Application of Hybrid Method of Bagging and Case-Based Reasoning to Solve Small-Businesses' Credit Assessment Problems

作者：Dong Yanwen^*

来源：Information-An International Interdisciplinary Journal, 2011, 14(2): 399-409.

• Data Mining
• Bagging
• Case-Based Reasoning
• Credit Risk
• Credit Scoring

Credit risk is simply defined as the potential that counterparty will fail to meet its obligations in accordance with agreed terms. As almost all of models and methods for credit assessment published so far are based on financial data or stock price and investigation data provided by special inquiry agencies, it is difficult to apply them to assess credit of minor and small businesses that do not disclose financial information. We have proposed some new approaches to assess the customers' credit only based on daily transaction data such as sales, payments by customers, amount of overdue payment, etc. This paper proposes a credit assessment system using hybrid method of bagging and case-based reasoning. It aims to deal with the issue that the number of unsound customers is much less than that of healthy ones and improve the ability for identifying unsound customers. The architecture of the system is described by giving the procedure for generating multiple versions of a customer's credit assessment through case-based reasoning (CBR) and aggregating these to get a final assessment through a plurality vote. The performance and effectiveness of the proposed system is confirmed by applying it to the real problems of the company.

• 出版日期2011-2