In this part we will explore how different countries utilize credit scoring. We will start our analysis with a general description of credit scoring and then we will deal with different country practices starting with United States.
According to an article quoted to Wikipedia, credit score is a numerical expression based on a statistical analysis of a person’s credit files, to represent the creditworthiness of that person. A credit score is primarily based on credit report information typically sourced from credit bureaus.

US Practice
In US, credit scoring is, a number based on a statistical analysis of a person’s past credit history. In theory credit scoring represents the creditworthiness of that person or entity. In other words it is the likelihood that people will pay their bills. Credit scoring is mainly based on some sort of a credit report. That report comes from one of the three major credit bureaus particularly: Experian, TransUnion, and Equifax. Contrary to common sense, income is not considered by the major credit bureaus when calculating a credit score.
We can talk about different methods of calculating credit scores. The most common of all is FICO, the most widely known type of credit score. It is a credit score developed by FICO, previously known as Fair Isaac Corporation.
Today, this method is used by several mortgage lenders who use a risk-based system to determine the possibility that the borrower may default on financial obligations to the mortgage lender. These bureaus of creditors all have their own credit scoring mechanisms and these are: Equifax’s Experian’s PLUS score, ScorePower, and TransUnion’s credit score. Moreover, each one of them also sells the VantageScore credit score. In addition to that, many of the large lenders, including the major credit card issuers, have developed their own proprietary scoring models. This helps them follow and suit a model which suits their interests most.

Well, the answer is: Numerous.
In order to make a comment about the methods used for credit scoring, one has to know the idea behind credit scoring. Moreover, the processes involved in building a model for credit scoring also entails knowing the possible methods that can be used. Because some of the methods used has advantages in one area but drawbacks in other areas.
The following part which is taken from the academic article “What is the point of credit scoring?” very well summarizes what can be done and what has been done up to know. Article was written by Loretta Mester who is a vice president and economist in the Research Department of the Philadelphia Fed. She is also the head of the department’s Banking and Financial Markets section.

Scoring Methods
Several statistical methods are used to develop credit scoring systems, including linear probability models, logit models, probit models, and discriminant analysis models. (Saunders discusses these methods.) The first three are standard statistical techniques for estimating the probability of default based on historical data on loan performance and characteristics of the borrower. These techniques differ in that the linear probability model assumes there is a linear relationship between the probability of default and the factors; the logit model assumes that the probability of default is logistically distributed; and the probit model assumes that the probability of default has a (cumulative) normal distribution. Discriminant analysis differs in that instead of estimating a borrower’s probability of default, it divides borrowers into high and low default-risk classes.

Two newer methods beginning to be used in estimating default probabilities include options pricing theory models and neural networks. These methods have the potential to be more useful in developing models for commercial loans, which tend to be more heterogeneous than consumer or mortgage loans, making the traditional statistical methods harder to apply. Options-pricing theory models start with the observation that a borrower’s limited liability is comparable to a put option written on the borrower’s assets, with strike price equal to the value of the debt outstanding. If, in some future period, the value of the borrower’s assets falls below the value of its outstanding debt, the borrower may default. The models infer the probability a firm will default from an estimate of the firm’s asset-price volatility, which is usually based on the observed volatility of the firm’s equity prices (although, as McAllister and Mingo point out, it has not been empirically verified that short run volatility of stock prices is related to volatility of asset values in a predictable way. Saunders discusses other assumptions of the options-pricing approach that are likely to be violated in certain applications.) Saunders reports that KMV Corporation has developed a credit monitoring model based on options-pricing theory.

Neural networks are artificial intelligence algorithms that allow for some learning through experience to discern the relationship between borrower characteristics and the probability of default and to determine which characteristics are most important in predicting default. (See the articles by D.K. Malhotra and coauthors and by Edward Altman and coauthors for further discussion.) This method is more flexible than the standard statistical techniques, since no assumptions have to be made about the functional form of the relationship between characteristics and default probability or about the distributions of the variables or errors of the model, and correlations among the characteristics are accounted for.

Some argue that neural networks show much promise in credit scoring for commercial loans, but others have argued that the approach is more ad hoc than that of standard statistical methods. (The article by Edward Altman and Anthony Saunders discusses the drawbacks.) A study by Edward Altman, Giancarlo Marco, and Franco Varetto analyzed over 1000 healthy, vulnerable, and unsound Italian industrial firms from 1982-92 and found that performance models derived using neural networks and those derived using the more standard statistical techniques yielded about the same degree of accuracy. They concluded that neural networks were not clearly better than the standard methods, but suggested using both types of methods in certain applications, especially complex ones in which the flexibility of neural networks would be particularly valuable.”

To give the issue a sense of an academic taste, we can refer to Loretta J. Mester who is a vice president and economist in the Research Department of the Philadelphia Fed. She is also the head of the department’s Banking and Financial Markets section. In her article which is named as “What’s the Point of Credit Scoring?” Loretta J. Mester introduces credit scoring in a funny way as following:
“When one banker asks another “What’s the score?” shareholders needn’t worry that these bankers are wasting time discussing the ball game. More likely they’re doing their jobs and discussing the credit score of one of their loan applicants. Credit scoring is a statistical method used to predict the probability that a loan applicant or existing borrower will default or become delinquent. The method, introduced in the 1950s, is now widely used for consumer lending, especially credit cards, and is becoming more commonly used in mortgage lending.”

