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Title |
Recognition of fraud in online banking by using confirmatory learning in neural network |
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Author |
Alireza Pouramirarsalani, Majid Khalilian, Alireza Nikravanshalmani |
| Citation |
Vol. 17 No. 8 pp. 280-284 |
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Abstract |
Nowadays, exploring knowledge from huge collections of data attracts many experts. Because of this matter, data mining is considered as one of the most efficient tool for analysis of data. Application of different techniques and algorithms of this tool in different areas like management of communication with customer, management and exploration of fraud, medical, sport etc. are evident for this claim and it is one of areas that can be considered as a field of data mining. In modern world, synchronous with advancement of information technology and communication infrastructures, banking systems and financial services also have developed. Banks and financial institutions try to present update and more efficient services and products by investing in modern technologies. Therefore, variety of products and related services and also number and proportional value of transactions are increased. In contrast with this advancement and development, immunization of transactions, identification of new ways of fraud and misuse of financial documents, exploration of performed frauds or in progress, identification and exploration of processes and money laundering operations are always the taut discussions in this field. This research introduces new approach for exploring fraud in online banking that has high speed in recognizing and predicting the fraud and automatically updated and completed. |
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Keywords |
recognition of fraud, online banking, confirmatory learning, neural network |
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