Hidden Markov Model using transaction patterns for ATM card fraud detection
ATM card fraud is causing millions of naira in losses for the card payment business. The most accepted payment mode in today’s world is ATM card for online and regular purchasing; hence frauds related with it are also increasing. To find the fraudulent transaction, this study proposes a hidden Marko...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
General Association of Economists from Romania
2021-12-01
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| Series: | Theoretical and Applied Economics |
| Subjects: | |
| Online Access: |
http://store.ectap.ro/articole/1566.pdf
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| Summary: | ATM card fraud is causing millions of naira in losses for the card payment business. The
most accepted payment mode in today’s world is ATM card for online and regular purchasing;
hence frauds related with it are also increasing. To find the fraudulent transaction, this study
proposes a hidden Markov Model (HMM) based on the Poisson distribution (HMM[Pois]), the
generalized Poisson distribution (HMM[GenPois]), and the Gaussian distribution (HMM[Gauss])
with the forward-backward algorithm which detects the fraud by using customers spending
behavior. The proposed estimation procedure based upon the three distributions for the HMM model
is used to construct a sequence of operations in ATM card transaction processing, and detect fraud
by studying the normal spending behavior of a cardholder, followed by checking an incoming
transaction against spending behavior of the cardholder. If the transaction satisfies a predefined
threshold value, then the transaction is decided to be legitimate else, the transaction is declared as
fraudulent. The evaluation statistics used shows that the HMM[Gauss] is the most appropriate
model in detecting ATM card fraudulent transactions. |
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| ISSN: | 1841-8678 1844-0029 |