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 …
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 …
Example-dependent cost-sensitive decision trees
Several real-world classification problems are example-dependent cost-sensitive in nature,
where the costs due to misclassification vary between examples. However, standard …
where the costs due to misclassification vary between examples. However, standard …
Multiple criteria decision aiding for finance: An updated bibliographic survey
Finance is a popular field for applied and methodological research involving multiple criteria
decision aiding (MCDA) techniques. In this study we present an up-to-date bibliographic …
decision aiding (MCDA) techniques. In this study we present an up-to-date bibliographic …
Computational approaches and data analytics in financial services: A literature review
The level of modeling sophistication in financial services has increased considerably over
the years. Nowadays, the complexity of financial problems and the vast amount of data …
the years. Nowadays, the complexity of financial problems and the vast amount of data …
[HTML][HTML] Multi-modal deep learning for credit rating prediction using text and numerical data streams
Knowing which factors are significant in credit rating assessments leads to better decision-
making. However, the focus of the literature thus far has been mostly on structured data, and …
making. However, the focus of the literature thus far has been mostly on structured data, and …
Multicriteria decision systems for financial problems
Financial decision making is involved with a plethora of important issues for individual and
institutional investors, managers of firms and organizations, as well as policy makers. The …
institutional investors, managers of firms and organizations, as well as policy makers. The …
[LLIBRE][B] Multicriteria analysis in finance
M Doumpos, C Zopounidis - 2014 - Springer
Since the 1970s, the field of finance has evolved rapidly, driven by the advances in
information technology and the introduction of financial innovations involving new financial …
information technology and the introduction of financial innovations involving new financial …
Decision‐making support for the evaluation of clustering algorithms based on MCDM
In many disciplines, the evaluation of algorithms for processing massive data is a
challenging research issue. However, different algorithms can produce different or even …
challenging research issue. However, different algorithms can produce different or even …
An academic review: applications of data mining techniques in finance industry
S Jadhav, H He, KW Jenkins - 2017 - dspace.lib.cranfield.ac.uk
With the development of Internet techniques, data volumes are doubling every two years,
faster than predicted by Moore's Law. Big Data Analytics becomes particularly important for …
faster than predicted by Moore's Law. Big Data Analytics becomes particularly important for …