Why Are Credit Scores Important?
http://www.financemeter.net/articles/10881/1/Why-Are-Credit-Scores-Important/Page1.html
faye bautista
The author is a freelance writer and also writes about business
topics such as call center
and call center in the philippines. By faye bautista
Published on 10/26/2008
Credit scores will determine if someone is going to be declined or approved on any credit type. Credit scores are numerical expression based on the statistical analysis of the person s credit files that is generated by this mathematical algorithm.
Credit scores will determine if someone is going to be declined or approved on any credit type. Credit scores are numerical expression based on the statistical analysis of the person s credit files that is generated by this mathematical algorithm.
Credit scores is going to determine the basis of certain amounts of credit that a person takes. His credit statement will be compared to the accounts of different people who will apply for credit to that same financial institution.
Credit card companies and bankers are termed as lenders they are using the credit scores in evaluating the potential risk but still lending money to consumers and alleviating losses because of bad debts. These are used by lenders to determine who will qualify for a loan and those who are not, what the interest rate, and the credit limits they could lend the money to that person and in what time and what the interest they would get their refund back.
There are lenders that will build or create regression models that can predict the amount of bad debt the customer may incur. But this is really hard and difficult to predict, the debt return is done to have an idea in the future if this person is a high risk or worthy of future credits.
Lenders are usually looking for a higher number as we have seen that people with the highest score get the lowest rate of interest. Different countries are using different techniques to make credit scores and there is a similarity between USA and Canada. But the system in Australia is said to be better.
For credit scorecards this is created with the help of statistics. First, all the past loan applications of interested consumers are collected categories. The first deals with the people who repaid their loans in due time without much hassle. The second deals with those that are defaulted.
Comparison of the first group with the second one is mandatory. This is to prepare an appropriate scorecard. Credit scorecards provide accurate measurement of the likelihood that this customer will repay the credit amount back in the amount of time allowed.
Probit or Logit are estimation techniques that are statistically used in predicting the probability of default of new clients based on the historical data base. The default probabilities will then be compared to a credit score. This score will then be ranked to the potential client by their height of risk without explicitly identifying their probability of default.
Credit scores is going to determine the basis of certain amounts of credit that a person takes. His credit statement will be compared to the accounts of different people who will apply for credit to that same financial institution.
Credit card companies and bankers are termed as lenders they are using the credit scores in evaluating the potential risk but still lending money to consumers and alleviating losses because of bad debts. These are used by lenders to determine who will qualify for a loan and those who are not, what the interest rate, and the credit limits they could lend the money to that person and in what time and what the interest they would get their refund back.
There are lenders that will build or create regression models that can predict the amount of bad debt the customer may incur. But this is really hard and difficult to predict, the debt return is done to have an idea in the future if this person is a high risk or worthy of future credits.
Lenders are usually looking for a higher number as we have seen that people with the highest score get the lowest rate of interest. Different countries are using different techniques to make credit scores and there is a similarity between USA and Canada. But the system in Australia is said to be better.
For credit scorecards this is created with the help of statistics. First, all the past loan applications of interested consumers are collected categories. The first deals with the people who repaid their loans in due time without much hassle. The second deals with those that are defaulted.
Comparison of the first group with the second one is mandatory. This is to prepare an appropriate scorecard. Credit scorecards provide accurate measurement of the likelihood that this customer will repay the credit amount back in the amount of time allowed.
Probit or Logit are estimation techniques that are statistically used in predicting the probability of default of new clients based on the historical data base. The default probabilities will then be compared to a credit score. This score will then be ranked to the potential client by their height of risk without explicitly identifying their probability of default.