Simple Bank-Loan Model; Using K-Nearest Neighbors

Nowadays there are many risks related to bank loans, especially for the banks so as to reduce their capital loss. The analysis of risks and assessment of default becomes crucial thereafter. 

Banks hold huge volumes of customer behavior related data from which they are unable to arrive at a judgement if an applicant can be defaulter or not. 

Data Mining is a promising area of data analysis which aims to extract useful knowledge from tremendous amount of complex data sets. 

In this research paper we aim to design a model and prototype the same using a historical bank data set. The model is a K-Nearest Neighbors based classification model that uses the functions available in the R Package.

Prior to building the model, the dataset was pre-processed, reduced and made ready to provide efficient predictions. The final model is used for prediction with the test dataset and the experimental results prove the efficiency of the built model 

View the research paper here

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