[HTML][HTML] Operational research and artificial intelligence methods in banking
Banking is a popular topic for empirical and methodological research that applies
operational research (OR) and artificial intelligence (AI) methods. This article provides a …
operational research (OR) and artificial intelligence (AI) methods. This article provides a …
Machine learning in energy economics and finance: A review
Abstract Machine learning (ML) is generating new opportunities for innovative research in
energy economics and finance. We critically review the burgeoning literature dedicated to …
energy economics and finance. We critically review the burgeoning literature dedicated to …
Artificial intelligence for decision support systems in the field of operations research: review and future scope of research
S Gupta, S Modgil, S Bhattacharyya, I Bose - Annals of Operations …, 2022 - Springer
Operations research (OR) has been at the core of decision making since World War II, and
today, business interactions on different platforms have changed business dynamics …
today, business interactions on different platforms have changed business dynamics …
Deep learning for credit scoring: Do or don't?
Developing accurate analytical credit scoring models has become a major focus for financial
institutions. For this purpose, numerous classification algorithms have been proposed for …
institutions. For this purpose, numerous classification algorithms have been proposed for …
[HTML][HTML] Interpretable machine learning for imbalanced credit scoring datasets
The class imbalance problem is common in the credit scoring domain, as the number of
defaulters is usually much less than the number of non-defaulters. To date, research on …
defaulters is usually much less than the number of non-defaulters. To date, research on …
Instance-based credit risk assessment for investment decisions in P2P lending
Recent years have witnessed increased attention on peer-to-peer (P2P) lending, which
provides an alternative way of financing without the involvement of traditional financial …
provides an alternative way of financing without the involvement of traditional financial …
Classification methods applied to credit scoring: Systematic review and overall comparison
The need for controlling and effectively managing credit risk has led financial institutions to
excel in improving techniques designed for this purpose, resulting in the development of …
excel in improving techniques designed for this purpose, resulting in the development of …
Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods
Credit risk assessment is a crucial element in credit risk management. With the extensive
research on consumer credit risk assessment in recent decades, the abundance of literature …
research on consumer credit risk assessment in recent decades, the abundance of literature …
A novel dynamic credit risk evaluation method using data envelopment analysis with common weights and combination of multi-attribute decision-making methods
Credit risk evaluation is always the most important factor in determining Customers' credit
status in financial institutions. Multi-Attribute Decision-Making (MADM) methods have been …
status in financial institutions. Multi-Attribute Decision-Making (MADM) methods have been …
A dynamic credit risk assessment model with data mining techniques: evidence from Iranian banks
S Moradi, F Mokhatab Rafiei - Financial Innovation, 2019 - Springer
Giving loans and issuing credit cards are two of the main concerns of banks in that they
include the risks of non-payment. According to the Basel 2 guidelines, banks need to …
include the risks of non-payment. According to the Basel 2 guidelines, banks need to …