Safety and Soundness and Compliance Issues on Credit Scoring Models
ثبت نشده
چکیده
Credit scoring models, or score cards, can contribute to bank safety and soundness as long as bank management actively participates in the development, implementation, monitoring, and validation of the model. Operational factors, such as accurate implementation of the credit scoring model and adequate training of data input staff, also can have an impact on the effectiveness of models. Changes in the environment in which a bank operates can affect the predictive ability of a credit scoring model over time. For all these reasons, a credit scoring model's performance must be analyzed regularly. This section describes several issues on which examiners and bank management should focus to ensure effective use of scoring models.
منابع مشابه
Investigating the missing data effect on credit scoring rule based models: The case of an Iranian bank
Credit risk management is a process in which banks estimate probability of default (PD) for each loan applicant. Data sets of previous loan applicants are built by gathering their data, and these internal data sets are usually completed using external credit bureau’s data and finally used for estimating PD in banks. There is also a continuous interest for bank to use rule based classifiers to b...
متن کاملE-banking and Soundness Indicators for the Banking Network of Iran
Development of E-banking has modified the structure of banking business and banking performance, efficiency, risk and challenges which have also been articulately recognized based on the international best practices. E-banking brazenly expedites and streamlines financial transactions via enhancing technology and expanding the bank services in comparison with conventional banking. Accordingly, o...
متن کاملImproved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm With New Validity measure and application to Credit Scoring
In data mining, clustering is one of the important issues for separation and classification with groups like unsupervised data. In this paper, an attempt has been made to improve and optimize the application of clustering heuristic methods such as Genetic, PSO algorithm, Artificial bee colony algorithm, Harmony Search algorithm and Differential Evolution on the unlabeled data of an Iranian bank...
متن کاملMatrix Sequential Hybrid Credit Scorecard Based on Logistic Regression and Clustering
The Basel II Accord pointed out benefits of credit risk management through internal models to estimate Probability of Default (PD). Banks use default predictions to estimate the loan applicants’ PD. However, in practice, PD is not useful and banks applied credit scorecards for their decision making process. Also the competitive pressures in lending industry forced banks to use profit scorecards...
متن کاملCredit scoring in banks and financial institutions via data mining techniques: A literature review
This paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in Credit scoring. Yet there isn’t any literature in the field of data mining applications in credit scoring. Using a novel research approach, this paper investigates academic and systematic literature review and includes all of the journals in the Science direct onli...
متن کامل