Systemic operational risk: does it exist and, if so, how do we regulate it?

Systemic Importance of Financial Institutions: Regulations, Research, Open Issues, Proposals

Decomposing the Smile: Systematic Credit Risk in Mortgage Portfolios

In China, commercial banks participate in shadow banking activities through interbank or channel businesses, which should be called bank’s shadow banking activities. Based on the co-opetition game model, we first analyse the fund flow mechanism between bank’s shadow banking and traditional credit business, which confirms that the greater the proportion of bank’s shadow banking investment, the higher the bank profit. By sampling 147 commercial banks in China during 2003 to 2019, we empirically study the impact of bank’s shadow banking on the individual risk of commercial bank by OLS regression and on the systemic risk of banks through the randomized effect model from the micro-level. The results confirm that Chinese bank’s shadow banking will increase the individual operating risk of commercial bank and its rapid development will increase the probability of banking system risk. Meanwhile, we find that global financial crisis has no significant effect on the risk of individual banks or banking systems, but the regulatory overhaul of bank’s shadow banking activities can significantly inhibit the individual bank’s operational risk, especially for listed banks.

The Covid-19 pandemic has brought about a heavy impact on the world economy, which arouses growing concerns about potential systemic risk, taking place in countries and regions. At this critical moment, it makes sense to interpret the systemic risk from the perspective of the financial crisis framework. By combing the latest research on systemic risks, we may arrive at some precautions relating to the current events. This literature review verifies the origin of systemic risk research. By comparing the retrieved and screened systemic literature with the relevant research on the financial crisis, more focus on the micro-foundations of systemic risk has been discovered. Besides, the measurement methods of systemic risks and the introduction of interdisciplinary methods have made the research in this field particularly active. This paper synthesizes the previous research conclusions to find the appropriate definition of systemic risk and combs the research literature of systemic risk from two lines: Firstly, conducting the division according to the sub-branch fields within the financial discipline and the relevant interdisciplinary research methods, which is helpful for scholars within and outside the discipline to have a more systematic understanding of the research in this field. Secondly predicting the research direction that can be expanded in this field.

Insurers as Systemically Important Financial Institutions (SIFIs)? Exploration and Methodology

To optimize the dispatch and operation control of high proportion renewable energy power system, it is necessary to accurately quantify and evaluate the operational risk of system. For the high proportion renewable energy power system with uncertain wind and light sources, this paper presents a operational risk assessment method of wind and water systems based on probability assessment. By analyzing the distribution of uncertainty probability of system, the state probability is expressed as wind power output probability, solar output probability, transmission line probability and real-time state probability of system components. Use the analytic hierarchy process to assign weight to each type of risk indicators to solve the importance matching problem of different types of risk. On this basis, a operational risk assessment model is built by using Monte Carlo method which is used to select the real-time system states. Finally, an example is analyzed based on the actual power grid in a certain area, and calculation results show that the proposed quantitative calculation method for operational risk assessment of wind, solar and water multi-energy power systems can effectively evaluate the actual operation risk of system and meet the risk assessment requirements of high proportion renewable energy power system.

Systemic risk refers to risks that have a broad and severe impact on the entire financial system or economic system. There are similarities in the definition of systemic risk in China and abroad, which usually refer to threats to the entire financial system or economic system, which can trigger a chain reaction and lead to a systemic collapse. In terms of characteristics and measurements, there may be some differences in views and methods at home and abroad. While foreign countries usually pay more attention to the interconnectedness of financial institutions, market liquidity, macroeconomic factors, etc., China may pay more attention to factors such as the stability of financial markets and the role of state-owned enterprises and governments in the economy. The shortcomings of systemic risk abroad may lie in the fact that the unique circumstances of some characteristic countries or regions are sometimes overlooked, because these factors are not universally applicable on a global scale. Due to its unique environment of large economic size, complex financial system, government intervention, and the influence of state-owned enterprises, the study of systemic risk is particularly important for China. This particular situation may require unique methods and metrics to measure and address risks to ensure the stability and sustainability of China's financial system. It is precisely in view of the lack of foreign research on China's specific context that it is of great significance to study the systemic risk of China's banking industry under China's financial system.

The multi-layer network nature of systemic risk and its implications for the costs of financial crises

For what it concerns the first aspect, there are several definitions of systemic risk (see for in‐ stance: [1]; [2], [3] and [4]), but there is not any widely accepted definition for it. Nevertheless, we agree with the position of [5] who claimed that systemic risk can be identified by the pres‐ ence of two distinct elements: an initial random shock, as the source of systemic impact, and a contagion mechanism (such as the interbank market or the payment system), which spread the negative shock wave to other members of the system. Along this vein, a growing body of em‐ pirical research has already bloomed: [6] suggested a network approach to analyze the impact of liquidity shocks into financial systems; a similar approach was followed by [7] discussing the case of United Kingdom, Boss [8] for Austria, and [9] for Switzerland; more recently Sora‐ maki et. al. (2012) developed a software platform1 that employs graphs models for various pur‐ poses, including to monitor financial contagion spreading effects.

