Credit Risk - Meaning, Example, Types, Modeling, Banks (2024)

What is Credit Risk?

Credit Risk is the probability of a borrower defaulting on debt obligations. Lenders risk not receiving the principal and interest component of the debt. This can result in an interrupted cash flow and increased cost of collection.

Financial institutions analyze the credit risk associated with each borrower to reduce losses and fraudulent activities. The term can be extended to other similar risks—a bond issuer may not be able to make payment at the time of its maturity, or an insurance company may not be able to pay a claim.

Table of contents
  • What is Credit Risk?
    • Credit Risk Explained
    • Types of Credit Risk
      • #1 - Default Risk
      • #2 - Concentration Risk
      • #3 - Country Risk
      • #4 – Downgrade Risk
      • #5 – Institutional Risk
    • Calculation and Formula
    • Credit Risk Example
    • Frequently Asked Questions (FAQs)
    • Recommended Articles
  • Credit risk is the uncertainty faced by a lender. Borrowers might not abide by the contractual terms and conditions.
  • Financial institutions face different types of credit risks—default risk, concentration risk, country risk, downgrade risk, and institutional risk.
  • Lenders gauge creditworthiness using the "5 Cs" of credit risk—credit history, capacity to repay, capital, conditions of the loan, and collateral.
  • The following formula is used to find the expected loss on debts:
    Expected loss = Probability of default × Exposure at default × Loss given default
Credit Risk - Meaning, Example, Types, Modeling, Banks (1)

Credit Risk Explained

A robust credit risk management predicts negative circ*mstances and measures the potential risks involved in a transaction. To manage risk, most banks rely on technological innovations. But these, risk management systems are very expensive. The system measures, identifies, and controls credit risk as part of Basel III implementation.

Credit Risk - Meaning, Example, Types, Modeling, Banks (2)

To determine the right amount that can be lent to a borrower, financial institutions use credit risk modeling. It is an alternative to traditional pricing techniques and hedging. Lenders use various models to assess risks—financial statement analysis, machine learning, and default probability. But, at the end of the day, none of the methods provide absolute results—lenders have to make judgment calls.

Types of Credit Risk

Credit risks are classified into three types:

#1 - Default Risk

It is a scenario where the borrower is either unable to repay the amount in full or is already 90 days past the due date of the debt repayment. Default risk influences almost all credit transactions—securities, bonds, loans, and derivatives.Due to uncertainty, prospective borrowers undergo thorough background checks.

#2 - Concentration Risk

When a financial institution relies heavily on a particular industry, it is exposed to the risk associated with that industry. If the particular industry suffers an economic setback, the financial institution incurs massive losses.

#3 - Country Risk

Country risk denotes the probability of a foreign government (country) defaulting on its financial obligations as a result of economic slowdown or political unrest. Even a small rumor or revelation can make a country less attractive to investors. The sovereign risk mainly depends on a country's macroeconomic performance.

#4 – Downgrade Risk

It is the loss caused by falling credit ratings. Looking at the credit ratings, market analysts assume operational inefficiency and a lower scope for growth. It is a vicious cycle; the speculation makes it even harder for the borrower to repay.

#5 – Institutional Risk

Borrowers may fail to comply with regulations. In addition to the borrower, contractual negligence can be caused by intermediaries between the lenders and borrowers.

Credit Risk - Meaning, Example, Types, Modeling, Banks (3)

Calculation and Formula

To gauge creditworthiness, lenders use a system called "The 5Cs of Credit Risk.”

  1. Credit history: Lenders look into borrowers' credit scores and check their backgrounds.
  2. Capacity to repay: To ascertain borrowers’ repayment ability, lenders rely on the debt-to-income ratio. It indicates efficiency in paying off debts from earnings.
  3. Capital: Lenders determine every borrower's net worth. It is computed by subtracting overall liabilities from total assets.
  4. Conditions of loan: It is important to determine if the terms and conditions suit a particular borrower.
  5. Collateral: Lenders assess the value of collateral submitted by borrowers. Collateralization mitigates lenders’ risk.

One of the simplest methods for calculating the expected loss due to credit risk is given below:

Expected Loss=PD×EAD×LGD

Here, PD refers to 'the probability of default.' And EAD refers to 'the exposure at default'; the amount that the borrower already repays is excluded in EAD. LGD here, refers to loss given default . If LGD is not given, it is calculated as ‘1 – recovery percentage.’

Credit Risk Example

Let us assume that a bank lends $1000,000 to XYZ Ltd. But soon, the company experiences operational difficulties—resulting in a liquidity crunch.

Now, determine the expected loss that could be caused by a credit default. The loss given default is 38%; the rest can be recovered from the sale of collateral (building).

Solution:

Given,

Exposure at default (EAD) = $1000,000

Probability of default (PD) = 100% (as the company is assumed to default the full amount)

Loss given default (LGD) = 38%

The expected loss can be calculated using the following formula:

Expected Loss = PD × EAD × LGD

Expected Loss = 100% × 1000000 × 38%

Expected Loss = $380000

Thus, the bank expects a loss of $380,000.

Frequently Asked Questions (FAQs)

What is credit risk analysis?

