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 PROJECTTABLE OF CONTENTSIntroduction 1Purpose 1Source of Information 1Authorization 1Overview 2The First Steps 3Computer-Synthesized Senses 4Visual Recognition 4Current Research 5Computer-Aided Voice Recognition 6Current Applications 7Optical Character Recognition 8Conclusion 9Recommendations 10Bibiography 11INTRODUCTION 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" rules. The problem with this approach is that people dont always know why they do what they do. And even when they can express this knowledge, it is not easily transla...
