Predicting bank financial failures using neural networks, support vector machines and multivariate statistical methods: A comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey.
Melek Acar BoyaciogluYakup KaraÖmer Kaan BaykanPublished in: Expert Syst. Appl. (2009)
Keyphrases
- statistical methods
- banking industry
- neural network
- commercial banks
- support vector
- risk management
- learning machines
- statistical tests
- large margin classifiers
- return on investment
- statistical analysis
- banking services
- information technology
- computational methods
- money laundering
- financial services
- radial basis function
- risk factors
- machine learning methods
- machine learning
- internet banking
- credit risk
- statistical approaches
- biological data
- statistical models
- generalization ability
- kernel function
- fraud detection
- support vector machine
- artificial neural networks
- decision support system
- data mining techniques
- financial institutions
- risk analysis
- sample size
- feature selection
- database
- back propagation
- information retrieval
- statistical analyses
- portfolio selection
- financial data
- probability density function
- stock market
- environmental sciences
- regression model
- saudi arabia
- data sets
- driving forces
- stock price