Bank Liquidity Risk Management Research Articles

Bank liquidity risk management through stable and volatile markets: The role of the asset-liability committee and lessons learned for the balance sheet governance operating model

This study examines the balance sheet management governance operating model of selected failed banks from 2007, 2008, 2009 and 2023, with emphasis on the corporate governance structure in place and the position of the asset-liability committee (ALCO), and draws conclusions and recommendations for future policy. All failed sample banks exhibited near-identical governance frameworks for management and oversight of balance sheet risk: namely an ALCO that reported to the senior executive management committee, and was at least two levels, if not three levels, below board level. It is inferred that, as the ultimate responsible and accountable forum for ensuring balance sheet viability and continuing going concern of the bank, the board would benefit from being closer to the balance sheet risk management process. This implies changing the governance structure such that the ALCO is closer to the board itself, and able to provide direct comfort to the board that the bank's capital and liquidity risks are being managed appropriately. The following bank governance measures are recommended, to be imposed by regulatory fiat if necessary: •Direct delegated authority of the ALCO to manage the balance sheet, from a long-term robustness and viability perspective, directly on behalf of the board. •The ALCO to report directly to the board, rather than via the executive management committee (or as an alternative approach, changed to become a sub-committee of the board). This recognises that the asset-liability management (ALM) discipline is at least as important as, if not more important than, the ‘audit’ oversight function undertaken by the board audit committee. •Technical expertise at ALCO and board level that is capable of discerning the genuine capital and liquidity risk exposure position of the bank, on a medium-term forward-looking basis, at all times.

Constructing early warning indicators for banks using machine learning models

This research contributes to bank liquidity risk management by employing supervised machine learning models to provide banks with early warnings of liquidity stress using market-based indicators. Identifying increasing levels of stress as early as possible provides management with a crucial window of time in which to assess and develop a potential response. This study uses publicly available data from 2007 to 2021, covering two severe stress periods: the 2007–2008 global financial crisis and the COVID-19 crisis. The current version of the developed model then applies backtesting using the data from the COVID-19 crisis. The findings of this study show that the ensemble model with the RUSBoost algorithm predicts “red” and “amber” days with a success rate 21% greater than the average of other machine learning models; thus, it can greatly contribute to bank risk management.

Intraday liquidity modelling using statistical methods

The correct approach to liquidity risk management in banks is essential for securing their financial stability. The position of liquidity risk among the rest of bank risks is specific because the negative outcome is not just a loss, but directly the bankruptcy of the institution. Such an occurrence might start a chain reaction and bring uncertainty into the entire financial system. This paper focused on one source of liquidity risk, i.e. management of liquidity throughout the day. The management of intraday liquidity is related to cash inflows and outflows occurring during the business day, their timing and settlement. In 2013, the BCBS published the document Monitoring tools for intraday liquidity management, often referred to by the regulatory authorities. It offers basic concepts of intraday liquidity monitoring and sketchily defines stress scenarios. The author suggests possibilities of how to perform intraday liquidity stress testing in a bank, which is often required by supervisors, even though no detailed approach or methodology as to how to proceed was introduced by the regulators. The research was carried out on anonymised data of cash inflows and outflows recorded on a central bank reserves account of one of the Slovak commercial banks. Both a base and four stress scenarios were developed and suggested for the better understanding of expected cashflows in standard conditions and during stress. The author’s aim was to develop scenarios in a non-traditional way by means of a basic and EWMA historical bootstrap simulations, respectively. Stress scenarios are supposed to simulate reputation crisis, disruption in RTGS payment system, increased deposit outflows and bank run. The purpose of the proposed intraday liquidity monitoring scenarios was to strengthen resilience not only for a concrete bank, but also the entire financial system. Intraday liquidity monitoring is a key factor in securing stability of the financial sector.

Security Optimization Management for loT-Assisted Bank Liquidity Risk Emergency Using Big Data Analytic-Based Case Reasoning

In modern times, financial institutions are the core carrier of efficient operation of financial markets. With the continuous development of financial models such as IoT (Internet of Things) finance, commercial banks have made many attempts in the integration and innovation of finance and logistics, but they have also increased the types and complexity of risks they face while improving financing efficiency. It has the characteristics of great destructiveness, strong infectivity, and high complexity. The establishment of a perfect emergency security optimization management for early warning of bank liquidity risk is an important part of timely detection and effective management of liquidity risk. In order to enable decision makers to accurately use the effective disposal of similar liquidity risk emergencies as a reference for decision-making, this paper studies the generation method of emergency security plan for bank liquidity risk using big data analytic-based case reasoning. Firstly, analyze the characteristics of various types of bank liquidity emergencies a, and identify the key risk points, and form the accident case database. Secondly, carry out the interval division according to the different numerical distribution characteristics of the indicators, and calculate the repeatability of the involved stages. Finally, calculate the comprehensive similarity to obtain the emergency security plan for reference. At the same time, taking A commercial bank as an example, verify the effectiveness of the method by using the constructed case-based reasoning model to generate emergency security plans intelligently. It provides reference for commercial bank liquidity risk management.

