Sustainable Finance Meets FinTech: Amplifying Green Credit’s Benefits for Banks
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsOverall assessment:
The paper contributes to the literature that studies the effect of green credit on bank performance, focusing on the question whether and how FinTech positively influences this relationship. The authors undertake a systematic empirical analysis of their research question. The paper is well-structured, carefully drafted, comprehensive and easy to follow for the reader. A few smaller points still deserve attention:
1) The exact definition of green credit. The authors could provide more information on when a bank loan is classified as green in China as compared to other countries. The motivation for the paper is to throw light on the opposite results in the academic literature: some studies find a positive impact of green credit on bank performance and other studies find a negative effect (line 61-63). Given their focus on Chinese banks, the authors draw on the green credit guidelines of the Chinese government (line 34). However, not all of the earlier studies referred to deal with the case of China. The governments of other countries may have developed different green credit guidelines than those of China, making a comparison with earlier studies that cover other countries less useful.
2) The missing role of non-green credit in the model. The basic regression model uses the scale of green credit as explanatory variable (line 396). The ratio of green credit to total loans is applied in the robustness test (line 767). However, the model never includes non-green bank credit. This could be seen as leading to a specification with a missing variable, since bank performance is of course affected by both green credit and non-green credit. The authors could test whether their empirical results for green credit still hold when adding non-green credit as an explanatory variable.
3) The broad definition of FinTech. FinTech is described in a rather broad way, encompassing a range of new technology elements (line 65-67). The FinTech variable is measured with three indicators (line 409). This makes it difficult to pin down which aspect of FinTech is responsible for amplifying the positive relationship between green credit and bank performance (see also line 550). Moreover, FinTech should be expected to benefit all bank activities, including non-green credit. How can one then ‘directly analyze whether FinTech reduces the marginal cost of green credit’ (line 608 and 614)? Banks will invest in FinTech to enhance their general performance. They will expect to benefit from the three assumed channels (cost reduction, reputation enhancement, risk mitigation) for their green credit, non-green credit, and any other business. They are also likely to distribute the costs of FinTech over all their business activities. The policy recommendation that banks should actively apply FinTech to their green credit business (line 20, line 905) could thus be seen as self-evident.
4) A unsupported policy recommendation. The suggestion that regulators should refine the standards for green credit business (line 890) comes out of the blue. Although this specific recommendation makes sense, it does not directly follow from the empirical analysis in this study.
5) The bias in the references. Most of the articles referred to seem to be from Chinese authors and/or related to Chinese financial institutions. Given the fact that the relationship between FinTech, green credit and bank performance is an international issue, it would make sense to draw on a broader range of academic studies, at least for the literature review.
Editorial comments:
Line 38: '… increase of 38.5%' since 2007? How much was the rise of the ratio of green credit to total loans?
Line 464: Another macroeconomic control variable at the level of provinces could be the interest rate on green and non-green bank loans.
Line 502: A separate Figure 2 could show the developments in the ratio of green credit to total loans for different types of banks.
Line 536: What is the basis for concluding that the overall level of risk in the Chinese banking industry is ‘low’?
Line 634: One could clarify that this sentence refers to bank performance in terms of non-interest income.
Line 676: Table 9 could mention the number of observations for each of the different bank types.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe article proposes an interesting topic, focusing on the intersection between green credit and financial technology (FinTech) and their influence on banks' performance. This topic is relevant not only for researchers, but also for financial practitioners, especially in the context of the rapid growth of the green credit market and the evolution of FinTech.
The structure of the article is well organized, following a logical flow from the introduction of basic concepts to empirical analysis and conclusions. Each section is clearly delineated, and the transitions between sections are fluid. However, some sections could benefit from more concise wording to avoid repetition and ensure easier reading. For example, the introductory part could be synthesized to give the reader a quicker overview of the issues discussed.
