Bad Banks Research Articles

Deutsche Bank Restart: Goodbye Goldman Sachs of Europe?

This public-sourced case describes the latest restructuring efforts by Deutsche Bank (DB) and gives a short history of prior restructuring efforts from the decade before. In July 2019, Christian Sewing, the new CEO of DB, announced a series of measures that included, among others, the elimination of global equity trading, the layoff of 18,000 employees, the creation of a “bad bank” to transfer noncore assets, and the suspension of dividends until 2022. The case describes key decisions a bank CEO makes when a bank needs to change course to return to profitability and growth. The case offers an opportunity to debate these key decisions, as well as discuss some of the prior ones during earlier restructuring efforts, and put the students in the CEO's shoes: What would you do and why? The case also describes key banking performance metrics (e.g., ROE, ROA) and other critical variables such as those reflecting capital health (Tier 1 ratio), as well as gives an overview of the bank business model and factors impacting bank profitability and value.

A critique of the national asset reconstruction company, India’s bad bank

PurposeThis study aims to provide a critique of the institutional framework of the National Asset Reconstruction Company Limited (NARCL), India’s “bad bank.”Design/methodology/approachThe approach followed is the development of an economic model of the gains to trade of an Asset Reconstruction Company.FindingsUsing an economic model, the paper shows that the rules of the game create an uneven playing field and are likely to lead to a systematic overpricing of nonperforming loans (NPLs). While this might increase the upfront cash received by the bank, it will come at the cost of higher liabilities for the government on account of the sovereign guarantee that is part of the proposed structure. The overpricing is also likely to act as an obstacle to efforts aimed at the revival of the distressed company. The NARCL could become a warehouse for NPLs subverting the objective of reconstruction.Practical implicationsSolutions to create a vibrant market for NPLs are proposed.Originality/valueThe Indian case is unique in the sense that a bad bank backed by the government has been introduced after almost two decades of the existence of similar entities in the private sector. To the best of the author’s knowledge, this paper is the first that addresses the design of such a market using economic modeling.

How effective are bad bank resolutions? New evidence from Europe

The paper studies the effectiveness of bank resolutions using a comprehensive database on banks headquartered in 18 European countries over the period 2000–19. By means of difference-in-differences methodology, we find that impaired asset segregations – otherwise known as bad banks – have been more effective than state-funded recapitalisations of distressed banks. While recapitalised banks seem to have used the injected funds mainly to clean up their balance sheets by reducing problem loans and cutting down on lending, banks that segregated assets increased progressively their lending after the creation of the bad bank. For both types of banking crisis interventions, we find a significant ex-post reduction in the cost of bank funding and shift towards deposit funding.

The impact of bank's engagement in shadow banking activities on bank's sustainability: Evidence from Chinese commercial banks.

The economic and environmental consequences of bad banking practices have aroused much attention. In China, banks are at the center of shadow banking activities through which they avoid regulation and support environmentally unfriendly businesses such as fossil fuel companies and other high-pollution enterprises. In this paper, we study the impact of bank's engagement in shadow banking activities on its sustainability by using annual panel data of Chinese commercial banks. The result shows that bank's engagement in shadow banking activities has a negative impact on its sustainability and the negative impact of bank's engagement in shadow banking activities is more pronounced for city commercial banks and unlisted banks which are less regulated and lack corporate social responsibility (CSR). Furthermore, we explore the underlying mechanism of our findings and prove that bank's sustainability is impeded because it transforms high-risk loan into shadow banking activities which are less regulated. Finally, by using difference-in-difference (DiD) approach, we find that bank's sustainability improved after the financial regulation on shadow banking activities. Our research provides empirical evidence that the financial regulation on bad banking practices is beneficial for bank's sustainability.

How Good is the Bad Bank for Wiping-Off the Bad Loans?

How Good is the Bad Bank for Wiping-Off the Bad Loans?

