Artificial Inteligence

Essay by Anonymous UserA+, November 1995

download word file, 10 pages 3.9 2 reviews


Current 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 of automated

financial transactions, current technologies in both speech recognition and handwriting

recognition are likely ready for mass integration into financial institutions.



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

Bibiography 11


· 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.


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 don't always know why they do what they do. And even when they can express this

knowledge, it is not easily translated into usable computer code. Also, expert systems are

usually bound by a rigid set of inflexible rules which do not change with experience gained

by trail and error. In...