Financial and Risk Analysis in Data Mining
Abstract
Commerce, credit cards are being widely used for online purchases. With increasing use of credit cards, there is also an increase in the risks related to them. This fact must be well understood by the banks and card holders in order to reduce risk and financial status to maximize the profitability. Risk refers to the chance of loss that may occur due to some external or internal vulnerabilities financially. There are some data mining methods that have been used for the risk and financial management. Like, classification, regression, multiple regressions, and optimization among which classification and regression are widely used. In this paper, we analyze the factors causing the operational financial and the security risks and the data mining methods used to minimize them. Here, in this paper we have dealt more with the financial risk analysis as it should be given prime attention since the losses caused by it are important. This paper presents a survey of various techniques used in financial and risk analysis.
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Chaiyakorn Yingsaeree and Philip Treleaven, UK Centre for Financial Computing, London Giuseppe Nuti, Citadel Securities, New York ”Computational Finance” published by the IEEE Computer Society,2010
R. Shenbagavalli, A. R. Shanmugapriya, and Y. Lokeshwara Chowdary “Risk Analysis of Credit Card Holders” International Journal of Trade, Economics and Finance, Vol. 3, No. 3, June 2012.
P-N. Tan, M. Steinbach, and V. Kumar, “Introduction to Data Mining, “Addison Wesley, 2006, pp.150-172
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