PEMBIAYAAN UMKM DAN LIKUIDITAS TERHADAP RESIKO PEMBIAYAAN BANK UMUM SYARIAH DI INDONESIA PERIODE 2019-2021

Poor financing quality can affect company profits and revenues, decreased profits have an impact on the ability of banks to channel financing which causes Islamic banking to experience financing risks or problematic financing. This study aims to find out how the independent variables (MSME financing and liquidity) influence the dependent variable (financing risk) of Islamic commercial banks in Indonesia for the 2019-2021 period. The method used in this study is quantitative with descriptive statistics, the classic assumption test, namely the normality test, multicollinearity, autocorrelation, and heteroscedasticity test, is also equipped with hypothesis testing, namely the t (partial) test and f (simultaneous) test. The population used in this study is the statistical financial reports of Islamic commercial banks with samples of MSME, FDR and NPF data for 2019-2021 obtained from the Financial Services Authority. From OJK data, the results show that MSME financing does not have a significant effect on financing risk because there is a guarantee from the government to the community, namely the people's business credit program (KUR) which is channeled through Islamic banking institutions, good and bad bank liquidity does not have an impact on financing risks and financing risks occur because problematic financing from customers is not caused by Islamic banking institutions or liquidity owned by Islamic banking. The conclusion of this study is that the Ho hypothesis is accepted, showing that one or both of the independent variables (MSME financing and liquidity) have no effect on the dependent variable (financing risk) of Islamic general banks in Indonesia for the 2019-2021 period.

How Bad Banks will help to Tackle NPA

Purpose: This paper presents a brief overview of bad banks, how they work, impact NPAs, a view on how bad banks can help to remove the stressed asset, the necessity for implementing bad banks, and a few key positive and negative opinions on basis of SWOT analysis or point of view on the establishment of bad banks. Methodology: The data has been collected from a variety of sources, including newspapers, research papers, websites, and journals. The information has been analyzed and synthesized to provide a comprehensive overview of the topic. Findings: A bad bank is a financial institution specializing in managing assets that are likely to default and is characteristic of troubled loans. The bank aims to separate risky assets from traditional banks so that they can be dealt with separately, either sold or restructured. High NPA’s suggest that banks’ funds are locked and the bank does not have enough money to lend. Originality: A bad bank is a financial institution that holds non-performing assets (NPAs) of another bank or financial institution. The purpose of a bad bank is to remove these NPAs from the original institution’s balance sheet so it can focus on its core operations. A bad bank is also sometimes known as an "NPA resolutions bank." Type of Paper: Conceptual Paper.

How Bad Banks will help to Tackle NPA

How Bad Banks will help to Tackle NPA

Bad Bank: The Concept of Making Good the Bad Assets of Banks

The study mainly focused on the concept of bad banks. Bad bank concept emerged as a solution to the crisis of non-performing assets. When bad bank is established with sufficient government and legal support, it works best. In India, the concept of a bad bank as long been shunned. The opportunity exists for the financial sector to be prepared to release cash thanks to bad bank that is actually an asset reconstruction company (ARC). As the effect of the global monetary crisis continue to be felt, there has been a rise in recent times in amount of public discussion surrounding ideas to place stressed assets in one or many bad banks. Globally, it is believed that managing non-performing assets requires government and legal support for a bad bank to succeed. The paper provided information on nonperforming assets and measures that banks can use to resolve them. Bad bank is a concept to solve the issues of stressed assets. The features of bad bank have been explained and the evolution of bad banks globally is also included in this study. The secondary source of data collected is from the analysis of various articles. The main goal is to identify the challenges faced by India in implementing bad banks.

INTRODUCTION OF BAD BANK IN THE INDIAN BANKING SYSTEM

A bank is a type of financial institution that deals with money and offers a variety of financial services. They have the responsibility of accepting the deposits and providing the loans to the customers and earning profit. The bank receives deposits from a range of customers, which are then circulated to the general public in the form of loans. If everything goes well, the loan is repaid on time then the loan is categorized as a normal asset, but if things go wrong the same asset can become a burden for the bank, if the repayment is not made on time for a variety of reasons, then these assets are classified as NPAs (non-performing assets). The idea of a bad bank has been suggested by many professionals in India, but during COVID-19 the idea got some major consequences. As a result, when presenting the budget for 2021-2022, the Union Finance Minister advocated the construction of these new types of banks. The governor of the Reserve Bank of India has also agreed to participate in this unique concept for maintaining the banking sector's growth and financial stability. The current paper examines the concept of bad banks, as well as its origins and implementations around the world.

Bank capital structure and regulation: Overcoming and embracing adverse selection

We study bank regulation under optimal contracting, absent exogenous distortions. In equilibrium, banks offer a senior claim (deposits) to external investors and retain equity; the return on equity is higher than the return on deposits due to a scarcity of skilled bankers. Inefficient equilibria emerge under asymmetric information. Optimally designed regulation restores efficiency. Our main result is that disclosure requirements by themselves can be endogenously costly because they may push the economy from a separating equilibrium to a less efficient equilibrium that pools good and bad banks, but always improve welfare when combined with capital regulation.

