【正文】 Issues in Credit Risk Modelling Risk Management Symposium September 2, 2023 Bank of Thailand Chotibhak Jotikasthira 1 Overview ? BIS regulatory model Vs Credit risk models ? Current Issues in Credit Risk Modelling ? Brief introduction to credit risk models – Purpose of a credit risk model – Common ponents – Model from insurance (Credit Risk+) – Credit Metrics – KMV ? Model parison Bank of Thailand 2 Risk Management Symposium September 2023 BIS Regulatory Model Vs Credit Risk Models BIS RiskBased Capital Requirements All privatesector loans (uncollateralized) are subjected to an 8 percent capital reserve requirement, irrespective of the size of the loan, its maturity, and the credit quality of the borrowing counterparty. Note: Some adjustments are made to collateralized/guaranteed loans to OECD governments, banks, and securities dealers. Bank of Thailand 3 Risk Management Symposium September 2023 Credit Risk Models Credit Risk+ Credit Metrics KMV Other similar models BIS Regulatory Model Vs Credit Risk Models Bank of Thailand 4 Risk Management Symposium September 2023 Disadvantages of BIS Regulatory Model 1. Does not capture creditquality differences among privatesector borrowers 2. Ignores the potential for credit risk reduction via loan diversification These potentially result in too large a capital requirement!!!!! BIS Regulatory Model Vs Credit Risk Models Bank of Thailand 5 Risk Management Symposium September 2023 BIS Regulatory Model Vs Credit Risk Models Big difference in probability of default exists across different credit qualities. C r e d i t R a t i n g P r ob a b i l i t y of D e f a u l tAAA 0. 00 %AA 0. 00 %A 0. 06 %C r e d i t R a t i n g P r ob a b i l i t y of D e f a u l tBBB 0. 18 %BB 1. 06 %B 5. 20 %CCC 19 . 79 %Note: 1. Probability of default is based on 1year horizon. 2. Historical statistics from Standard Poor’s CreditWeek April 15, 1996. Bank of Thailand 6 Risk Management Symposium September 2023 BIS Regulatory Model Vs Credit Risk Models Default correlations can have significant impact on portfolio potential loss. KMV finds that correlations typically lie in the range to . 8% 8% BIS model requires 8% of total. 8% 8% Correlation = 1 Correlation = Actual exposure is only 6% of total. Bank of Thailand 7 Risk Management Symposium September 2023 BIS Regulatory Model Vs Credit Risk Models The capital requirement to cover unexpected loss decreases rapidly as the number of counterparties bees larger. Unexpected loss of counterparties 1 16 8% % Assumption: All loans are of equal size, and correlations between different counterparties are . Bank of Thailand 8 Risk Management Symposium September 2023 Current Issues in Credit Risk Modelling Adapted from “Credit Risk Modelling: Current Practices and Applications”, April 1999, by Basle Committee on Banking Supervision To pi c C o nceptua l Is s ues / C o ncernsD efi n i t i o n of ri s kSh o u l d cred i t ris k in cl u d e on l y defa u l t or b o t h defa u l t and rati n g mig rat i o n s ? Is th ere a materi al di fferen ce b et w een th e de fau l t mod e an d th e mark t o mark et mod e mod el s ?Ri s k dri v ers W h en do es defa u l t actu al l y occ u r? In th e th res h o l d mod el s , w h at ob s erv ab l e v ari ab l e sh o u l d be u s ed to repr es en t ab i l i t y to pay ?Mo d el con cep t Is th e mod el th at st art s from a p o o l of s i mi l ar lo an s or o b l i g o rs real i s t i c? Po o l ed dat a us u al l y hi d e cred i t sp eci fi c ri s k s .Pro b ab i l i t y d en s i t y fun ct i o nN o agre emen t on th e fami l y o f di s t ri b u t i o n s to us e. L o s s di s t ri b u t i o n is no t n o rmal 。 it empi ri cal l y has fat t er ta i l s .Co rrel at i o n of cred i t eve n t sH o w sh o u l d como v emen t amon g rati n g mig rat i o n s and defa u l t s be mo d el ed ? Imp l i ci t or ex p l i ci t ?Co n d i t i o n al V s U n co n d i t i o n alCu rren t l y , mo s t mod el s are u n co n d i t i o n al (in d ep en d en t from t h e st at e of eco n o my ). U s i n g th es e mod el s , ri s k can un d ers t at ed or o v ers t at ed dep en d i n g o n th e lo cat i o n w i t h i n th e bu s i n es s cyc l e?Bank of Thailand 9 Risk Management Symposium September 2023 Current Issues in Credit Risk Modelling Adapted from “Credit Risk Modelling: Current Practices and Applications”, April 1999, by Basle Committee on Banking Supervision To pi c P a ra m eter Speci fi ca ti o n Is s ues / C o ncernsL o s s gi v en d efau l t (L G D )L G D is rand o m。 hen ce, a di s t ri b u t i o n is nee d ed to repr es en t L G D . L ack of s en s i t i v i t y ana l y s i s w i t h resp ect to L G D . L ack of h i s t o ri cal dat a to val i d at e cu rren t l y us ed mod el s .Ri s k rati n g s , ex p ect ed defa u l t freq u en cy (E D F), an d mi g rat i o n p ro b ab i l i t i esIn det ermi n i n g E D F and mig rat i o n pro b ab i l i t i es , In t ern al rati n g sy s t ems may n o t be accu rat e or h av e en o u g h hi s t o ry . E D F and mig rat i o n pro b ab i l i t i es of p u b l i cl y trad ed bo n d s may n o t be accu r