CSUGC Loan Database Analysis Predictors Discussion – Assignment Help

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Read Example 1 and explain your take away from it and add more information. Your document should be minimum 150 words. Please have credible references.

Example1:

  • Which attributes do you think might predict which loans will go delinquent and which will ultimately be fully repaid?

The loans which are most likely to get paid are the ones to people or businesses that have successfully managed leverage or debt in the past and have a reasonable DTI ratio. If someone is inexperienced with taking on more risk but has managed their personal finances well is the most worrisome for me. One economic turn in their personal life or in the economy and that person can’t pay off their debts any longer — depending upon the amount of assets and what those generate. People not being able to manage their leverage is more detrimental – and could quite possibly be on a path for delinquency. Again, this all just depends on how bad their DTI is in comparison to their revenue.

  • How could we test that?

Three analyses to predict whether they will receive a loan. 1) DTI; 2) Employment Length; and 3) Credit score and past rejected loans.

  • What three items do you believe would be most useful in predicting loan acceptance or rejection?

The largest risk factor would be someone with low credit, low employment length, and high DTI. Now, someone like this isn’t supposed to get a loan. This just makes it far too risky. This actually didn’t stop banks from loaning out money for years to people with these qualifications – that is a different topic. Someone would actually get a loan and still be considered high risk would be someone with good credit, very high DTI, and long employment length. This person has always had employment, always paid off their debts, but is one bad economic turn for the worse to not being able to pay back any debts. This is the type of person that lives off leverage in their life – even if you consider extenuating circumstances.

  • What additional data do you think could be solicited either internally or externally that would help you predict loan acceptance or rejection?

The amount of interest on the current liabilities of that business or person. This would determine what amount their revenue will need to be allocated for the interest to make minimum payments. Example: person A and person B both have $100k in debt and make a total income of $50k annually. However, person A average interest on their debts equates to 3% while person B interest averages to 12%. Personal A spends $3k per year on debt while person B spends $12K.

  • If you were in a position to accept or deny a loan application, how might you look differently at this data? I wouldn’t. As a bank, part of the calculated risk is having the Federal Reserve print you more money.
  • Would you be more lenient or stringent? Neither. Risk association doesn’t matter when I call sell the loan to another bank that needs to increase their assets on the balance sheet.

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