A comparison of the performance of alternative Machine Learning algorithms on a credit risk dataset

2021 ◽  
Author(s):  
Roberto Torresetti
Keyword(s):  
Machine Learning ◽  
Credit Risk ◽  
Learning Algorithms ◽  
Machine Learning Algorithms

scholarly journals Research on the Application of Machine Learning Algorithms in Credit Risk Assessment of Minor Enterprises

CONVERTER ◽  
2021 ◽  
pp. 696-706
Author(s):  
Huichao Mi
Keyword(s):  
Machine Learning ◽  
Credit Risk ◽  
Industrial Development ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Small Scale ◽  
Scale Data

Under the influence of COVID-19, minor enterprises, especially the manufacturing industry, are facing greater financial pressure and the possibility of non-performing loans is increasing. It is very important for financial institutions to reduce financial risks while providing financial support for minor enterprises to promote industrial development and economic recovery. In order to understand the function of machine learning algorithms in predicting enterprise credit risk, the research designs five models, including Logistic Regression, Decision Tree, Naïve Bayesian, Support Vector Machine and Deep Neural Network, and adopts SMOTE and Undersampling to process imbalanced data. Experiments show that machine learning algorithms have high accuracy for both large-scale data and small-scale data.

An Empirical Study on Loan Default Prediction Models

2019 ◽  
Vol 16 (8) ◽  
pp. 3483-3488
Author(s):  
Uzair Aslam ◽  
Hafiz Ilyas Tariq Aziz ◽  
Asim Sohail ◽  
Nowshath Kadhar Batcha
Keyword(s):  
Machine Learning ◽  
Credit Risk ◽  
Prediction Models ◽  
Historical Data ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Loan Default ◽  
Default Prediction ◽  
The World ◽  
Credit Scores

Loan lending has been playing a significant role in the financial world throughout the years. Although it is quite profitable and beneficial for both the lenders and the borrowers. It does, however, carry a great risk, which in the domain of loan lending is referred to as Credit risk. Industry experts and Researchers around the world assign individuals with numerical scores known as credit scores to measure the risk and their creditworthiness. Throughout the years machine learning algorithms have been used to calculate and predict credit risk by evaluating an individual’s historical data. This study reviews the present literature on models predicting risk assessment that use machine learning algorithms.

Credit Risk Assessment Using Machine Learning Algorithms

2017 ◽  
Vol 23 (4) ◽  
pp. 3649-3653 ◽  
Author(s):  
Girija V. Attigeri ◽  
M. M. Manohara Pai ◽  
Radhika M Pai
Keyword(s):  
Machine Learning ◽  
Risk Assessment ◽  
Credit Risk ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Credit Risk Assessment
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