Green credit is intended to support firms with truly environmental potential, but the widespread greenwashing by firms undermines its effectiveness and hinders progress toward sustainable development goals. This study investigates whether the adoption of artificial intelligence (AI) by banks can address this issue. Using a dataset of 1209 loan contracts issued in China between 2019 and 2023, which is one of the largest polluters and green finance implementors, we find that banks adopting AI impose significantly higher interest spreads on firms exhibiting signs of greenwashing. The effect is more prominent for loan contracts granted by green-experienced banks and those to non-polluting firms. Our analysis identifies two underlying mechanisms: AI enhances banks' capabilities for both risk identification and legitimacy. These findings offer novel insights into the role of technological advancement in green credit practices and contribute to the growing literature at the intersection of finance, sustainability, and digital transformation.

This paper studies the effects of financial market development on bank deposits in a cross-country setting. Our empirical evidence shows that investors in developed and developing economies engage with financial markets differently, leading to varying impacts on bank deposits. For instance, in financially developed economies, financial markets typically complement the banking sector by facilitating deposit growth. Conversely, in financially developing economies, financial markets and banks often compete for deposits, thereby constraining bank deposits growth. This dynamic, however, is shaped by country-specific factors such as market concentration and the level of deposit insurance. Moreover, we find that financial market development increases per capita savings, which in turn strengthens bank deposit growth. These findings remain consistent across a range of model specifications and robustness checks.

Loss Given Default (LGD) modelling for residential mortgages presents persistent challenges in bank risk management. This study proposes a three-stage decomposition framework for LGD prediction, aligned with operational collection processes: pre-collateral disposition, collateral disposition, and post-collateral disposition recovery. Using the Freddie Mac Single-Family Loan-Level dataset (1999–2020), we demonstrate that this approach significantly outperforms traditional single-component models, including OLS regression, two-step selection models, and random forest techniques in out-of-time predictions. The decomposition reveals previously obscured stage-specific drivers and their varying influences across recovery stages. Our findings contribute to both theoretical understanding of recovery processes and practical applications in risk management, capital allocation, and loss provisioning.

This paper examines how monitoring market structure by regulators and competition authorities can support the creation of a stable banking system. Using an unbalanced panel of 16,013 banks across 76 developed and developing countries between 2000 and 2019, our estimates show that competition for deposits increases both deposit growth and retail deposit growth. However, these results vary according to banking system structure. In less concentrated banking markets, interest rates play a major role in attracting deposits compared to highly concentrated markets. Our results hold in response to several robustness tests.

In this paper, we propose a straightforward way to estimate the Fisher ideal total factor productivity (TFP) index (FI) in cases where price information is unavailable, using ‘shadow prices’ derived from data envelopment analysis (DEA). A Monte Carlo experiment shows that the shadow price Fisher ideal TFP index (SPFI) can effectively estimate the ‘true’ FI with relatively small (and stable) errors. The empirical application to the US agriculture sector (1948–2017) further suggests that the SPFI is a (superior) alternative to the traditional Malmquist DEA, especially in dealing with unbalanced panel or time series data when price data are unknown.

We explore success drivers of reward-based crowdfunding for poverty alleviation in China. The results from our econometric modeling using data from 4375 reward-based crowdfunding campaigns suggest that poverty alleviation campaigns, as compared to ordinary ones, benefit from higher funded amounts, larger backer numbers, and greater success rates. The results also suggest that poverty alleviation campaigns perform better when the products sold originate from poorer (as compared to wealthier) regions and when price premiums are lower (as compared to higher). We corroborate important findings from the field study with an experimental study, showing that the consumer’s feeling of warm glow accounts for the positive effects of poverty alleviation campaigns (as compared to ordinary) campaigns. We expand the applications of warm-glow theory into the context of reward-based crowdfunding campaigns for poverty alleviation and offer new insights into success drivers of such campaigns.

This study uses the multi-criteria decision-analysis (MCDA) approach to construct a composite performance index (CPI) directly from the CAMELS financial ratios. The CPI has several promising characteristics, such as (i) being an absolute measure of performance that allows for adding or removing data without affecting the existing scores; (ii) employing CAMELS ratios directly in its calculation without the need for normalization or imputation of positive values; (iii) employing the dynamic weighting system of data envelopment analysis (DEA); (iv) providing more robust insights on the Vietnamese banking system under the Shannon entropy approach; and (v) can be an alternative measure of bank stability, compared to the CAMELS ratings and z-scores. Based on a rich dataset of 45 Vietnamese banks spanning from 2002 to 2020, our findings suggest that the proposed CPI could offer an overall view consistent with other approaches for measuring banking sector performance and stability and identifying specific strengths and weaknesses of banks.

