Data Mining Techniques to Acquire New Customers.

      Аннотация: The aim of the book is to discuss the most widespread data mining techniques: logistic regression, decision tree and neural network, and to assess whether these techniques provide financial gains for private institutions that have active processes for business development. A company from the financial sector is used as a study subject, specifically in the processes of acquiring new customers for adhesion to consumer credit (in Brazil CC, or Cr?dito Direto ao Consumidor). This survey will show the results of the three abovementioned techniques, to check whether the statistical models indicate relevant differences between the prospects? intentions to adhere to consumer credit. In the meantime, the techniques are checked to see whether they leverage financial gain. These gains are expected to come from better focused and directed marketing efforts. The paper presents the functioning of each technique theoretically, and as the results indicate, data mining is a great opportunity for a company to boost profits.

Ключевые слова: Data Mining, Decision Tree, Financing, neural networks, Customer Credit, Logistc Regression