Credit scoring models for student loans – Important considerations
In order to create a good credit scoring model for student loans, one needs to understand what has been done in the past and in this case, the best way to understand who to grant a loan to, one needs to understand the reasons for default. This way, banking system can develop a model to include all eligibility criteria variables that will need to be considered before granting a loan.
Policy makers have started monitoring the default rates for student loans to assess the efficiency of the student loans given. In 2008, a federal study was carried out to calculate and assess factors that contribute to student loan defaults. The results showed that in four years time, default rates increased by 6 percent among student groups (Choy and Li, 2006 cited in Gross et al, 2009) and 60% among some types of institutions (Lederman, 2008 cited in Gross et al, 2009) These statistics prompted regulations to take control and figure out the factors that contribute to high defaults, which makes the importance of credit scoring models for student loans all the more crucial. Banking system should improve their credit scoring models to reflect the past default rates.
In order to find out what variables should be included in credit scoring models, thorough r...
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...tics should be tested to see the correlation between the variable and default likelihood. Using the statistical model to control for other factors, the tests will yield a conclusion on an accept or reject basis, which serves as an answer to the hypotheses created.
It is evident from the analyses that this is an issue in the retail credit scoring that has not been pursued recently in the financial industry and should be worthwhile to find out. Given previous researches that have led to the identification of this research gap, it would be beneficial to financial institutions for this gap to be filled. The need for pursuing higher level of education today has made it increasingly important for financial institutions to be able to accurately assess student loan applicants so that demand from student loan is sufficiently met while minimizing default rates.
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