Current neural network technology is the most progressive of the artificial intelligence Applications of neural networks have made the transition from laboratory curiosities to large, successful commercial applications. To enhance the security of automated financial transactions, current technologies in both speech recognition and handwriting recognition are likely ready for mass integration into financial institutions. RESEARCH PROJECT TABLE OF CONTENTS Introduction 1 Purpose 1 Source of Information 1 Authorization 1 Overview 2 The First Steps 3 Computer-Synthesized Senses 4 Visual Recognition 4 Current Research 5 Computer-Aided Voice Recognition 6 Current Applications 7 Optical Character Recognition 8 Conclusion 9 Recommendations 10 Bibliography 11 INTRODUCTION Purpose The purpose of this study is to determine additional areas where artificial intelligence technology may be applied for positive identifications of individuals during financial transactions, such as automated banking transactions, telephone transactions , and home banking activities. This study focuses on academic research in neural network technology . This study was funded by the Banking Commission in its effort to deter fraud. Overview Recently, the thrust of studies into practical applications for artificial intelligence have focused on exploiting the expectations of both expert systems and neural network computers. In the artificial intelligence community, the proponents of expert systems have approached the challenge of simulating intelligence differently than their counterpart proponents of neural networks. Expert systems contain the coded knowledge of a human expert in a field; this knowledge takes the form of "if-then"...
