Finansal Suçların Tespitinde Veri Madenciliği Yaklaşımı ve Literatüre Bakış

Year 2016, Volume: 11 Issue: 2, 93 - 118, 01.08.2016

M. Fevzi Esen

Abstract

Sadece Amerika Birleşik Devletleri hisse senedi piyasalarında günlük ortalama işlem miktarının 7 milyar adet olarak gerçekleştiği bile baz alındığında, stratejik, taktik ve operasyonel karar süreçlerindeki problemlerin daha düşük maliyetle ve yüksek güvenilirlikle çözülebilmesi için veri içerisinde saklı bulunan bilgilerin keşfedilmesi gerektiği bir gerçektir. Veri madenciliği olarak adlandırılan bu bilgi keşfi süreci; risk ve portföy yönetimi gibi bankacılık uygulamalarının yanısıra; şirketlerdeki finansal raporlamaların denetlenmesi ve piyasa oyuncuları arasında doğru bilgi akışının sağlanmasında etkin bir şekilde kullanılmaktadır. Bu çalışmada, 1994 - 2015 yılları arasında yayınlanan 79 adet bilimsel makale, finansal suç kategorisine göre sınıflandırılmış ve veri madenciliği tekniklerine göre değerlendirilmiştir. Çalışmada, veri madenciliği tekniklerinin çoğunlukla bankacılık ve sigorta suçlarının tespitinde kullanıldığı tespit edilmiş olup; finansal suçların veri madenciliğiyle tespiti ve tahminlenmesine yönelik Türkiye’deki çalışmaların yetersiz olduğu sonucuna varılmıştır.

Keywords

Finansal Suçlar, Veri Madenciliği, Hile Tespiti, Literatür Çalışması

Data Mining Approach In Financial Fraud Detection and a Literature Review

Abstract

Only in USA Stock Exchanges, daily avarage trading volume is about 7 billion units. Just depending on this statistics, the necessity of information discovery hidden in data is a reality to tackle the problems in strategic, tactical and operational decision processes with lower costs and higher reliability. Information discovery from databases, namely, data mining is an effective method for auditing financial statements in companies and providing flow of information between market players as well as risk and portfolio management as banking applications. In this study, 79 journal articles related to the subject published 1994-2015 have been classified and evaluated in terms of data mining techniques. It has been found that data mining techniques have been applied most extensively to detection of banking and insurance fraud. However, the findings of literature review show that the number of studies in detection and prediction of financial fraud is not enough in Turkey.

Keywords

Financial Fraud, Data Mining, Fraud Detection, Literature Review

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