Abstract:
Every lender’s organization such as banks and credit card companies use credit
score system to determining the creditworthiness of their clients. Currently, they
are using numerical scoring system in where the score determined by the compering
new customer vs. existing customer profile. This does not capture the exact
behavior of certain individual entities or more optimal ways to segment scoring
models for which few loan trends to classify in a result organization are deprive
of profit and lead to the loss. Now it analyzed that the problem can be optimized
using Machine Learning technique and possible to forecast the behavior of the
customer. In this study, we applied various machine learning technique to predict
the classified loans, minimize credit risk and maximize the profit of the lender’s
organization. Hence, this study intended to find the best modeling with best performance
and accuracy by the comparing their results.
