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This study Paper has problems using formatting ABSTRACT Current neural network technology is the most innovative of their artificial intelligence technologies today. Applications of neural networks have made the transition from laboratory curiosities into big, successful industrial applications. To enhance the safety of automated financial transactions, current technologies in both speech recognition and handwriting recognition are likely prepared for mass integration to financial institutions. RESEARCH PROJECT TABLE OF CONTENTS Intro 1 Purpose 1 Supply of Info 1 Authorization 1 Overview 2 T he First Measures 3 Computer-Synthesized Senses 4 Visible Recognition 4 Current Research 5 Computer-Aided Voice Recognition 6 Present Applications 7 Optical Character Recognition 8 Conclusion 9 Recommendations 10 Bibiography 11 I NTRODUCTION В· Goal The purpose of this research is to determine additional areas where artificial intelligence technologies may be employed for positive identifications of individuals during financial transactions, including automatic banking transactions, telephone trades, and household banking tasks. This analysis concentrates on academic research in neural networking technology. This analysis was financed 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 hopes of the expert systems and neural network servers. From the artificial intelligence community, the proponents of expert systems have approached the challenge of simulating intelligence otherwise compared to their counterpart proponents of neural networks. Expert methods contain the coded knowledge of a human expert in a field; this understanding takes the form of "if-then" rules. The issue with this strategy is that people donвЂ™t necessarily know why they do what they do. And even if they can express this understanding, it is not easily translated into usable computer code. Also, specialist systems are often bound by a rigid set of rigid rules which do not change with experience obtained by trail and error. By comparison, neural networks are made around the construction of a biological version of the mind. Neural networks are made up of simple components called "neurons" every having simple tasks, and simultaneously communi...