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The Organization of Data Warehouse Activities

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Customer Relationship Management in the Financial Industry

Part of the book series: Management for Professionals ((MANAGPROF))

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Abstract

In the last decade, the configuration of the banking market has seen a steady increase in competition levels, owing to the relaxation of restrictions on banks’ operational independence, to the entry of nonbanking operators into the payments system, and to the banks’ new role in the financial market (Banca d’Italia 2010).

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Notes

  1. 1.

    We refer to the innovations introduced by EU directives on banking coordination, and, in Italy’s particular case, to the new overall regulation system for the banking industry.

  2. 2.

    Porter and Millar (1985) in How Information Gives You Competitive Advantages, classify different industrial sectors through an information intensity matrix. The said matrix allows analysis of the needs in terms of information intensity of processes and contents for the products/services typical of each sector. They then give an evaluation of existing and potential information intensities of processes and products, stating that these can determine role and dimension of IT in every industrial sector. Porter and Millar demonstrate how IT is a fundamental variable in all activities carried out by the bank. They do this by focusing on the needs and information contents typical of the banking sector which, in order to fulfil its objectives, uses IT in a consistent and systematic way. They thus conclude by saying the high information contents in products/services and the high information intensity in processes make the banking sector one of the most enthusiastic in the use of IT. On the same issue see also Rossignoli (1997).

  3. 3.

    It is interesting to remark that artificial intelligence systems, which are now included in data mining systems, are a technology that was already available in the 1950s. However, they partly owing to a natural reaction of resistance to change among management, partly because of the high implementation costs, and partly because of technical factors making it impossible to implement them, such as difficulties in accessing and reusing company data.

  4. 4.

    On this issue, CeTIF carried out a research study on 40 banks of different sizes were involved (accounting at the time for 50 % of the profits of the entire banking sector). Five different areas were explored: control over several sectors of the financing area, management control, management information system, strategic planning and ALM (Asset and Liability Management). It emerged from the results that while in the first two sectors information systems enjoyed a certain, if not sufficient, diffusion, the third and fourth areas had a limited use for such tools, since many activities were still performed by hand and in the fifth there was an extremely low spread of information systems, because there were few companies implementing innovations.

  5. 5.

    Such as data modelling, information engineering, and other approaches.

  6. 6.

    In this case we refer to data contained in company archives and to data coming from information providers, or from the Internet, or from the banking system in general.

  7. 7.

    An example is supplied by the data on a certain geographical area, or data from the Risk Centre, or those originating from information providers such as Reuters or Bloomberg.

  8. 8.

    Sometimes “datamart” is used to mean a number of decision support systems, isolated from one another and oriented to specific business problems. On other occasions the term is used to refer to server-based, local applications, which are fed by a central DWH. They are also called subsidiary datamarts.

  9. 9.

    It is possible to have a data mart for the loans area, one for the financial area, and so on.

References

  • Banca d’Italia (1996). Tematiche aziendali: La tecnologia dell’informazione e la Banca d’Italia (2nd ed.), Roma: Banca d’Italia. November.

    Google Scholar 

  • Banca d’Italia (2010). Rapporto sullo stato di automazione del sistema bancario. http://www.cipa.it/docs/rileva/rileva.htm

  • Berson, A., Smith, S., & Thearling, K. (2000). Building data mining applications for CRM (Datamanagement). Osborne: McGraw-Hill.

    Google Scholar 

  • Bielski, L. (2001). Giving your customer a face. ABA Banking Journal, 93(4), 49.

    Google Scholar 

  • Brown, S. A. (2000). Customer relationship management: Linking people, process and technology. New York: Wiley.

    Google Scholar 

  • Camuffo, A., & Costa, G. (1995). Banca and organizzazione. Milano: Edibank.

    Google Scholar 

  • Carignani, A. (2001). Mobile commerce: Tecnologie, falsi miti e opportunità. In A. Carignani & M. Sorrentino (Eds.), On-line banking. Milano: McGraw-Hill.

    Google Scholar 

  • Cash, J. I., McFarlan, W. F., & McKenney, J. L. (1988). Corporate information systems management. Homewood: Irwin.

    Google Scholar 

  • Ciborra, C. (Ed.). (2000). From control to drift: The dynamics of corporate information infrastructures. Oxford: Oxford University Press.

    Google Scholar 

  • CIPA/ABI (1999). Rilevazione dello stato dell’automazione del sistema creditizio.

    Google Scholar 

  • Cranford, S. (1998). Knowledge through DWH: DM, the intelligent component, DM Review, May, www.dmreview.com

  • De Marco, M. (2002). I sistemi informativi aziendali. Temi di attualità. Milano: FrancoAngeli.

    Google Scholar 

  • Dyché, J. (2000). e-Data: Turning data into information with data warehousing. Boston: Addison-Wesley.

    Google Scholar 

  • Earl, M.J. (1996). The risk of IT outsourcing. Sloan Management Review, 37(3), 26–32.

    Google Scholar 

  • Groth, R. (1998). Data mining. A hands-on approach for business professionals. Santa Clara: Prentice Hall PTR.

    Google Scholar 

  • Imhoff, C., Loftis, L., Geiger, J.G., foreword by Inmon, W.H. (2001). Building the customer-centric enterprise: Data warehousing techniques for supporting customer relationship management. Canada: Wiley.

    Google Scholar 

  • Inmon, W. H. (1996). Building the data warehouse (2nd ed.). New York: Wiley.

    Google Scholar 

  • Kelly, S. (1997). Data warehousing in action. New York: Wiley.

    Google Scholar 

  • Kimball, R. (1996). Data warehouse toolkit. New York: Wiley.

    Google Scholar 

  • Mayes, N. (2001). Banks still keen on CRM and outsourcing. Global Computing Services, 5 October.

    Google Scholar 

  • McFarlan, F. W., & Nolan, R. L. (1995). How to manage an IT outsourcing alliance. Sloan Management Review, 36, 9–24.

    Google Scholar 

  • McKeen, J. D., & Smith, H. A. (1996). Management challenges in IS: Successful strategies and appropriate action. Chichester: Wiley.

    Google Scholar 

  • Morris, G. (2002). Beyond CRM: Assessing clients’ value. Bank Investment Marketing, 10(2), 9.

    Google Scholar 

  • Porter, M. E., & Millar, V. E. (1985). How information gives you competitive advantages. Harvard Business Review, 63(4), 149–162.

    Google Scholar 

  • Rajola, F. (Ed.). (2000). L’organizzazione dei sistemi di business intelligence nel settore finanziario. Milano: FrancoAngeli.

    Google Scholar 

  • Rossignoli, C. (1997). Organizzazione e sistemi informativi. Milano: FrancoAngeli.

    Google Scholar 

  • Scott, W. G. (1997). Presentazione. In M. Bertucci (Ed.), Conoscere il cliente. Edibank: Milano.

    Google Scholar 

  • Virtuani, R. (1997). L’outsourcing nei sistemi informativi aziendali. Milano: FrancoAngeli.

    Google Scholar 

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Rajola, F. (2013). The Organization of Data Warehouse Activities. In: Customer Relationship Management in the Financial Industry. Management for Professionals. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35554-7_6

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  • DOI: https://doi.org/10.1007/978-3-642-35554-7_6

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