Bank Credit Risk Management Using Machine Learning Algorithms


  • Rajesh Kumar Hamdard University Karchi,Pakistan
  • Kapeel Dev Sindh Univeristy Jamshoro,Pakistan
  • Muhammad Ali Shaikh Mehran University of Engineering and Technology, Jamshoro 76020,Pakistan
  • Aftab Ul Nabi Ilma Univeristy Karachi,Pakistan
  • Tahreem Fatima Bahria Univeristy Karachi,Pakistan


Type — Machine learning, SVM, Credit Risk Software Development, Neural Networks, Support Vector Machines


Prior PCs was simply sorted as a need of an individual yet now it turns into a need of a person. AI fills in as a significant part in field of PC. Machine can't thoroughly consider various circumstances however it can draw diverse kind of connections between various highlights and qualities. The significant piece of our life is to stay away from false exercises yet till now we can't authority over it. Credit business is one of the significant organizations of business banks. Deceitful exercises can be handle through installing AI calculations in our everyday life. In this venture we will utilize directed AI and for that we need to give named information to the AI calculation. This paper centers around anticipating SME client status for time of a half year by using application scoring extra to client conduct highlights. By using Neural Networks, Support Vector Machines and Inclination Boosting, execution examination and furthermore highlight investigation for client conduct are directed.


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How to Cite

Kumar, R. ., Dev, K. ., Shaikh , M. A. ., Ul Nabi, A. ., & Fatima, T. . (2020). Bank Credit Risk Management Using Machine Learning Algorithms . International Journal of Computer (IJC), 38(1), 164–172. Retrieved from