Downturn LGD Study 2020 Corporates, Banks and Non-Bank Financial Institutions A statistical examination of the downturn October impact on credit losses to inform COVID-19 2020 assessment Downturn LGD Study 2020 This Global Credit Data (GCD) study looks into the historical effects of previous downturns on bank credit losses across various debtor types, industries and regions, with a view to helping banks understand not only the high-level impacts of a downturn, but also how credit risk drivers are impacted, including sector specific impacts across different portfolio types. Combined with banks’ independent inputs for key risk drivers – including macroeconomic forecasts, portfolio biases, and the differences between the current and previous crises – the data in this report equips banks with the fundamental tools necessary to make accurate adjustments to their credit loss estimates for the COVID-19 crisis. Global Credit Data Contributors: Nina Brumma, Head of Analytics and Research Nunzia Rainone, Analyst & Member Support Executive Richard Crecel, Executive Director Contact: [email protected] contents ABOUT GLOBAL CREDIT DATA ..................................................................................3 WHAT IS LOSS GIVEN DEFAULT? ............................................................................4 FOREWORD .............................................................................................................................5 EXECUTIVE SUMMARY ...................................................................................................6 COVID-19 VS. THE GLOBAL FINANCIAL CRISIS: FACTORING IN THE VARIABLES .................................................................................................................... 7 REFERENCE DATA SET ...................................................................................................9 DOWNTURN EFFECTS ON GCD HISTORICAL DATA - CORPORATES .....................................................................................................10 DOWNTURN EFFECTS ON LGD FOR BANKS AND NON-BANK FINANCIAL INSTITUTIONS ............................................................20 CONCLUSION ...................................................................................................................... 22 FAQS .......................................................................................................................................... 23 GLOBAL CREDIT DATA | PAGE 3 About Global Credit Data Global Credit Data (GCD) is a non-profit In 2009, GCD introduced a PD database association owned by 50+ member which now has over 15 years of default banks with the simple mission to help rates and PDs. GCD also runs a name banks better understand and measure and cluster benchmarking database to their credit risks through data pooling help banks calibrate and benchmark and benchmarking activities. GCD’s their PD, LGD and EAD models. data pools support the key parameters of banks’ credit risk modelling: Probability GCD operates all databases on a “give of Default (PD), Loss Given Default to get” basis, meaning that members (LGD), and Exposure at Default (EAD). must supply high-quality data to receive data in return. The robustness of GCD’s GCD started collecting historical loss data collection infrastructure helps data in 2004, offering exclusive access to place GCD’s databases as the global its member banks. These banks receive standard for credit risk data pooling. the detailed anonymised database and can therefore confirm results and www.globalcreditdata.org test them on customised sub-sets of data. The LGD database now totals over 230,000 non-retail defaulted loans from around the world to approximately 130,000 borrowers covering 11 Basel asset classes. GLOBAL CREDIT DATA | PAGE 4 WHAT IS LOSS GIVEN DEFAULT? Loss given default (LGD) reflects how much money a bank or other non-bank financial institution loses when a borrower defaults on a loan, expressed as a percentage of total exposure at the time of default. LGD is one of the key factors used to calculate expected credit losses and Advanced Internal Ratings-Based (AIRB) regulatory capital along with probability of default (PD) and exposure at default (EAD). GCD’s LGD data set What’s new with LGD? GCD’s LGD data set comprises over Requirements for accurate credit loss and 230,000 non-retail defaulted loan facilities LGD modelling have been significantly from around the world, encompassing increased by developments in regulation approximately 130,000 borrowers and 11 and standards over the last several Basel asset classes. Collected since 2004, years. Business usage of acute pricing the data details the resolution of defaults information can also provide valuable from 2000 to 2017, the best part of two insights in competitive markets. Both decades – taking in numerous sector regulatory capital frameworks, impairment shocks, as well two major crises, the dot- frameworks (such as IFRS 9 and CECL) com crash and the global financial crisis. and stress-testing frameworks (CCAR) created a need for detailed default and The quality of this data set is ensured loss data. Investors, regulators and by GCD’s high standards for inputs from accountants require banks to be able member banks. The effectiveness of this to project expected and unexpected approach is underlined by the data’s loss levels under different scenarios. consistency over time. GCD has published Both banks’ business as well as their updated LGD reports every year for the capital holding strategies are significantly last three years, alongside a Downturn influenced by these calculations. Banks LGD Study in 2013 and 2017, adding new benefiting from GCD’s consistent data from each year gone by, as well as information exchange and wealth of additional data from new member banks. data are also able to fine-tune their final The extra three years of robust data in this estimates via benchmarking. latest study add further depth and rigour to our time series analysis. GLOBAL CREDIT DATA | PAGE 5 forewOrd These are turbulent times for banks and them unique to their business – from their their credit risk teams. Record-high loss macroeconomic projections to the unique provisions have become headline news exposures of their portfolios. In combination, as institutions look to fortify their positions these can help form a sensitive estimate of against the fallout from the COVID-19 the impacts on their own business. pandemic, adding extra pressure to the teams responsible for calculating the likely For all the uncertainty, statistical analysis losses on their bank’s portfolios. of historical observed LGD is still by far our best tool for determining future estimates. Global Credit Data exists to help banks With this in mind, we offer our Downturn get these calculations right. To this end, LGD Study, in the hope that it can form part we recently released our LGD Report of the raw material from which banks can 2020 for Large Corporates, detailing the form their own accurate projections and help long-term average loss given default steer a course through today’s challenging (LGD) for banks on loan portfolios to large landscape. corporates. Covering the full workout of two previous crises (the dot-com bubble of 2001-2002 and the global financial crisis of 2008-2009), this data helps shed valuable light on what banks can expect in terms of recoveries. Richard Crecel Now, with uncertainty still surrounding Global Credit Data the duration and impact of the pandemic Executive Director – as well as the continued provision of government support and the possible development of a vaccine – we are looking to go a step further with this, the Downturn LGD Study 2020. This study looks specifically at the historical effects of previous downturns on bank credit losses across various debtor types, industries and regions, with a view to helping banks understand not only the high-level impacts of a downturn, but also some of the sector- specific impacts across different types of portfolios. Of course, moving from historical observed LGD rates to future losses requires further inputs and judgement calls. Building on the data in this report, banks must also factor in a range of variables, many of GLOBAL CREDIT DATA | PAGE 6 highly unlikely to be successfully resolved EXECUTIVE SUMMARY during a crisis, but also because banks tend to adjust their workout strategies in a crisis This report examines a topic that has been – for example, they may hold on to collateral thrown into the spotlight in recent months for longer in order to sell during the recovery by the outbreak of COVID-19 – namely, how at a better price. For this reason, the analysis bank credit losses are affected by economic shows a greater alignment between crisis downturns. In particular, it focuses on loss years and LGD values when looking at the given default (LGD) – the amount a bank peak cash flow date – the centre point of loses after a customer defaults – and how recovered cash flow – rather than by the this is affected by downturns. time the default was incurred. The report analyses two global reference Of course, there are many other factors data sets (RDSs): one for corporates that affect how a given loan or portfolio is comprising 86,583 defaulted loans, and affected by a downturn. This study explores another for banks and non-bank financial GCD’s historical data set, assessing the institutions (FIs) containing over 2,000 downturn effects on corporate debt – defaulted loans. As with the Global