Building the ensembles of credit scoring models
نویسندگان
چکیده
منابع مشابه
Building credit scoring models using genetic programming
Credit scoring models have been widely studied in the areas of statistics, machine learning, and artificial intelligence (AI). Many novel approaches such as artificial neural networks (ANNs), rough sets, or decision trees have been proposed to increase the accuracy of credit scoring models. Since an improvement in accuracy of a fraction of a percent might translate into significant savings, a m...
متن کاملCredit Risk Scoring Models
Credit scoring models play a fundamental role in the risk management practice at most banks. They are used to quantify credit risk at counterparty or transaction level in the different phases of the credit cycle (e.g. application, behavioural, collection models). The credit score empowers users to make quick decisions or even to automate decisions and this is extremely desirable when banks are ...
متن کاملExploring the behaviour of base classifiers in credit scoring ensembles
Many techniques have been proposed for credit risk assessment, from statistical models to artificial intelligence methods. During the last few years, different approaches to classifier ensembles have successfully been applied to credit scoring problems, demonstrating to be more accurate than single prediction models. However, it is still a question what base classifiers should be employed in ea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neuro-Fuzzy Modeling Techniques in Economics
سال: 2018
ISSN: 2415-3516,2306-3289
DOI: 10.33111/nfmte.2018.034