Predictive Analytics for Digital Transactions

Sasikala C., Anil Kumar Bandi, Ambica Cheluru, Aswartha Reddy Settipi, Durga Bhavani Vanka, Tarun Kumar Reddy Peram

2025

Abstract

In the domain of monetary misrepresentation location, accomplishing harmony among straightforwardness and security is basic. Conventional methodologies frequently neglect to give both elevated degrees of exactness and clear, justifiable clarifications for navigation, all while safeguarding delicate information. They attempt to uncover the solutions that United Learning (FL) and Reasonable Computer-based Intelligence (XAI) provide on these particular challenges. Financial institutions utilizing quantitative predictions must deeply trust their models, and XAI provides models for them. However, Unified Learning considers the construction of AI models to a collection of dispersed data sources where sensitive financial data is properly siloed. In detail, this study looks at how different algorithms, which include Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), Decision Trees, Random Forests, and Support Vector Machines, are utilized in fraud detection tasks and how these algorithms are integrated into the multi-task learning framework. In addition, the study investigates fusion methods for models such as Stochastic Gradient Descent (SGD) and its variants. This study investigates how financial institutions could enhance fraud detection systems while ensuring transparency, confidentiality, and compliance with data protection laws by integrating the best of both XAI and FL worlds.

Paper Citation

in Harvard Style

C. S., Bandi A., Cheluru A., Settipi A., Vanka D. and Peram T. (2025). Predictive Analytics for Digital Transactions. 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 56-61. DOI: 10.5220/0013922500004919

in Bibtex Style

@conference{icrdicct`2525,
author={Sasikala C. and Anil Bandi and Ambica Cheluru and Aswartha Settipi and Durga Vanka and Tarun Peram},
title={Predictive Analytics for Digital Transactions},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={56-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013922500004919},
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 - Predictive Analytics for Digital Transactions
SN - 978-989-758-777-1
AU - C. S.
AU - Bandi A.
AU - Cheluru A.
AU - Settipi A.
AU - Vanka D.
AU - Peram T.
PY - 2025
SP - 56
EP - 61
DO - 10.5220/0013922500004919
PB - SciTePress