Abstract
Computer programs that reason like highly skilled human experts are a most exciting result of research in artificial intelligence (AI). In this paper we present some backgrounds for building of knowledge-based systems in banking environment. An important consideration is the choice of hardware and software to support AI work. Several practical benefits from the cooperative use of expert systems (ES) with database management systems (DBMS) can be identified (coupling AI and traditional data processing concepts and techniques into a single environment is most desirable). The features of ES can result in some attractive benefits for companies in almost any business classification. The applications listed in the paper by no means represent a complete list of candidates, but should offer a stimulus for further investigation.
Within the development of a knowledge-based system, several AI methodologies have been widely explored and adopted. The hybrid ES architecture seems to us particularly useful in banking and finance. Next, in the paper, a hybrid ES model has been proposed to facilitate credit approval tasks. To see how a mathematical subsystem of such model can be realized in practice we describe the principles of subjective probability and clustering (numerical taxonomy).
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Slahor, L. (1986). Some Backgrounds for Building an Expert System in Banking Environment. In: Schulz, A. (eds) Die Zukunft der Informationssysteme Lehren der 80er Jahre. Betriebs- und Wirtschaftsinformatik, vol 17. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-71384-2_29
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DOI: https://doi.org/10.1007/978-3-642-71384-2_29
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