Using decision tree to modeling a bad debt account taxation information system

Autor:	Kai-Chi Chuang, Ching-Hui Hsieh, Tian-Syung Lan, Ming-Chang Lee, Jian-Hua Qin
Rok vydání:	2019
Předmět:	Finance business.industry Creditor Decision tree learning Decision tree Debtor Bad debt Condensed Matter Physics Electronic Optical and Magnetic Materials Set (abstract data type) Hardware and Architecture Information model Information system Electrical and Electronic Engineering business
Zdroj:	Microsystem Technologies. 27:1805-1810
ISSN:	1432-1858 0946-7076
Popis:	How to reduce the ratios and liquidate the non-performing assets are considered as the important issues for financial institutions. The non-performing loans rations of financial institutions are overly high in Taiwan. In this study, the decision tree algorithm is used to set up an inquiring bad accounts’ taxation information model for financial institutions. The data used in this study is sourced from the essential of acceptance for creditor inquiring about the taxation information for debtor as released by the Financial Information center of Ministry of Finance. The well-known Decision Tree Approach is taken. In the end, it is discovered that inquiring about bad accounts’ taxation information for financial institutions could be categorized fast and efficiently by using decision tree algorithm. With this method, the financial institutions are capable to select those samples that are suitable for inquiring and achieving efficient management.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d04ece41aa6828138382ce24ef8b1ff6 https://doi.org/10.1007/s00542-019-04587-w Zobrazit plný text záznamu Full text from SpringerLink