![]() ![]() These factors are typically ratios such as liquidity, sales growth, operating expense ratios, and so on. These systems were developed using banks’ historical charge-off experiences-with the help of credit and lending experts-to relate certain quantitative ratios and qualitative factors to the expectation of loss. This new system would allow you to enjoy the benefits from an origination and portfolio management standpoint as outlined above.Įxpert judgment-based risk rating systemsĪn expert judgment risk rating system (ERR) is not entirely based in statistical methods. Then, we will look at a typical implementation path for moving from a simple system that relies only on expert judgment to one that adds empirical rigor and separates borrower and facility risk. Let us take a step back to understand what expert judgment and dual risk rating systems are and how they differ. Also, the information for mitigation strategy to focus on either collateral or borrower deficiency is lacking. The ability to understand which firms would be affected more than others is very limited within these types of rating systems. These scorecards lack the granularity to differentiate loans from businesses that are experiencing acute stress due to the economic turmoil from those with more fundamental weaknesses. ![]() Normally in such times, a rating system based on expert judgment can result in overly short pipelines as only the safest borrowers, based on your experience, gain approval. Using a DRR system would show a more detailed picture, allowing more flexibility to mitigate risk.įor origination processes, while expert judgment-based scorecards have worked well for many firms in the past, they could fall short during times of stress. ![]() Both situations might have a similar impact on expected loss and so would result in a similar master rating. However, current business conditions could remain strong, so the probability of default would stay the same, leading to unchanged expectations in terms of expected loss. Alternatively, economic turmoil could have a pronounced effect on one asset class in particular, increasing facility risk. At the same time, the asset securing the loan may retain its value so recovery expectations should not change. Liquidity issues can endanger cash flows from the borrower, which increases default risk. Importantly, these differences are accentuated during times of stress. 1 This allows more time to react when a loan becomes stressed, as the factors that affect default can be different than those that affect recovery. The purpose of this paper is to describe at a high-level how a DRR system makes each of these tasks easier for institutions that have relied on expert judgment systems, without focusing on specific asset classes.įor portfolio management, separating borrower and facility risk means moving from a system based on expected loss or charge-offs to one that informs both default and recovery, preferably based on empirical methods. Both of these tasks are made easier with a dual risk rating (DRR) system, which combines expert judgment with an empirical foundation that splits borrower and facility risk. A secondary consideration is to plan for your next origination. Figure 1 shows probability of recession worldwide within the next reporting cycle under the Moody’s Analytics forecasted COVID-19 pandemic scenario.Īside from ensuring that your bank has sufficient liquidity to navigate the crisis, understanding the impact of the crisis on your current portfolio is of primary importance. The coronavirus (COVID-19) has caused widespread economic disruption and, combined with the drop in oil prices, pushed us much closer toward recession-if we are not already in one. Our recommendations can help you improve capital allocation by using analytics to supplement expert judgment, particularly during periods of duress. We will describe at a high-level how a dual risk rating (DRR) system makes each of these tasks easier for institutions that have relied on expert judgment systems, without focusing on specific asset classes. In this paper, we explore risk rating options and advise what you can do now to enhance your origination process. Additionally, a rating system based on expert judgment may not have provided loan officers with the necessary evidence to get approval, whereas an empirical system would have satisfied credit committees. Institutions that lacked efficient risk rating systems were not given enough information to differentiate between borrowers unless the applicant was so clearly creditworthy as to overcome the uncertainty. The result was very low origination volumes and the rejection of creditworthy applicants, often because the threshold for approval was set too high in an effort to inoculate against the uncertainty caused by market turmoil. ![]()
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