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This study investigates the relationship between credit booms and bank risk in Association of Southeast Asian Nations (ASEAN) countries, with credit information sharing acting as a moderator.

The authors use a two-step System Generalized Method of Moments (SGMM) estimator on a sample of 79 listed banks in 5 developing ASEAN countries: Indonesia, Philippines, Malaysia, Thailand and Vietnam in the period 2006–2019. In addition, the authors perform robustness tests with different proxies for credit booms and bank risk. The data are collected on an annual basis.

Bank risk is positively related to credit booms and is negatively associated with credit information sharing. Further, credit information sharing reduces the detrimental effect of credit booms on bank stability. The authors find that both public credit registries and private credit bureaus are effective in enhancing bank stability in ASEAN countries. These results are robust to regression models with alternative proxies for credit booms and bank risk.

Banks in ASEAN countries tend to have strong lending growth to support the economy, but this could be detrimental to stability of the sector. Credit information sharing schemes should be encouraged because these schemes might enable growth of credit without compromising bank stability. Therefore, policymakers could promote private credit bureaus (PCB) and public credit registries (PCR) to realize their benefits. The authors' research focuses on developing ASEAN countries, but future research could provide more evidence by expanding this study to other emerging economies. In-depth interviews and surveys with bankers and regulatory bodies about these concerns could provide additional insights in the future.

The study is the first to examine the role of PCB and PCR in alleviating the negative impact of credit booms on bank risk. Furthermore, the authors use both accounting-based and market-based risk measures to provide a fuller view of the impact. Finally, there is little evidence on the link between credit booms, credit information sharing and bank risk in ASEAN, so the authors aim to fill this gap.

The purpose of this paper is to analyze the vertical disintegration of the bank loan origination value chain. This paper conducts a study on the credit information market from the perspective of the bank’s decision to vertically disintegrate the loan origination value chain. The main aim is to identify the relevant drivers of the decision to vertically disintegrate the credit assessment phase in the lending business.

Transaction cost economics and information asymmetry are the typical perspectives of analysis of the vertical scope of business value chains.

This paper argues that in order to capture the drivers underlying the dynamic evolution of the vertical scope of bank loan origination business models, the above perspectives must be combined and integrated further with a resource-based view and the modularity perspective. Combining managerial and financial perspectives, this paper offers an examination of the drivers of vertical disintegration in the lending value chain and, specifically, in the credit assessment phase.

Although the existence of substantial research on value chain vertical integration/disintegration in the literature, none has directly focussed on the credit assessment value chain. It leaves a gap that the paper aims to overcome. The value chain disintegration has deep managerial and financial implications at firm and industry levels, and the comprehension of the rational underlying it is critical to maintaining competitive business model configurations in the bank lending industry.

Social information is crucial to credit ratings and can improve the accuracy of the traditional credit assessment model. Drawing on the resource-based view (RBV) and social capital theory (SCT), this research explores the relationships between corporate social activities, network centrality and corporate credit behavior.

The authors used social network analysis (SNA) and regression analysis to analyze the data collected from 14,544 enterprises on the Alibaba platform.

The results indicate that among the four types of social activities, the number of corporate questions and posts shows a positive relationship with credit behavior; while the number of corporate comments has negative relationship with credit behavior. Further, degree and betweenness centralities mediate the relationship between the number of corporate questions, posts and comments with credit behavior.

This study contributes to the literature on non-financial factors (soft information) by exploring the social behavioral factors related to corporate credit. In addition, this study offers a new theoretical lens and reasonable explanations for investigating the relationship between corporate social activities, network centrality and credit behavior from the perspective of the resource-based view, while most studies are predictive and methodological. Moreover, this study provides new insights for platforms to evaluate enterprise credit and for managers to improve credit behavior.

This paper examines the activities carried out in the UK by credit refer agencies, current business practices, and the legal standing of credit reporting.

Legal analysis that aims to demonstrate that the current legal framework is inadequate.

It suggests areas and issues for further legal debate and policy consideration. Ultimately, this study puts forward the case for specific legislative intervention to strike a balance between privacy rights, discrimination concerns, and the needs of the credit industry.

Little or no research has been conducted on the topic by lawyers.

This study aims to investigate the determinants of a shift in lending towards household sectors during the growth of fintech credit using a sample of 41 countries between 2015 and 2018.

This study uses a fixed-effects model by adding indicators for geographic areas and year dummy variables to achieve this objective.

The findings show that the household credit to firm credit ratio is positively associated with credit information sharing and financial literacy, emphasising the importance of credit information sharing mechanism and financial literacy to household credit growth. More interestingly, the findings show that fintech credit development plays a more critical role in the evolution of firm credit than household credit. Nonetheless, fintech credit development may complement the growth of conventional lending. The results still hold when using several robustness checks.

This is the first attempt to examine the roles of credit information sharing, financial literacy and fintech credit development in a shift in lending activities towards households.

The purpose of this paper is to investigate the mechanism how the platform obtains and uses undisclosed information to determine individual borrowers’ credit score and to examine the effectiveness of credit scoring in predicting default. The motivation stems from the fact that there is little evidence about the role of P2P platform, which has been positioned as a kind of information intermediary.

