The Usage of Data Mining Technology in Financial Information System
Ceren Uzar
International Journal of Finance & Banking Studies · 2014 · Vol. 3 / Issue 1 · 51-61
Publication metrics
External links open provider records or DOI searches. Provider counts are not combined. Mendeley readership measures saves, not citations.
Dimensions
Live provider badge. If unavailable, use the Dimensions link above.
Observed 21 Oct 2026, 00:21 UTC
Observed 21 Oct 2026 00:22 UTC
Observed 21 Oct 2026 23:02 UTC
OpenAlex and Mendeley observations refresh on article visits, at most once per 24 hours. Unavailable data is not zero. Google Scholar opens a DOI search.
Citations received by this article, grouped by the year of the citing work. Crossref and OpenAlex lifetime totals remain separate in Publication metrics.
2017–2026 Annual history last updated:
Citations received
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
View data & coverage
2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Years beyond a saved observation’s window remain unknown (—). Older citations are excluded, so this chart’s sum may differ from the OpenAlex lifetime total. The date above belongs to this annual history; an unsuccessful refresh keeps the previous observation.
Abstract
Data mining technology is one of the new technologies that have become increasingly popular. Data mining enables to form forecasts and models regarding future by making use of past data. It can be costly, risky and time consuming for enterprises to gain knowledge. Firms gain important competitive advantage by data mining methods. This study analyzes on the readiness to implement and the extent of utilization of data mining technologies in the Financial Information Systems (FIS) in Borsa Istanbul and also researches the level of understanding of, perceptions of and readiness to implement data mining technologies within the Borsa Istanbul. Analysis was undertaken using SPSS. Manufacturing and financial enterprises are the universal of this study. Primary data were obtained by using survey method and questionnaire technique and findings of the study were evaulated. Technological, organisational and human resources issues had a significant role in the decision to, or not to utilize data mining technology. The ability to use data mining technology was found to be increased the performance of the Financial Information System.
Keywords: {'name': 'Data Mining'}, {'name': 'Information Systems'}, {'name': 'Financial Information System'}
Authors & affiliations
Ceren Uzar
Affiliation not supplied
Deposited references
Supplied references, not a list of publications citing this article.
Akgöbek, Ö., Çakır, F. (2009). Veri Madenciliğinde Bir Uzman Sistem Tasarımı, Akademik Bilişim’09 - XI. Akademik Bilişim Konferansı Bildirileri 11-13 Şubat 2009 Harran Üniversitesi, Şanlıurfa.
Akkaya, G. C., Uzar, C. (2011). Data Mining And Application Of It To Capital Markets. International Journal Of Economics and Finance Studies, ISSN: 1309-80552011 (Online): 3 (2): 57-67.
Aktaş, R.,Kargın, M. (2011). Timeliness of Reporting and the Quality of Financial Information. International Research Journal of Finance and Economics. ISSN 1450-2887, 63: 71-77.
Albayrak, A. S., Yılmaz Koltan, Ş. (2009). Veri Madenciliği: Karar Ağacı Algoritmaları ve IMKB Verileri Üzerine Bir Uygulama. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 14 (1): 31-52.
DOI: 10.1002/isaf.199
DOI: 10.1111/j.1468-5957.1987.tb00106.x
DOI: 10.1016/j.eswa.2008.03.020
Dass, R. (2006). Data Mining in Banking and Finance:A note for Bankers. Indian Institue of Managemenet Ahmedabad, s.1-15.
DOI: 10.1016/j.eswa.2006.07.007
DOI: 10.1016/S0167-9236(96)80006-6
Karacabey, A. A. (2006). Banka Başarısızlıklarının Düzeltilmiş Minumum Sapma Modeli ile Tahmin Edilmesi. Ankara Üniversitesi SBF Dergisi, 89-109.
Koyuncugil, A. S. (2007). Veri Madenciliği ve Sermaye Piyasalarına Uygulanması, Sermaye Piyasası Kurulu Araştırma Raporu. ss.1-17.
Koyuncugil, A. S., Özgülbaş, N. (2008) . IMKB’de İşlem Gören Kobi’lerin Güçlü ve Zayıf Yönleri: Chaıd Karar Ağacı Uygulaması. Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi Cilt:23 Sayı:1, ss:1-21.
Koyuncugil, A. S.,Özgülbaş, N. (2009). Data Mining: Using And Applications In Medicine And Healthcare. Journal of Information Technology, 2(2): 21-32.
Newyork Stock Ehxchange. 2011. Stock Watch, http://www.nyse.com/glossary/glossarylinks.html?a=1048903219379, (20.02.2011).
Rahman, M. S. A. (2008). Utilisation of Data Mining Technology within the Accounting Information System in the Public Sector: A Country Study – Malaysia. (Unpublished Doctoral Dissertation). Malaysia: University of Tasmania.
Shirata, C. Y. (1998). Financial Ratios as Predictors of Bankruptcy in Japan: An Empirical Research. Proceedings of The Second Asian Pacific Interdisciplinary Research in Accounting Conference, http://www3.bus.osaka-cu.ac.jp/apira98/archives/pdfs/31.pdf, 20.11.12.
The Stock Exchange of Thailand. 2011. Investor Protection, http://www.set.or.th/en/regulations/protection/protection_p1.html, (20.02.2011).
Torun, İ. H. (2007). Finansal Başarısızlık Tahmininde Geleneksel İstatistiki Yöntemlerle Yapay Sinir Ağlarının Karşılaştırılması Ve Sanayi İşletmeleri Üzerinde Uygulama. Erciyes Üniversitesi. Sosyal Bilimler Enstitüsü. İşletme Ana Bilim Dalı. Doktora Tezi.