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This study aims to assess the effectiveness of the banking market discipline in relation to the development of Financial Technology (FinTech) startups.

Using panel data collected from 144 banks in Indonesia from 2004 to 2018, this study’s regression models were estimated using fixed effects with robust standard errors.

This study finds that FinTech startups disturb bank deposits. Meanwhile, market discipline exists in Indonesian banks, as indicated by depositors’ behavior with higher credit and liquidity risks. However, market discipline does not exist for bank insolvency risk, which is indicated by a significant and positive relationship with the dependent variable. Therefore, the higher the number of FinTech startups, the more effective the market discipline. Empirical findings also revealed that the joint impact between FinTech startups and bank risk is also important in explaining the difference in the effectiveness of banking market discipline.

This study has policy implications for banks in mitigating risk associated with market discipline and instability of financial intermediation.

This study offers a significant contribution to the empirical literature because it specifically explores the effectiveness of the banking market discipline by focusing on the joint impact of FinTech startups and bank risk on deposits. Furthermore, this study contributes to providing empirical evidence that links between FinTech startups and bank risk affect depositor behavior at government-owned, private, large and small, as well as nonmobile and mobile adoption banks.

The academic literature has examined why bank runs happen based on the work of 2022 Nobel Prize-winning economists Diamond and Dybvig. They have found the source of banking/financial crisis in terms of mismatch between liabilities (deposits being short term and savers wanting to short-term access to their money) and assets (long term and illiquid). The Lakshmi Vilas Bank (LVB) crisis intensified when it came under Prompt Corrective Action (PCA) of the Reserve Bank of India (RBI). This situation provides the opportunity to study whether the elements embodied in the theoretical models like Diamond and Dybvig hold true for LVB crisis. This study aims to examine the reasons for the demise of LVB in India using DuPont financial model, peer group analysis and time series structural break in crucial financial parameters.

The study examines the reason for insolvency of LVB using financial ratios, financial models (DuPont), financial distress model (Z-score) and asset-liability management. The study also adopts univariate structural break models using quarterly financial data covering the key financial measures used in the RBI’s PCA framework.

LVB crisis is like Diamond–Dybvig model, in the sense, savers requiring short-term access to their money (liquidity for their deposits) on the information of high non-performing assets, which further deteriorates the illiquid nature of loan portfolio (assets) of banks. The study finds its profit margin (net interest margin and non-interest margin) and managerial efficiency had started deteriorating since 2018. The study finds that LVB’s main weakness lies in its limited credit appraisal ability, its monitoring and weak internal controls. Lending to sensitive sectors (like real estate, capital markets and commodities) and exposure to large business groups also contributed to its weakness. The study also finds huge, elevated asset-liability mismatch, especially in the short-term maturity buckets. Using univariate econometric time series model, the study also confirms financial weakness being evident much earlier than the time when resolution was undertaken by the RBI through PCA.

The study has implications for analysing and monitoring financial distress of banks. The study also has implications for devising banking regulation and supervision.

The study brings in a perspective of the banking regulations using the application of PCA framework on a listed private sector bank. The authors combine an accounting ratio model and combine risk measures that could identify the incipient risks in a bank. The authors believe this will help in refinement of banking regulations and better monitoring mechanisms.

The purpose of this study is to analyze the intersection of research on impact investing and its closely related financial vehicles.

The paper explores 196 articles collected from Scopus and Web of Science using bibliometric and content analysis methodologies.

Despite a growing academic interest in impact investing, scholars generally investigate impact investing as a social phenomenon, using the specific financial mechanism of social impact bonds. This perspective potentially deflates the complex nature of impact investing, which actually combines both social and financial targets and uses a plurality of financial vehicles to reach its goals.

The emerging themes identified will provide both academics and practitioners additional tools to further the debate on impact investing and the understanding of its potential and limits according to the different financial forms it takes. This review should pave the way for a discussion about the boundaries of the social impact sector itself.

Despite the strong international commitment toward impact investing, tensions still exist. A comprehensive overview on the relevant aspects not yet thoroughly investigated will foster the growth of impact investments.

To the best of the authors’ knowledge, this is the first holistic overview of impact investing, that jointly examines both literature on impact investing and literature on the correlated financial products used in the industry. The result is a comprehensive report of what is known about impact investing in its different financial forms, opening up new pathways for future studies.

This study empirically demonstrates a contradiction between pillar 3 of Basel norms III and the designation of Systemically Important Banks (SIBs), also known as Too Big to Fail (TBTF). The objective of this study is threefold, which has been approached in a phased manner. The first is to determine the systemic importance of the banks under study; second, to examine if market discipline exists at different levels of systemic importance of banks and lastly, to examine if the strength of market discipline varies at different levels of systemic importance.

This study is based on all the public and private sector banks operating in the Indian banking sector. The Gaussian Mixture Model algorithm has been utilized to classify banks into distinct levels of systemic importance. Thereafter, market discipline has been observed by analyzing depositors' sentiments toward banks' risk (CAMEL indicators). The analysis has been performed by employing the system Generalized Method of Moments (GMM) to estimate models with different dependent variables.

