subset of the global banking network.
Journal Article
Credit risk linkages in the international banking network, 2000–2019
We estimate the evolution of credit risk linkages in an international banking network of 46 advanced and emerging market economies between January 2000 and December 2019. In our study, credit risk is proxied with the aggregate probability of default (PD) in the banking sector, and cross-country linkages are described by two types of networks: one representing predictive Granger relationships between the PD measures, and the other representing contemporaneous partial correlations. During the Global Financial Crisis and its aftermath, the density of the networks appears the highest, while experiencing a substantial decline in the post-crisis period triggered by massive deleveraging and the implementation of prudential measures. Throughout the whole observation period, the causal network exhibits the small-world pattern which tends to fuel risk propagation within the network, and the increasing degree of dissortativity which exerts a countervailing effect. On the country level, we document the centrality of the major Asian economies’ banking sectors and France, whereas the role of the USA, the UK and Germany appears moderate, which contrasts with the extant literature. Overall, from the policymaking perspective, our findings indicate that credit risk linkages in the international banking networks can notably differ from the relationships derived from cross-country bank claims.
Journal Article
Social Network Banking: A Case Study of 100 Leading Global Banks
Social media is widely recognized as a challenging new communication technology in both economic and social contexts. The present article explores how banks have exploited this technology in the range of consumer retail banking services offered by 100 leading global banks on the three major social networking sites (SNS): Facebook, Twitter, and YouTube. Viewing social network (SN) banking as a separate delivery channel and offering a working definition of SN banking, the article shows that banks have been more cautious than other businesses in using SNS. The available services are classified on nine main dimensions: marketing, financial education and advice, information support, customer support, sales representativeness, customer engagement, online recruitment, survey and polling, and other services. The scope of these SN banking services is for the most part non-cash-based. Conclusions, implications, and recommendations are discussed and future research priorities are identified.
Journal Article
Systemic cascades on inhomogeneous random financial networks
This article presents a model of the financial system as an inhomogeneous random financial network (IRFN) with N nodes that represent different types of institutions such as banks or funds and directed weighted edges that signify counterparty relationships between nodes. The onset of a systemic crisis is triggered by a large exogenous shock to banks’ balance sheets. Their behavioural response is modelled by a cascade mechanism that tracks the propagation of damaging shocks and possible amplification of the crisis, and leads the system to a cascade equilibrium. The mathematical properties of the stochastic framework are investigated for the first time in a generalization of the Eisenberg–Noe solvency cascade mechanism that accounts for fractional bankruptcy charges. New results include verification of a “tree independent cascade property” of the solvency cascade mechanism, and culminate in an explicit recursive stochastic solvency cascade mapping conjectured to hold in the limit as the number of banks N goes to infinity. It is shown how this cascade mapping can be computed numerically, leading to a rich picture of the systemic crisis as it evolves toward the cascade equilibrium.
Journal Article
Constructing banking networks under decreasing costs of link formation
The structure of networks plays a central role in the behavior of financial systems and their response to policy. Real-world networks, however, are rarely directly observable: banks’ assets and liabilities are typically known, but not who is lending how much and to whom. This paper adds to the existing literature in two ways. First, it shows how to simulate realistic networks that are based on balance-sheet information. To do so, we introduce a model where links cause fixed-costs, independent of contract size; but the costs per link decrease the more connected a bank is (scale economies). Second, to approach the optimization problem, we develop a new algorithm inspired by the transportation planning literature and research in stochastic search heuristics. Computational experiments find that the resulting networks are not only consistent with the balance sheets, but also resemble real-world financial networks in their density (which is sparse but not minimally dense) and in their core-periphery and disassortative structure.
Journal Article
Ranking consistency of systemic risk measures: a simulation-based analysis in a banking network model
In a banking network model, I analyse the ranking consistency of common systemic risk measures (SRMs). In contrast to previous studies, this model-based analysis offers the advantage that the sensitivity of the ranking consistency with respect to bank and network characteristics can easily be checked. The employed network model accounts, among others, for bank insolvencies as well as illiquidities, stochastic dependencies of non-bank loans as well as of liquidity buffer assets across various banks, bank rating-dependent volumes of deposits and interbank liabilities, and the funding liquidity reducing effect of fire sales of other banks. Within the assumed banking network model, I find that, in general, the ranking consistency (measured by the rank correlation) of various SRMs is rather low. A further finding is that the ranking consistency can significantly vary in statistical terms, for example for an increasing correlation between the returns of the liquidity buffer assets across banks, an increasing volatility of these assets or an increasing default rate in the non-bank loan portfolios. However, forecasting which effect a specific change in parameters, bank behavior or network characteristics has on the ranking consistency of SRMs seems to be difficult because the sign of the effect can be different for different pairs of SRMs. Furthermore, the economic significance of these changes on the overall ranking consistency as measured by Kendall’s coefficient of concordance in general is rather low.
