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 a lot of jobs supporting the IT functions. Salaries have increased tremendously in IT compared to other business areas. The 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 on the payments. This is where applying analytics for assessment of the risk of providing the credit came along and the birth of credit scoring.
Credit Risk is the risk of losing 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 the early days of lending businesses used to judge borrowers based on 5 Cs:
- The character of the applicant
- The capacity of the applicant to borrow
- Capital as backup
- Collateral as security for credit
- Conditions which were mostly external factors
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 customer's 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 messages 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 arrive at how much loss the company will incur, due to nonpayment 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 the cost of insurance product for a Customer
Today applying analytics to the data to get such insights is of prime importance.