Credit Scores: You Do the Math

What is a credit score?

Credit scores are tools used to predict an outcome, most commonly repayment of a debt. Credit scores look at an individual’s credit history and calculate the relative risk that the individual will not fulfill the terms of an agreement based on their past performance.

The scores are based on the information in an individual’s credit report at a point in time but are not a part of the credit report itself.

It is important to remember that a credit score is only one tool used by lenders and other companies in their decision making process.


A world of different scores

Lenders, insurance companies, utility and telco providers check credit scores and use them as guidelines for making business decisions. Companies select the scoring models that best support  their particular type of business decision. Each model utilizes the data from an individual’s credit file to generate a score. The proprietary algorithms compare a huge number of data points to be able to classify each file based on the future risk level it presents. Many of the score developers refine their algorithms over time to reflect trends that emerge in the marketplace. Some companies transition to new models over time.

Scoring models all attempt to predict a risk level as it pertains to the product or service being offered. Since so many models are in use an individual can have a lot of credit scores.

While all credit scores look at the same information, they weigh the information differently depending on the specific purpose of the scoring model. For example, scores used for auto loans might give more weight to how previous aworldscoreuto loans were repaid, while scores used for credit card lending may give more importance to past credit card payments.

All of these unique models look at distinct aspects of one’s credit history and generate a score based on the information.  Many of the models have different score ranges. Sometimes companies even use varying brand or product names for the same scoring models.

One well-known score developer is the Fair Isaac Corporation and their models are known as FICO scores.  Their models are commonly used by mortgage lenders to rate applicants’ credit worthiness, and many of their scoring models range from 300 to 850. Lenders may use other models, including those developed by VantageScore LLC or other score developers.  VantageScore models ranges from 501 to 990, with a higher score being better.

Knowing your score

knowscoreThere is a lot of buzz about knowing your credit score.  That buzz can be misleading because there is no one credit score for each person.

There are many different credit scoring models that co-exist in the marketplace including generic scores, proprietary lender scores, industry specific scores and educational scores. A number of the scores available for purchase are considered educational and do not coincide with the exact scores that a creditor will obtain when you apply for credit.

Typically you have to pay a nominal fee to get a score generated from your report.  Federal law entitles us all to one free report each year from the three major bureaus, Equifax, Experian, and TransUnion, but it doesn’t provide for a free credit score.

Buying all your different scores would be expensive, not to mention the time involved in tracking down all the different models and their uses.  So, which score should you know? And, do you really need to know all those numbers?

What a score really means

While all the models look at an individuals credit history and generate different numbers, or scores, the one thing they have in common is the goal of determining risk.lookreport_1

Lenders and other institutions use the scores to put individuals into risk ranges based on the model being used. Often times the risk range you fall into is tied to the interest rate or premium that you have to pay.

The specific numbers, by themselves, have no meaning. In order to understand any credit score it must be put into the context of risk ranges.  Each model has different numerical ranges tied to levels of credit risk.

Some scoring models, such as the VantageScore, equate the numerical ranges to letter grades. On their system a score of 901-990 is an A, or super prime and thus a very low risk.  This same risk level on the FICO scoring system corresponds to a score above 800.  Here is how the top two risk levels look on both systems:


While the numbers are different the risk levels and the way lenders view that risk would be the same.

All scores, once in the context of their risk range, provide the same basic information.  Knowing one specific score is not as important as understanding the risk level a score assigns to an individual’s credit history.

Since not all lenders and issuers use the same scoring models, consumers who understand their assigned risk level and underlying risk factors are better able to shop around for loans, insurance and other products that use credit history to determine pricing without needing to know all their different credit scores.

Shopping around for the best terms and rates is very important.  Credit issuers have different business goals and risk tolerances. Consumers may find their credit profile and its associated risk range will garner different offers from various lenders in the marketplace.

A recent report issued by the Consumer Financial Protection Bureau discusses the differences between consumer and creditor purchased scores.

intoscoreWhat goes into a score?

While each model is unique in the way it weighs and balances different aspects of an individual’s credit history, all models work with the same data.

Payment history looks at whether payments are made on time and in the full amount required.  Once a payment is 30 days or more late it can be reported in a credit file. The more late payments a file has the higher the individual’s risk level.