Mechanism of a Bad Bank is to Reduce Stress Assets for achieving economic growth and Financial Stability

The setting of Bad bank for purpose of resolve the Non-Performing Assets/ Taxie Assets.1US based Mellon Bank created the First bad back in 1988. Government created2Stressed Asset Stabilization Fund (SASF) in 2004, When IDBI was converted in to Bank. The 2008 Financial Crises, Coronavirus Pandemic 19 ,implementation of 3Bankruptcy Code and the recent amendment to the Banking Regulation Act4,creation of a ‘bad bank mechanism is assess the bad loans of corporate, individuals , Small and Medium enterprise’s(SME), PMMY and the true extent of stressed assets. Bad Bank mechanism has been implemented in other countries including Sweden, Finland, France and Germany5, Japan set up bad bank in the name of Credit Co-operative Purchasing Company which bought the stressed

Classification of Non-Performing Financing Using Logistic Regression and Synthetic Minority Over-sampling Technique-Nominal Continuous (SMOTE-NC)

Financing analysis is the process of analyzing the ability of bank customers to pay installments to minimize the risk of a customer not paying installments, which is also called Non-Performing Financing (NPF). In 2020 the NPF ratio at one of the Islamic banks in Indonesia increased due to the decline in people’s income during the Covid-19 pandemic. This phenomenon has led to bad banking performance. In December 2020 the percentage of NPF was 17%. The imbalance between the number of good-financing and NPF customers has resulted in poor classification accuracy results. Therefore, this study classifies NPF customers using the Logistic Regression and Synthetic Minority Over-sampling Technique Nominal Continuous (SMOTE-NC) method. The results of this study indicate that the logistic regression with SMOTE-NC model is the best model for the classification of NPF customers compared to the logistic regression method without SMOTE-NC. The variables that have a significant effect are financing period, type of use, type of collateral, and occupation. The logistic regression with SMOTE-NC can handle the imbalanced dataset and increase the specificity when using logistic regression without SMOTE-NC from 0.04 to 0.21, with an accuracy of 0.81, sensitivity of 0.94, and precision of 0.86. Keywords: Classification, Islamic Bank, Logistic Regression, Non-Performing Financing, SMOTE-NC.

Bad Bank is Actually a Good Idea

This article demonstrates the effect of bad loans in India which was developed recently by the Indian Finance Minister. Bad banks operate like a concept in the domestic debt sector where the amount of domestic debt is high and even the market has enough scale to bear enough price-discovery and market-making. there was a proposal made to the government, to merge the NPA portfolio with a new establishment known as an Asset Rehabilitation Corporation (ARC), that would purchase the principal of the Non-performing Assets (NPA) portfolio at a book valuation (not market value) and these accounts would be taken over by the new company to manage the portfolio of the new command (which will be established with a capital of Rs 10,000 crore). The government says that it is intervening to mitigate potential damages that the banks could suffer as a result of the provisioning for non-performing assets and recapitalisation that the government (as a majority investor of most PSBs) may be required to invest on. With the forthcoming Union budget’s planning an outpouring of clamour and market demand is being felt to set up a ‘poor bank’ to sweep bad debts.

Banks as Potentially Crooked Secret Keepers

AbstractBank failures are generally liquidity as well as solvency events. Whether it is households running on banks or banks running on banks, defunding episodes are full of drama. This theater has, arguably, lured economists into placing liquidity at the epicenter of financial collapse and liquidity provision as opposed to improved intermediation as the rationale for banks. But loss of liquidity describes how banks fail . Bad news about banks explains why they fail. This paper models banks as arising from asymmetric information. Banks have superior knowledge of investment opportunities. But bankers, or at least a subset, also know how to steal. Hence, we model banking crises as triggered by news that the degree (share) of banking malfeasance is likely to be particularly high. The malfeasance share follows a Markov process. When this period's share is high, agents rationally raise their probability that next period's share will be high as well. Whether or not this proves true, agents invest less in banks, reducing intermediation and output. Worse, bad bankers can infect good bankers. When bad bankers are thought to abound, good bankers have less incentive to secure a high return on their investment. Deposit insurance prevents defunding runs and stabilizes the economy. But it sustains bad banking, lowering welfare. Private monitoring helps, but is no panacea. It partially limits banking malfeasance. But it does so inefficiently as households needlessly replicate each other's costly information acquisition. Moreover, if private audits become public, private monitoring breaks down due to free‐riding. Redistribution between generations that do and do not confront the highest share of banking malfeasance does not relieve the problem. What does improve matters is government real‐time disclosure of banking malfeasance. This mitigates, if not eliminates, the asymmetric information problem leading to potentially large gains in both nonstolen output and welfare.

