Presented at the 3rd International Symposium on Innovative Approaches in Scientific Studies (Engineering and Natural Sciences) (ISAS2019-ENS), Ankara, Turkey, Apr 19, 2019

SETSCI Conference Proceedings, 2019, 4, Page (s): 180-183 , https://doi.org/

Published Date: 01 June 2019    | 745     22

In recent years, the financial sector has been considerably developed, especially in electronic banking. As individual users in the financial sector use e-banking and e-finance systems, the concept of loyalty in the banking sector has shifted from traditional branch banking where staff and customers have personal relations to self-service online banking. As expected, online banking competition is based on pricing and service quality. In this work special pricing, discounts, campaigns data and potential customers’ searches are analyzed from available data. Modeling and segmentation were carried out with data mining and machine learning methods.

Keywords - Data Mining, e-banking, e-finance, Machine Learning, Modeling, Segmentation

[1] Choi, H. & Varian, H. Predicting the Present with Google Trends. The Economic Record 88, 2–9 (2012).

[2] Preis, T., Moat, H. S., Stanley, H. E. & Bishop, S. R. Quantifying the Advantage of Looking Forward. Scientific Reports 2, 350 (2012).

[3] P. Smith, "Google's MIDAS touch: Predicting UK unemployment with internet search data," J. Forecast. 35(3), pp. 263-284,2016.

[4] N. Askitas, K. F. Zimmermann, "Google econometrics and unemployment forecasting," Appl. Econ. Quart. 55(2), pp. 107-120,2009.

[5] P. Smith, "Google's MIDAS touch: Predicting UK unemployment with internet search data," J. Forecast. 35(3), pp. 263-284,2016.

[6] N. Askitas, K. F. Zimmermann, "Google econometrics and unemployment forecasting," Appl. Econ. Quart. 55(2), pp. 107-120,2009.

[7] F. D'Amuri, J. Marcucci, "Google it! Forecasting the US unemployment rate with a Google job search index," FEEM Working Paper 31,2010.

[8] Y. Fondeur, F. Karame, "Can Google data help predict French youth unemployment?" Econ. Model. 30, pp. 117-125,2013.

[9] J. Ginsberg, M. H. Mohebbi, R. S. Patel, L. Brammer, M. S.Smolinski, L. Brilliant, "Detecting influenza epidemics using search engine query data," Nat. 457(7232), pp. 1012-1014,2009.

[10] J. A. Doornik, "Improving the timeliness of data on influenza-like illnesses using Google search data," Working Paper, 2009= J. A. Doornik, "Improving the timeliness of data on influenza-like illnesses using Google search data," Working Paper, 2009.

[11] P. C. Cooper, P. K. Mallon, S. Leadbetter, A. L. Pollack, A. L.Peipins, "Cancer internet search activity on a major search engine, United States 2001-2003,"/. Med. Internet Res. 7(3), e36,2005.

[12] G. Eysenbach, "Infbdemiology: Tracking flu-related searches on the web for syndromic surveillance," AMIA Annual Symposium Proceedings, pp. 244-248,2006.

[13] P. M. Polgreen, Y. Chen, D. M. Pennock, F. D. Nelson, R. A. Weinstein, "Using internet searches for influenza surveillance," Clin. Infect. Dis. 47(11), pp.1443-1448,2008.

[14] A. Hulth, G. Rydevik, A. Linde, "Web queries as a source for syndromic surveillance," PLOS ONE 4(2) e4378,2009.

[15] M. J. McCarthy, "Internet monitoring of suicide risk in the population," J. Affect. Disord. 122(3), pp. 277-279,2010.

[16] J. F. Gunn HI, D. Lester, "Using Google searches on the internet to monitor suicidal behavior," J. Affect. Disord. 148 (2-3), pp.411-412,2013.

[17] H. Sueki, "Does the volume of Internet searches using suicide related search terms influence the suicide death rate: Data from 2004 to 2009 in Japan," Psychiatry Clin. Neurosci. 65(4), pp.392-394,2011.

[18] Fehr, E. Behavioral science - The economics of impatience. Nature 415, 269–272(2002).

[19] Shleifer, A. Inefficient Markets: An Introduction to Behavioral Finance (Oxford University Press, Oxford, 2000).

[20] Lillo, F., Farmer, J. D. & Mantegna, R. N. Econophysics - Master curve for price impact function. Nature 421, 129–130 (2003).

[21] Watanabe, K., Takayasu, H. & Takayasu, M. A mathematical definition of the financial bubbles and crashes. Physica A 383, 120–124(2007).

[22] Bouchaud, J. P., Matacz, A. & Potters, M. Leverage effect in financial markets: the retarded volatility model. Physical Review Letters 87, 228701 (2001).

[23] Sornette, D. & von der Becke, S. Complexity clouds finance-risk models. Nature 471, 166 (2011).

[24] Schweitzer, F. et al. Economic Networks: The New Challenges. Science 325,422–425 (2009).

[25] Buldyrev, S. V., Parshani, R., Paul, G., Stanley, H. E. & Havlin, S. Catastrophic cascade of failures in interdependent networks. Nature 464, 1025–1028 (2010).

[26] J. B. MacQueen, "Some Methods for classification and Analysis of Multivariate Observations", Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability. Berkeley, University of California Press, 1 pp.281-297, 1967.

[27] Kaufman, L. & Rousseeuw, P.J., Finding Groups in Data: An Introduction to Cluster Analysis, John Wiley and Sons, Inc., New York ,1990.

[28] Legendre, P. & L. Legendre, Numerical Ecology, Second edition. Elsevier Science BV, Amsterdam, the Netherlands, 1998.

[29] Bradley & Fayyad , "Scaling Clustering Algorithms to Large Databases", Proceedings of the Fifteenth International Conference on Machine Learning ICML98, pp.91-99, 1998.

[30] T. Kanungo,DM Mount, N. Netanyahu, Christine D. Piatko, Ruth Silverman & Angela Y. Wu, " An efficient kmeans clustering algorithm: Analysis and implementation", IEEE Trans. Pattern Analysis and Machine Intelligence, 24, pp.881 -892,2002.

[31] K. Krishna & Raghu Krishnapuram, " A Clustering Algorithm for Asymmetrically Related Data with Applications to Text Mining", Proceedings of the International Conference on Information and Knowledge Management(CIKM2001), Atlanta, Georgia, USA, pp.571- 573, 2001.

[32] S. Guha, R. Rastogi & K. Shim, "CURE: An efficient clustering algorithm for large databases", Proceedings of ACM SIGMOD International Conference on Management of Data. New York, pp. 73- 84, 1998.

[33] P. Kotler and K. L. Keller, "Marketing Management, Global Edition. 15th ed." Edinburgh Gate, England: Pearson Education Limited,pp.194-209, 2015.

[34] T. Milner and D. Rosenstreich, "A review of consumer decision making models and development of a new model for financial services." Journal of Financial Services Marketing, vol. 18(2), pp.106-120, 2013.