Call For Paper Volume:4 Issue:10 Oct'2017 |

Modeling Data Mining Techniques with Financial Applications

Publication Date : 31/03/2015

Author(s) :

Prof. S. Golash , R. K. Yadav , Mogal Rihan Beig Hamja Beig.

Volume/Issue :
Volume 2
Issue 3
(03 - 2015)

Abstract :

Data mining is a scientific tool based on statistical and AI techniques. It is becoming strategically important area for many business organizations including financial institutions and banking sector. It is a process of analyzing the data from various perspectives and summarizing it into valuable information. Data mining assists the banks to look for hidden pattern in a group and discover unknown relationship in the data. Today, customers have so many opinions with regard to where they can choose to do their business. Early data analysis techniques were oriented toward extracting quantitative and statistical data characteristics. These techniques facilitate useful data interpretations for the banking sector to avoid customer attrition. Customer retention is the most important factor to be analyzed in today’s competitive business environment. And also fraud is a significant problem in banking sector. This paper is organized in different sections. In the first section we have analyzed the introduction and relevance of the study. In the second section we have made the detailed study of the tools and techniques required for the purpose. In the third section we have proposed our model for making data mining used in finance and banking sector. The Detecting and preventing fraud is difficult, because fraudsters develop new schemes all the time, and the schemes grow more and more sophisticated to elude easy detection. In this paper we have analyzed the data mining techniques and its applications in banking sector like fraud prevention and detection, customer retention, marketing and risk management. The outcome of the research paper is listed along with mathematical results.

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Modeling Data Mining Techniques with Financial Applications

February 23, 2015