A banker's use of simulation and artificial intelligence for assessing the economics of electronic money networks

Abstract

This research paper demonstrates how discrete event simulation and artificial intelligence lend insight and decision support to American bankers who are operating or planning to operate local EFT (electronic fund transfer) networks. The key to making good EFT decisions is understanding the trade-offs between the costs and performance of different network possibilities. Being able to explore the suitability and effectiveness of choices prior to the actual commitment of resources is essential in assessing the economics of a particular EFT network. The simulation process described here illustrates a computer model that approximates the performance and economics of alternative local EFT designs. An aspect of Artificial Intelligence technology is incorporated to allow bankers the convenience of interacting with the model in a natural language format.