This paper investigates the effects of healthcare expenditure on bank deposits in a cross- country analysis. We use government healthcare expenditure, and government and compulsory contributions to the healthcare system as a proxy for healthcare development. The results show a positive relationship between healthcare expenditure and bank deposits. This result is stronger in high income countries and those with a high level of healthcare infrastructure. The results are robust with various specifications tests, including in the COVID-19 pandemic period.

Banks' off-balance sheet activities are among the many factors blamed for the risk-taking that led to the 2007-2008 financial crisis. We test whether and how off-balance sheet exposures influ-enced risk-taking at publicly traded commercial banks in the G-7 countries between 1998 and 2018. Contrary to expectations, we find strong evidence that larger off-balance sheet exposures are associated with lower aggregate and idiosyncratic risk but higher tail risk. Further, we observe a non-linear relationship between off-balance sheet activities and risk. Our results suggest that placing absolute limits on OBS activities might increase bank risk-taking.

This paper investigates the impact of the global financial crisis (GFC) on banking market structure and efficiency in both countries, and the relationship of bank size and market competition with cost and profit efficiencies. Efficiencies of 11 Australian and New Zealand large commercial banks are estimated with a one-stage stochastic frontier approach (SFA) for the period 2003–2017. The Herfindahl- Hirschman Index (HHI) and Lerner index are used as proxies for market competition along with eight banking environment variables. Cost and profit efficiencies significantly declined during 2008 and 2009, but the impact of the GFC persisted longer in New Zealand than in Australia. The level of risk and competition has reduced, and bank size increased in the post-GFC period. Bank size is found to be positively associated with bank efficiency. Market competition negatively influenced cost and profit efficiencies during the study period, especially after the GFC.

While the z-score has been widely used to evaluate bank risk, it is criticized as a backward-looking measure. We propose a forward-looking method to construct the z-score by incorporating analyst forecasts. Empirical results show that the forward-looking z-score can predict the movement of the standard z-score one quarter ahead of time, and its predictive ability on banks' downward risk is better than the standard z-score. Moreover, we find that the predictive ability of the forward-looking z-score improves after the Dodd-Frank Act of 2010, especially for large banks, showing the consequences of strengthened regulation and transparency. The forward-looking z-score is also significantly associated with the probability of default and market-based risk measures and can provide predictive signals for banks' future profitability. Overall, our findings suggest that the forward-looking z-score mitigates the shortcomings of the standard z-score and provides a reliable early warning signal for banks' future risk and performance.

Purpose The study aims to analyze the changes in banking market structure and their impact on the bank efficiency. Design/methodology/approach This study uses a one-stage stochastic frontier analysis (SFA) to compare the impact of the market structure and the GFC on the economic efficiency of the major banks in both countries. Findings A significant negative impact of the GFC is observed on bank efficiency. Overall, Canadian banks posted better efficiency scores than their American counterparts. Additionally, cost-efficient banks are found to be more resilient to crises and more profit-efficient in the post-GFC period. The authors found that market power had a positive impact on the cost and profit efficiency of banks. Higher levels of equity, market power and concentration helped banks be more cost-efficient. Research limitations/implications Only large banks are selected for study although it represents the majority stake of both banking sectors. Practical implications Banking regulators should include more measures to assess the banking market structure and performance. Originality/value As per the best knowledge of the authors, it is the first study to assess the change in banking market structure and efficiency of the US and Canadian banking sectors in the post-GFC period.

According to previous studies, China's green credit policy, which was launched in 2012, increases environment-friendly manufacturing enterprises' loan amounts. In this paper, we focus on a redistribution mechanism among environment-friendly manufacturing firms, namely, we determine whether the effects of the green credit policy differ between small and medium-sized environment-friendly manufacturing enterprises (SMEMEs) and large environment-friendly manufacturing enterprises (LEMEs). Using a difference in difference model (DID) and a difference in difference in difference model (DDD), we find that SMEMEs obtain more loans than LEMEs due to the green credit policy. We further analyze three potential foundations of this redistribution mechanism: information asymmetry, financial development, and government environmental investment. The results demonstrate that the redistribution effect occurs in both low and high information asymmetry conditions but only in regions with satisfactory financial development and with lower government environmental investment. Our findings enrich the literature on green credit, sustainable finance, and small finance, and they provide references for enterprises, banks, and governments.

