INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Credit card scam could be a genuine issue in budgetary administrations.Credit card scam may be a frame of a broader category of wrongdoing known as personality burglary, by which offenders utilize your individual data to mimic you and capture your funds. In expansion to credit card data, personality hoodlums can utilize qualification counting your title, date of birth, address and social security number to require over bank account, take out advances in your title, and apply for fake charge discounts, unemployment benefits and social security checks - taking advantages if benefits you’ve earned. One common sort of scam the company is when riders are paid through stolen credit cards behind each trick there’s a structure design that gets to be obvious in the event that you see near sufficient. Scam discovery may be a set of exercises that are taken to avoid cash or property from being gotten through false falsifications. Scam can be committed totally different ways and in numerous businesses. E-commerce and numerous other online locales have expanded the online installment modes, expanding the chance for online fakes. Increment in scam rates, analysts begun utilizing diverse machine learning strategies to identify and dissect fakes in online exchanges. Credit card scam for the most part happens when the card was stolen for any of the unapproved purposes or indeed when the fraudster employments the credit card data for his utilize.
Keywords:
Credit card scam, data science, applications of machine learning, artificial intelligence, automated scam detection.
Cite Article:
"Credit Card Scam Detection", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 5, page no.231-233, May-2022, Available :http://www.ijnrd.org/papers/IJNRDA001045.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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