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Field Study 2: X_Workflow for Overdraft Management in a Bank

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1096)

Abstract

This chapter describes the application of the organisational models and workflow management systems developed so far in this research report, in an Italian bank. The proposed approaches were applied as discussed in the previous chapters for business process re-engineering, workflow analysis and design, cooperative networks and the use of workflow management systems. The author participated in this project for business process re-engineering from the very early analysis until the final implementation of the computer system. The objective was to guarantee the change of traditional structures and procedures of the bank into customer-oriented processes for financial services. The bank had to react to the changing competitive and financial situation due to the market liberalisation and to the stronger anti-crime control on financial transactions in Italy, by redesigning its market-oriented business processes. For this aim, first of all the customer related credit processes were analysed using the method here developed, based on the customer/supplier model. Thus the credit management process was the target for a workflow-based reporting system. The system copes with events in the daily occurrence of overdrafts on current accounts which have to be managed by the agency director and the branch’s staff. The reporting system developed is part of a global change from the centralised into a distributed credit management information system based on a client/server architecture. The functional architecture for workflow management technology defined in Chapter 4 was applied to integrate the different functional modules (message handling, data management and document management) and, in particular, electronic data processing (EDP) on the mainframe with end user computing.

Keywords

Business Process Expert System Agency Director Current Account Area Manager 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

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