Criteria Selection of Housing Loan Based on Dominance-Based Rough Set Theory: An Indian Case
Round 1
Reviewer 1 Report
Review Report for Manuscript # jrfm-2450034
Criteria Selection of Housing Loan Based on Dominance-based Rough Set Theory: An Indian Case
Summary:
This paper provides an approach based on the Dominance-based Rough Set Theory to help Indian bank managers in the criteria selection of housing loan. I can appreciate all the work the authors have put in. However, I have several major concerns about the current paper’s contribution, and execution. Below, I outline my concerns.
1. In line 91 stated, “This study aims to propose an innovative extraction approach for preference ordered in banking. I am a little hesitant about the innovation of the article because:
· From the methodological point of view it is not innovative because Chen et al. (2022) applied DRSA for Loan Defaults of Used Cars, Sawicki and J. Zak (2014), Augeri, et al. (2015) applied DRSA in their case studies, and Marcin Szeląg, Roman Słowiński (2022) applied Dominance-based Rough Set Approach Bank Customer Satisfaction Analysis.
· From the subject’s point of view, Chen et al. (2022) applied DRSA for Loan Defaults.
This article can justify its innovation to some extent only in terms of the study location (India) and the specific type of loan (Housing loan). It is recommended to explain more on the innovation and distinction of your study in a separate paragraph at the end of introduction section.
2. In line 41 stated "Therefore, the goal of this study is to forecast how much money customers will be able to borrow from banks." According to the title of the article “Criteria Selection of Housing Loan Based on Dominance-based Rough Set Theory: An Indian Case” , this article uses a dominance-based rough set approach to provide a pattern that helps managers in making decisions in Criteria Selection of Housing Loan. In addition, as stated in line 91 “This study aims to propose an innovative extraction approach for preference ordered in banking.
Thus, it does not determine how much money a customer can borrow. Otherwise, show part of the article that shows such information and provide the amounts of your case.
3. In line 58 stated “Thus the technique is able to deal with inadequate knowledge like fuzzy theory, statistical techniques, discriminate analysis and probability theory [4, 5, 18]”. In addition, in line 273 it is highlighted that “A good strategy for multi-attribute decision-making problems is D-RSA”.
Since D-RSA is able to deal with inadequate knowledge like fuzzy theory, statistical techniques, discriminate analysis, and probability theory as to the methods, it is a good idea for the author to explain why DRSA is selected for this paper. It seems necessary that after line 59, in a comparative way, the authors explain the difference in nature of these techniques and then the distinction and superiority of the DRSA technique for this case.
4. To make it easier for the readers of the article to understand, in the methodology section, it is good if a flowchart describes the research process.
Formatting corrections of the article:
1. In the keywords section, some words are written entirely with capital letters (Dominance-based Rough Set), some are written entirely with small letters (factor analysis) and others are written as a combination of small and capital letters )Mortgage Loan sanction(. It is necessary to be uniform and consistent with the Journal Format guidelines.
2. The distance between the lines in the texts of different parts of the article is not the same and is different. For example, the spacing between the lines of sections 3.5, 3.6, and 4.1 is different from the spacing between the lines of section 3.1.
3. In line 418 section 5 (Results and discussion), it was stated that Table 3 depicts the precision of approximation as high as 0.918… . It seems that Table 7 shows such information.
4. The reference in the article is not written uniformly. For example, in reference 1, all the words in the title of the article start with a capital letter, in reference 5, all words in the title of the article start with a small letter, while in reference 2, some words in the title of the article start with a small letter and the rest with the capital letter.
5. The reference of the articles usually starts with the last name of the first author. While this is not the case in references 3, 11, and some other references.
6. When the number of authors is more than two, some references use “and” while some are marked with “&". Keep Journal Format guidelines.
7. The “year” in references is sometimes mentioned at the end of the article (reference 36) while sometimes after the name of the last author of the article (reference 35, 39, 40…).
