Based on the predictions generated by this model for this scoring data, what is the lowest credit score a person could have and still achieve a classification of Low? 662 700 710 650
The correct answer and explanation is:
Correct Answer: 662
Explanation (Approx. 300 words):
In a credit scoring classification model, scores are typically used to predict the likelihood of a borrower defaulting or repaying a loan. The classification “Low” generally indicates a low risk of default, meaning the individual is considered creditworthy.
In this question, you are provided with four credit scores: 662, 700, 710, and 650. These scores are likely arranged around a threshold that separates individuals into categories like “Low,” “Medium,” or “High” risk. The task is to determine the lowest score that still results in a Low classification — meaning it is the minimum score that still qualifies as low-risk according to the model.
To solve this, let’s evaluate each option:
- 710 and 700 are both high scores and would almost certainly fall into the “Low risk” category.
- 662 is lower but still reasonably within what many scoring systems (like FICO) would consider the edge of “Good” credit.
- 650 is a more borderline score; it typically falls into the “Fair” category, which might correspond to a “Medium” or even “High” risk depending on the model thresholds.
Assuming the classification model used a specific cutoff — say, 660 — then:
- 650 would be just below the cutoff and not classified as Low.
- 662 would be just above the cutoff and thus the lowest score still qualifying as Low.
Therefore, among the given options, 662 is the lowest score that could be classified as “Low” according to the model’s prediction logic. This answer assumes the model has a cutoff around 660, which aligns with general credit risk models and industry practices.
In summary, 662 is the correct answer because it is the minimum score among the options that still qualifies for a “Low” risk classification based on typical credit model thresholds.