Regulating Systemic Risk: Towards an Analytical Framework

Purpose: This study develops a novel methodology for measuring systemic risk through a multidimensional approach, focusing on the impact of exogenous factors. By identifying systemic risk and analysing individual risk factors, we aim to provide a more comprehensive understanding of vulnerabilities in the financial sector. Design/methodology/approach: We use econometric models to assess systemic risk, applying our method to eight systemically important financial institutions in Poland between 2005 and 2023. Our analysis covers various risk factors, including climate risk, stock market fluctuations, and interbank liquidity, enabling both isolated and overall assessment of the impact of exogenous shocks on the system. Findings: Our results show that climate risk is becoming increasingly significant, particularly in light of recent crises such as the COVID-19 pandemic and Russia's invasion of Ukraine. We also observe an increase in systemic risk during specific periods (2008-2009 and 2011 2013), with the impact of individual shocks varying. Research limitations/implications: Our results highlight the need for sophisticated, multidimensional analyses of systemic risk to enhance the resilience of financial systems against diverse shocks. Practical implications: This research contributes to the existing literature by offering a universal framework for assessing systemic risk that aggregates multiple exogenous factors, particularly emphasizing the often-overlooked role of climate risk. Social implications: The research provides a framework for identifying systemic risks, including climate-related vulnerabilities, enabling policymakers to enhance the resilience of financial systems and protect societal stability against diverse economic and environmental shocks. Originality/value: Importantly, we are the first to combine transition risk indicated by stranded assets with physical risk, measured by temperature deviations from the multi-year average, in the assessment of Polish systemic climate risk.

Systematic risk has been a focus for stress testing and risk capital assessment. Under the Vasicek asymptotic single risk factor model framework, entity default risk for a risk homogeneous portfolio divides into two parts: systematic and entity specific. While entity specific risk can be modelled by a probit or logistic model using a relatively short period of portfolio historical data, modeling of systematic risk is more challenging. In practice, most default risk models do not fully or dynamically capture systematic risk. In this paper, we propose an approach to modeling systematic and entity specific risks by parts and then aggregating together analytically. Systematic risk is quantified and modelled by a multifactor Vasicek model with a latent residual, a factor accounting for default contagion and feedback effects. The asymptotic maximum likelihood approach for parameter estimation for this model is equivalent to least squares linear regression. Conditional entity PDs for scenario tests and through-the-cycle entity PD all have analytical solutions. For validation, we model the point-in-time entity PD for a commercial portfolio, and stress the portfolio default risk by shocking the systematic risk factors. Rating migration and portfolio loss are assessed.

Risks of payment system of banking institutions of Ukraine are considered in this study. Risk events clearly correlate to the effectiveness of network interaction of banking institutions to adapt information technology of payment systems in the payment portfolio of banks when changing operating environment, so mechanism for minimizing their probability has been developed. Economic elements of the mechanism of minimizing the risks of payment systems are identified, which allow forming the planned level of profitability, risk and liquidity of institutions (organizations) within the relevant principles, methods, levers, cash flows in order to respond and adapt to changes in the environment. A methodical approach to assessing the effectiveness of risk management of payment systems of banking institutions, which is from the standpoint of multivariate structuring and a list of their indicators of the microeconomic level, forms an optimal set of tools to minimize the set of risks. Indicators of payment systems of Ukraine are determined, according to the net level of credit risk, liquidity risk, business risk, investment risk, legal risk, operational risk, systemic risk, technological and information security risk. The impulse index of functioning of payment systems of Ukraine is calculated. A neuro-fuzzy model for assessing the individual credit risk of participants – legal entities (users-borrowers) of card payment scoring of a banking institution is developed. The basic criteria for assessing the individual credit risk of a participant-legal entity (user-borrower) by card payment scoring are determined.

Global financial crisis in 2008 has driven special attention to systemic banking sector risk that cause byindividual bank default. Though, banking crisis significantly affect economic growth and national macroeco-nomic condition. Individual bank default non only affect banking industry but also has serious injured theeconomy. Bank default risk not only affect systemic risk but also systematic risk.ASEAN financial integrationplan raise a need to understand characteristics of ASEAN banking industry. Close relationship and intercon-nection between ASEAN economies will make individual bank default a serious issue that its effect will spreadto all ASEAN economy. This research aimed to investigate the effect of bank default risk on systemic andsystematic risk in 5 ASEAN countries. We find that bank default risk significantlyraised systemic risk, esspeciallyin country with high concentration in its banking industry structure. Big banks tend to more serious effect onsystemic risk. Systematic risk tend to be affected by macroeconomy condition, rather than default risk ofindividual bank.

Operational Risk is More Systemic than You Think: Evidence from U.S. Bank Holding Companies