Credit Score Cards


Share on LinkedIn

Information Technology as a industry has grown up in leaps and bounds. You may not find any organization on the planet which does not have any IT involved. This has given rise to lot of jobs supporting the IT functions. Salaries have increased tremendously in IT compared to other business areas. Overall economy had gone up which increased the tendency of people to afford & buy more & more.
This has increased the usage of Credit in everyday life. “Buy now pay later” syndrome became common. Everyone started using the credit cards and also started availing credit or loans for big purchases like home, car etc.
Eventually this resulted in many people avoiding or defaulting the payments. This is where assessment of the risk of providing the credit came along and birth of credit scoring.
Credit Risk is the risk of loss a bank or credit giving company will incur when Customer does not repay the mortgage, unsecured personal loan, auto loan, credit card amount, overdraft etc.
In early days of lending businesses used to judge borrowers based on 5 Cs:
  • Character of the applicant
  • Capacity of applicant to borrow
  • Capital as backup
  • Collateral as security for credit
  • Conditions which were mostly external factors
Then Credit Scoring was introduced by Fair Isaac which is now commonly known as FICO score.

Credit Scoring in simple terms giving some numbers to customers based on certain parameters like age, earnings, accommodation type (owned or rented), expense history & payment history etc.
There are 3 types of Scorecards which are currently used.
Application Scorecard: This is mainly used in scoring the customers applications for credit. This tries to
predict the probability that the customer would become “bad”. The score given to a customer is usually a three or four digit integer which is finally used to approve or reject the credit application of the customer. This is where you get messeges from Banks that you have pre-approved loans or Credit cards.
Behavioral Scorecard: This is mainly used to identify or predict which of the existing customers are likely defaults on the payment so alternative measures can be taken to contact the customers & ensure that payments are received on time.
Collection Scorecards – This is mainly used to how much loss company will incur due to non payment from groups of Customers.
How businesses are using Credit Scorecards:
  • Banks are using them to separate good borrowers from bad borrowers
  • Financial institutions are using it to determine credit limits
  • Early detection of high risk account holders to reduce potential losses
  • Improved debt collection
  • Insurance companies are using it for cost of insurance product for a Customer

Republished with author's permission from original post.

Sandeep Raut
Sandeep Raut is Founder and CEO at Going Digital.He is ranked in top 10 global influencers and thought leaders in Digital Transformation.


  1. The article Sandeep Raut wrote has errors concerning credit scores. First, he states “Credit Risk is the risk of loss a bank or credit giving company will incur when Customer does not repay the mortgage, unsecured personal loan, auto loan, credit card amount, overdraft etc.”

    Credit Risk is risk based on the credit score. Those with higher credit scores will have a lower risk of paying the debt back then with someone who has lower credit scores. It doesn’t matter if it is a bank, mortgage bank, a local store, and a large conglomerate. Risk is accessed differently by each sector. Fair Issaac was the first company to develop an algorithm to determine risk scores. These scores informed those giving credit on how good someone would pay back the debt owed. For every industry using a risk model there are at least 14 different models for each industry. The different models are slight variations. This is the reason for different scores when using a 3rd party repository.

    Behavior has some input into credit scores. When a person pays his or her debt on time they score will go up but if the behavior of paying late on a constant basis will bring the score down. Each person makes decisions on how to pay their debt. If a person decides to pay their debt on a bi-weekly basis the scores go up. The behavior is more favorable because they are developing an acceptable payment pattern.

    In order to determine what a person can afford for a loan we use the debt to income ratios. This is determined by the total monthly payments divided by total monthly income. To determine the housing ratio it is monthly housing payment divided by total monthly income. Once this is determined then we would know how much of a loan amount a person can obtain.

    Inquiries hurt a persons score. The problem with the inquiries on a credit report is the algorithm cannot distinguish if the person got the credit or was an inquiry. The more inquiries on a credit report the lower the credit score. The repositories state a person is allowed 12-14 inquiries before it affects the score. I have seen it affect a credit score with only 2 inquiries on a report. It may lower the score by 2 points each inquiry.

    Credit Scores do not discriminate against a persons religion, race, or affiliations. Credit scores are a number that informs a company if you are able to pay back a debt and currently are paying debts on a regular basis without being late. Credit scores have flaws but it is the only system we can rely on.


Please use comments to add value to the discussion. Maximum one link to an educational blog post or article. We will NOT PUBLISH brief comments like "good post," comments that mainly promote links, or comments with links to companies, products, or services.

Please enter your comment!
Please enter your name here