Risk Evaluation of the New Fintech Institutions in China Based on Fuzzy Analytical Hierarchy Process
The ongoing digital transformation is being undertaken by the financial institutions on the upgrade in China. The risks are accumulated synchronously in the middle of establishing differentiated competitive advantages through information technology innovations by the new fintech institutions. In thi...
Gespeichert in:
Veröffentlicht in: | Mathematical problems in engineering 2022-07, Vol.2022, p.1-9 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 9 |
---|---|
container_issue | |
container_start_page | 1 |
container_title | Mathematical problems in engineering |
container_volume | 2022 |
creator | YU, Kui |
description | The ongoing digital transformation is being undertaken by the financial institutions on the upgrade in China. The risks are accumulated synchronously in the middle of establishing differentiated competitive advantages through information technology innovations by the new fintech institutions. In this study, a fuzzy analytical hierarchy process is adopted to figure out the risk evaluation of the new fintech institutions in China, identifying those at risk as early as possible. Firstly, several level 1 indicators of the risk evaluation system of the new fintech institutions and corresponding subordinate level 2 indicators are determined, followed by rating the level 2 indicators of each new fintech institution ready for risk evaluation ranking, which leads to the risk evaluation matrix of each level 1 indicator. Secondly, the new fintech institutions are classified into the theoretically ideal “optimal,” “medium,” and “worst” categories by establishing the membership matrix of each level 1 indicator in the application of linear transformation formula. Thirdly, the degree of proximity is exploited in comparison of the fuzzy sets in pairs to form the fuzzy recognition model of each level 1 indicator in pursuit of the new fintech institutions least risky regarding each level 1 indicator. Finally, the fuzzy recognition models of each level 1 indicator are integrated into the construction of the fuzzy recognition model regarding the whole risk evaluation system to achieve the risk ranking of the new fintech institutions. This study aimed to provide a theoretical ground and an applied method for national regulators to monitor the fintech risks, which are prone to be avoided by the enterprises and individuals. |
doi_str_mv | 10.1155/2022/9338032 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2690829683</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2690829683</sourcerecordid><originalsourceid>FETCH-LOGICAL-c224t-190b3575a17d0f9cb441dbf5eb76f0c8d17e2f9e40fbd2feee78889893153e0a3</originalsourceid><addsrcrecordid>eNp9kE1Lw0AQhoMoWKs3f8CCR43dj2yye6yltQVREQVvYbOZJVtjUnc3lvTXm9KePc3APDPM-0TRNcH3hHA-oZjSiWRMYEZPohHhKYs5SbLTocc0iQlln-fRhfdrjCnhRIyi8s36LzT_VXWngm0b1BoUKkDPsEUL2wTQFVo1PtjQ7cce2QbNKtso9KA8lGjYWHS7XY-mjar7YLWq0dKCU05XPXp1rQbvL6Mzo2oPV8c6jj4W8_fZMn56eVzNpk-xpjQJMZG4YDzjimQlNlIXSULKwnAostRgLUqSATUSEmyKkhoAyIQQUkhGOAOs2Di6OdzduPanAx_yddu54TGf01RiQWUq2EDdHSjtWu8dmHzj7LdyfU5wvveY7z3mR48DfnvAh9Sl2tr_6T-5wnJI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2690829683</pqid></control><display><type>article</type><title>Risk Evaluation of the New Fintech Institutions in China Based on Fuzzy Analytical Hierarchy Process</title><source>Wiley Online Library Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>Alma/SFX Local Collection</source><creator>YU, Kui</creator><contributor>Lo Schiavo, Alessandro ; Alessandro Lo Schiavo</contributor><creatorcontrib>YU, Kui ; Lo Schiavo, Alessandro ; Alessandro Lo Schiavo</creatorcontrib><description>The ongoing digital transformation is being undertaken by the financial institutions on the upgrade in China. The risks are accumulated synchronously in the middle of establishing differentiated competitive advantages through information technology innovations by the new fintech institutions. In this study, a fuzzy analytical hierarchy process is adopted to figure out the risk evaluation of the new fintech institutions in China, identifying those at risk as early as possible. Firstly, several level 1 indicators of the risk evaluation system of the new fintech institutions and corresponding subordinate level 2 indicators are determined, followed by rating the level 2 indicators of each new fintech institution ready for risk evaluation ranking, which leads to the risk evaluation matrix of each level 1 indicator. Secondly, the new fintech institutions are classified into the theoretically