Prof. Poonam Sadafal
Sinhgad Institute of Technology And Science, Narhe Pune
Akanksha Bairagi
Sinhgad Institute of Technology And Science, Narhe Pune
Mamta Jadhav
Sinhgad Institute of Technology And Science, Narhe Pune
Chetna Rathod
Sinhgad Institute of Technology And Science, Narhe Pune
Sakshi Hajare
Sinhgad Institute of Technology And Science, Narhe Pune
Download PDFData mining is the computing process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. It is an essential process where intelligent methods are applied to extract data patterns. Nowadays, there are many risks related to bank loans, health loan, car loan, for the bank and for those who get the loans. This paper describes data mining with predictive analytics for banking policy applications and explores methodologies and techniques in data mining area combined with predictive analytics for application driven results for interested customers. The basic idea is to apply patterns on available data and generate new assumptions and anticipated behavior using predictive analysis. Data mining methods used in these applications naive Bayes data analysis. Data Mining is one of the most motivating and vital area of research with the aim of extracting information from tremendous amount of accumulated data sets. The model has been built using data from banking sector to predict the status of loans particular user if they want. The model has been built using data from banking sector. Here we find out the interested user who wants the service.
Keywords: Predictive Analysis; Loan; data mining; algorithm
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