The 2007/08 global financial crisis has reaffirmed the importance of liquidity risk. In the world of efficient financial markets with perfect information, banks could only fail if their underlying fundamentals are not good. In such markets, banks can always finance their liquidity demands by borrowing from wholesale markets. But, in the real world financial markets with asymmetry of information, banks will face difficulty obtaining funding if there are concerns about the solvency irrespective of their validity. Even well capitalized financial institution may not be able to maintain a sound balance between its near term cash inflows and outflows or alternatively may pay excess cost to achieve that balance.
Liquidity risk measures
Liquidity risk exposure is assessed with a gap analysis, where both the asset side and liability side of the balance sheet is profiled for liquidity position in various time bands. Aggregated relative measures such as funding ratios for a given duration can also be used. The short-term funding ratio estimates percentage of liabilities with maturity less than 31 days to total liabilities. The long-term funding ratios match the long term assets with long term liabilities.
Stress tests and scenario selections help identify and quantify potential liquidity problems. The scenario selection is the most crucial part of the stress testing; the scenarios should be “extreme yet plausible”. The other type of stress tests is “stress it until it breaks”. The scenarios can be identified by using historical data, expert judgment and bank specific reverse type assessment.
Basel III liquidity risk framework
The Basel Committee published the Basel III framework on liquidity risk regulation established two complementary minimum standards for funding risks namely Liquidity coverage ratio LCR and Net stable funding ratio (NSFR). Along with reporting criteria, Basel III also provided monitoring criteria including structural liquidity mismatch, funding concentration, unencumbered assets and market monitoring.
Liquidity coverage ratio (LCR)
The LCR guideline aims to improve the short term resilience of the banking system. It achieves this by ensuring banks hold a minimum level of unencumbered high-quality liquid assets (HQLA) to withstand an acute stress scenario lasting 30 days.
High-quality liquid assets (HQLA) can be immediately converted to cash without significant loss in value. The net cash outflow is defined as the total expected cash outflows less the inflows under stress scenarios for next 30 days. The implementation guidelines suggests 60% LCR reach by Jan-2015 and a progressive increase of 10% each year to reach 100% LCR by 2019.
Net Stable Funding Ratio (NSFR)
NSFR is meant to promote the resilience of the banking system over a medium time horizon. It incentivizes banks to fund their assets with more stable (longer term) sources of funds.
Where ASF is a fraction of equity and liabilities reliable over the next year under stress scenario; RSF is a fraction of assets which are expected to be funded with stable funding. To improve NSFR, banks can increase the ASF or decrease RSF. To increase ASF it is important for banks to decrease the reliance on wholesale unsecured funding and increase reliance on retail stable deposits or long term deposits. Similarly to reduce RSF, banks could focus on covered bonds or senior debt with good credit ratings. On the liability side banks need to change the composition of medium to long term liabilities. This transformation in the balance sheet might require changes in the business strategy. For example, changing the deposit mix more towards retail will improve NSFR but it will be difficult for pure play wholesale banks to do so unless they are ready to change their business strategy.
US liquidity risk regulation comparison with Basel III
The liquidity risk management qualitative principles are covered in the Dodd Frank Act as Enhanced Prudential Standards (EPS). On October 24, 2013, the Federal Reserve (Fed) released an inter-agency proposal for US version of LCR to complement EPS with the quantitative measures.
On the face of the comparison, Fed’s LCR proposal is considered to be more stringent than BCBS’s proposal. Another major difference is estimation of the Net Cash Outflows in stress scenario. The cash inflows can only offset a maximum of 75% of the outflows on a daily basis, whereas 75% offset criterion is applied on a 30 day basis.
The implementation guidelines for the Fed’s LCR proposal is more urgent compared to proposal by BCBS. US firms should meet 80% LCR by January 1, 2015 with an increase of 10% each year to reach 100% by January 1, 2017.
Planning for Liquidity Risk
Factoring in for liquidity risk is inevitable in any banking business model; the regulatory guidelines will help banks prepare well for liquidity stress events. For banks to successfully comply with regulations, they need to manage and control their data properly. It means banks need IT systems to capture and warehouse client data, transactions and positions. Banks should internally be aware of the contractual liquidity mismatches and behavioral aspects adjusted mismatches, funding concentration, funding ratios, stress test results, LCR and NSFR. Banks need tactical and strategic adjustments to cope with Basel III liquidity regulations. The liquidity regulation lead to increase in cost of funding, it is important for banks develop an optimal funding structure to improve profitability.
Liquidity risk has grown to be the most important aspect in bank risk management in the wake of recent financial crisis. The Basel III framework for liquidity risk regulation provides guidance for two complementary minimum standards – the LCR and the NSFR. These standards aim to improve the mismatches in asset and liability and prepare banks to face a liquidity stress scenario. These minimum standards have different levels of impact on different banking business models and pose tactical and strategic challenges to banks. Banks need to optimally manage their assets and liabilities to ensure its compliance and run profitably. It is essential for liquidity risk systems and processes to capture data from all the transactions and positions for all business segments and efficiently forecast the behavioral and contractual aspects of cash flows.