{"title":"Promoting Entrepreneurship at the Base of the Social Pyramid via Pricing Systems: A case Study","authors":"J. Lara-Rubio, A. Blanco-Oliver, R. Pino-Mejías","doi":"10.1002/isaf.1400","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Historically, microfinance institutions (MFIs) have played a significant social role by helping people at the base of the socio-economic pyramid escape from social exclusion through the creation of microenterprises. However, international banks have recently started competing in the microfinance sector. In this adverse environment, MFI management tools should be more innovative and technologically advanced to increase efficiency, solvency and profitability and to compete with commercial banks on equal terms. This study therefore strives to develop a credit-risk management tool based on a multilayer perceptron (MLP) credit-scoring model for a Peruvian MFI, and to calculate the capital requirements and microcredit pricing on both internal ratings-based (IRB) and standardized approaches, analysing the impact of these models on the management of the MFI. Our findings show that the implementation of an IRB approach with default probabilities obtained from an MLP credit-scoring model produces the best benefit by the MFIs in terms of higher accuracy (reduction of misclassification costs by 13.78%), lower capital requirements (in the range of 8.5–78%) and the best risk-adjusted interest rates. Furthermore, with the establishment of interest rates adjusted to the real risk of each client, MFIs are fairer and more socially engaged by preventing economically viable low-risk projects from becoming unviable due to excessive interest rates. This leads to the creation of more small businesses by people from the base of the socio-economic pyramid and greater economic development and social cohesion. The IRB model should therefore be implemented to improve MFI solvency, profitability, efficiency, survival, management and social performance.</p>\n </div>","PeriodicalId":53473,"journal":{"name":"Intelligent Systems in Accounting, Finance and Management","volume":"24 1","pages":"12-28"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/isaf.1400","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Systems in Accounting, Finance and Management","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/isaf.1400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 9
Abstract
Historically, microfinance institutions (MFIs) have played a significant social role by helping people at the base of the socio-economic pyramid escape from social exclusion through the creation of microenterprises. However, international banks have recently started competing in the microfinance sector. In this adverse environment, MFI management tools should be more innovative and technologically advanced to increase efficiency, solvency and profitability and to compete with commercial banks on equal terms. This study therefore strives to develop a credit-risk management tool based on a multilayer perceptron (MLP) credit-scoring model for a Peruvian MFI, and to calculate the capital requirements and microcredit pricing on both internal ratings-based (IRB) and standardized approaches, analysing the impact of these models on the management of the MFI. Our findings show that the implementation of an IRB approach with default probabilities obtained from an MLP credit-scoring model produces the best benefit by the MFIs in terms of higher accuracy (reduction of misclassification costs by 13.78%), lower capital requirements (in the range of 8.5–78%) and the best risk-adjusted interest rates. Furthermore, with the establishment of interest rates adjusted to the real risk of each client, MFIs are fairer and more socially engaged by preventing economically viable low-risk projects from becoming unviable due to excessive interest rates. This leads to the creation of more small businesses by people from the base of the socio-economic pyramid and greater economic development and social cohesion. The IRB model should therefore be implemented to improve MFI solvency, profitability, efficiency, survival, management and social performance.
期刊介绍:
Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.