Dependent Variable

Net Stable Funding Ratio:

In the aftermath of the US 2007 subprime loan crisis, the need for improved bank liquidity management practices, drew increasing regulatory attention. To address these requirements, the Basel Committee on Banking Regulation and Supervision (BCBS) proposed several international guidelines for banks to assess their liquidity position (BIS, 2009). Among them, the Basel III accords include the implementation of NSFR across the globe. This ratio is a micro- prudential measure of maturity transformation risk that limits the banks to excessively rely on un-stable short-term funding (Arvanitis & Drakos, 2015). In other words, it proposes managing the bank's liquidity position over a one-year period by introducing continuous structural changes in the bank’s balance sheet, to fund their activities with more stable funding sources.

In an attempt to harmonize the robust management and monitoring of liquidity risk in the Islamic banking industry, across the Islamic jurisdictions, the Islamic Financial Services Board (IFSB) endorsed the Basel III liquidity regulations, with some modifications to the criteria to calculate the NSFR, to account for the unique asset and liability structure of Islamic banks. IFSB issued the Guidance Note No. 6 (GN-6), to calculate the net stable funding ratio for Islamic banks (IFSB, 2015).

Similar to the conventional banking system, the NSFR (under the IFSB’s guidelines), is a ratio of the available amount of stable funding to the required amount of stable funding. The available amount of stable funding constitutes bank capital, liabilities with residual maturities

of one year or more, and stable deposits.8 _{The required amount of stable funding is the value} of bank assets that are difficult to liquidate or utilize as collateral in secured borrowing, during liquidity stress conditions, over a one-year period.

The net stable funding ratio is calculated as:

𝑁𝑆𝐹𝑅 =𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑙𝑒 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑓 𝑠𝑡𝑎𝑏𝑙𝑒 𝑓𝑢𝑛𝑑𝑖𝑛𝑔

𝑅𝑒𝑞𝑢𝑖𝑟𝑒𝑑 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑓 𝑠𝑡𝑎𝑏𝑙𝑒 𝑓𝑢𝑛𝑑𝑖𝑛𝑔> 100% (3.4)

To calculate the available amount of stable funding (ASF) and required amount of stable funding (RSF) utilizing the IFSB guidelines, each of the assets and liabilities categories are assigned appropriate weights. For example, to calculate RSF factor, the highly liquid assets (cash) receive a weighting of 0%. A 100% weight is assigned to highly illiquid assets (fixed assets). For the ASF factor, the weights assigned to funding sources depends on their stability and ranges from 100% for total regulatory capital (excluding Tier 2 with residual maturity less than one year) to 0% for net Sharı’ah-compliant hedging instruments. A detailed breakdown of the proposed weights assigned to the respective balance sheet items of Islamic banks is provided in Appendix Table A.1.

Although the IFSB’s GN-6 provides comprehensive quantitative guidelines, the major limitation in calculating the NSFR is the lack of available granular data on liquidity risk reporting across Islamic banks. Most of the NSFR related studies in the recent past, use the approximation method to assign weights to various balance sheet items, while calculating the NSFR utilizing Basel III guidelines (Giordana & Schumacher, 2011; Gobat, Yanase, & Maloney, 2014; Hong et al., 2014; King, 2013). These assumptions are in line with broader interpretations of corresponding assets and liabilities, giving due consideration to their liquidity and maturity profile. Following the conventional approach, to compute the NSFR variable, we made the following assumptions in regard to liquidity and the maturity of various balance sheet items of Islamic banks, according to Ashraf et al.’s (2016) methodology.

8A portion of non-maturity deposits and term deposits, with effective maturities of less than one year, are expected

a) The conservative approach is applied when treating the financing. A weighting of 85% is assigned to all financing with a residual maturity of less than 1 year, while a weighting of 100% is assigned to all other financing with a residual maturity of more than one year.

b) Since the classification of encumbered and unencumbered assets and high-quality liquid assets (HQLAs) is not available in most of the publicly available data, we assigned a 5% weight to investment in government securities, consistent with the GN-6 NSFR, and a 50% weighting to all other securities with a maturity of more than one year. c) A 100% weight is assigned to all other assets, including fixed assets financing to

financial institutes with a residual maturity of more than one year and 5% to the off- balance sheet items.

d) We also assumed a 100% weight for total regulatory capital.

e) A 50% haircut is applied to all non-remunerative deposits and funding from financial institutions with a residual maturity of less than one year.

f) Because of the limitation in publicly available data on the classification of stable and unstable deposits, we utilized the maturity disclosure of banks’ funding. A factor of 95% is assigned to all deposits with a residual maturity of more than one year and a 90% factor is assigned to deposits with a residual maturity of less than one year, consistent with the GN-6 guidelines.

Equation 3.5 shows the mathematical from of the NSFR (IFSB, 2015), as follows:

𝑵𝑺𝑭𝑹 = [𝟎. 𝟓 ∗ (𝐝𝐞𝐦_𝐝𝐞𝐩𝐨𝐬𝐢𝐭 + 𝐬𝐭_ 𝐦𝐚𝐫𝐤𝐞𝐭_𝐝𝐞𝐛𝐭 + 𝐨𝐭𝐡𝐞𝐫_𝐬𝐭_𝐥𝐢𝐚𝐛) + 𝟎. 𝟗𝟎 ∗ (𝐝𝐞𝐩 < 𝟏 𝐲𝐞𝐚𝐫) + 𝟎. 𝟗𝟓 ∗ (𝐝𝐞𝐩 > 𝟏 𝐲𝐞𝐚𝐫) + 𝟏 ∗ (𝐥𝐭_𝐦𝐚𝐫𝐤𝐞𝐭_𝐥𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 + 𝐫𝐞𝐠_𝐜𝐚𝐩)] [𝟎. 𝟎𝟓 ∗ (𝐠𝐨𝐯_ 𝐬𝐞𝐜 + 𝐎𝐁𝐒) + 𝟎. 𝟓 ∗ (𝐥𝐭_𝐦𝐚𝐫𝐤𝐞𝐭𝐚𝐛𝐥𝐞_𝐚𝐬𝐬𝐞𝐭𝐬 + 𝐟𝐢𝐧_𝐅𝐈𝐬 < 𝟏 𝐲𝐞𝐚𝐫) + 𝟎. 𝟔𝟓 ∗ (𝐫𝐞𝐚𝐥_𝐞𝐬𝐭𝐚𝐭𝐞 > 𝟏 𝐲𝐞𝐚𝐫) + 𝟎. 𝟖𝟓 ∗ (𝐜𝐨𝐧𝐬𝐭_𝐥𝐨𝐚𝐧𝐬 < 𝟏 𝐲𝐞𝐚𝐫) + 𝟏 ∗ (𝐜𝐨𝐧𝐬𝐭_𝐥𝐨𝐚𝐧𝐬 > 𝟏 𝐲𝐞𝐚𝐫 + 𝐨𝐭𝐡𝐞𝐫_𝐥𝐨𝐚𝐧𝐬 + 𝐨𝐭𝐡𝐞𝐫_𝐚𝐬𝐬𝐞𝐭𝐬 + 𝐟𝐢𝐱𝐞𝐝_𝐚𝐬𝐬𝐞𝐭𝐬)] (3.5)

A higher value of NSFR corresponds to more stable funding available than the required amount of stable funds, in which case the banks find less difficulty in meeting their current liquidity obligations. Whereas, the lesser value of this ratio refers to the extent of a bank’s inability to meet unexpected customer withdrawal requirements, without borrowing money from external sources or fire selling assets at a discount, consequently exposing them to an increased maturity transformation risk (Roulet, 2011).