Probability of Default

Probability of Default

The probability when a borrower or debtor defaults on loan repayments, is termed as the Probability of Default (PD). In financial markets, the asset’s probability of default is the probability that the asset yields no return to its holder over its lifetime and the asset price touches zero. This is used by investors to calculate the expected loss from an investment.

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What does it indicate?

Sometimes people encounter the concept of default probability when they purchase the property. When a homebuyer applies for a loan on a piece of real estate, the person/ organization giving the loan makes an assessment of the buyer’s default risk, which is based on their credit score and financial resources. The higher the estimated probability of default, the greater is the amount of interest rate that will be offered to the borrower.

For businesses, it is based on their credit rating. It may also be estimated using some historical data and statistical techniques. Probability of Default is used along with “loss given default” (LDG) and “exposure at default” (EAD) in various risk management models to estimate possible losses faced by lenders. Usually, the higher the default probability, the higher the interest rate the lender will charge the borrower.

Method of Estimation:

A probability of default (PD) is already assigned to a specific risk measure, per guidance, and represents the percentage expected to default, measured most frequently by going through the past dues. Loss given default (LGD) helps to measure the expected loss, net of any recoveries, expressed as a percentage and will be unique to the industry or segment.

When combined with the variable exposure at default (EAD) or current balance at default, the expected loss can be calculated using:

Expected Loss = EAD x PD x LGD

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  • Financial institutions usually use several steps of the probability of default (PD) analysis for credit risk processes, and each use-case provides a different benefit to the bank that directly impacts its workflow efficiency, credit decision quality, and most likely profitability.
  • A PD analysis can be an effective way to perform pre-screens before any financial statements have been spread. Lenders can analyze a business in a few minutes and quickly see if the loan could be worthwhile (yes) or if they should quickly pass (no). These pre-screens help in reducing strain on the credit department.
  • It helps provides management with a tool that helps them perform a deeper and more objective analysis when making credit decisions.
  • Similarly, a financial institution uses a probability of default model to validate its risk rating process. For a loan that may be lying between ratings, a calculated PD for a business could help provide additional clarity with respect to its appropriate rating.

Bottom Line:

When evaluating the risk attached with lending money to a prospective customer, various criteria, like revenues, operating margin trends, and cash flows with respect to the company’s debt should also be considered when determining the probability of default. It is a great measure and should be used frequently.

Author: Mahek Medh

About the Author: Currently, I am in my second-year bachelor’s program and over the period of time I have realized that I enjoy learning about numbers and money, and I find topics of Finance to very interesting thus this is the domain and space where I wish to etch my long term career.

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