S10_Credit_Answer

S10_Credit_Answer - transactions. Neural network:- yes,...

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Session 10, Credit Co., Answer Guide For each intelligent system listed in the text [expert system, natural language processing, neural network, fuzzy logic], indicate whether it would or would not be suitable for the company to help combat (or to help identify) credit card fraud. What other types of systems could be usable to prevent or detect credit card fraud? How? Justify your answers. Source, text, section 9.5. Expert System: - yes, this system might be suitable. An expert system learns from experience. The company could load into the system past fraudulent transactions, and the characteristics of those transactions. An exception reporting system could be used to identify large transactions and have the expert system indicate whether they might be fraudulent transactions. Natural language processing and voice technologies: - no, not suitable. These systems are primarily used for processing input or output, not for analyzing
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Unformatted text preview: transactions. Neural network:- yes, definitely suitable. Neural networks are programmed to learn from past history, and so would be very good at examining past patterns of transactions by customer to determine whether there are any transactions that appear to be fraudulent. Fuzzy logic:- no, not suitable. These systems simulate human reasoning, and are designed to have computers behave less precisely. To identify potential fraud transactions, the computer systems need to be specific in identifying the potentially fraudulent transactions. Other suitables:- most types of information systems that we have discussed could be suitable, for example an MIS system could provide exception reports, a DSS could use statistical analysis to identify potential at risk transactions...
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This note was uploaded on 04/11/2011 for the course ADMS 2511 taught by Professor Jiu during the Spring '09 term at York University.

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