Theroy And Implemenation Of Data Warehouse And Risk Analysis For Consumer Finance Industry

Recently, consumer finance, which provides loans to people, grows a lot in financial industry. It was started at 1920s in USA, to lend money to customers to buy big products. Now the business involves mortgage, auto loan, personal loan and credit card. Since 1980, consumer finance has been growing rapidly, which helps quite a lot banks make large fortune. In China, it was started since 1980, mainly focusing on home loan. Now Chinese people are being asked to spend more money, which is helpful to increase the GDP. The information technology challenges consumer finance a lot, and banks without provide profitable services and products are not able to survive. It's very important to manage customer relation and risk now.Risk management is the most important thing for consumer finance industry. Both the risk team and the sales team are the key parts. For consumer finance, risk and sales should be balanced, in order to maximum bank's benefit. We get customers' risk by investigating their historical behavior.In order to manage customer relation and risk, data warehouse is needed, which extracts data from various team or branch. Information will be integrated into one single data storage, which supports decision-making.By facilitating integrated data warehouse, workload of front-end's database will be decreased, cost will be reduced, and more profitable products can be provided and delinquency will be reduced by reasonable prediction, which helps to avoid such crisis like sub-prime and to ensure banks' long-term growth. Statistic method is used for risk analysis, which is supported by most database vender, and SAS is almost the only choice. Currently, logistic regression domains, which uses credit score to predict delinquency. This helps risk team and underwriting team to automate their jobs with higher efficiency and lower cost. Scorecard also helps sales team to improve their marketing rate.