The widespread usage of machine learning systems and econometric methods in the credit
domain has transformed the decision-making process for evaluating loan applications …

The proliferation of bibliometric review articles is a true reflection of how bibliometrics is
gaining popularity and has been widely adopted in various disciplines. The growing interest …

This literature review critically evaluates the fairness of credit scoring models concerning
mortgage accessibility for under-reserved populations. The review scrutinizes a diverse …

As the main demand side of rural financial services, farmers' cooperatives are an important
part of China's rural finance. However, due to the lack of effective collateral, farmers' …

This comprehensive paper delves into the role of data analytics in finance and mortgage
sectors, particularly its potential to alleviate the disparities faced by under-reserved …

This study empirically analyzes factors influencing the coupling and coordinated
development of rural urbanization and rural finance. For this purpose, the study employs the …

In contrast to human intelligence, which comes from innate knowledge, artificial intelligence
(AI) and big data refers to the mental capacity demonstrated by robots. AI has been …

Credit is considered as an essential tool to make informal labor's income better. In order to
improve quality of their life, the state should have some supports them in credit access. This …

The term Fairness is used in the field of Machine Learning to refer to a suite of evaluation
techniques, measures, and process adjustments focused on the reduction of bias in …

Machine learning algorithms are revolutionizing processes in all fields including; real-estate,
security, bioinformatics, and the financial industry. The loan approval process is one of the …