Financial revolution: a systemic analysis of artificial intelligence and machine learning in the banking sector

Raúl Jáuregui-Velarde, Laberiano Andrade-Arenas, Pedro Molina-Velarde, Cesar Yactayo-Arias


This paper reviews the advances, challenges, and approaches of artificial intelligence (AI) and machine learning (ML) in the banking sector. The use of these technologies is accelerating in various industries, including banking. However, the literature on banking is scattered, making a global understanding difficult. This study reviewed the main approaches in terms of applications and algorithmic models, as well as the benefits and challenges associated with their implementation in banking, in addition to a bibliometric analysis of variables related to the distribution of publications and the most productive countries, as well as an analysis of the co-occurrence and dynamics of keywords. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework, forty articles were selected for review. The results indicate that these technologies are used in the banking sector for customer segmentation, credit risk analysis, recommendation, and fraud detection. It should be noted that credit analysis and fraud detection are the most implemented areas, using algorithms such as random forests (RF), decision trees (DT), support vector machines (SVM), and logistic regression (LR), among others. In addition, their use brings significant benefits for decision-making and optimizing banking operations. However, the handling of substantial amounts of data with these technologies poses ethical challenges.


Artificial intelligence; Banking sector; Ethical challenges; Fraud detection; Machine learning;

Full Text:



Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).