rates are below the long - run average, and need for loan loss provisions are less. therefore, loan loss provisions are usually under - funded during a boom period. when the business cycle turns and economic conditions deteriorate, borrowers ’ credit quality tends to worsen leading to a higher probability towards default in servicing interest and principal payment. these loans become non - performing assets ( npas ). banks ’ profits go down but at the same time they are required to make higher loan loss provisions for the non - performing loans. this is the cyclical property of credit losses. this results in banks becoming cautious and restricts lending ; as a result the risk spills over to the real sector of the economy. procyclicality thus has the impact of amplifying business cycles. in terms of the accounting standard for recognizing credit losses, the ias 39 – financial instruments : recognition and measurement, a financial asset is impaired and impairment losses are incurred if and only if, there is objective evidence of impairment as a result of one bis central bankers ’ speeches or more events ( i. e., loss event / s ) that occurred after the initial recognition of the assets, and that loss event ( or events ) has an impact on the future cash flows of the financial asset that can be reliably estimated. this approach to provisioning, also known as “ incurred loss ” based approach waits for certain events to happen such as default, delinquency in interest or principal payments, significant financial difficulty of the borrower, etc., before losses can be recognized. provision for losses can only be made after the loss event has been identified, or loss has been incurred, and not in a proactive manner ex ante before the event, based on “ expected losses ”. the incurred loss model came under severe criticism after the recent global financial crisis for delaying loss recognition. there is a view that earlier recognition of loan losses based on “ expected losses ” could have potentially reduced the cyclical impacts of the recent crisis. however, accountants were not comfortable with the expected loss based provisioning on the fear that it could foster earnings management by profit smoothening and compromise the raison d ’ etre of accounting to give a “ true and fair ” or transparent picture of the financials of an entity as on the reporting date. improvements in credit risk models have supported the concept of expected losses and unexpected losses. from a conceptual point of view, loan loss provisions should cover expected losses while capital

a suitable framework for release of dynamic provisions will be formulated by rbi. in times when dynamic provisions have not been released by rbi, banks will not be allowed to dip into dynamic provisions if their profitability is not sufficient to accommodate the specific provisions. methodology adopted for calibration of alpha ( expected losses ) expected losses over next one year was calculated using basel ii irb formula i. e., pd * lgd. movement of npa data over 5 – 10 years was used to calibrate pd and lgd. alpha was calculated on a system wide basis for all the banks as well as for four asset classes, viz., housing, retail, corporates ( other than infrastructure and sme ) and others based on a sample of 9 banks comprising 32. 53 % of gross advances of scheduled commercial banks as on march 31, 2010. impact of the proposed framework while the impact of the proposed framework on individual banks was not assessed, on system wide basis, the provisioning charge on profit and loss account stood at 1. 37 % of gross advances annually. from the system - wide data collected at rbi, the average annual charge on profit and loss account on account of standard asset provision and specified provisions ( including write offs ) over the 8 year period ( from 2003 to 2010 ) amounted to 1. 04 % of gross advances. the additional charge is mainly attributed to calibration of alpha based on downturn lgd. bis central bankers ’ speeches issues some of the issues worth debating and considering while implementing dynamic provisioning are the following : data challenges for the calibration of alpha, apart from the “ bank as a whole ” data, data was called from all the banks in respect of 8 segments viz. infrastructure, commercial real estate ( cre ), small and medium enterprises ( sme ), other corporate, retail, housing, credit cards and others. however, useful data for the purpose of this study could be submitted only by 9 banks for retail, housing and other corporate ( corporate excluding infrastructure, sme and cre ). due to this, the study was limited to retail, housing, other corporate ( corporates excluding infrastructure, sme and cre ) and others ( which was a residual category ). ideally, alpha ( expected loss ) should be calculated for different loan segments which may exhibit different levels of riskiness and thus warrant a higher provisioning. calibration of alpha should be based on forward - looking through - the - cycle