State Bank directs IBIs to adopt AAOIFI Shariah Standard

  • The failure to comply with these instructions may invoke penal action under the provisions of Banking Companies Ordinance 1962, said SBP.
02 Sep, 2020

The State Bank of Pakistan (SBP), with a view to further strengthen Shariah compliance framework and harmonize the Shariah practices in the Islamic banking industry, has adopted the AAOIFI Shariah Standard No. 49 - Unilateral and Bilateral Promise (SS – 49) with immediate effect.

The adoption of the 'Accounting and Auditing Organization for Islamic Financial Institutions' (AAOIFI) Shariah Standard(s) is in addition to current regulations, other instructions and directives issued by SBP from time to time.

The failure to comply with these instructions may invoke penal action under the provisions of Banking Companies Ordinance 1962, said SBP.

Guidelines on Stress Testing

The central bank on Wednesday released a revised suite of Guidelines on Stress Testing, which replaces the earlier guidelines issued in 2012. Stress testing is a key tool used globally by banks for risk management and capital planning.

Accordingly, the revised guidelines will further strengthen the risk management capacity of the banks, Development Finance Institutions (DFIs) and Micro-Finance Banks (MFBs), in line with evolving international best practices and changing local economic and financial dynamics. The scope of revised guidelines has been broadened to incorporate guidance on Macro-stress Testing (MST), besides the Sensitivity Analysis (SA) with an enhanced number of shock scenarios.

In terms of coverage, besides banks/DFIs, the Islamic Banks/Islamic Banking Branches (IBs/IBBs) and MFBs will also perform SA exercise. Further, the Domestic Systemically Important Banks (D-SIBs) will be required to conduct MST annually, which will facilitate in improving the supervision and monitoring of these large sized banks. Moreover, the data submission requirements have been rationalized and financial institutions will now be required to furnish data on a minimal number of variables.

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