Extensions of the external validation for checking learned model interpretability and generalizability
We discuss the validation of machine learning models, which is standard practice in
determining model efficacy and generalizability. We argue that internal validation …
determining model efficacy and generalizability. We argue that internal validation …
Information gain directed genetic algorithm wrapper feature selection for credit rating
S Jadhav, H He, K Jenkins - Applied Soft Computing, 2018 - Elsevier
Financial credit scoring is one of the most crucial processes in the finance industry sector to
be able to assess the credit-worthiness of individuals and enterprises. Various statistics …
be able to assess the credit-worthiness of individuals and enterprises. Various statistics …
Mining corporate annual reports for intelligent detection of financial statement fraud–A comparative study of machine learning methods
P Hajek, R Henriques - Knowledge-Based Systems, 2017 - Elsevier
Financial statement fraud has been serious concern for investors, audit firms, government
regulators, and other capital market stakeholders. Intelligent financial statement fraud …
regulators, and other capital market stakeholders. Intelligent financial statement fraud …
Machine learning for financial risk management: a survey
Financial risk management avoids losses and maximizes profits, and hence is vital to most
businesses. As the task relies heavily on information-driven decision making, machine …
businesses. As the task relies heavily on information-driven decision making, machine …
Two-stage consumer credit risk modelling using heterogeneous ensemble learning
M Papouskova, P Hajek - Decision support systems, 2019 - Elsevier
Modelling consumer credit risk is a crucial task for banks and non-bank financial institutions
to support decision-making on granting loans. To model the overall credit risk of a consumer …
to support decision-making on granting loans. To model the overall credit risk of a consumer …
Applications of artificial intelligence and Machine learning-based supervisory technology in financial Markets surveillance: A review of literature
S Maheshwari, NN Chatnani - FIIB Business Review, 2023 - journals.sagepub.com
Supervisory Technology (SupTech) combines artificial intelligence (AI) with machine
learning (ML) for the specific purpose of supervision of the financial markets. SupTech offers …
learning (ML) for the specific purpose of supervision of the financial markets. SupTech offers …
A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in …
G Yao, X Hu, G Wang - Expert Systems with Applications, 2022 - Elsevier
Enterprise credit risk prediction in the supply chain context is an important step for decision
making and early credit crisis warnings. Improving the prediction performance of this task is …
making and early credit crisis warnings. Improving the prediction performance of this task is …
Loan default prediction by combining soft information extracted from descriptive text in online peer-to-peer lending
Predicting whether a borrower will default on a loan is of significant concern to platforms and
investors in online peer-to-peer (P2P) lending. Because the data types online platforms use …
investors in online peer-to-peer (P2P) lending. Because the data types online platforms use …
The effect of feature selection on financial distress prediction
D Liang, CF Tsai, HT Wu - Knowledge-Based Systems, 2015 - Elsevier
Financial distress prediction is always important for financial institutions in order for them to
assess the financial health of enterprises and individuals. Bankruptcy prediction and credit …
assess the financial health of enterprises and individuals. Bankruptcy prediction and credit …
A comparative study of forecasting corporate credit ratings using neural networks, support vector machines, and decision trees
P Golbayani, I Florescu, R Chatterjee - The North American Journal of …, 2020 - Elsevier
Credit ratings are one of the primary keys that reflect the level of riskiness and reliability of
corporations to meet their financial obligations. Rating agencies tend to take extended …
corporations to meet their financial obligations. Rating agencies tend to take extended …