Risk analysis is the process of interpreting the credibility of borrowers. It ascertains repayment efficiency. The process determines the level of uncertainty involved with each borrower.

What are the most effective credit risk management strategies?

Effective risk management strategies include periodic MIS reporting, risk-based pricing, limiting sector exposure, and inserting covenants.

What is the best way to mitigate risk?

Following are four risk mitigation methods:
1. Staying clear of high-risk business activities.
2. Accepting risk and preparing for it.
3. Taking measures to reduce or control the impact of uncertainties.
4. Mitigating risk by acquiring insurance—transferring risk onto other entities.

Recommended Articles

This has been a guide to guide to what Credit Risk means. We discuss credit risk definition, types, modeling, analysis, banking, credit ratings, credit scores, risk mitigation, risk assessment & analyst jobs. You can learn more about financing from the articles below -

  • Country Risk Premium Formula
  • Credit Spread Calculation
  • Credit Analysis Ratios
  • Investment Risk
Credit Risk - Meaning, Example, Types, Modeling, Banks (2024)

FAQs

Credit Risk - Meaning, Example, Types, Modeling, Banks? ›

Credit Risk is the probability of a borrower defaulting on debt obligations. Lenders risk not receiving the principal and interest component of the debt. This can result in an interrupted cash flow and increased cost of collection.

What is credit risk modeling in banks? ›

Credit risk modeling is a technique used by lenders to determine the level of credit risk associated with extending credit to a borrower. Credit risk analysis models can be based on either financial statement analysis, default probability, or machine learning.

What is an example of a credit risk in a bank? ›

Credit risk is the biggest risk for banks. It occurs when borrowers or counterparties fail to meet contractual obligations. An example is when borrowers default on a principal or interest payment of a loan. Defaults can occur on mortgages, credit cards, and fixed income securities.

What is the best model for credit risk modelling? ›

For instance, a linear regression model can help predict the probability of default based on a borrower's credit score, income, and debt-to-income ratio. The model outputs a probability score, which indicates the likelihood of default. The higher the score, the more likely the borrower is to default.

What are PD, LGD, and EAD models? ›

Loss given default (LGD), probability of default (PD), and exposure at default (EAD) are calculations that help banks quantify their potential losses.

What is model risk in banking? ›

In financial services, model risk is the risk of loss resulting from using insufficiently accurate models to make decisions, frequently in the context of valuing financial securities, and becoming prevalent in activities such as assigning consumer credit scores, real-time probability prediction of fraudulent credit ...

What are the three categories of credit risk exposures? ›

Credit Spread Risk: Credit spread risk is typically caused by the changeability between interest and risk-free return rates. Default Risk: When borrowers cannot make contractual payments, default risk can occur. Downgrade Risk: Risk ratings of issuers can be downgraded, thus resulting in downgrade risk.

What are the three risk modelling methods? ›

Among assumptions, modeling also uses economic, statistical, and financial techniques to predict potential/maximum risk. Some people like to break modeling into three main types: quantitative, qualitative, and a hybrid version.

What are the three types of model risk? ›

Type A: model specification risk, Type B: model implementation risk, and. Type C: model application risk.

What are the disadvantages of credit risk modeling? ›

Credit risk modeling faces several challenges and limitations, including: Data quality and availability: The accuracy and completeness of the data used in the models are crucial for their reliability. Inadequate or inconsistent data can lead to incorrect predictions and misinformed credit decisions.

What are the different types of LGD models? ›

List of Statistical Loss Given Default Models
Model NameSimple / CompositeDynamic Factors
Censored Gamma RegressionSimpleObserved Covariates
Two-Tiered Gamma RegressionMixtureObserved Covariates
Beta RegressionSimpleObserved Covariates
Inflated Beta RegressionMixtureObserved Covariates
5 more rows
Sep 16, 2021

What are ECL models? ›

ECL are a probability-weighted estimate of credit losses. A credit loss is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive discounted at the original effective interest rate.

What is PD and LGD difference? ›

The likelihood of loss materialization is tied to the borrower's probability of default (PD) while the severity of loss in the event of default is accounted for the loss given default (LGD).

How do banks determine credit risk? ›

Lenders look at a variety of factors in attempting to quantify credit risk. Three common measures are probability of default, loss given default, and exposure at default. Probability of default measures the likelihood that a borrower will be unable to make payments in a timely manner.

What are the disadvantages of credit risk modelling? ›

Credit risk modeling faces several challenges and limitations, including: Data quality and availability: The accuracy and completeness of the data used in the models are crucial for their reliability. Inadequate or inconsistent data can lead to incorrect predictions and misinformed credit decisions.

How to manage credit risk in banking? ›

Best Practices for Managing Credit Risks
  1. Constantly evaluate your data sources. ...
  2. Validate your scorecard model consistently. ...
  3. Proactively monitor your model. ...
  4. Leverage dynamic data. ...
  5. Take advantage of artificial intelligence and machine learning. ...
  6. Prepare for financial crimes. ...
  7. Use today's top software.
Jun 12, 2024

What is credit risk capital modelling? ›

Credit risk capital modelling refers to the use of these models to gauge minimum requirements to set aside as a buffer against such losses. Banks permitted to use this family of approaches must measure two components: a borrower's probability of default, and the bank's own loss given default.

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