Predictive analysis models are often being used for identifying the risk or business potential associated with specific customers or before a transaction process. Credit scoring is one of the parts of such model, which is being used for many financial services for scoring customers credit history and analyzing future payment prophecy through different data. These analysis models include individual probability of future credit payment and behavior patterns that helps an organization for segmentation and decision making process through statistical techniques that may vary case to case.
The central part of predictive analytics relies on to predict future trends and behavior patterns by confining relationship between equitable variables and the predicted variable from past history that can help an organization to exploit the predict future outcomes in advance. You can build this model more significant by adding additional information about particular consumers demographic, geographic and behavior in order to get more accurate prediction. Apart from prediction a predictive analytics can provide you information to identify new marketing channel and other competitive advantage through cross selling by exploiting the hidden relationship in the data you congregate.
This model can also help you to retain customers by increasing customer activities as reaching to certain phase you can even start predicting their future behavior in advance before it occur, especially when you have gathered information and linked the data accurately. These industries- credit card company, Insurance companies, retail merchants, manufacturers, telecommunication can even reduce a business exposure to “attempt fraud” through a predictive model in greater extent.