‘Bad Banks’ with Chinese Characteristics: an Ongoing Transformation

ABSTRACT This article analyzes the experience of four asset management companies (AMCs) or ʽbad banks’ established in China in 1999 to address a systemic build-up of non-performing loans (NPLs). It describes the modalities of NPL transfers across several rounds of government interventions. It explains the AMCs evolving asset structure, funding and operations, with particular focus on a significant change in their business model. Overall, AMCs have helped stabilize the Chinese financial sector, albeit at a substantial fiscal cost. While they became permanent features of the financial system, the expansion of non-core activities has reduced their ability to perform their original function and generated additional systemic risk. Recent developments point to a renewed role, although a deeper reform of the NPL market will also be needed.

Relationship Lending and Switching Costs under Asymmetric Information about Bank Types

This theoretical paper extends the pioneering articles on relationship lending (e.g., Sharpe. J Finance XLV(4): 1069-1087, 1990; Rajan. J Financ 47: 1367–1400, 1992; von Thadden. Financ Res Lett 1(1): 11–23, 2004) by examining relationship lending and hold-up problems in credit markets when borrowers are identical and banks are different. The results show that existing borrowers are informationally captured by good banks and yield profits to them, but new borrowers are unprofitable. In this market, short-term loan contracts and unsecured loans are optimal while loan commitments should not be used. Further, banks and borrowers have long-term relationships. This paper challenges the standard theories on product quality, reputation and experience goods by introducing scenarios in which good and bad banks can retain their existing borrowers. In the standard theories, consumers leave bad producers and search for good ones.

Determinants of Losses on Construction Loans: Bad Loans, Bad Banks, or Bad Markets?

Determinants of Losses on Construction Loans: Bad Loans, Bad Banks, or Bad Markets?

In from the socialist “cold,” but burned by the capitalist “heat”? The dynamics of political revolution and economic transformation in Eastern Germany after 1990

This article examines the crisis-ridden path from planned to market economy in Eastern Germany after the fall of the Berlin Wall in 1989. By analyzing the history of the highly debated Treuhandanstalt—the so-called Trust Agency and the main actor of the economic reconstruction—the discussion sheds light on the political modes of decision making in the East and especially its long-term effects. The focus is on the negotiations carried out at the Central Round Table in early 1990, the first free elections in March 1990, the deliberations between Federal and East German governments in summer 1990, the discrete bargaining strategy of the Treuhand in 1991‒1992, and the massive public debates and scandals connected to the Treuhand in 1993‒1994. The organization is interpreted as an exceptional regime of economic experts that managed the socioeconomic “shock” of economic reconstruction as a kind of “shield of protection” for the political system, but at the same time it was unable to buffer the dramatic sociocultural consequences of closures and mass unemployment: Recent debates and election campaigns in 2019 highlight the fact that the Treuhand is still present as a negative myth or “bad bank” of East German memory culture open for populist campaigning.

Novo Banco – what good out of a bad bank?

Research methodology Analysis of public sources. Case overview/synopsis The bank named “Novo Banco” (New Bank in Portuguese) was created because of an emergency intervention by the Bank of Portugal to save the “good” assets of the once great but bankrupt Banco Espírito Santo (BES) on August 4, 2014. The toxic assets remained in BES (dubbed “bad bank”). BES was one of the biggest private banks in Portugal, with origins mounting back to the year 1869. In 2013, it was headed by the founder’s great-grandson, Ricardo Salgado, when an external audit revealed several problems with the bank’s accounting and concluded that BES had a severe financial problem (the risky credit represented 11.1% of the bank’s accounts). The bank underwent a public capital increase (endorsed by several public figures, including the Portuguese President at the time, Cavaco Silva) of €1.045m to reposition itself, which was 100% successful (demand of about 160%, with a significant part of foreign investors). However, continued amounts of suspicions led Ricardo Salgado to be replaced by Vitor Bento (via a settlement between BES’s shareholders and the Bank of Portugal) in July 2014. At the end of that same month, BES announced imparities totaling the amount of €4.2535m. This led the European Central Bank to suspend BES’s access to the financial operations, forcing it to reimburse its credit to the Eurosystem in the value of €10.000m. In two days, the stock prices dropped by 80% to around €0.03 per share. It was later proven that the administration led by Ricardo Salgado had disobeyed the Bank of Portugal 21 times between December 2013 and July 2014, apparently acting against the institution’s best interests. Some carousel schemes with companies within the Espirito Santo Group were also detected in BES’ financial movements to improve the bank’s financial statements. Complexity academic level Finance Valuation, Strategy