Paper Title
Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms
Article Identifiers
Registration ID: IJNRD_301238
Published ID: IJNRD2410137
: Click Here to Get
About Hard Copy and Transparent Peer Review Report
Keywords
Fraud detection, deep learning, machine learning, online fraud, credit card frauds, transaction data analysis.
Abstract
People could use credit cards to buy things online because they are handy and easy to use. As more people use credit cards, more people abuse them too. People who use stolen credit cards lose a lot of money, and so do banks and other financial institutions. The main goal of this research study is to find these frauds, such as those with a lot of false alarms, data that is open to the public, data that shows a big difference in class, and changes in the type of scam. There are several credit card recognition methods based on machine learning that have been written about. Think about the Extreme Learning Method, SVM, Random Forest, Decision Tree, XG Boost, and Logistic Regression. State-of-the-art deep learning algorithms are as yet expected to limit fake consumptions in light of their poor accuracy. Utilizing the latest deep learning strategies has been the objective. Machine learning and deep learning theories were differentiated to come by great results. The whole scientific stealing research uses the European Card Benchmark sample. First, the information was put through a machine learning method, which helped find frauds to some degree. In the end, three designs based on convolutional neural networks are used to make scam detection work better. By adding more levels, the accuracy of recognition went up by a large amount. A full observational study was carried out using the most up-to-date models and changing the number of secret layers and epochs. By looking at the study work, we can see that the results got better. The accuracy went up to 99.9%, the f1-score went up to 85.71%, the precision went up to 98%, and the AUC curves had ideal values of 93%, 98%, 85.71%, and 99.9%. The suggested model does a better job of recognizing credit cards than modern machine learning and deep learning methods. We also tried using deep learning and adjusting the data to get the false negative rate down. There are good ways to spot credit card theft in the real world that are being shown.
Downloads
How To Cite (APA)
PAMPANA GNANA VENKATA SAl, DR.P. SRINIVASULU, & TULASI RAJU NETHALA (October-2024). Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(10), b310-b318. https://ijnrd.org/papers/IJNRD2410137.pdf
Issue
Volume 9 Issue 10, October-2024
Pages : b310-b318
Other Publication Details
Paper Reg. ID: IJNRD_301238
Published Paper Id: IJNRD2410137
Research Area: Science and Technology
Author Type: Indian Author
Country: West Godavari , Andhra Pradesh , India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2410137.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2410137
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
UGC CARE JOURNAL PUBLICATION | ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International UGC CARE JOURNAL PUBLICATION, Low Cost, Scholarly Open Access, 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
Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG
Copyright & License
© 2026 - Authors hold the copyright of this article. This work is licensed under a Creative Commons Attribution 4.0 International License. and The Open Definition.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0).
🛡️ Disclaimer: The content, data, and findings in this article are based on the authors’ research and have been peer-reviewed for academic purposes only. Readers are advised to verify all information before practical or commercial use.
The journal and its editorial board are not liable for any errors, losses, or consequences arising from its use.
Publication Timeline
Article Preview: View Full Paper
Call For Paper
IJNRD is a Scholarly Open Access, Peer-Reviewed, Refereed, and UGC CARE Journal Publication with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost, and Transparent Peer Review Journal Publication that adheres to the New UGC CARE Transparent Peer-Reviewed Journal Policy and aligns with Scopus Journal Publication standards to ensure the highest level of research quality and credibility.
IJNRD offers comprehensive Journal Publication Services including indexing in all major databases and metadata repositories, Digital Object Identifier (Crossref DOI) assignment for each published article with additional fees, citation generation tools, and full Open Access visibility to enhance global research reach and citation impact.
The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse academic and professional fields. The journal promotes global knowledge exchange among researchers, developers, academicians, engineers, and practitioners, serving as a trusted platform for innovative, peer-reviewed journal publication and scientific collaboration.
Indexing Coverage: Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many other recognized academic repositories.
Transparent Peer Review Journal Publication: IJNRD operates a strict double-blind peer review system managed by 3000+ expert reviewers, ensuring ethical, unbiased, and high-quality review for every research paper.
For Indian Authors : Get a transparent peer review report from Scholar9.com for just ₹1000. View Sample Report
For Foreign Authors : A detailed peer review report is available through Scholar9.com for $20 USD. View Sample Report
Transparent Peer Review Journal Publication
⭐ Transparent Peer Review | 🕵️♂️ Double-Blind | 👨🏫 3000+ Expert Reviewers | 🇮🇳 Report for India Author ₹1000 | 🌐 Report for Foreign Author $20 | 📄 Sample Reports on Scholar9.com | 🌍 High Credibility | ⚖️ Ethical & Unbiased Evaluation
How to submit the paper?
By Our website
Click Here to Submit Paper Online
Recently, the UGC discontinued the UGC-CARE Journal List and introduced new parameters that allow publication in Transparent Peer-Reviewed (Refereed) Journals. IJNRD is Transparent Peer Review Journal Valid As per New UGC Notification.
You can now publish your research paper in IJNRD.ORG. IJNRD is a Transparent Peer-Reviewed Open Access (Refereed Journal), UGC and UGC CARE Approved, Crossref DOI, Multidisciplinary, Impact Factor calculate by Google Scholar. As an International, open-access, and online journal, Publishing with us ensures wider reach, academic credibility, and enhanced recognition for your work.
For more details, refer to the official notice: UGC Public Notice
⭐ Low Cost ₹1570 | 📚 UGC CARE Approved | 🔍 Peer-Reviewed | 🌐 Open Access | 🔗 Crossref DOI & Global Indexing | 📊 Google Scholar Impact Factor | 🧪 Multidisciplinary
Submit Paper Online Call for Paper About IJNRD UGC CARE Approval
Important Dates for Current issue
Paper Submission Open For: May 2026
Current Issue: Volume 11 | Issue 5 | May 2026
Impact Factor: 8.76
Last Date for Paper Submission: Till 30-Jun-2026
Notification of Review Result: Transparent peer review process - your paper is evaluated by experts, and you receive acceptance or rejection updates via email and SMS.
Publication of Paper: Once all documents are submitted, your paper is published without delay, and you can instantly download your certificate and confirmation letter online.
Frequency: Monthly (12 issue Annually).
Journal Type: IJNRD is an international open-access journal offering Low Cost Journal Publication, transparent Peer Review Journal Publication, Crossref DOI, and multidisciplinary research visibility under UGC CARE Approved Journal Publication.
Subject Category: Research Area
Approval, Licenses and Indexing: More Details
Call For Paper - Volume 11 | Issue 5 | May 2026
IJNRD.org offers low-cost journal publication starting at ₹1570 with UGC CARE Approved, refereed, peer-reviewed, open-access publishing. This multidisciplinary monthly journal, available in both online and print formats, features a strong Google Scholar-based impact factor of 8.76, Transparent Peer Review, CrossRef DOI, global indexing, fast publication, and complete metadata for maximum research visibility and citation impact across multidisciplinary domains.
Volume 11 | Issue 5 | May 2026 | IJNRD Transparent Peer Review Certificate | Submit Paper Online
⭐ UGC CARE Approved Refereed Journal | 🔍 Transparent Peer Review | 🌐 Open Access Publishing | 💰 Low-Cost ₹1570 | 🔗 CrossRef DOI & Global Indexing | 📊 Google Scholar Impact Factor 8.76 | 🧪 Multidisciplinary | Online & Print
Submit Paper Online