ideal “optimal,” “medium,” and “worst” categories by establishing the membership matrix of each level 1 indicator in the application of linear transformation formula. Thirdly, the degree of proximity is exploited in comparison of the fuzzy sets in pairs to form the fuzzy recognition model of each level 1 indicator in pursuit of the new fintech institutions least risky regarding each level 1 indicator. Finally, the fuzzy recognition models of each level 1 indicator are integrated into the construction of the fuzzy recognition model regarding the whole risk evaluation system to achieve the risk ranking of the new fintech institutions. This study aimed to provide a theoretical ground and an applied method for national regulators to monitor the fintech risks, which are prone to be avoided by the enterprises and individuals.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2022/9338032</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Analytic hierarchy process ; Bank technology ; Decision making ; Employees ; Fuzzy sets ; Indicators ; Innovations ; Linear transformations ; Mathematical analysis ; Ranking ; Ratings & rankings ; Recognition ; Risk assessment ; Supervision</subject><ispartof>Mathematical problems in engineering, 2022-07, Vol.2022, p.1-9</ispartof><rights>Copyright © 2022 Kui Yu.</rights><rights>Copyright © 2022 Kui Yu. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c224t-190b3575a17d0f9cb441dbf5eb76f0c8d17e2f9e40fbd2feee78889893153e0a3</cites><orcidid>0000-0002-7035-4619</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><contributor>Lo Schiavo, Alessandro</contributor><contributor>Alessandro Lo Schiavo</contributor><creatorcontrib>YU, Kui</creatorcontrib><title>Risk Evaluation of the New Fintech Institutions in China Based on Fuzzy Analytical Hierarchy Process</title><title>Mathematical problems in engineering</title><description>The ongoing digital transformation is being undertaken by the financial institutions on the upgrade in China. The risks are accumulated synchronously in the middle of establishing differentiated competitive advantages through information technology innovations by the new fintech institutions. In this study, a fuzzy analytical hierarchy process is adopted to figure out the risk evaluation of the new fintech institutions in China, identifying those at risk as early as possible. Firstly, several level 1 indicators of the risk evaluation system of the new fintech institutions and corresponding subordinate level 2 indicators are determined, followed by rating the level 2 indicators of each new fintech institution ready for risk evaluation ranking, which leads to the risk evaluation matrix of each level 1 indicator. Secondly, the new fintech institutions are classified into the theoretically ideal “optimal,” “medium,” and “worst” categories by establishing the membership matrix of each level 1 indicator in the application of linear transformation formula. Thirdly, the degree of proximity is exploited in comparison of the fuzzy sets in pairs to form the fuzzy recognition model of each level 1 indicator in pursuit of the new fintech institutions least risky regarding each level 1 indicator. Finally, the fuzzy recognition models of each level 1 indicator are integrated into the construction of the fuzzy recognition model regarding the whole risk evaluation system to achieve the risk ranking of the new fintech institutions. This study aimed to provide a theoretical ground and an applied method for national regulators to monitor the fintech risks, which are prone to be avoided by the enterprises and individuals.</description><subject>Analytic hierarchy process</subject><subject>Bank technology</subject><subject>Decision making</subject><subject>Employees</subject><subject>Fuzzy sets</subject><subject>Indicators</subject><subject>Innovations</subject><subject>Linear transformations</subject><subject>Mathematical analysis</subject><subject>Ranking</subject><subject>Ratings & rankings</subject><subject>Recognition</subject><subject>Risk assessment</subject><subject>Supervision</subject><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE1Lw0AQhoMoWKs3f8CCR43dj2yye6yltQVREQVvYbOZJVtjUnc3lvTXm9KePc3APDPM-0TRNcH3hHA-oZjSiWRMYEZPohHhKYs5SbLTocc0iQlln-fRhfdrjCnhRIyi8s36LzT_VXWngm0b1BoUKkDPsEUL2wTQFVo1PtjQ7cce2QbNKtso9KA8lGjYWHS7XY-mjar7YLWq0dKCU05XPXp1rQbvL6Mzo2oPV8c6jj4W8_fZMn56eVzNpk-xpjQJMZG4YDzjimQlNlIXSULKwnAostRgLUqSATUSEmyKkhoAyIQQUkhGOAOs2Di6OdzduPanAx_yddu54TGf01RiQWUq2EDdHSjtWu8dmHzj7LdyfU5wvveY7z3mR48DfnvAh9Sl2tr_6T-5wnJI</recordid><startdate>20220708</startdate><enddate>20220708</enddate><creator>YU, Kui</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0002-7035-4619</orcidid></search><sort><creationdate>20220708</creationdate><title>Risk