Basel IV, which requires financial institutions to implement by 2022, makes more conservative restrictions on CCF. Understanding CCF behavior empirically is important for institutions to make reasonable CCF assumptions. For the unfunded part, one way is to use credit conversion factor (CCF) 2 to convert off-balance-sheet exposure to EAD. Usage can be used to estimate the exposure. For the funded part, institutions can look at the usage model for EAD estimation. Institutions thus need reliable estimation of EAD for both funded part and unfunded part of the loans throughout the life of the loans. Current Expected Credit Losses (CECL), introduced by Financial Accounting Standards Board (FASB) in 2016 and effective starting December 15, 2019, requires estimation of expected losses over the life of the loans, for both on-balance sheet and off-balance sheet items. Basel III’s liquidity coverage ratio, intended to ensure that banks have adequate funding sources relative to the total demand of cash outflows, includes credit line drawdown. Credit line usage also factors into banks’ liquidity management, as simultaneous drawdown on the credit lines by different borrowers can significantly affect both the asset side and the liability side of the balance sheet. Economic capital calculations require the assessment of the loss risk associated with credit line drawdown. Exposure at default (EAD), the usage estimation conditional upon default, enters into the regulatory capital calculation under Basel II, together with probability of default (PD) and loss given default (LGD). Understanding credit line usage patterns is important to banks, for many reasons and different applications. was USD$8 trillion, almost 44% of these institutions’ aggregate assets (USD$18 trillion). By the end of 2019 Q1, the unused commitment across all depository institutions in the U.S. 1, 2014.Ī major source of firm funding and liquidity, credit lines can pose significant credit risk to the underwriting banks. *An earlier version of this paper appears in the Journal of Credit Risk, Vol. Taken together, the results suggest that credit line usage is a function of both borrowers’ characteristics and banks’ monitoring and control of these lines. This pattern applies for both non-defaulted firms and defaulted firms. Further, we find evidence that usage ratios are higher during economic downturns. Usage ratios also vary by collateral type, commitment size, loan purpose type, and prior usage. We find that firms rated as “pass” grade by the lender draw down the credit lines less than those rated below “pass” grade. Riskier borrowers tend to utilize a higher percentage of their credit lines. They also increase their usage when approaching default. We find that defaulted borrowers draw down more of their lines than non-defaulted borrowers.
0 kommentar(er)