Using a sample of 5,176 unsecured P2P loans having expired before December 31, 2015 on Renrendai.com and an approach of two-stage regression, the paper first estimates the undisclosed information embedded in credit score by regressing credit score on four types of public information about a borrower’s creditworthiness. Then, the authors use a Logit regression to examine the role of the excess information in predicting the default probability.

The certification information provided by the platform is the most important determinant for a borrower’s credit score and the undisclosed information embedded in credit score can predict the loan performance better than the public information of posted listings. Moreover, the predictive ability of the undisclosed information is better for high-risk borrowers than for low-risk ones.

Providing a credit score for each individual is a way for P2P platforms to play an information intermediary role. More evidence about whether or how a platform plays its role are worthy to be exploited by investigating a platform’s operating policies in detail and doing cross-platform comparative studies.

The results about the effect of various types of information on loan performance can provide an insightful guidance for P2P platforms to optimize their mechanism on information disclosure and credit scoring.

The existing literature mainly focuses on the effects of information voluntarily disclosed by borrowers and the behaviors of investors on P2P lending outcomes. The paper highlights the information intermediary role played by the platform and presents empirical evidence that credit scoring for individual borrowers is a way for P2P platforms to promote the direct lending for individual.

The study aims to investigate the relationship between a shift in lending activities toward households, credit information sharing and bank stability.

A system generalized method of moments (GMMs) as proposed by Arellano and Bover (1995) is employed to examine the relationship using a sample of 80 countries from 2005 to 2014.

The findings demonstrate that, in general, a shift in lending strategy toward the household sector may increase bank instability while credit information sharing has a positive impact on bank stability. When credit information sharing is promoted widely, this shift may become beneficial for the banking system. The results are robust when using different measures of credit information sharing, including the depth of index and the coverage of credit information sharing mechanisms.

The results demonstrate that a shift in lending activities toward households should be considered a key variable in conducting macro-prudential policies. When a shift toward household credit relative to firm credit is evolved, the findings suggest that the authorities around the world should enact laws that magnify the scope and coverage of credit information shared and thus promoting the effectiveness of information sharing.

The current study is the first attempt that examines the impacts of a shift in lending activities toward households and credit information sharing on bank stability.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

Consumer culture is promoting immediate gratification, and the rise of digital financial services is increasing the risk of indebtedness while debt reduces well-being and affects mental health. The authors assess the effects of consumer information provision, debt literacy, chronic debt and attitudes toward debt on the intent to purchase on credit.

An online survey including an experiment with a credit offer vignette was conducted in a representative sample of Estonia (n = 1204). Treatment conditions depicted either the total cost and duration of the credit agreement or the annual percentage rate.

Receiving modified information resulted in a 26 to 30 percentage points decrease in propensity to purchase on credit. Purchasing on credit was associated with attitudes towards credit and chronic debt, but not with debt literacy.

The findings reveal large effects of information provision and highlight the limited effects of debt literacy on credit decisions. Limitations may emerge from differences in financial regulation across countries.

The authors' results highlight the importance of applying behavioural insights in consumer credit information provision, both in the financial sector and policy. Testing the messages allows having evidence-based solutions that promote responsible purchasing on credit.

The findings call for changes in credit information provision requirements. Their effect is significantly larger compared to the literature, emphasizing the role of credit information provision in less regulated online markets.

This study aims to explore and analyse the credit risk assessment procedure conducted by the Indonesian Islamic banks to address the issue of asymmetric information among their micro-, small- and medium-sized enterprise (MSME) clients. This study also investigates the gaps in credit risk assessment procedures by comparing Islamic banks’ practices and presenting several recommendations to reinforce the credit risk evaluation procedures and eventually promote more inclusion of the MSME segment into the Islamic financial services.

This paper adopts a qualitative method by implementing a multi-case study research strategy. The data were gathered primarily through an interview approach by incorporating purposive uncontrolled quota sampling.

The result of this study implies that the Islamic banks in Indonesia have their own unique approaches and strategies in assessing the credit risk and have several similarities in performing their evaluation procedures for the MSME. Despite seemingly adequate approaches and measures taken by the Islamic banks to eliminate the asymmetric information problem, the study identifies several gaps that occur within the Islamic banks’ methods of credit risk assessment.

Since this study focuses on Indonesia and emphasises the two segments of Islamic banks, which consist of Islamic commercial and rural banks, in performing the MSME credit risk assessment; therefore, the findings of this study were limited around the observed Islamic banks within the MSME segment purview.

By referring to the recommendations as proposed by this paper, four implications could be expected from adopting these respective recommendations, among others: more effective evaluation procedures for the MSME, provision of a clear path and more efficient approach to assess the MSME units, lower financing cost and increase the confidence of Islamic banking industry in disbursing more financing to the MSME sector. This mechanism will potentially improve Islamic financial inclusion for the MSME due to the greater access to financial services; hence, the sector could contribute even more to Indonesia’s growing economy.

By incorporating a multi-case study among Indonesian Islamic banks pertaining to their methods in evaluating MSME customers, this study identifies several gaps affecting the effectiveness of MSME credit risk assessment. Furthermore, this study also presents a proposed framework to address these gaps accordingly by suggesting the salient strategies to minimise the issues of information asymmetry and enhance the MSME credit risk assessment procedure.