A Review of Contribution and Challenge in Predictive Machine Learning Model at Financial Industry. Issue 3 (March 2020)

• Record Type: Journal Article
• Authors: Hermadi, Irman; Nurhadryani, Yani; Ranggadara, Indra; Amin, Ruhul
• Is Part Of: Journal of physics. Volume 1477:Issue 3(2020)
• Publication Date: 2020-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1477/3/032021
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Prediction is essential one of them in the financial industry, with the prediction of this industry to be confident in determining the next steps to develop business. In the era of developing technology now, the application of machine learning to help the industry is essential, not only helps to count alone but can also help industry players to be able to predict in cases faced in the industry. In Machine Learning, financial industry players can create a credit risk analysis model based on available alternative data so that they can better manage overall risk. In this study aims to provide information on the contribution and challenges of machine learning in the financial industry and generate information on how the contributions and challenges in the application of machine learning have compiled from other researchers.