This research assesses the effectiveness of China's green credit policy. We explore whether firms with better external environmental disclosure and internal green innovation receive more bank loans because of green credit, and utilize a panel of 1086 listed Chinese manufacturing enterprises from 2012 to 2017 to test our hypotheses. The results suggest that firms with higher environmental disclosure quality do not obtain more loans, and only green innovation promotes access to corporate loans. We show that the underlying cause of this phenomenon is corporate green-washing, which is prevalent in soft environmental disclosure and hinders enterprises from obtaining more loans. Our findings contribute to the literature on green credit policy, corporate green innovation, environmental disclosure, and green-washing, and provide a reference for companies, banks, and governments to make decisions.

This paper examines the relationship between Economic Policy Uncertainty (EPU) and bank performance in India over the period 2000–2016. We investigate the role of international crude oil price in this relationship that previous studies have ignored. We also investigate whether the effect of oil prices depends on inflationary conditions. Using a sample of Indian commercial banks from 2000 to 2016, we find that an increase in the Indian EPU is associated with increased risk-taking (insolvency, credit and liquidity risks), but improved cost management efficiency and profitability. The EPU and risk-taking relationships are aggravated by higher international oil prices. These effects of oil prices are not conditional on the inflation level in India. The results are robust to alternative Indian EPU calculations and estimation methods. We also investigate the role of international oil prices in the spillover of the US EPU to Indian banks' performance. We find that the US EPU affects Indian banks' credit risk, cost efficiency and profitability in the same sign as the Indian EPU, but the two latter effects are amplified by oil price rises, and the amplification effects are conditional on Indian inflation. The findings have important implications for policies for financial reform and financial stability in India.

We propose a new systemic risk measure based on the z-score, which defines a leave-one-out (LOO) contribution to systemic risk. The LOO z-score measure quantifies the systemic risk contribution of individual banks by the difference between the joint risk-taking of a banking system and the risk-taking of the same system when excluding a bank. The accounting-based LOO z-score measure can be used as a complement to market-based systemic risk measures, and it can also assess systemic risk contribution for unlisted banks. Empirical results show that the LOO z-score measure can identify the four largest New Zealand banks as systemically important.

This paper provides a new method to define a Euclidean common set of weights (ECSW) in data development analysis (DEA) that (1) allows ranking both efficient and inefficient firms, (2) is more realistic in terms of determination of weights, and (3) generates rankings for banks consistent with their credit ratings. We first use DEA to determine the efficient frontier and then estimate a common set of weights that can minimize the Euclidean distance between the firms and that frontier. This process is illustrated by a simple numerical example and is extended to a real-life situation using the Eurozone banking sector. Our ECSW approach outperforms other common set of weights approaches in both numerical and real-life examples, and in terms of providing rankings consistent with banks' credit ratings.

This paper examines whether there is a causal relationship between bank loans and deposits in the Vietnamese banking system and the efficiency of the use of loans and deposits by the Vietnamese banks. In a country such as Vietnam, where inter-bank money markets are relatively underdeveloped, one would expect a reasonably strong relationship between deposits and loans. A pooled cross-sectional sample of financial ratios is collected from annual reports of 44 Vietnamese banks covering the period 2008–2015. The explanatory power of instrumental variables in relation to the endogenous variables is tested. A deterministic frontier model based on corrected ordinary least squares, estimated by three-stage least squares on a simultaneous equations model, is employed to derive the frontiers for the sampled banks as well as to estimate the causality between bank loans and deposits. Our findings suggest that, in an underdeveloped banking system such as Vietnam, bank deposits have a positive and significant impact on bank loans, but the reverse relationship is not significant. It is further suggested that in deposit-taking and loan-creating activities, Vietnamese banks performed moderately well over the period examined; however, in the near future, they should start to focus more on deposit-taking activities.

This paper investigates whether banks were able to create value for their shareholders after the Global Financial Crisis (GFC) and whether operational efficiency is related to shareholder value creation in informationally efficient stock markets. The impact of GFC on bank efficiency and shareholder value creation is assessed for 29 large banks in the USA, UK, Canada, New Zealand, and Australia during the period 2003-15. These countries are studied as group because of the asymmetrical impact of the GFC on what were otherwise relatively integrated markets. The significant impact of GFC is observed on bank efficiency and shareholder value during 2008-09. A significant relationship between profit efficiency and shareholder value creation is observed. Consistent with prior studies, we did not find a significant relationship between shareholder value and cost efficiency. Important determinants of shareholder value and bank efficiency are also identified, which suggest important policy implications.