Market Power and Bank Liquidity Risk: Implementations of Basel III using Net Stable Funding Ratio Approach

Net Stable Funding Ratio (NSFR) published by Basel III as a new standard of bank liquidity risk management. In Indonesia, the Financial Services Authority (OJK) issued the OJK Regulation No. 50/POJK. 03/2017 concerning the obligation to fulfill the NSFR for commercial banks. The research objective is to test the influence of bank market power of assets, loans, and third-party funds toward bank's liquidity risk that measured by NSFR. The research uses a data panel from 37 commercial banks in Indonesia in the period 2018Q1-2019Q4. The hypotheses are examined by using linear regression methods with a random effect model. The result shows that the effect of market power on the risk of bank liquidity is proved. Market power will increase the NSFR, which means the higher the market power, the better management of liquidity risk. This research is expected to contribute theoretically to provide the latest literature on the application of Basel III through the NSFR approach, a current measurement for bank liquidity risk. Furthermore, this research is expected to contribute practically to banks and regulators in the formulation of policies related to market control and bank liquidity risk management. Based on the result, financial consolidation to enhance market power can be a solution to encourage bank liquidity. DOI : https://doi.org/10.26905/jkdp.v25i2.5525

Liquidity risk regulation and its practical implications for banks: the introduction and effects of the Liquidity Coverage Ratio

Following the financial crisis, quantitative liquidity risk regulation was introduced by means of the Liquidity Coverage Ratio (LCR). This literature study aims to investigate whether the introduction of the LCR leads to better liquidity risk management in banks. It elaborates on the drivers and definition of liquidity risk as well as the history, benefits and goals of this regulation. It also delves into the exact composition of the ratio and the assumptions used. The impact on bank lending as well as banks' business model and risk management is addressed, as well as the interaction with monetary policy operations and capital regulation. This paper then describes the operational differences that were observed after the implementation, and behavioral aspects. We also address the Net stable Funding Ratio (NSFR) and the discussion on interaction between the two indicators and possible redundancy. We have found that the introduction of the LCR leads to better management of liquidity risk for most financial institutions, but more harmonious implementation throughout the sector could reduce liquidity risk even further.

The Role of Regulation in Banking: Liquidity Risk Perspective

The liquidity crisis in 2008 sparked interest in the role of regulation that could promote resilience and stability in the banking system. While the Public Interest theory suggests that legal policies could discipline banking activities, the Private Interest theory predicts otherwise, which impairs banking performance. The conflicting theories warrant comprehensive research, especially for Islamic banks, as they emerge to gain their systemic importance. Given this, this study examines the role of banking regulation on liquidity risk management of banks in OIC countries from 2000 to 2014. The findings suggest that restrictions on banking activities and capital requirement pose a significant impact on liquidity risk. However, the marginal effect of regulatory capital is more pronounced in conventional banks compared to Islamic banks.

Modeling of Cash Flows from Nonperforming Loans in a Commercial Bank

Abstract The purpose of this paper is to derive a model for calculation of maturities and volumes of repayments that a bank may expect from nonretail nonperforming loans (hereafter NPLs). Expected inflows from nonretail NPLs follow a probability distribution, defined by size and timing of historic repayments of NPLs. Empirical analysis has shown that probability distribution of expected inflows from nonretail NPLs considerably deviates from symmetric distribution and is asymmetric to the right. Accuracy of derived model depends upon available data in banks about NPLs by corporate sectors and recovery rates by time intervals. The model in this paper is in interest of any bank and in particular of banks with a higher fraction of NPLs in their loan portfolio. Contribution of this paper to the added value in the area of liquidity risk management in banks is high because the remaining literature does not deliver other models for the same purpose.

Mencegah Gejolak Keuangan dengan Manajemen Risiko Likuiditas Perbankan

Sound liquidity risk management is needed to deal with the impact of liquidity risk that can bring contagion effects that threatens the financial system stability of a country. This study aims to analyze the necessary issues in liquidity risk management in Indonesia, which emphasized on four pillars. The main pillars of the bank's liquidity risk management include active oversight board of commissioners and directors; policies, procedures, and liquidity risk limits; liquidity risk management process; and internal control systems.

