stomers, neural networks are still in the simple pattern matching stages and will need more development before commercially acceptable products are available. Speech recognition, on the other hand, is already a huge industry with customers ranging from individual computer users to international telephone companies. For security, voice recognition could be an added link to the chain of pre-established systems. For example, automated account inquiry, by telephone, is a popular method for customers to determine the status of existing accounts. With voice identification of customers, an option could be added for a customer to request account transactions and payments to other institutions. For credit card fraud detection, banks have relied on computers to identify suspicious transactions. In fraud detection, these programs look for sudden changes in spending patterns such as large cash withdrawals or erratic spending. The drawback to this approach is that there are more accounts flagged for possible fraud than there are investigators. The number of flags could be dramatically reduced with optical character recognition to help focus investigative efforts. It is expected that the upcoming neural network chips and add-on boards from Intel will add blinding speed to the current network software. These systems will even further reduce losses due to fraud by enabling more data to be processed more quickly and with greater accuracy.Recommendations Breakthroughs in neural network technology have already created many new applications in financial transaction security. Currently, neural network applications focus on processing data such as loan applications, and flagging possible loan risks. As computer hardware speed increases and as neural networks get smarter, "real-time" neural network applications should become a reality. "Real-time" processing means the network processes t...