Journal Article
Macroprudential regulation for a dynamic Chinese banking system with a scale-free network
The frequent global financial crises in recent years show that it is necessary to implement macroprudential regulation for the banking system. At present, quantitative research on the macroprudential regulation for the dynamic Chinese banking network system is lacking, while the related studies in other countries have not considered the interbank network structure. Therefore, in the present paper, we construct a dynamic banking network model with a scale-free network and a dynamic macroprudential regulation model under four risk allocation mechanisms (CVaR, Incremental VaR, Shapley value EL, and ΔCoVaR) for the dynamic Chinese banking network system. Then, we conduct empirical research to study the effect of the macroprudential regulation model on the Chinese banking network system. Our results show that the Chinese banking network system was the most unstable in 2010 and that the average default probability decreased every year after the macroprudential regulation, indicating the effectiveness of the macroprudential regulation model. From the perspective of the scale-free network structure, we find that the intrinsic mechanism of macroprudential regulation is to rewire the interbank linkages from small banks to large banks with more interbank lending to prevent contagious risk, thereby improving the stability of the entire banking system. Moreover, the regulation effects of ΔCoVaR and CVaR mechanisms are found to be better than those of the other mechanisms. The regulation effect of ΔCoVaR is the most significant.
Journal Article
Assessment of EU banking network regionalization during post-crisis period
Research background: Recent financial crisis of 2007?2008 has influenced global banking system and led to reduction of cross-border bank lending in the EU and worldwide. Global banking network has been analysed extensively in prior or post-crisis periods, but the literature on regionalization is scarce, especially with regard to the banking sector in the EU. Moreover, in previous empirical research evaluation of banking sector regionalization using network analysis methodology has not been yet applied. Purpose of the article: The aim of the article is to map the EU banking network and to assess its regionalization during post-crisis period. Methods: the paper employs comparative literature analysis and synthesis; BIS bilateral interbank cross-border claim yearly flows matrix data and network analysis method (including network mapping, structural and comparative analysis and the data of intraregional and interregional banking network matrices) to assess the changes in regionalization of the EU banking system. Findings & Value added: The results of the research show that during post-crisis period both, EU 12 and EU 28, banking networks became more clustered and more decentralized; also the level of regionalization within the EU banking network increased. Such results prove that the EU banking network has undergone structural changes with respect to bilateral interbank cross-border claims. This research adds to the knowledge of regionalization processes within the EU banking network during the post-crisis period and intends to be beneficial for market participants, EU level governmental bodies and financial policy makers.
Journal Article
Applying the Clique Percolation Method to analyzing cross-market branch banking network structure: the case of Illinois
This study applies the Clique Percolation Method (CPM) to an investigation of the changing spatial organization of the Illinois cross-market branch banking network. Nonoverlapping community detection algorithms assign nodes into exclusive communities and, when results are mapped, these techniques may generate spatially disjointed geographical regions, an undesirable characteristic for geographical study. Alternative overlapping community detection algorithms allow overlapping membership where a node can be a member of different communities. Such a structure simultaneously accommodates spatial proximity and spatial separation which occur with respect to a node in relation to other nodes in the system. Applying such a structure in geographical analysis helps preserve well-established principles regarding spatial relationships within the geography discipline. The result can also be mapped for display and correct interpretation. The CPM is chosen in this study due to the complete connection within cliques which simulates the practice by banking institutions of forming highly connected networks through multi-location operations in order to diversify their business and hedge against risks. Applying the CPM helps reveal the spatial pattern of branch banking connections which would otherwise be difficult to see. However, the CPM has been shown to not be among the best performing overlapping community detection algorithms. Future research should explore other possible algorithms for detecting overlapping communities. Detecting communities in a network only reveals certain characteristics of the spatial organization of the network, rather than providing explanation of the spatial-network patterns revealed. Full interpretation of the pattern must rely on the attribute data and additional information. This may illustrate the value of an integrated approach in geographical analysis using both social network analysis and spatial analysis techniques.
Journal Article