A Look at the Liquidity Management Practices of Banks in South Africa

In an effort to strengthen bank liquidity-risk management practices, the Basel Committee proposed new liquidity requirements for banks in 2010 under the Basel III framework. However, despite the good intentions of the liquidity requirements the new regulations are likely to present some challenges for banks in the course of managing their liquidity. However, before any inference can be made about the possible implications of the liquidity standards on bank liquidity management practices, it is imperative to have insight into the current liquidity management strategies of banks. This paper seeks to determine the current liquidity management practices of banks in South Africa by examining whether South African banks have target liquidity levels which they pursue and also by determining the variables that drive bank liquidity ratios. The study sample comprised six commercial banks operating in South Africa over the period 1993 to 2009. For analysis, a partial adjustment model was developed and estimated using the generalized method of moments (GMM) estimator. The rate at which South African banks adjust their balance sheets was estimated at 8%. This adjustment speed implies that South African banks adjust their balance sheets slowly – probably due to high adjustment costs. Thus, South African listed banks have passively managed their liquidity and partially adjust their liquidity levels in an attempt to reach the optimal level. Furthermore, the following variables were considered to be the main drivers of liquidity ratios in South Africa: bank size, capital adequacy, loan loss reserves, and financial crisis.

Poor Bank Liquidity Risk Management and Bank Failures: Nigerian Perspective

Nigeria has a long and sad history of bank failures. The problem became worse in the 1990s when many banks failed and in 2011 when several hitherto strong banks failed due to largely poor bank liquidity risk management. The Central Bank of Nigeria spent over US$6.8bn in purchasing the non-performing loans) of the failed banks. In fact, in the last few years the Central Bank of Nigeria and the Asset Management Corporate of Nigeria have been preoccupied in a bazaar of non-performing loans. Banks as custodians of depositors funds are expected to exercise due care and prudence in their lending activities and with regard to bank liquidity risk management best practice. This study was designed to asses the relationship between poor bank liquidity risk management and bank failures. Bank liquidity risk is a risk of loss to a bank arising from a bank not having adequate funds to meet deposit withdrawals and loan demands. The survey research design was deployed for the study. Data were generated from both primary and secondary sources. Reliability for the instrument used for the collection of data was calculated at 0.93 through the Cronbach’s Alpha technique. Coded data were analyzed by descriptive statistics and the Pearson’s correlation methods. The result of correlation was r = .993*, which meant that poor bank liquidity risk management has strong positive relationship with bank failures. Five recommendations were made based on the result of this study.

Loan Sales and Bank Liquidity Risk Management: Evidence from a U.S. Credit Register

We examine the impact of banks' liquidity risk management on secondary loan sales. We track the dynamics of bank loan share ownership in the secondary market using data from the Shared National Credit Program, a credit register of syndicated bank loans administered by U.S. regulators. We analyze the 2007-2009 financial crisis as a market-wide liquidity shock and control for loan demand using a loan-year fixed effects approach. We find that banks with greater reliance on wholesale funding at the onset of the crisis were more likely to exit loan syndicates during the crisis. Our analysis identifies the importance of bank liquidity risk management as a motivation for loan sales, in addition to the credit risk transfer motive emphasized in prior literature.

Loan Sales and Bank Liquidity Risk Management: Evidence from a U.S. Credit Register

We examine the impact of banks' liquidity risk management on secondary loan sales. We track the dynamics of bank loan share ownership in the secondary market using data from the Shared National Credit Program, a credit register of syndicated bank loans administered by U.S. regulators. We analyze the 2007-2009 financial crisis as a market-wide liquidity shock and control for loan demand using a loan-year fixed effects approach. We find that banks with greater reliance on wholesale funding at the onset of the crisis were more likely to exit loan syndicates during the crisis. Our analysis identifies the importance of bank liquidity risk management as a motivation for loan sales, in addition to the credit risk transfer motive emphasized in prior literature.

Loan Sales and Bank Liquidity Risk Management: Evidence from a U.S. Credit Register

Loan Sales and Bank Liquidity Risk Management: Evidence from a U.S. Credit Register

Loan Sales and Bank Liquidity Risk Management: Evidence from a U.S. Credit Register

Loan Sales and Bank Liquidity Risk Management: Evidence from a U.S. Credit Register

