College of Computer Science and Mathematics, University of Kufa discussed a master dissertation on the factors influencing the use of mobile banking services based on machine learning algorithms by the postgraduate student, Mr. Walaa Hakim Hashim.

The dissertation aimed at enhancing the use of mobile banking services by analyzing customer behavior, trust factors and technological barriers.

The dissertation reviewed integrating demographic factors and customer perspectives using statistical tools and machine learning algorithms to identify the key factors influencing the adoption of these services.

The dissertation highlighted that perceived risk, ease of use, and customer trust play a fundamental role in mobile banking adoption, among the machine learning algorithms tested, the SVM algorithm achieved the highest accuracy of 89%, compared to the NB and KNN algorithms.

The dissertation recommended providing strategic insights to financial institutions on how to enhance mobile banking services by addressing challenges related to infrastructure and digital culture, while also proposing innovative solutions to improve the user experience and expand the adoption of these services in Iraq.