Analysing Data Mining Techniques on Bank Customers for Credit Score

The aim of this paper is to detect and find out risk in sanctions of loan of banks. The approach here applying data mining methods on particular data set on current customers of bank to which bank has already sanction loan. Now data mining methods play a major role, analyse the data records of current customers and give a result on the value of different attributes of customers' record. Now the result of mining give a basic idea to banking system that which attribute value is important for any customer to return their loan on time or not returning the loan on time. So on that basis of result a framework is designed to which bank used to analyse the new customer for sanctioning the loan or not. In this way bank can reduce their losses and non-performing assets and can increase their profit. There are different data mining algorithms, using some one of them and also comparing which algorithm is the best. To decide this, firstly trained the different algorithm with some number of percentages of data set and then test with some number of percentage of data set and on that basis accuracy result will decide that which algorithm is best for the bank.