Credit scores are used to determine the credit risk of loan applications. This is done using historical data as well as statistical techniques. The score can be used by banks to produce a rank for the loan applicants and borrowers in terms of risk factors.
To build this model developers analyze historical data of previously made loans. They do this to determine which borrower characteristics will help them to predict whether the loan had a good performance or not. The better the model design, the higher the percentage will be. A higher percentage of high scores are awarded to borrowers whose loans perform well and a lower percentage is given to those whose loans do not. However, no model is absolutely perfect so some bad accounts receive higher scores then some of the better ones.
Reports on borrowers come from loan applications and from the credit bureaus. They will contain such information as the applicants’ monthly income, their outstanding debt, their financial assets, how well they performed on a previous loan, whether they own a home or rent one, the type of bank they use, and even how long they have been at their job. The regression...
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