INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
The banking zone is the maximum important area in our generation, in which almost absolutely everyone offers with the bank both bodily or online. In relationships with banks, clients and banks provide the possibility to fall into the entice of fraud. Examples of fraud include coverage fraud, credit score card fraud, account fraud, and many others. Therefore, fraud detection is a essential pastime to control these costs. This paper discusses financial institution fraud detection using gadget studying techniques; affiliation, linkage, prediction and type to analyze patron information to pick out styles that could result in fraud. Once the styles are identified, a better stage of verification/authentication can be introduced to banking procedures.
Keywords:
Bank Fraud, Machine Learning, Decision Tree, Credit Score Fraud.
Cite Article:
"Bank Fraud Detection Using Machine Learning Algorithm", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.948 - 953, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304161.pdf
Downloads:
000338719
Publication Details:
Published Paper ID: IJSDR2304161
Registration ID:205271
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 948 - 953
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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