Approach To The Detection Of Financial Fraud In Credit Card Transactions Using Machine Learning

Authors

DOI:

https://doi.org/10.24054/face.v25i2.4029

Keywords:

measurement of economic activity, material and personal well-being, macroeconomic indicators, national accounting, machine learning

Abstract

Today's society presents various and quite adverse social and environmental situations. The application of social marketing is needed to raise individual and collective awareness in their resolution. The purpose of this research is to demonstrate the benefits of applying social marketing in promoting positive behavior for communities through various studies by non-profit institutions, the health sector, and the Autonomous University of Sinaloa (UAS). A comprehensive bibliographic review was conducted by various authors and the latest report from the UAS rector, which reflects the social work that the Rosalina house has been carrying out for more than 150 years. The application of social marketing is observed in non-profit organizations such as those in the District of Santa Marta, the health sector during the COVID-19 pandemic, and at the UAS, where it proved beneficial in solving social problems. The need to continue implementing social marketing in addressing social problems, protecting the environment, and in altruistic endeavors is evident, as well as in areas of opportunity to contribute to the well-being of young people, their families, workplaces, and communities.

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References

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Published

2025-06-03

How to Cite

Niño, C., & López, O. (2025). Approach To The Detection Of Financial Fraud In Credit Card Transactions Using Machine Learning. FACE: Revista De La Facultad De Ciencias Económicas Y Empresariales, 25(2), 217–225. https://doi.org/10.24054/face.v25i2.4029

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Artículos