Last updated on November 29th, 2021 at 10:58 am
Financial institutions around the globe manage and give loans to companies/businesses that need help. But hey have to manage the records of its clients and has to find out the possibility of non-payment. A good financial institution always has an expert team dedicated to this job.
They analyze the data/information of the clients and based on some attributes; they find out the trustworthiness factor on any particular client. This helps the bank to identify those clients who can ditch them in the future and thus they take measures accordingly.
In this article, let us discuss some famous methods which are widely used by people to calculate credit risk.
What is an Underwriting Model?
Underwriting is a structured process which is used by financial institutions/investors to find out the level/degree of vulnerability in terms of non-payment, late payment of dues can occur. It is a type of analytical job. It helps in reducing the chances of credit risk.
Let us discuss various types of underwriting which are widely used.
Widely used underlying models in credit risk
- Traditional approach – There are many sites and surveys which determine the potential of risk in different sectors. Agencies like S&P, Moody, etc. determine the level of credit risk in different sectors such as mortgage loans, industrial loans, education loans, etc. financial institutions use this data and view the potential of risk according to them only. There is no specialized analytics conducted at the workplace. Such an approach is not bad because these agencies are highly credited and certified.
- Rating based system – Its formula is the product of Probability of Default (PD), Exposure at Default (EAD) and Loss Given Default (LGD). It gives us the value of the expected loss. Expected loss = PD * EAD * LGD, Where, EAD is defined as the amount of credit given to any particular client. PD is defined as the low approval ratings and bad records which lead to the possibility of credit risk. For default companies, PD is 100%, LGD is the loss faced by the company/firm. A lot of analytical work is done in these types of approaches but they give more accurate results. Many financial institutions have dedicated workplaces and a highly valued job for credit risk analysts.
- Advanced rating system – It has two types which are as follows:Calculated internally in the bank whereas EAD & LGD are provided by the bank supervisors who can also use various existing frameworks provided by BASEL to determine these aforementioned attributes. A lot of analysis is based on algorithms in this method.Advanced IRB approach in which all the attributes are calculated internally by the Foundation IRB (Internals Ratings Based) approach in which PD is Bank but the work is mainly automated through good analytical models and frameworks.
The Five Fundamental C’s of Credit Risk
Five basic attributes are used across each model. These are the Credit history of the customer, Capital, Capacity of repayment, Collateral and Conditions of the loan. These C’s are manipulated into mathematical values and institutions find the potential/vulnerability of the credit risk from any particular customer. There are many accords and regulations such as BASEL III, IFRS 9, etc. which help in determining credit risk.
Conclusion
There are many types of fraud activities witnessed by financial institutions. To protect any such incidents, the institutions try to dig up about the client and conclude that if he is eligible for the loan or not. He will get the loan only if the approvers think that he/she can repay in due time.
This protects banks /investors from losses. There is a credit rating for each borrower which fluctuates based on his repayment. If he/she fails to repay, his credit ratings may go below and he/she may be denied a loan in the future. This article was all about widely used models for determining credit risk.
