TY - THES ID - 146386739 TI - Impacts of Basel III finalised regulations on banks and their credit risk assessment AU - Arcadipane, François AU - Artige, Lionel AU - Hübner, Georges AU - Di Bartolomeo, Jean-Pierre PY - 2019 PB - Liège Université de Liège (ULiège) DB - UniCat KW - Basel IV, Bâle IV KW - Credit risk KW - Banks KW - Regulation KW - Finance KW - Sciences économiques & de gestion > Finance UR - https://www.unicat.be/uniCat?func=search&query=sysid:146386739 AB - Executive summary: The BCBS crusade to eliminate the scars of the 2007-2009 financial and economic crisis continues with the new Basel III finalised framework which will be set in place by 2022. This new regulation brings a series of novelties and review of existing mechanisms under the Basel III regulation. Indeed, it will revise the operational risk and market frameworks as well as the leverage ratio requirements. However, the most controversial measures are identified as the setting up of an output ratio for all IRBs assessment methods and the proposal of more constrained IRBAs for credit risk RWA calculations. The scientific working papers available on the potential impacts which will be caused by the new Basel regulation by 2022 are very scarce. The research carried out by the author aims at determining the aftermaths of the input floor policy on the bank risk appetite, competitiveness and portfolio composition. To do so, the most significant 25 European G-SIBs were selected based on the asset size criterion. Then, they were divided into 3 business model: universal bank, retail bank and wholesale bank. An overview of the breakdowns of their exposure portfolio, credit risk RWA and application of IRBAs methods has been done based on the data retrieved in the pillar 3 disclosure reports required by the CRD IV and CRR. When assessing the impact of the increase of the input floors, we observed an increase in the RWA amount even after having subtracted the scaling factor reduction. Moreover, the lower the maturity, the more significant the augmentation in RWA was. The relative results were very homogenous, meaning that the different correlation formula have an impact on the absolute amounts, but the variation proportions are well preserved by the IRBA RWA formula from an exposure class to another. Then, variations of RWA due to LGD and EAD floors were considered. The relationship between those risk parameters and the RWA amount was forecasted as to have a linear impact on the RWA amount when their value is below the different thresholds. With these results, we determine that UL and risk weight density will be the main drivers of credit portfolio and will trigger the decision to shift from a lending strategy to another. The risk of a credit crunch for safest exposures exists as banks will consider the input floors as an incentive to take more risk. ER -