8. In line 127 stated “DEA (Date Envelope Analysis) was utilized for evaluating the relative efficiency of consistent decision-making for the data of State Bank of Patiala in India”. The reference of this article is not specified in the text.
9. In case studies, usually, the characteristics of the study (such as the name of the bank, the period of study, the place of operation, the size, and importance of the selected bank for the case study) were presented in the methodology section.
Comments for author File: Comments.pdf
Author Response
Manuscript No.: jrfm-2450034
Manuscript title: Criteria Selection of Housing Loan Based on Dominance-based Rough Set Theory: An Indian Case
Reviewers #1
Comment:
This paper provides an approach based on the Dominance-based Rough Set Theory to help Indian
bank managers in the criteria selection of housing loan. I can appreciate all the work the authors
have put in. However, I have several major concerns about the current paper’s contribution, and
execution. Below, I outline my concerns.
- In line 91 stated, “This study aims to propose an innovative extraction approach for preference
ordered in banking. I am a little hesitant about the innovation of the article because:
- From the methodological point of view it is not innovative because Chen et al. (2022)
applied DRSA for Loan Defaults of Used Cars, Sawicki and J. Zak (2014), Augeri, et al.
(2015) applied DRSA in their case studies, and Marcin Szeląg, Roman Słowiński (2022)
applied Dominance-based Rough Set Approach Bank Customer Satisfaction Analysis.
- From the subject’s point of view, Chen et al. (2022) applied DRSA for Loan Defaults.
This article can justify its innovation to some extent only in terms of the study location (India) and the specific type of loan (Housing loan). It is recommended to explain more on the innovation and distinction of your study in a separate paragraph at the end of introduction section.
Responses:
Thank you for the comment. Here, we would like to mention that we have gone through the existing studies of Chen et al. (2022), Sawicki and J. Zak (2014), Augeri, et al. (2015), and Sawicki and Słowiński (2022). However, in spite of the contributions of all these studies, to the best of our knowledge, the contributions done in our proposed study are yet to be presented in the existing literature. We mention our contribution to our study under consideration as follows.
* Dominace-based rough set approach is applied based on housing loan data which would guide and aid the financial institution for loan sanction. This model focuses on decision-making, which is further controlled by various “if…..then” decision rules. The bank management defines These decision rules, which consider other relevant and important factors regarding housing loans.
* (ii) Factor analysis is used to consider the dataset, and a comparative study is done to analyze the performance of the factors.
Comment:
- In line 41 stated "Therefore, the goal of this study is to forecast how much money customers will be able to borrow from banks." According to the title of the article “Criteria Selection of Housing Loan Based on Dominance-based Rough Set Theory: An Indian Case” , this article uses a dominance-based rough set approach to provide a pattern that helps managers in making decisions in Criteria Selection of Housing Loan. In addition, as stated in line 91 “This study aims to propose an innovative extraction approach for preference ordered in banking. Thus, it does not determine how much money a customer can borrow. Otherwise, show part of the article that shows such information and provide the amounts of your case.
Responses: The amount of money a customer can borrow for a housing loan in India can vary depending on several factors. These factors include the borrower's income, employment status, credit history, age, existing financial obligations, and the lending policies of the financial institution providing the loan. Additionally, lenders may have a maximum loan-to-value (LTV) ratio, which is the percentage of the property's value that can be borrowed. For example, if the maximum LTV ratio is 80% and the property is valued at INR 1 crore, the maximum loan amount would be INR 80 lakhs.
Comment:
- In line 58 stated “Thus the technique is able to deal with inadequate knowledge like fuzzy theory, statistical techniques, discriminate analysis and probability theory [4, 5, 18]”. In addition, in line 273 it is highlighted that “A good strategy for multi-attribute decision-making problems is D-RSA”. Since D-RSA is able to deal with inadequate knowledge like fuzzy theory, statistical techniques, discriminate analysis, and probability theory as to the methods, it is a good idea for the author to explain why DRSA is selected for this paper. It seems necessary that after line 59, in a comparative way, the authors explain the difference in nature of these techniques and then the distinction and superiority of the DRSA technique for this case.
