FRAUD DETECTION IN BANKING USING KNN (K-NEAREST NEIGHBOR) ALGORITHM

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Khodabakhshi Masoud; FARTASH MEHDI

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON RESEARCH IN SCIENCE AND TECHNOLOGY
Year:2016 | Issue:5

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Information Seminar Paper

Title

FRAUD DETECTION IN BANKING USING KNN (K-NEAREST NEIGHBOR) ALGORITHM

Author(s)

Khodabakhshi Masoud | FARTASH MEHDI | Issue Writer Certificate

Keywords

FRAUD DETECTION

ELECTRONIC BANKING

KNN ALGORITHM

ASSOCIATION RULES

Abstract

FINANCIAL ABUSES AND FRAUD IN TRANSACTION BANKING HAS BEEN INCREASED BECAUSE OF USING MODERN BANKING SYSTEM. THESE ABUSES LOSE SIGNIFICANT FINANCIAL RESOURCES AND DECREASE TRUST OF CUSTOMERS IN USE OF MODERN BANKING SYSTEM AND REDUCE EFFECTIVENESS OF THESE SYSTEMS IN OPTIMUM CAPITAL MANAGEMENT AND FINANCIAL TRANSACTIONS. ALTHOUGH THE BEST WAY TO REDUCE FRAUD IS PREVENTING FRAUD BUT THE FRAUDSTERS ACHIEVE THEIR GOALS IN SOME WAYS. SO WE NEED METHODS TO IDENTIFY SUSPICIOUS TRANSACTION. IN RECENT YEARS, DATA MINING TECHNIQUES HAVE BEEN ABLE TO SUCCESSFULLY PREVENT MONEY LAUNDERING AND DETECT CREDIT CARD FRAUD. IN THIS STUDY WE USED K-NEAREST NEIGHBOR TECHNIQUE WITH ASSOCIATION RULES TO IMPROVE ACCURACY OF ALGORITHMS FOR DETECTING OUTLIERS IN TRANSACTIONS WHICH IS USED IN CREDIT CARD IN ELECTRONIC BANKING SYSTEM. FINALLY, THE RESULTS OF PROPOSED METHOD IN TERMS OF ACCURACY AND SPEED HAVE BEEN COMPARED AND EVALUATED WITH OTHER METHODS.

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APA: Copy

Khodabakhshi, Masoud, & FARTASH, MEHDI. (2016). FRAUD DETECTION IN BANKING USING KNN (K-NEAREST NEIGHBOR) ALGORITHM. INTERNATIONAL CONFERENCE ON RESEARCH IN SCIENCE AND TECHNOLOGY. SID. https://sid.ir/paper/927674/en

Vancouver: Copy

Khodabakhshi Masoud, FARTASH MEHDI. FRAUD DETECTION IN BANKING USING KNN (K-NEAREST NEIGHBOR) ALGORITHM. 2016. Available from: https://sid.ir/paper/927674/en

IEEE: Copy

Masoud Khodabakhshi, and MEHDI FARTASH, “FRAUD DETECTION IN BANKING USING KNN (K-NEAREST NEIGHBOR) ALGORITHM,” presented at the INTERNATIONAL CONFERENCE ON RESEARCH IN SCIENCE AND TECHNOLOGY. 2016, [Online]. Available: https://sid.ir/paper/927674/en

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