Explain Probability of default and briefly discuss its uses………………………………………………………(10)
The probability of default (PD) of a borrower or group of borrowers is the central measurable concept on which the IRB approach is built. The PD of a borrower does not, however, provide the complete picture of the potential credit loss. Banks also seek to measure how much they will lose should a borrower default on an obligation. This is contingent upon two elements. First, the magnitude of likely loss on the exposure: this is termed the Loss Given Default (LGD) and is expressed as a percentage of the exposure. Secondly, the loss is contingent upon the amount to which the bank was exposed to the borrower at the time of default, commonly expressed as Exposure at Default (EAD). These three components (PD, LGD, EAD) combine to provide a measure of expected intrinsic, or economic, loss.
Probability of Default Defined
According to Joseph (2013) probability of default is nowadays used in the selection of clients, monitoring of credit quality, allocation of capital as well as in better pricing of credit risk. By definition “probability of default refers to the statistical percentage probability of a borrower defaulting in most cases within a one-year period time horizon” (Joseph: 2013). It is important to take note that, probability of default is linked to credit risk grades. The probability of default ranges from nil to 100% in the event of a very high customer (Joseph: 2013). According to BBVA (2011) Probability of default measures the credit rating that is assigned internally to a customer with a goal of estimating the probability of default within a year.
Guiding factors in arriving at PD
According to Joseph (2013), the guiding factors at arriving at the probability of default include past data, historical trends, and external sources. The credit risk grades of the probability of default range from 1 – 20, where credit ratings between 1-12 resemble good quality, 13-16 represent risky assets, 17-19 shows a very high risk and 19-20 are default cases. “Higher credit risk grades (i.e., low quality) have higher PDs, reflecting higher credit risks. For example, a credit risk grade of 12 has a PD of 1.2% p.a. It means that the likelihood of a firm rated under this category defaulting is only 12 in 1,000 per year. A high-risk customer rated 16 has a PD of 7.44% – i.e., the likelihood of default is 74.4 in 1,000, per year” (Joseph: 2013).
Uses of Probability of default
As stated above the uses of the probability of default were highlighted and include the qualification of credit risk, allocation of capital, better credit risk pricing, client selection, and credit quality. These uses of the probability of default will be explained further below.
- Quantification of credit risk – According to Boris, Ivana, and Anna credit metrics models can be used to analyze and manage the credit risk of investment instruments portfolio and thus quantify the credit risk. In addition to this, the probability of default does help in distinguishing the credit risk of different asset classes and also assists in judging the creditworthiness of the obligor.
- Allocation of Capital – in allocating capital, the probability of default suggests that, if the probability of default is high capital allocation will also be higher.
- Better Credit risk pricing – a higher probability of default (PD) means a higher risk of default which means the risk premium has to be higher for example PD is the major risk driver in pricing credit default swaps.
- Client selection – the information from rating agencies like behavioral scoring and proactive scoring does provide a ranking of the customers and helps in screening the customers (BBVA: 2011). This information can be used by financial institutions as a benchmark in client selection.
- Credit Quality – According to BBVA (2011), reactive scoring can be used to forecast the credit quality of loan applications submitted by customers. In providing insight into credit quality, the probability of default enables financial institutions to monitor high-risk customers.
References
Joseph. C. 2013. Advanced Credit Risk Analysis and Management. John Wiley & Sons, Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom.
Internet Source.
BBVA. 2011. Probability of default (PD), Financial Report. Available and Access on 10/02/2021
https://shareholdersandinvestors.bbva.com/microsites/informes2010/en/Riskmanagement/ProbabilityofdefaultPD.html