{"title":"Configuring the RegTech business model to explore implications of FinTech","authors":"Jen-Sheng Wang , Yen-Tzu Chen","doi":"10.1016/j.eij.2024.100483","DOIUrl":null,"url":null,"abstract":"<div><p>Regulatory technology (RegTech) is a significant technology in the financial technology (FinTech) field that can assist FinTech and innovations to solve issues of complying with laws and regulations. However, RegTech is mainly composed of the finance, regulatory and emerging technology sectors, and its business model involves multiple dimensions, such as those among governments, banks and technology companies and cross-border FinTech. Therefore, RegTech startups exhibit distinctive features, and the optimum business model for their operation needs to be rapidly determined. This study uses a business model canvas (BMC) as an example to configure the elements and determinants of a RegTech start-ups and applies the Delphi technique and multiple criteria decision-making (MCDM) approaches for the analysis.</p><p>The results indicate that ‘customer relations (CR)’ and ‘key activities (KA)’ are the most significant BMC elements. Additionally, the relevant top-ranked determinants are, in their order of importance, ‘Big Data analysis’, ‘system feasibility evaluation’, ‘long-term customization’, ‘data assessment and stakeholder descriptions’, and ‘short-term projects’. In particular, business models of RegTech are the most complex in FinTech. This study concludes with business elements that can be beneficial not only for RegTech advancement but also for other emerging technologies in the FinTech.</p></div>","PeriodicalId":56010,"journal":{"name":"Egyptian Informatics Journal","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S111086652400046X/pdfft?md5=ff431b4c3f4e17c2efee3cf549a501cb&pid=1-s2.0-S111086652400046X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Egyptian Informatics Journal","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S111086652400046X","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Regulatory technology (RegTech) is a significant technology in the financial technology (FinTech) field that can assist FinTech and innovations to solve issues of complying with laws and regulations. However, RegTech is mainly composed of the finance, regulatory and emerging technology sectors, and its business model involves multiple dimensions, such as those among governments, banks and technology companies and cross-border FinTech. Therefore, RegTech startups exhibit distinctive features, and the optimum business model for their operation needs to be rapidly determined. This study uses a business model canvas (BMC) as an example to configure the elements and determinants of a RegTech start-ups and applies the Delphi technique and multiple criteria decision-making (MCDM) approaches for the analysis.
The results indicate that ‘customer relations (CR)’ and ‘key activities (KA)’ are the most significant BMC elements. Additionally, the relevant top-ranked determinants are, in their order of importance, ‘Big Data analysis’, ‘system feasibility evaluation’, ‘long-term customization’, ‘data assessment and stakeholder descriptions’, and ‘short-term projects’. In particular, business models of RegTech are the most complex in FinTech. This study concludes with business elements that can be beneficial not only for RegTech advancement but also for other emerging technologies in the FinTech.
期刊介绍:
The Egyptian Informatics Journal is published by the Faculty of Computers and Artificial Intelligence, Cairo University. This Journal provides a forum for the state-of-the-art research and development in the fields of computing, including computer sciences, information technologies, information systems, operations research and decision support. Innovative and not-previously-published work in subjects covered by the Journal is encouraged to be submitted, whether from academic, research or commercial sources.