A STUDY OF APPLYING BUSINESS INTELLIGENCE TO CUSTOMER CREDIT RISK MANAGEMENT - AN EXAMPLE ON N COMPANY

• Main Authors: Sheng-Lin Tseng, 曾勝麟
• Other Authors: Huei-Huang Chen
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/93370677447131663383

碩士 === 大同大學 === 資訊經營學系(所) === 97 === Since the beginning of the U.S. sub-loan crisis, the world face financial tsunami, including Lehman Brothers, Merrill Lynch and other banks that have a long history and reputation of financial institutions, can not resist the tide, cause merge or bankruptcy. Global business in this wave can not get out, it is difficulty of obtaining operating funds because bank loans made to reduce, and more difficult because purchasing power caused by the sharp fall. It is inevitable that customers collapse or bad credit, in this difficult time, customer credit risk management is of particular importance. To enhance the competitiveness, Enterprise Resource Planning (ERP) is one of the necessary information system, along with the best of enterprise resource planning process comes a huge transaction data; the data on enterprises is a very valuable asset, for the effective analysis of these data, supporting business decision-making, Business Intelligence through online analytical system, provide immediate, accurate decision-making on the existing transaction system, can make up for Enterprise Resource Planning inadequate. In this study, we use sales and receivables accumulated information based on the Enterprise Resource Planning. and use Data Warehousing (DW) and Online Analytical Processing (OLAP) technology to provide risk managers clear risk management indicators of credit risk as the customer decision-making, and use Association Rules of Data Mining(DM) technology to analysis relation of this indicators. We use Microsoft SQL Server and Strategy Companion Analyze tool to do data processing and analysis to a multi-dimensional way, and handle customer sales and receivables credit information, providing managers a clear analysis and clear strategy supporting information to manage customer credit risk.