A more detailed discussion of methodological limitations and possible effects of variables that were not included in the model would be useful. Although the research questions are stated, more precise reformulations that emphasize the specific relationships between the variables studied may be useful. This will help the reader better understand the direction of the research from the first sections of the article. The research design could be explained in more detail, including the motivation for the choice of the study period and the justification for the selection of the banks analyzed. A more detailed description of the process by which independent and dependent variables were established would contribute to a better understanding of the study structure. To increase consistency, a section making a direct link between each hypothesis formulated and the specific method used to test it would be useful.
Given that the study focuses on Chinese banks, a more in-depth discussion of how generalizable these results are globally would be useful. The specific context of the Chinese market could limit the applicability of the conclusions in other regions.
Although the literature review is comprehensive, authors could benefit from a more critical approach, discussing more explicitly where their contributions lie compared to previous work and how they go beyond the limits of existing studies.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsReviewer's Comment
The manuscript entitled "Sustainable Finance Meets FinTech: Amplifying Green Credit’s Benefits for Banks", This article investigates whether FinTech companies influences the effect of green credit on bank performance. I believe that, given these issues, the current work is not suitable for publication at this stage. However, if it is necessary to accept publication, the following issues need to be addressed before considering publication:
1. Although the paper mentions the different perspectives of the existing literature on the impact of green credit, the in-depth analysis and critical discussion of this literature seems to be insufficient, and the literature review section could be further extended to compare and analyze the different perspectives in more depth.
2. The hypotheses formulated in the paper, although closely related to the research topic, could be further strengthened in terms of the logic of the hypotheses' development, e.g. a more detailed explanation of why FinTech enhances the positive impact of green credit could be provided.
3. The findings of the empirical analysis are explained in the results section of the thesis, but the specific implications of these findings for different types of banks (e.g., state-owned banks, joint-stock banks, etc.) could be further explored, as well as the possible long-term implications.
4. Although graphs and charts are mentioned in the text (e.g., Figures 1 and 2), they are not included in the reviewed text. Charts and visualizations are important tools to help readers understand complex data, and it should be ensured that clear charts and adequate explanations are included in the final manuscript.
5. The year of data analysis in the article is 2022. Will there be any other changes to these data in the past two years? Does the authors also need to add the latest literature data support.
6. The article selected data from 127 Chinese commercial banks, with a large sample size but mainly concentrated in China, which may limit the generalizability of the research conclusions. It is suggested that future research consider incorporating data from more countries for comparative analysis.
7 The introduction should clearly and concisely explain the background of the research, the gaps in existing literature, and the contribution and importance of this study. The author's language description in this section is too verbose, please simplify the sentences. And in the later paragraphs of the introduction, the author seems to repeat the conclusion. When writing the article, please do not confuse the introduction and conclusion.
8. The image lacks clarity and aesthetics, and a three line table should be used as much as possible to ensure the beauty of the layout. Please revise them.
9. For the specific measurement indicators that affect the three mechanisms of FinTech influences, further detailed explanations can be provided to help readers better understand the basis for model construction.
Author Response
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Author Response File: Author Response.pdf
Reviewer 4 Report
Comments and Suggestions for AuthorsThe manuscript is clear, relevant to the field and presented in a well-structured manner. The research is current, supported by data and an up-to-date bibliography. References cited are mostly recent publications (within the last 5 years) and relevant (with some exceptions). The manuscript sounds scientific; the methods used meet the possibilities and limitations of the data collected for the study. The applied design and steps for scientific processing of the data are suitable for proving the hypothesis. All inferred definitions of fault used in the model are clear, correct and meet the best regulatory and scientific standards. The results of the manuscript are based on the content given in the methods section. Descriptive statistics support the achievement of research objectives. The figures and tables clearly contribute to the scientific purpose of the article. Statistical analysis and data obtained are also relevant from a specific database. The heterogeneity analysis section is at the highest scientific level. All conclusions are consistent with the evidence and arguments presented. The signed disclosure of potential conflict of interest is clear and without any negative impact on publication rules.
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors have adressed all the issues, and the paper can be published in present form.