The findings affirm the existence of market discipline across all levels of systemic importance. However, the strength of market discipline varies with the systemic importance of the banks, with weak market discipline being a negative externality of the SIBs designation.

By employing the Gaussian Mixture Model algorithm to develop a framework for categorizing banks on the basis of their systemic importance, this study is the first to go beyond the conventional method as outlined by the Reserve Bank of India (RBI).

This study aims to attempt to investigate the factors that influence non-Muslims’ withdrawal behavioural intention from Islamic banking in Malaysia.

The push–pull–mooring approach is used to examine the determinants of withdrawal intention by non-Muslims from Islamic banking in Malaysia. Variables used in this study include religiosity (RELG) under push, deposit guarantee (DG), rate of return (RR), Islamic banks’ specific factors (IBSF) under pull and mooring factors as social influence (SI) and voluntary switching (VS) as the determinants of withdrawal intention from Islamic banking. In this study, the SPSS Statistics Version 22 and smart partial least squares were used to measure the withdrawal level.

Three variables, namely, SI, RR and IBSF are found to significantly influence the withdrawal behaviour intention. Meanwhile, three other variables, namely, RELG, DG and VS are not significant.

This study provides valuable insights pertaining to non-Muslim consumer withdrawal behaviour from Islamic banks. Bank managers, marketers and regulators could use these findings in developing effective strategies to increase and retain customer withdrawal.

This study expands the understanding of key determinants of the non-Muslim withdrawal behaviour from Islamic banks in Malaysia. To the best of the authors’ knowledge, this research is among the pioneer empirical study to assess the issue.

This paper models the benefits of Islamic banking on the efficiency of the banking sector and on societal happiness. This paper aims to examine how the adoption of Islamic banking to various degrees affects economics outcomes.

This study uses machine-learning tools to build a happiness function and integrate it in an agent-based model to test for the direct and indirect welfare effects of implementing Islamic banking principles.

This study shows that even though Islamic banking systems tend to reduce economic activity, financial stability and societal happiness is improved. Additionally, a banking sector using Islamic principles across all its members is better equipped to handle banking crises because contagion to both economic activity and societal welfare is greatly reduced. At the same time, adoption of the profit-and-loss sharing (PLS) paradigm by banks may also slow down economic growth.

The findings extend existing literature on the advantages of Islamic banking, by quantifying the welfare benefits of the PLS paradigm on happiness and financial stability.

To the best of the authors’ knowledge, this paper is the first to combine agent-based modelling with machine learning tools to examine the benefits of the Islamic banking model on financial stability, social welfare and unemployment.

The use of digital technologies in the financial service industry has brought new complexities to the corporate governance in banks. Relying on the agency perspective of the shareholder, debtholder and societal governance in banks, this research examines the impact of financial technology innovation (FinTech) on banks' performance by enlightening the monitoring role of female independent directors.

Relying on a sample of Italian banks observed during the period 2016–2020, the authors hand-collected data on the use of FinTech by considering (1) the in-house provisions of FinTech solutions, (2) the collaboration with external FinTech firms and (3) a combination of both measures. The authors run a panel data regression analysis with fixed effects, measuring bank performance through bank competitiveness and bank riskiness.

The authors find that FinTech increases bank competitiveness in gathering money from depositors and that independent women on board mitigate the negative relationship between FinTech and the riskiness of banks' assets, ameliorating the conflicting interests among shareholders, debtholder and societal governance.

This study emphasizes the complexities of bank governance when dealing with FinTech in the wider perspective of equity governance, debt governance and the societal governance spotlighting the importance of appointing female directors in independent positions to enhance the bright sides of financial innovation. The authors enrich the literature on FinTech with a finer understanding of the drivers and implications of in-house provisions of FinTech solutions versus the collaboration with external FinTech firms.

The purpose of this study is to develop a new framework to measure waqif preference of waqf-based qardhul hassan financing in Malaysia.

Using a maqāṣid approach, this study’s data were drawn from 286 valid usable questionnaires to examine the effects of consumer, family, ummah and humanity factors on the preference.

The study found that the said factors sourced from Attia’s maqāṣid al-Shariah were instrumental in determining waqif preference to donate in waqf-based qardhul hassan financing.

Like others, this study’s findings are limited in terms of their generalisations and applications. The theory, context and variables used should be expanded in future works.

The results obtained are useful as a yardstick to enable the offered waqf-based qardhul hassan financing for improved mutual well-being among different classes of the wealth of societal groups in Malaysia. Furthermore, the results provide valuable insights into the direction for practitioners mainly managers involved in introducing waqf-based qardhul hassan financing as a new Islamic social financial instrument for poor and needy folks, at best.

This study is novel in terms of the proposed conceptual framework, where the waqif perspective comes into play.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.