Data mining techniques to analyze risk giving loan(bank)

Data mining

ABSTRACT In this project the main focus is to identify and analyse the risk in giving loan of commercial banks.the domain is data mining so we are using data mining techniques to analyze risk giving loan.it includes analysing and processing data from various resources and summarise into a valuable information. Traditional process of lending is very tedious task because it includes a large manual work.whereas our project is design to automate all the manual work this will increase the speed and accuracy.This will improve the quality of banking system thus improving the customer retention. We are using C4.5 classification algorithm of Data mining.Applying it on a dataset of customer and predicting the risk percentage for individual to give loan.Today, customers have so many opinions with regard to where they can choose to do their business.Executives in the banking industry,therefore,must be aware if they are not giving each customer their full attention,the customer can simply find another bank. Early data analysis techniques were oriented toward extracting quantitative and statistical data characteristics. These techniques facilitate useful data interpretations and can help to get better insights into the processes behind the data. Although the traditional data analysis techniques can indirectly lead us to knowledge, it is still created by human analyst. The banks and many investment companies are pioneers in taking advantage of Data Mining.

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