A simple oracle data miner application

Develop a small financial data mining application using 'Oracle Data Miner' capable of Loan payment prediction, Targeted marketing & Detection of money laundering ## Deliverables **Other Requirements:** A data mining application is to be developed for financial data analysis. The functionalities that the application has to provide is listed below: ** **Loan payment prediction and customer credit policy analysis**** Loan payment prediction and customer credit analysis are critical to the business of a bank. Data mining methods, such as feature selection and attribute relevance ranking will help in identifying important factors for analysis. Then a critical factor analysis is carried out to make important decisions. **Classification and clustering of customers for targeted marketing** Classification and clustering methods can be used for customer group identification and targeted marketing. For example, customers with similar behaviours regarding banking and loan payments may be grouped together by multidimensional clustering techniques. Effective clustering and collaborative filtering methods (with the help of various techniques such as neighbour classification, decision trees etc) can help identify customer groups, associate a new customer with an appropriate customer group, and facilitate targeted marketing. **Detection of money laundering and other financial crimes** To detect money laundering and other financial crimes, it is important to integrate information from multiple databases (for e.g. bank transaction databases and federal crime history databases). Multiple data analysis tools can then be used to detect unusual patterns, such as large amounts of cash flow at certain periods. Helpful tools include data visualisation tools, linkage analysis tools, classification tools, clustering tools, outlier analysis tools and sequential pattern analysis tools. These tools can be used to identify important relationships and patterns of activities and help investigators focus on suspicious cases. **Detect patterns of fraudulent credit card use** **Identify loyal customers** **Predict customers likely to change their credit card affiliation** **Determine credit card spending by customer groups** **Find hidden correlations between different financial indicators** **Find out stock trading rules from historical market data** ** **Tools for development**** 1) Oracle Data Miner and 2) Oracle Database 10g ***The data analyst needs to mine data using ‘Oracle data miner’, thus completing necessary steps such as data preparation, data mining, model evaluation and model scoring process. Then the data needs to be transformed, the model built and finally the results are to be interpreted. Then the code needs to be generated from the ‘Oracle data miner PL/SQL Code Generator’ and thus transform the data mining steps into an integrated data mining application. Finally real data sets must be used from the industry so as to test the application.***