Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Credit Score Cards
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Analytics > Modeling > Credit Score Cards
ModelingRisk Management

Credit Score Cards

Sandeep Raut
Sandeep Raut
4 Min Read
SHARE
Information Technology as an 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.
Information Technology as an 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

  

Share This Article
Facebook Pinterest LinkedIn
Share
BySandeep Raut
Follow:
Founder & CEO at Going Digital - Digital Transformation, Data Science, BigData Analytics, IoT Evangelist

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

BI Case Study: Building an Open Data Portal

10 Min Read

“Pricing to Win” Makes Losers Out of Winners

4 Min Read
Image
AnalyticsBest PracticesCommentaryExclusiveKnowledge ManagementRisk ManagementSoftware

Technology Training Needs a Hands-On Approach

5 Min Read

Crying “Cyber Attack” in Illinois

4 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?