The corporate road to credit portfolio management
According to Intrum Justitia, bad debts of more than € 350 billion were written off in Europe in 2013, which is around three percent of all outstanding transactions. Internal research into Dutch companies with debtor portfolios in excess of € 250 million reveals that some companies have had to write off up to 10 percent of their net result on their customers. According to some estimates, around 25 percent of companies actually go bankrupt due to bad debt losses alone. It is with good reason that many annual reports state that credit risks are often the biggest threat to business continuity. In this article, we explain our approach to credit risk management for corporates.
As well as weakening companies’ credit ratings, high bad debt losses are also a factor in the disintermediation of banks that has begun in recent years. This development is due in part to more stringent balance sheet requirements for banks, such as those imposed by the impending Basel III agreement.
The real sector is now increasingly self-financed as a result, which means that, at many companies, working capital is actually higher than it was a number of years ago. As a consequence of this, debtor risks are increasing. Further professionalization of credit risk management is therefore very important.
A company’s financial continuity is contingent on its profitability, solvency and liquidity. Consistent and transparent credit risk management that proactively supports sales is therefore critically important. Often, however, risk management is reactive and aimed primarily at collecting outstanding accounts receivable – which is of course extremely important, but the approach is not sufficiently proactive in terms of seeking to acquire solid, healthy customers.
Implementing and correctly using credit ratings is the first step towards effective credit portfolio management. The first thing to consider is linking credit limits to individual companies’ credit ratings. At portfolio level, concentration risks for each class of rating, industry and country can be used for steering purposes.
Implementing and correctly using credit ratings is the first step towards effective credit portfolio management.
The landscape is rather uneven on the whole: disparate in terms of stage, industry and country and the pace of implementation. Often, lots of different departments are responsible for the execution: treasury, local business units, working capital, finance, credit risk, etc. although there is a general trend towards more central coordination.
Good credit management requires good tools. A growing number of large corporates use rating models to measure credit risks. Usually, a rating model is based on a financial analysis and a business analysis. The financial analysis looks at quantitative variables relating to the customer’s business activities, liquidity, capital structure and debt service.
The values of the financial ratios are often compared with those for the business sector in which the company operates. The business analysis may cover various qualitative factors, such as the quality of the management, track record, accounting risk, industry prospects, etc. Unlike rating models, scoring models merely involve a basic financial analysis.
The resulting rating is directly linked to a PD (Probability of Default): the likelihood of non-payment measured in percent, or the likelihood that a borrower will default within a period of one year. If the EAD (Exposure at Default: the expected outstanding amount at default) and LGD (Loss Given Default: the expected loss as a percentage of the EAD in the event that the company is in default, dependent in part on any conditions and collateral) are also used in the analysis, this is known as a best-in-class approach.
The Expected Loss on an outstanding debtor is then the product of these three parameters; see example 1 in the box. The following paragraph explains how these tools and parameters are used.
A debtor with a rating of BBB3 has a PD of 0.44% on the Zanders PD rating scale. If the EAD estimate is €500,000 and no collateral has been furnished (i.e. LGD is 100%), the Expected Loss is €2,200.
In country “X”, the maximum exposure is €100 million; for industry “Y” it is €20 million; and for rating class “BB” it is €5 million.
Figure 1 illustrates how one of our clients uses ratings in the sales process. The portfolio concerned comprises more than 60,000 companies whose ratings are regularly updated. The horizontal axis represents the ratings ranging from very strong (AA) to very weak (C). The vertical axis shows the percentage distribution of customers, including defaults (dark green bar) for each rating class, over those rating classes. The top bar shows the decisions made (“Go”, “Yes, but” and “No, provided”). With a rating of B1 or weaker, limits may still be considered due to the mere presence of collateral (guarantees, credit insurance) and conditions (discounts, payment terms). For better ratings, collateral and conditions are relaxed or omitted. Weak companies are closely monitored. This system relies on efficient and transparent interplay between sales and risk management.
