Interest rates are rising and continued economic uncertainty, absolute time to be more structured and systematic liquidity precision. As inflation pressures continuing, central banks across the globe are heightening up interest rates and cramping monetary policies, forcing banks to contend with scarcer and more expensive liquidity this year and onward. Financials of different banks indicate, these forces have already reduced their liquidity coverage ratios (LCRs) and net stable funding ratios (NSFRs). Further deterioration will increase costs for funding, and that may have profound implications for operations and profitability.
Several proven steps banks can address the liquidity shortage for instance, through deposit pricing, active portfolio rotation, and corporate strategy. But these can be expensive or complicated to implement and may hurt the business by diverting resources and forcing changes in daily operations. In addition to such traditional levers, some banks are exploring an alternative way to address balance-sheet expense and funding issues: improving the accuracy of liquidity metrics and the calculation of liquidity positions. Improved liquidity accuracy can identify significant liquidity opportunities and thereby contribute to a bank’s profit and loss, at virtually no cost. These accuracy initiatives fall into three categories: regulatory accuracy (by ensuring the correct interpretation and implementation of the regulations for LCR and NSFR calculations), the accuracy of calculations (by ensuring good data quality and calculation processes), and accurate models. Because of the technical nature of these initiatives, they impose no significant costs on the business.
The benefits of improved liquidity accuracy are far from incidental and well worth the effort. Evidence shows that the typical impact is two to four percentage points for the LCR and one to three percentage points for the NSFR. Improving liquidity accuracy is a fairly low-cost way to tackle the funding problems, but banks can’t change ratios immediately. Further analysis shows that results typically appear in banks’ balance sheets after four to six months. Banks usually capture more than eighty percent of the potential after nine to 15 months.
Applicable guidance to improve their liquidity precision, may be (1) sprint-based work: The accuracy project should be organized in sprints, typically lasting six to eight weeks. The goal of each sprint is to explore a limited number of initiatives, prioritized by their potential impact. Typically, the sprints have a two-tiered governance structure for fast validation. One tier involves operational stakeholders (for regulatory interpretation, the calculation engine, and risk, among other things), and the other involves senior stakeholders in finance and risk up to the CFO and the chief risk officer (CRO). This structure ensures that decisions are made swiftly even on the most complex topics. (2) a light and expert team: Avoid committing too many bank resources.
Mobilize and empower a small project team with the mandate and knowledge to review the liquidity calculation chains end to end, from data sources to regulatory interpretations. Often LCR and NSFR engine experts and regulatory interpretation experts are supported by external experts who can help improve the status quo by providing a fresh, alternative view. (3) a collaborative approach: To build, analyze, validate, and implement initiatives, the relevant business teams (such as retail, corporate and investment banking, and markets), the metric production teams, and the regulatory teams collaborate closely at the request of the project team. The CFO, the CRO, and other organizational heads commit themselves to collaborate with the project team from day one to ensure internal alignment and the availability of dedicated resources. (4) a focus on implementation: Early in the process of analyzing initiatives but before validating them banks carefully consider the requirements and ramifications of implementation. This initial focus gives banks the time to mobilize the required resources and, potentially, to discard initiatives with low returns on investment.
Global markets are showing strains as investors have recently become more risk-averse amid heightened economic and policy uncertainty. Financial asset prices have fallen as monetary policy has tightened, the economic outlook has deteriorated, recession fears have grown, borrowing in hard currency has become more expensive, and stress in some non-bank financial institutions has accelerated. Bond yields are rising broadly across credit ratings, with borrowing costs for many countries and companies already rising to the highest levels in a decade or more. Emerging markets are confronting a multitude of risks, including high external borrowing costs, stubbornly high inflation and volatile commodity markets. They also face heightened uncertainty about the global economy, and policy tightening in advanced economies. At the same time, the ease and speed with which assets can be traded at a given price has deteriorated across some key asset classes due to volatile interest rates and asset prices. This poor market liquidity, together with pre-existing vulnerabilities, could amplify any rapid, disorderly repricing of risk, were it to occur in the coming months. Investors have so far continued to differentiate across emerging economies. While many frontier markets are at risk of sovereign default, many of the largest emerging markets are more resilient to external vulnerabilities to date. Having said that, after the stabilization of outflows in the first half of the year, foreign investors are again pulling back.
Uncertainty induces multifaceted unfavorable impacts on bank lending. Concretely, banks tend to restraint loan growth, suffer more credit risk, and charge higher lending rates during periods of higher uncertainty. Further investigation reveals that lending activities of banks with greater market power are less sensitive to adverse uncertainty shocks; in other words, increased competition in the banking system is associated with more substantial consequences of uncertainty on bank lending. Simultaneously having the impacts of uncertainty on quantity, quality and prices of bank lending.
Areas are to reduce costs and improve bank liquidity: strengthening bank liquidity starts with understanding where your money is coming from and where it might be going. Large sums of money potentially could flow out of banks, which would present a major liquidity problem if the banks have deployed the cash reserves on more loans. So the first question is, how much of this sudden influx of money will stay in the bank for the following periods. Unfortunately, that question will be very difficult to answer until it’s already too late which brings us to our next question: How can banks convert as much of this incoming cash as possible into core deposits that are sticky, retainable, and not interest-sensitive. Banks can assess new accounts and plan to capture long-term customers. Know where your new balances are coming from: While banks generally have improved their understanding of their customers, some still don’t do basic tasks involved with new accounts namely, examining where the money came in from. This is especially important in determining the expected retainability of a new account. Understand what kinds of “new” customers are getting: Next, it’s important to sort through the types of customers who are opening new accounts, especially those with bigger balances. Have many of them never banked with before, are substantial numbers of existing customers adding new services, are any of them former customers, also note the demographics: Have you suddenly added several depositors who are under 30 years old, getting that kind of information can help you discern who might be more receptive to adding new accounts and adding to existing ones.
TDM/MI
