CSUGC Loan Database Acceptance and Refusal Discussion – Assignment Help

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Read Example 2 and explain your take away from it and add more information. Your document should be minimum 150 words. Please have credible references.

Example 2:

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

At some point in time, most adults find them in a position of needing to borrow money. When times like the current puts interest rates at all time lows, it can seem like taking a loan is the better decision. When looking at lending money from a bank perspective, the most critical question that is asked is simply, how risky is the borrower? In determining risk, I would consider the three items that would be most useful is FICO scores, when taking or apply for loans there is usually a minimum score required. It’s interesting that so much is placed on FICO scores, because to me they do not show your relationship with money but more your relationship with debt. However, credit scores are a good way to judge whether a person pays their debt in a timely manner. Another important items would be DTI: Debt-to-Income ratio, this falls along the just because you can does not mean you should. While a person making 100k a year, with 99k a year in debt payments does not have the DTI to finance something above his means. For myself, when we applied for our mortgage, the underwriters required a lot of information. About our jobs, our financial situation, but also about our family. They wanted information on whether we paid for daycare, child support and other family obligations that could have impacted our ability to cover the mortgage. While it seems intrusive, it’s a way for the bank to feel more confident in predicting positive loans. The third item I would consider useful is inquires in the past 6 months, knowing if someone is taking multiple loans or financing many items very close together would seem like important information.

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

To help better predict loan acceptance, I would consider the type of loan. Certain loans carry higher risk, such as unsecured loans since there is no collateral such as a home or car. Information that could be solicited could be financial records, and employment records. Information about how long they have been employed, and stability of financial information.

  • If you were able to accept or deny a loan application, how might you look differently at this data? Would you be more lenient or stringent?

When reviewing the large amount of information from underwriters, I think its important to look at information as a whole and not just black and white. Someone who has no credit score, but no debt and a stable financial and employment history, would be something to consider. I do think that I would look at the information in a different light, from being the borrower to the giver. However, I don’t think that you can afford to be to lenient in the given circumstances.


Richardson, V., Teeter, R., & Terrell, K. (2018). Data Analytics for Accounting (1st ed.). New York, NY: McGraw-Hill.

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