The key requirement is effective interplay between sales and risk. This can be illustrated by means of the credit cycle (see figure 2). In this combination, credit ratings can be applied in all kinds of ways to promote sustainable sales, a healthy debtor portfolio and improved working capital.
Firstly, ratings can be used when launching new products. This involves determining, for instance, which credit limits will be used in the credit cycle for each country, industry and rating class; see example 2 in the box. In a product range, the manner in which risk management supports sales in every phase of the cycle is meticulously defined.
When attracting new customers, credit ratings serve as a prospect filter. Selection at the gate is important in order to build a healthy debtor’s ledger. Account managers pay sales visits with preset credit limits, which enhances efficiency. Potential risks can be contained in advance by stipulating collateral and conditions, such as payment terms, in line with industry practice; see example 3 in the box.
One advanced approach is to include other financial risks in the prospect filter, as well as quantifying the credit risk. An example of this is RaRoS – Risk adjusted Return on Sales – whereby an implicit price is calculated for all financial risk categories which, combined with COGS (Cost Of Goods Sold), results in a risk-adjusted profit margin.
Because ratings are updated annually, the existing debtor portfolio can then be closely monitored and managed. Negative rating migrations serve as early warnings. Credit limits can be promptly revised downwards and, if necessary, collateral and conditions can be tightened up.
Conversely, an improvement may be cause to increase limits. Another option is to use concentration limits, which can be adjusted if necessary for certain industries or countries. A portfolio management dashboard enables the company to make timely adjustments.
With collections, ratings can be used to determine the tempo and techniques used when collecting debts for each debtor and for each industry. This is often done on the basis of aging criteria.
Further analysis on the basis of Expected Loss supports the prioritization process and, ultimately, helps reduce loan losses. This parameter can also be included in the selection and “price” in the event that debts are transferred to a collection agency.
Over the next few years, once it has been approved by the European Union, IFRS 9 is expected to be introduced in stages for banks and all listed companies in Europe. This means that, from that date, provisions for accounts receivable must be based on the aforementioned Expected Loss model rather than the current Incurred Loss model.
In the latter model, loan losses often come to light too infrequently and too late, a lesson taught by the credit crisis. Implementing the new model will have a major impact, including on balance sheet ratios. What’s more, it will make for better alignment between risk and finance. Annual figures will soon present a more accurate picture of the underlying risks. It is vital to prepare early for the new rules in a different landscape.
Implementing and using credit ratings is the first step towards credit portfolio management. Another, equally important step is determining whether the rating models are fulfilling expectations. Particularly when large numbers of customers are involved, it is necessary – and financially worthwhile – to validate models annually in light of their actual performance.
Another, equally important step is determining whether the rating models are fulfilling expectations.
An analysis based on back-testing ratings against actual defaults yields essential information that can be used to improve the model’s performance. Statistical tests can be carried out into aspects such as discriminating power (is there sufficient granularity, are customers with low credit ratings singled out?) and calibration: are the realized defaults (RDs) close to the expected PDs? A reliable model benefits the interplay between sales and risk.
The ultimate goal
Implementing a credit portfolio management framework helps reduce debtor losses, create greater consistency and transparency between sales and risk and improve speed and accuracy in business processes. It also translates into healthier turnover, lower operational costs, improved working capital and – ultimately – better business continuity.
Zanders Rating Advisory
Zanders Rating Advisory is aimed at financial institutions, corporates and the public sector. It provides the following services:
- The EAGLE corporate rating model, in partnership with Bureau van Dijk, linked to a financial database of more than 130 million companies worldwide. The FALCON scoring tool, also developed with Bureau van Dijk. Implementation of various types of rating models for rating SMEs, trade and commodity finance, project finance, etc.
- Transparent rating reports with peer and scenario analyses with respect to the rating of a company, bank, hospital, housing corporation, etc. The reports are used for a variety of purposes, including financing applications.
- Validation of rating models.
- Portfolio management dashboard.
- Implementation of rating systems and processes.