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ABSTRACTCurrent neural network technology is the most progressive of the artificial intelligence systems today Applications of neural networks have made the transition from laboratory curiosities to large successful commercial applications To enhance the security ofautomated financial transactions current technologies in both speech recognition and handwriting recognition are likely ready for mass integration into financial institutionsRESEARCH 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 whereartificial intelligence technology may be applied for positive identifications of individualsduring financial transactions such as automated banking transactions telephonetransactions and home banking activities This study focuses on academic research in neuralnetwork technology This study was funded by the Banking Commission in its effort to deterfraudOverview Recently the thrust of studies into practical applications forartificial intelligence have focused on exploiting the expectations of both expert systems andneural network computers In the artificial intelligence community the proponents ofexpert systems have approached the challenge of simulating intelligence differentlythan their counterpart proponents of neural networks Expert systems contain the codedknowledge of a human expert in a field this knowledge takes the form of if-then rulesThe problem with this approach is that people dont always know why they do what they do Andeven when they can express this knowledge it is not easily translated into usable computer code Alsoexpert systems are usually bound by a rigid set of inflexible rules which do not changewith experience gained by trail and error In contrast neural networks are designed aroundthe structure of a biological model of the brain Neural networks are composed of simplecomponents called neurons each having simple tasks and simultaneouslycommunicating with each other by complex interconnections As Herb Brody states Neural networksdo not require an explicit
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