Abstract
Banking transactions require storage and processing of large amounts of data. Knowledge discovery processes allow analysis of such data with the aim of spotting complex behaviour patterns and characteristics of the variables contained in the archives. Knowledge discovery processes and data mining systems can be used in a wide range of financial applications.
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Notes
- 1.
We refer to a data warehouses, datamarts, or other, simpler, archives especially created to support the knowledge discovery process.
- 2.
As already mentioned, it must be noted that artificial intelligence systems, which are now incorporated in data mining systems, were already available technology back in the 1950s. However, they failed to catch on, owing partly to a natural resistance of company managements to change, partly to the high implementation costs, and partly also to technical impossibilities, such as difficulty in accessing and reusing company data.
- 3.
For example, the user may be more interested in understanding the model than in originating a prediction.
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Rajola, F. (2013). Organization of Knowledge Discovery and Customer Insight 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_7
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DOI: https://doi.org/10.1007/978-3-642-35554-7_7
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