Post‐crisis bank liquidity risk management disclosure

PurposeThe purpose of this paper is to investigate post‐crisis measures banks have adopted in a bid to manage liquidity risk. It is based on the fact that the financial liquidity market was greatly affected during the recent economic turmoil and financial meltdown. During the crisis, liquidity risk management disclosure was crucial for confidence building in market participants.Design/methodology/approachThe study investigates if Basel II pillar 3 disclosures on liquidity risk management are applied by 20 of top 33 world banks. Bank selection is based on information availability, geographic balance and comprehensiveness of the language in which information is provided. This information is searched from the World Wide Web, with a minimum of one hour allocated to “content search”, and indefinite time for “content analyses”. Such content scrutiny is guided by 16 disclosure principles classified in four main categories.FindingsOnly 25 per cent of sampled banks provide publicly accessible liquidity risk management information, a clear indication that in the post‐crisis era, many top ranking banks still do not take Basel disclosure norms seriously, especially the February 2008 pre‐crisis warning by the Basel Committee on Banking Supervision.Research limitations/implicationsBank stakeholders should easily have access to information on liquidity risk management. Banks falling‐short of making such information available might not inspire confidence in market participants in events of financial panic and turmoil. As in the run‐up to the previous financial crisis, if banks are not compelled to explicitly and expressly disclose what measures they adopt in a bid to guarantee stakeholder liquidity, the onset of any financial shake‐up would only precipitate a meltdown. The main limitation of this study is the use of the World Wide Web as the only source of information available to bank stakeholders and/or market participants.Originality/valueThe contribution of this paper to literature can be viewed from the role it plays in investigating post‐crisis measures banks have adopted in a bid to inform stakeholders on their management of liquidity risk.

Zarządzanie ryzykiem płynności w bankach działających w Polsce w dobie globalnego kryzysu finansowego

Zarządzanie ryzykiem płynności w bankach działających w Polsce w dobie globalnego kryzysu finansowego

BANK LIQUIDITY RISK: ANALYSIS AND ESTIMATES

In today’s banking business, liquidity risk and its management are some of the most critical elements that underlie the stability and security of the bank’s operations, profit-making and clients confidence as well as many of the decisions that the bank makes. Managing liquidity risk in a commercial bank is not something new, yet scientific literature has not focused enough on different approaches to liquidity risk management and assessment. Furthermore, models, methodologies or policies of managing liquidity risk in a commercial bank have never been examined in detail either. The goal of this article is to analyse the liquidity risk of commercial banks as well as the possibilities of managing it and to build a liquidity risk management model for a commercial bank. The development, assessment and application of the commercial bank liquidity risk management was based on an analysis of scientific resources, a comparative analysis and mathematical calculations.

English

The paper investigated liquidity management by commercial banks when there was hyperinflation. The main enquiry of this study was to understand how Zimbabwe commercial banks managed liquidity risk in a hyperinflationary environment. To achieve this, information was obtained from primary sources with data collected from decision makers of fifteen commercial banks which met the criteria of full scale operation from 2000 -2009. To compliment this, secondary data sources were used. Focal areas of the study were to analyse years of bank business; ownership; liquidity risk management responsibility; products offered by commercial banks; major sources of funds and applications; internal and external liquid instruments to manage liquidity risk, impact of inflation on liquidity risk management; and the effect the Reserve Bank of Zimbabwe instruments introduced to fight inflation. The findings show that liquidity risk management during the hyperinflation was a challenge. The Instruments used by the Reserve Bank of Zimbabwe to fight inflation had negative effect on commercial banks asset and liability management. In line with this, the monetary authorities were recommended to put in place measures which took into consideration the impact of their policies on bank liquidity risk management when there are problems of high inflation. The study also recommends commercial banks to take proactive management measures and long term views to operations, in other words beyond the current challenges posed by inflation. In the process banks would create new demand for the products. Key words: Commercial banks, liquidity management, assets, liabilities, hyperinflation, Reserve Bank of Zimbabwe.

Bank liquidity risk management: A South African survey to determine future change

In 2008 the global financial system and, more particularly, the world banking system suffered a financial crisis worse than any earlier crises. The financial crunch brought to light that liquidity risk management in banks poses a problem, and that the world’s financial institutions will have to change their current practices as it relates to this risk. Apart from the importance of liquidity and the risk that it may cause, the integrated nature of all risks made banks more aware of the fact that none of these risks can be managed in isolation. For various reasons, South African banks were not as exposed to the problems experienced in the global context. However, SA banks may have learned new lessons from the crisis and may plan to change the way they manage liquidity risk in particular, in the future. In order to determine how SA banks perceive liquidity management and liquidity risk, a survey of all SA banks was carried out. The majority of respondents indicated that the financial crisis reminded them of the importance of liquidity risk management in the South African banking system as well as the global banking system. The majority of banks rate all the liquidity risk management tools as extremely important and rate corporate governance, strategy, policy and risk tolerance, liquidity risk measurement and intra-day liquidity as their number one priority. Basel III is generally perceived as being effective, but 30% of respondents perceived it as neither effective nor ineffective, because South African banks already have similar measures in place.