A Microservice-Based Architecture for Real-Time Credit Card Fraud Detection with Observability

Robson S. Santos, Robesvânia Araújo, Paulo Rego, José M. da S. M. Filho, Jarélio G. da S. Filho, José D. C. Neto, Nicksson C. A. de Freitas, Emanuel Rodrigues, Francisco Gomes, Fernando Trinta

2025

Abstract

The growth of real-time financial transactions has increased the demand for scalable and transparent fraud detection systems. This paper presents a microservice-based architecture designed to detect credit card fraud in real time, integrating machine learning models with observability tools to monitor operational behavior. Built on OpenTelemetry (OTel), the architecture enables detailed tracking of performance metrics, resource usage, and system bottlenecks. Experiments conducted in a cloud-based environment demonstrate the scalability and efficiency of the solution under different workloads. Among the tested models, XGBoost outperformed Random Forest in throughput and latency, handling over 25,000 concurrent requests with response times under 50 ms. Compared to previous work focused solely on model accuracy, this study advances toward real-world applicability by combining fraud detection with runtime observability and elastic deployment. The solution is open-source and reproducible, and it contributes to the development of robust data-driven systems in the financial domain.

Paper Citation

in Harvard Style

Santos R., Araújo R., Rego P., Filho J., Filho J., Neto J., A. de Freitas N., Rodrigues E., Gomes F. and Trinta F. (2025). A Microservice-Based Architecture for Real-Time Credit Card Fraud Detection with Observability. In Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-758-0, SciTePress, pages 748-755. DOI: 10.5220/0013650000003967

in Bibtex Style

@conference{data25,
author={Robson Santos and Robesvânia Araújo and Paulo Rego and José Filho and Jarélio Filho and José Neto and Nicksson A. de Freitas and Emanuel Rodrigues and Francisco Gomes and Fernando Trinta},
title={A Microservice-Based Architecture for Real-Time Credit Card Fraud Detection with Observability},
booktitle={Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2025},
pages={748-755},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013650000003967},
isbn={978-989-758-758-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - A Microservice-Based Architecture for Real-Time Credit Card Fraud Detection with Observability
SN - 978-989-758-758-0
AU - Santos R.
AU - Araújo R.
AU - Rego P.
AU - Filho J.
AU - Filho J.
AU - Neto J.
AU - A. de Freitas N.
AU - Rodrigues E.
AU - Gomes F.
AU - Trinta F.
PY - 2025
SP - 748
EP - 755
DO - 10.5220/0013650000003967
PB - SciTePress