Fraud Detection On Event Log Of Credit Business Using Hidden Markov Model Algorithm

Abstract

Illegal instances of banks have ascended by 55% of every 2016. One reason is the misrepresentation in business forms can't be distinguished early. Reacting to that issue, this exploration proposes a strategy for identifying extortion on business forms in the bank credit application. This technique utilizes Hidden Markov Models and action data recorded in the occasion log. Concealed Markov Model that utilized for ascertaining likelihood plausibility of extortion in view of the occasion log. The outcomes demonstrate that HMM strategy can identify extortion properly. Hidden Markov Model that used for calculating probability possibility of fraud based on the event log. The results show that HMM method can detect fraud appropriately. The experimental results also show that the accuracy of the results is 96%.

Authors and Affiliations

Shilpa. Mukthapuram, Dr. J. Narayan Singh, Shivaraj Kumar

Keywords

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  • EP ID EP399145
  • DOI -
  • Views 75
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How To Cite

Shilpa. Mukthapuram, Dr. J. Narayan Singh, Shivaraj Kumar (2018). Fraud Detection On Event Log Of Credit Business Using Hidden Markov Model Algorithm. International Journal of Humanities and Social Science Invention, 7(6), 64-68. https://europub.co.uk./articles/-A-399145