Machine Learning Anti-Fraud Detection Model for Internet Loans

S. Aslam Shareef, Kuruva Akhila, Benakala Likhitha, Bobbala Anusha, Gundala Likitha

2025

Abstract

The rise of digital lending platforms has further exacerbated fraudulent activities, making fraud detection a prominent challenge in financial services. The proposed solution is a machine learning-based system that detects and prevents fraud in loan applications in the case of internet-based loan services. Using supervised learning algorithms such as Random Forest, Support Vector Machines (SVM), and Neural Networks, the system analyses borrower profiles, transaction history, and behavioural patterns. The model learns from historical data, allowing it to effectively separate valid applicants from potential fraudsters based on characteristics like credit history, stable income, and loan payment records.Feature engineering techniques and ensemble learning methods are used to improve accuracy, minimizing false positives while increasing fraud detection performance. The real-world financial datasets are used to train and validate the system and the high precision and recall on the detection of suspicious loan requests is achieved. Moreover, these capabilities are accessible in real time via an APIbased integration with online lending platforms for automated risk assessment and fraud alerts.By effectively predicting fraud, this model minimizes financial risks for lenders and allows for better decision-making, while providing a high level of security for digital loans. This includes adapting strategies to incorporate advanced machine learning methods, along with responsive models that can adjust to new behaviours and patterns in fraud as it evolves.

Paper Citation

in Harvard Style

Shareef S., Akhila K., Likhitha B., Anusha B. and Likitha G. (2025). Machine Learning Anti-Fraud Detection Model for Internet Loans. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 271-277. DOI: 10.5220/0013911700004919

in Bibtex Style

@conference{icrdicct`2525,
author={S. Shareef and Kuruva Akhila and Benakala Likhitha and Bobbala Anusha and Gundala Likitha},
title={Machine Learning Anti-Fraud Detection Model for Internet Loans},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={271-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013911700004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Machine Learning Anti-Fraud Detection Model for Internet Loans
SN - 978-989-758-777-1
AU - Shareef S.
AU - Akhila K.
AU - Likhitha B.
AU - Anusha B.
AU - Likitha G.
PY - 2025
SP - 271
EP - 277
DO - 10.5220/0013911700004919
PB - SciTePress