Responses: Thanks for the insightful comment. Here, we would like to mention that our data is preference ordered based data so D-RSA can easily tackle such type of data set efficiently.
Comment :
- To make it easier for the readers of the article to understand, in the methodology section, it is good if a flowchart describes the research process.
Response: Thanks for the comment. In the revised version of the manuscript, we have presented the flowchart in Fig. 1 of our proposed methodology.
Comments:
- Formatting corrections of the article:
- In the keywords section, some words are written entirely with capital letters (Dominance-based Rough Set), some are written entirely with small letters (factor analysis) and others are written as a combination of small and capital letters )Mortgage Loan sanction(. It is necessary to be uniform and consistent with the Journal Format guidelines.
- The distance between the lines in the texts of different parts of the article is not the same and is different. For example, the spacing between the lines of sections 3.5, 3.6, and 4.1 is different from the spacing between the lines of section 3.1.
- In line 418 section 5 (Results and discussion), it was stated that Table 3 depicts the precision of approximation as high as 0.918… . It seems that Table 7 shows such information.
- The reference in the article is not written uniformly. For example, in reference 1, all the words in the title of the article start with a capital letter, in reference 5, all words in the title of the article start with a small letter, while in reference 2, some words in the title of the article start with a small letter and the rest with the capital letter.
- The reference of the articles usually starts with the last name of the first author. While this is not the case in references 3, 11, and some other references.
- When the number of authors is more than two, some references use “and” while some are marked with “&". Keep Journal Format guidelines.
- The “year” in references is sometimes mentioned at the end of the article (reference 36) while sometimes after the name of the last author of the article (reference 35, 39, 40…).
- In line 127 stated “DEA (Date Envelope Analysis) was utilized for evaluating the relative efficiency of consistent decision-making for the data of State Bank of Patiala in India”. The reference of this article is not specified in the text.
- In case studies, usually, the characteristics of the study (such as the name of the bank, the period of study, the place of operation, the size, and importance of the selected bank for the case study) were presented in the methodology section.
Responses: Thanks for the comment. In the revised version of the manuscript, we have eliminated all the issues related to the formatting corrections.
Author Response File: Author Response.pdf
Reviewer 2 Report
In this paper, the authors studied the banking attributes related to home loans using the Dominance-based Rough Set Approach (D-RSA). In order to categorise the customer's attributes, this study suggested using a preference-based "if...then" decision rule. Therefore suggested rule by the authors can aid decision-makers in understanding the risk factors associated with loan factors of a financial organisation.
Author Response
Comments and Suggestions for Authors:
In this paper, the authors studied the banking attributes related to home loans using the Dominance-based Rough Set Approach (D-RSA). In order to categorise the customer’s attributes, this study suggested using a preference-based "if...then" decision rule. Therefore suggested rule by the authors can aid decision-makers in understanding the risk factors associated with loan factors of a financial organisation.
Responses: We are thankful to the reviewer for appreciating our proposed study.
Reviewer 3 Report
This article is certainly of interest for the context to which it is applied. The original methodology is based on data from an Indian bank. I'm not sure the results can be fully extended to all banks' business models and other banking regulations
Author Response
Comments and Suggestions for Authors:
This article is certainly of interest for the context to which it is applied. The original methodology is based on data from an Indian bank. I'm not sure the results can be fully extended to all banks' business models and other banking regulations.
Responses: We are indebted to the reviewer for recognizing our work. Furthermore, we would like to mention that our methodology which is based on an Indian bank can be employed to any bank’s business model provided the bank consider the same criteria which we have mentioned in our study as far as approval of an housing loan to an eligible customer is concerned