She also gives a strict definition of credit scoring:
“Credit scoring is a method of evaluating the credit risk of loan applications. Using historical data and statistical techniques, credit scoring tries to isolate the effects of various applicant characteristics on delinquencies and defaults. The method produces a “score” that a bank can use to rank its loan applicants or borrowers in terms of risk. To build a scoring model, or “scorecard,” developers analyze historical data on the performance of previously made loans to determine which borrower characteristics are useful in predicting whether the loan performed well. A well-designed model should give a higher percentage of high scores to borrowers whose loans will perform well and a higher percentage of low scores to borrowers whose loans won’t perform well. But no model is perfect, and some bad accounts will receive higher scores than some good accounts”

Credit scoring is a procedure where an institution or an individual is evaluated based on its past payment patterns. In today’s highly globalized environment credit scoring is getting important day by day. It is important firstly, because it reduces the time and energy spent when evaluating a customer to give credit or enter into a transaction. The counterparty which is mostly the creditor or banks, checks the credit worthiness of its applicant just by entering simple identity numbers such as a social security number (SSN). This might well be the Tax ID or Citizenship ID depending on the country the method is employed.

One other reason why such procedures are important is that it increases the efficiency of the system in the sense that the creditor is ensured and on the safe side. This also reduced the bad loan ratio of the creditor company and builds trust among the other institutions of the country thereby helps reduce the interest rates as a whole.

One other advantage is to the end user. Nowadays in many countries, consumers or people seeking loans can easily get their answer simply by sending their SSN (Social Security Numbers) or Citizenship IDs as a Text Message to the numbers designated by banks or credit institutions. Getting their answers as positive or negative, consumers then decide on other options. Credit scoring procedures has advantages, since this method provides consumers the means to compare different quotes given by  different institutions.

Most of us have been tricked by ads on the internet, radio, and tv about being able to check our credit scores/reports for free. There is an old adage that says nothing in life is free, while that is true for the most part, there are actually ways to get your credit report/score for free.

The Fair Credit and Reporting Act (FCRA) requires each of the 3 credit reporting agencies to provide everyone ONE free credit report every 12 months. As stated by the Federal Trade Commission, the only website you can go to access this free credit report is at annualcreditreport.com. This is absolutely the only site that is part of this program. But there is one drawback, this site only provides you a credit report/history, and not your credit score. You have to pay extra for the score.

Don’t fret, there are some other ways to get to get a free credit report and score. Many of the websites that offer credit reports have 30 day free trials. For instance, about a year ago I used freecreditreport.com, part of Experian. I ordered my credit report and score, checked it online, took notes, then called in a canceled within 4 hours of ordering the service. I was never charged a thing. Also, at one point, and I believe they still are now, American Express was offering a 30 day free trial to its card holders to receive credit reports and scores. Just login into your americanexpress.com account, and under other services sign up for the credit report/score program. Assuming you cancel the program within 30 days you will not have to pay a dime, and you will get your credit report and score from all 3 bureaus.

Another way you can sometimes get a free credit score is from your bank. Many banks use their own version of your credit score, some call it a soft score, meaning it is their own proprietary formula/score. I do know Bank of America uses this and it is factored into credit card application and mortgages with them. If you are nice to one of the branch employees, they will often share with you your soft score. While this is not your actual credit score, it will give you a very good idea of what your score is.

Also, if you meet one of these requirements you are eligable for a free credit report.

1) Denied credit, insurance, or a job due to information on your credit report. A notice stating which credit bureau supplied the report should be included in your letter of denial. You then have 60 days to request a free copy of your report from them.
2) Unemployed. You are entitled to one free report a year if you are unemployed and anticipate looking for a job within 60 days.
3) On welfare
4) Believe you are a victim of identity theft. Maybe you recently found a suspicious transaction, or lost your wallet. Place a fraud alert on your file and then ask for a free copy of your credit report.

Any people know ways to increase their credit score, but what factors actually lower your credit score?

1) Accounts that have been open less than three years. Having long term credit accounts that you consistently pay on time is an important indicator of stability. As your credit history ages, your score should increase.

2) Anytime your credit report is pulled. This is if you apply for a loan and the lender requests a copy of your report, or you order a copy of your credit report yourself directly from the credit bureau. This is when an inquiry is added to your report. Hard inquires are bad, soft inquiries are ok. Hard inquired are from creditors and lenders with whom you have applied for credit or a loan. A Soft Inquiry is when you request your own copy of your report or when an employer checks your credit history. Lenders and creditors do not see these inquiries. Inquiries remain on your report for up to 2 years.

3) An account that goes unpaid or becomes delinquent.

4) Bankruptcy.

5) Closing old accounts. Having old accounts open, even if they are not used regularly, is good for your credit score.

6) Constantly using too high of a percentage of your credit line. For example, it is good to stay under the 30% mark for the amount of credit your have used in your credit line.

If most of you reading this are like me (which is unlikely because my mom always told me I was special) you receive a lot of pre-approved credit card offers in the mail. Do you typically just throw it away? If you do, don’t. The advice I am about to give might seem overly cautious, but more and more people are going through trash to retrieve information to steal identities. What should you do then? Good question. What I do is to take the response card and anything with personal information on it, and put it through the shredder. This way, no one can go through your trash, fill out the forms, and receive a pre-approved credit card in your name. Taking this measure to protect your identity and credit score can go a very long way. Better yet, you can also do what I have done, in an attempt to cut down on the pre-approved offers, is to take yourself off the list. You can “opt out” by going to http://optoutprescreen.com/ and taking yourself off the mailing lists for pre-approved offers. If for some reason you can’t opt out online, you can also call their hotline at 1-888-5OPTOUT.

And remember, keep reading to increase your credit score. I received a report from one subscriber (aka a friend) who has increased his score by 40+ points in just a few months from tips that have appeared on this blog.