Tag: credit risk modelling

What is Credit Risk Modeling?

A large number of varying factors affect credit risk. This makes it harder to assess the credit risk of a borrower and with such large sums hanging in the balance, credit risk modelling becomes crucial.

Credit risk model involves utilising various data models in order to find out the probability of the loan being defaulted and also the impact of this default on the financial environment of the people lending the money.
Thus, institutions of finance depend on credit risk models to find out the risks where potential clients are concerned. Decisions regarding whether the loan is to be given and the amount of interest on the loan are made on the basis of the credit risk models that are being used.

With technological advancement, novel ways of credit risk modelling have been developed. The emergence of various kinds of risks and advancement in the economy today has served to affect the way in which credit risk modelling is done. Taking a credit risk course would make this topic a lot easier to comprehend while providing the person taking it with all the necessary tools to succeed.

Factors Affecting Credit Risk Modelling

From disruption of cash flow as well as a higher cost of collection to losing interest and principal, the risks of lending are of many kinds. Thus predicting the various risks in an accurate manner is important to prevent these from happening. While assessing credit risk, factors like the financial health of the customer and the effects of any default on both the lender as well as the borrower, the three important factors to consider are as follows:

1. PD (Probability of Default): This involves predicting and determining the probability of a borrower to commit a credit default.
2. Loss Given Default; This is in reference to the complete loss that the creditor will have to endure in case of default. This is a very crucial part of credit risk modelling.
3. Exposure at Default: This refers to the measure of complete exposure of a creditor at a particular time.

On taking a credit risk course, an in-depth understanding of the above-mentioned topics will be available to the person taking the course.

Topics in Credit Risk Modelling Right Now

After the financial crisis that took place recently, regulators have put into effect a large emphasis on decreasing expectation for support from the government. Instead, a larger focus is asked to be placed on bettering the management and assessment of credit risks by banks. The current topics being discussed right now regarding credit risk and the statistical implications of these are listed in brief below.

• Expecting governmental support when a matter of distress arises in banks: Using the special features of the credit swap market, it is found that government support has decreased towards banks in distress.
• Estimation of covariance matrices through the eyes of risk management in the market: This issue, for instance, comes from centralised credit default swap clearing. A large number of special functions in regard to the loss as well as an efficient visualization tool for assessment of estimators is what is being proposed. Regularisation would improve the overall performance of various portfolio variance models.
• Assessment and estimation of risks in pricing products: This would involve strategically picking mispriced products by a well-informed person when the measures are unknown. The total risk of estimation can be reduced.

Credit risk courses would help individuals to better understand these discussion points. A credit risk course would allow aspirants to excel in this field by providing them with all the required information.

Also Read: What is Credit Risk Modelling

Credit risk modelling is a financial concept where models are created to calculate the chances of a borrower defaulting on his credit repayment. An example is an individual who has taken a credit card in his name; the risk model will speculate if and how he will default on the monthly card payments. And if he does, the total amount that he owes and the total loss to the lender is also calculated.

The use of this type of models that are created using historical data to gauge the probability of a credit default is known as credit risk modelling. It is an important resource for banks and financial institutions to check the credit holding capacity of individuals and businesses. The goal is to prevent losses.

How Does Credit Risk Modelling Define Borrowers?

A risk model essentially divides customers (borrowers) into two types:

Bad borrower

• Has defaulted their payments several times over a short period of time
• Has filed for bankruptcy
• Last payment was more than 90 days ago
• Associated accounts being inactive

Good borrower
Anyone who does not fall under the ‘bad borrower’ category is placed here
It should be noted that this classification is general in nature. Different organizations have different credit risk models. In some cases, the calculation mechanism of the models can also differ.

How Does It Work?
Credit risk modelling uses two methods to estimate the probability of a defaulting. Here they are:
In Judgmental Method, several factors defining the borrower are assessed. These also help in creating credit scores.

• Credit history of the borrower
• The difference of assets and liabilities of the borrower
• Presence and value of the collateral such as property or gold
• External factors such as recession
• Borrower’s sources of income

Credit professionals look at these parameters to get an idea about the borrower. If none of the parameters yields a positive rating, the credit is usually denied.

On the other hand, in the Statistical Method, as the name suggests, statistics and historical data are used to conclude the credit capacity of a borrower. The advantage of this method is that it does not include the factor of bias in its calculation. Borrowers can be sure that they got an unbiased assessment.

Sources of Data for Credit Risk Modelling

Since it is not possible to collect data on a case-by-case basis, organizations depend on a variety of sources for this task. There are three main sources of data in this type of modelling:

• Demographic – Personal details that are easy to collect as the borrower will furnish them during application (loan or credit card)
• Individual History – The historical data about that specific borrower will be collected through partner agencies. If the borrower already has another account in the bank, this data and associated behaviour are also used
• Credit Bureau – Credit score and other details are sourced from a central database

Credit risk modelling helps banks and financial institutions keep their money lending processes in check. It is one of the most reliable methods to prevent fraud.

Also Read: What is Credit Risk Management