Using Python and Microservices for Real-Time Credit Risk Assessment in Embedded Lending Systems

• Author(s): Bolaji Iyanu Adekunle ; Samuel Owoade ; Ejielo Ogbuefi ; Oyejide Timothy Odofin ; Oluwademilade Aderemi Agboola; Oluwasanmi Segun Adanigbo
• Paper ID: 1708760
• Page: 369-381
• Published Date: 31-10-2021
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 4 October-2021

Abstract

This paper explores the integration of Python and microservices in developing a real-time credit risk assessment system for embedded lending platforms. Embedded lending systems require robust, scalable architectures capable of processing vast amounts of transactional and behavioral data to make timely lending decisions. By leveraging microservices, this study presents an approach that ensures modularity, scalability, and resilience in handling data across multiple services. Python, with its rich ecosystem of libraries and frameworks, is employed for data processing, machine learning model development, and API integration, facilitating real-time credit risk evaluations. The developed credit risk model combines traditional credit scoring methods with machine learning techniques, utilizing transactional data, alternative data sources, and continuous learning for more accurate risk assessments. Performance evaluations show that the system can process up to 10,000 transactions per minute with low latency, achieving an accuracy rate of 85% in predicting defaults. The findings highlight the potential of this approach to enhance financial inclusion, offering an efficient solution for assessing borrower risk in real-time. Future work will focus on optimizing machine learning models, expanding data sources, and adapting the system for global applications.

Keywords

Embedded Lending Systems, Real-Time Credit Risk Assessment, Python, Microservices Architecture, Machine Learning, Financial Inclusion

Citations

IRE Journals:
Bolaji Iyanu Adekunle , Samuel Owoade , Ejielo Ogbuefi , Oyejide Timothy Odofin , Oluwademilade Aderemi Agboola; Oluwasanmi Segun Adanigbo "Using Python and Microservices for Real-Time Credit Risk Assessment in Embedded Lending Systems" Iconic Research And Engineering Journals Volume 5 Issue 4 2021 Page 369-381

IEEE:
Bolaji Iyanu Adekunle , Samuel Owoade , Ejielo Ogbuefi , Oyejide Timothy Odofin , Oluwademilade Aderemi Agboola; Oluwasanmi Segun Adanigbo "Using Python and Microservices for Real-Time Credit Risk Assessment in Embedded Lending Systems" Iconic Research And Engineering Journals, 5(4)