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credit_risk_predictor

Banks play a crucial role in market economies. They decide who can get finance and on what terms and can make or break investment decisions. For markets and society to function, individuals and companies need access to credit. 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 judgment if an applicant can be defaulter or not. Credit Risk assessment is a crucial issue faced by Banks nowadays which helps them to evaluate if a loan applicant can be a defaulter at a later stage so that they can go ahead and grant the loan or not. This helps the banks to minimize the possible losses and can increase the volume of credits. This project evaluates the perfect execution of credit risk problem to classify the potential customers who are eligible for lending loans. This is a basic classification problem with important business applications. The goal of this problem solution is to build a model that lending institution can use to help make the best financial decisions.

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