Evaluation of the New Fintech Institutions in China Based on Fuzzy Analytical Hierarchy Process</title><author>YU, Kui</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c224t-190b3575a17d0f9cb441dbf5eb76f0c8d17e2f9e40fbd2feee78889893153e0a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Analytic hierarchy process</topic><topic>Bank technology</topic><topic>Decision making</topic><topic>Employees</topic><topic>Fuzzy sets</topic><topic>Indicators</topic><topic>Innovations</topic><topic>Linear transformations</topic><topic>Mathematical analysis</topic><topic>Ranking</topic><topic>Ratings & rankings</topic><topic>Recognition</topic><topic>Risk assessment</topic><topic>Supervision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>YU, Kui</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>Mathematical problems in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>YU, Kui</au><au>Lo Schiavo, Alessandro</au><au>Alessandro Lo Schiavo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk Evaluation of the New Fintech Institutions in China Based on Fuzzy Analytical Hierarchy Process</atitle><jtitle>Mathematical problems in engineering</jtitle><date>2022-07-08</date><risdate>2022</risdate><volume>2022</volume><spage>1</spage><epage>9</epage><pages>1-9</pages><issn>1024-123X</issn><eissn>1563-5147</eissn><abstract>The ongoing digital transformation is being undertaken by the financial institutions on the upgrade in China. The risks are accumulated synchronously in the middle of establishing differentiated competitive advantages through information technology innovations by the new fintech institutions. In this study, a fuzzy analytical hierarchy process is adopted to figure out the risk evaluation of the new fintech institutions in China, identifying those at risk as early as possible. Firstly, several level 1 indicators of the risk evaluation system of the new fintech institutions and corresponding subordinate level 2 indicators are determined, followed by rating the level 2 indicators of each new fintech institution ready for risk evaluation ranking, which leads to the risk evaluation matrix of each level 1 indicator. Secondly, the new fintech institutions are classified into the theoretically ideal “optimal,” “medium,” and “worst” categories by establishing the membership matrix of each level 1 indicator in the application of linear transformation formula. Thirdly, the degree of proximity is exploited in comparison of the fuzzy sets in pairs to form the fuzzy recognition model of each level 1 indicator in pursuit of the new fintech institutions least risky regarding each level 1 indicator. Finally, the fuzzy recognition models of each level 1 indicator are integrated into the construction of the fuzzy recognition model regarding the whole risk evaluation system to achieve the risk ranking of the new fintech institutions. This study aimed to provide a theoretical ground and an applied method for national regulators to monitor the fintech risks, which are prone to be avoided by the enterprises and individuals.</abstract><cop>New York</cop><pub>Hindawi</pub><doi>10.1155/2022/9338032</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-7035-4619</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1024-123X |
ispartof | Mathematical problems in engineering, 2022-07, Vol.2022, p.1-9 |
issn | 1024-123X 1563-5147 |
language | eng |
recordid | cdi_proquest_journals_2690829683 |
source | Wiley Online Library Open Access; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
subjects | Analytic hierarchy process Bank technology Decision making Employees Fuzzy sets Indicators Innovations Linear transformations Mathematical analysis Ranking Ratings & rankings Recognition Risk assessment Supervision |
title | Risk Evaluation of the New Fintech Institutions in China Based on Fuzzy Analytical Hierarchy Process |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-02T07%3A33%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Risk%20Evaluation%20of%20the%20New%20Fintech%20Institutions%20in%20China%20Based%20on%20Fuzzy%20Analytical%20Hierarchy%20Process&rft.jtitle=Mathematical%20problems%20in%20engineering&rft.au=YU,%20Kui&rft.date=2022-07-08&rft.volume=2022&rft.spage=1&rft.epage=9&rft.pages=1-9&rft.issn=1024-123X&rft.eissn=1563-5147&rft_id=info:doi/10.1155/2022/9338032&rft_dat=%3Cproquest_cross%3E2690829683%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2690829683&rft_id=info:pmid/&rfr_iscdi=true |