Debt-to-credit limit ratio is the amount owed divided by the total of a person’s credit limits.  For example: if someone has a credit card with a $20,000 limit and they owe $5,000 on that card their ratio would be 25%.  This is also sometimes called credit utilization. The lower the utilization level the lower the risk level.

Length of credit history is the amount of time an individual has had access to credit. A longer history of responsible use often correlates to a lower risk level.

Types of debt include installment loans, such as mortgages and car loans, and revolving debt, such as credit cards.  Some models apply different weight to one type over another. A scoring model used for automobile financing might weigh installment loan data more heavily than revolving debt, for example. Variety in debt types also is seen as beneficial to risk level because it demonstrates that you can manage different kinds of debt.

A recent surge in new credit applications can make an individual seem like a greater risk. Shopping around for a specific loan (such as a mortgage or auto) typically doesn’t affect a score because most models lump together inquiries of the same type so they are counted as only one inquiry.

Calculating your score

It is impossible to know the exact credit score a business uses without obtaining it directly from that business.  Additionally, scores fluctuate based on the activity in your credit file and can vary from day to day. While the number can change daily, the risk level it assigns is usually much more stable unless a very negative item is reported.

The most important step in understanding your credit risk level is knowing what is in your credit files at each of the three major bureaus; Equifax, Experian, and TransUnion. By law you are entitled to one free copy from each bureau annually.[1]


Occasionally inaccurate information can be posted on one or all of your files. It is important to check your file at each bureau at least once a year to ensure all of the information is accurate.

Remember that each of the three major credit bureaus may have slightly different information in their file. Which of your creditors report to each agency and how frequently they send in their data can cause these differences.

Once you have a copy of your credit file and have dealt with any inaccuracies look at your data to see how it adds up.

calcscoreHow does your payment history look?

Have you been making all your payments on time?

(If you have a late payment last month it will have a greater negative
impact than a late payment from 3 years ago.)

Do you pay the full amount required?

When and how late was your last payment?

In most models these are the most important factors in determining risk. Accounts with no negative payment history will stay in your file forever if they remain open and for 10 years after they are closed. Negative information, such as missed payments, bankruptcies and judgments will linger for 7-10 years. Loans for which you have cosigned are also included in your debt analysis.

Are your balances too high compared to your credit limits? What is your current debt to credit ratio? Add up all of your outstanding revolving debt and divide by the total of all your credit limits. Most experts recommend keeping your credit card accounts below 10% utilization to be considered the lowest risk level and below 30% to have good scores. Many models weight this information very highly as well.

How long have you had access to credit? This is often a smaller factor in determining your risk level than debt ratio and payment history.

Do you have both revolving and installment debt in your credit history? Do you service both types of debt equally? Installment debts require a specific payment each month.

Have you applied for credit recently? Each time your credit report is accessed a record of that access is added to your file. That record is called an inquiry.

New credit inquiries are added to your credit report when you apply for new accounts or request an increase to existing account limits. These can negatively impact your risk level because they represent potential new debt, although inquiries alone have minimal impact on credit scores.

New inquiries are also added each time companies request your file in order to offer you a product or service. These have no adverse effect on your risk level because you did not initiate the transaction. The same is true for personal inquiries into your file.

Once you considered these factors you should have a better understanding of how your credit history adds up and the level of risk you represent in credit transactions.

How to improve your score

improvescoreTo learn what affects your personal scores, get a list of the risk factor statements for the score you received. Those factors are provided with most credit scores you purchase.

The risk factors describe what had the most negative impact on your credit score. By comparing those factors to your credit report, you can begin to take steps to change your credit management behavior over time, which will result in improved credit scores.

While the numbers can be quite different from one credit score model to another, risk factors tend to be very consistent. So, addressing the risk factors from one score will help you improve all credit scores calculated using your credit report.

improvescore2Making payments on time and in full is the best way to keep your risk level low.  Mistakes you have made in the past will have less of an impact as they become more distant.

A number of companies promise quick and easy fixes for credit problems.  They often talk about credit repair and the ability to erase negative information from your file. However, there is no way to permanently remove negative information, unless it is inaccurate.

The FTC has information on credit repair:

The three national credit bureaus:

Trans Union

[1] Call For Action recommends checking one file every 4 months from a different bureau.  This allows you to spread your free reports out over the course of a year.  To obtain your free reports

Some states allow for an additional copy.  Identity Theft victims are also entitled to additional copies. For more information on identity theft please visit:

[*] Terminology is based on the VantageScore model


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