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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21470
Article Published : 8508
Total Authors : 22383
Total Reviewer : 805
Total Countries : 157
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| Paper Title: | Online Fraud Detection On Loan Apps By Using Machine Learning And Deep Learning |
| Authors Name: | P.RAGHUVEER , M.RAJITHA , J.SRILEKHA , MD.AMEERSUHAIL , L.TEJASAIVARMA |
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IJRTI_189729
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| Published Paper Id: | IJRTI2404125 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Internet finance has become increasingly popular in recent years. However, bad debt has become a serious threat to internet financial companies. With the exponential growth of internet loan apps, ensuring security against fraudulent activities has become paramount. One approach to combat online fraud in internet loan apps is through the integration of machine learning (ML) and deep learning (DL) techniques. Traditional rule-based systems are often insufficient to detect sophisticated fraudulent behaviors. This approach employs a combination of traditional machine learning (ML) techniques such as Random Forest and Decision Trees, along with deep learning (DL) methodologies represented by Feedforward Neural Networks (FNN). In the context of burgeoning fraudulent activities in online lending platforms, a robust and adaptable detection system is imperative to ensure the security and trustworthiness of these applications. Extensive experimentation on real-world datasets obtained from internet loan apps demonstrates the efficacy of the proposed approach. Performance evaluation metrics such as precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC) attest to the superior detection capabilities of the hybrid model compared to standalone ML or DL approaches |
| Keywords: | Recognizing frauds, identifying fraud apps based on data, Decision tree, Random forest(Machine Learning), Feed Forward neural networks. |
| Cite Article: | "Online Fraud Detection On Loan Apps By Using Machine Learning And Deep Learning ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.902 - 909, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404125.pdf |
| Downloads: | 000205328 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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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Published Paper ID: IJRTI2404125
Registration ID:189729
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 902 - 909 Country: VIJAYAWADA, ANDHRAPRADESH, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2404125 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2404125 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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