Machine Learning Based Risk Assessment Analysis for SMEs Loan Grant

Lending money is a major activity of the banking industry. Principal borrowers pays interest to the bank along with the principal the depositor has borrowed. Large number of Non-Performing Assets (NPAs) are formed due to failure to repay the money. Evaluation of the customers data for credit risk is an important field in risk management in finance. The decision whether the application is rejected or accepted is led by credit risk evaluation. Many times loans are sanctioned without any background check because the firm has/had a good name in the market; thus lessening the scope of new Small Medium Enterprises (SMEs) to get financial help. Also most of the current systems consider only the financial aspects. Our idea is to create a model which automatically calculates the credit worthiness of an applicant which not only considers the data directly provided by applicants but also extract insights from their behavioral and psychological trends of spending using Clustering Algorithms, Classifiers,etc.