Liquidity management in banking: Definition, ways to improve, benefits

March 2023 saw the biggest bank failure since the 2007-2008 financial crisis. In just two days, Silicon Valley Bank (SVB) failed following a run on deposits. The resulting panic took down Signature Bank, as well. It also put the final nail in the coffin of Credit Suisse, which was forced into an acquisition by UBS, its rival. 

This story can teach banks of all sizes a valuable lesson — how not to manage their liquidity. SVB put its money into federal bonds without properly diversifying its portfolio. When its clients rushed to withdraw their funds, SVB had to quickly transform those bonds into cash — and the deal cost the bank $1.8 billion in losses. 

In any period of turmoil, no bank is safe from a panic-induced run on deposits. So, how should banks approach liquidity management? 

Let’s break it down, starting with a definition of liquidity management. In banking, it’s the ensemble of actions banks take to mitigate liquidity risks. The purpose of liquidity management is to allow an organization to meet its short-term financial obligations promptly and without substantial losses. 

Liquidity management in banks is crucial for multiple reasons. Investors use accounting liquidity to assess a bank’s financial health, for one. As March 2023 also demonstrated, external panic-inducing events out of a bank’s control can cause a run on deposits at any time. 

What characterizes sound liquidity management? 

• Continuous tracking of all incoming and outgoing cash flows 
• Diversification of revenue streams and investment portfolios to include highly liquid assets 
• Unceasing overview of receivables and liabilities 
• Precise, detailed and constantly updated liquidity and contingency funding planning

Old approaches to liquidity management may not be as efficient as they once were. 

Fortunately, new technology in the field opens up better ways to ensure liquidity: 

Without anticipating cash flows accurately, it’s impossible to predict a bank’s financial standing in the future. So, executives can’t allocate inflowing cash to long-term investments without second-guessing their decision. A bank also risks being unprepared for foreign exchange volatility and finance industry turbulence. 

Cash flow forecasting includes both sides of the equation — inflows and outflows. It relies on granular data of the bank’s past financial performance and payments due in the short and long run. It should also account for more significant economic trends, like federal interest rates. 

To introduce precision to cash flow forecasting, banks need to automate manual processes and centralize all data necessary for prediction. Software tools do both. They also automate real-time data collection and create and continuously adjust forecasts based on it. 

Another liquidity risk in banks:  lenders who miss out on their payments. In this case receivables management has to come in and power the bank’s collection efforts. Apart from loan payments, receivables in banking include investment profits, invoice payments and other sources of revenue that are not collected immediately. 

A sound approach to receivables management allows banks to ensure they will receive cash inflows when they are due. This prevents the risk of an unexpected misbalance between inflows and outflows that can make it impossible for them to meet their short-term financial obligations. 

Here are four marks of efficient receivables management: 

• Proactivity in collections. Remind lenders and partners when their payments are due and notify them about any policy changes. Ensure paying is straightforward and convenient for them. 
• Prompt response to past-due receivables. Don’t let receivables go uncollected for too long. Regularly contact past-due clients to remind them of the payments due and the penalties they may incur. 
• Incentives and penalties. Consider offering a reward for early payments and a payment plan for past-due clients. Remember to add the stick to the carrot: Outline late fees and other penalties. 
• Manual task automation. All three components above require automation to track all receivables due and send out various reminders on time. 

Liquidity risks are constantly evolving based on rapidly shifting factors like: 

• Uncollected receivables 
• Seasonality 
• Stock market and foreign exchange volatility 
• The state’s monetary policy

That’s why banks can’t do a liquidity analysis once and leave it untouched for months. 

Instead, some analyses, like cash flow forecasts, are best reviewed and updated at least weekly or, ideally, daily. When it comes to predictions, remember to create them for the following week, month, quarter and 12 months. 

Of course, adjusting projections and performing systematic analyses can be labor-intensive without the right tools. That’s why banks will need a software solution that automatically: 

• Aggregates all the data executives need to conduct analyses 
• Calculates basic liquidity indicators like the cash ratio and liquidity position 
• Uses granular, industry and macroeconomic data to create and adjust forecasts 
• Accounts for different possible scenarios in predicting banking liquidity 

If financial data remains fractured across multiple software tools, liquidity management is bound to be inefficient. It’ll take more time and human resources to pull that data together, update it and make sense of it. It also exposes the institution to the risk of human error. 

To track liquidity, all the data should be accessible from a single interface. This is where, once again, technology saves time and money by automating data sourcing. Software tools can bring together all the internal data in one system: 

• Accounts receivable and payable 
• Data from other platforms —  e.g., ERP systems, Treasury Management System (TMS) or financial systems 
• Actuals like account activity, turnover, transactions and balances 
• Cash pool structures 
• Asset portfolio 
• Multiple subsidiaries’ data 

The chosen liquidity management tool should also account for external factors. To this end, it should automatically extract certain types of data from third-party sources. Such data includes: 

• Federal interest rates 
• Inflation rates 
• Stock prices 
• Foreign exchange (FX) rates 
• Consumer confidence 

Manual reporting may unnecessarily take up a substantial chunk of working time. And like all manual tasks, it comes with a higher risk of human error. 

A liquidity management software solution can eliminate that risk — and make reports available in a couple of clicks. This allows the top management to make data-driven decisions fast, especially if the report requires pulling data from multiple sources. Automation also facilitates compliance reporting across the board. 

When shopping for a liquidity management tool, executives need to pay close attention to its reporting automation features. It should work with pre-built and custom-made templates for maximum reporting flexibility. 

Moreover, some treasury management tools work with real-time data, meaning employees can generate end-of-day reports and projections. This will help the top management stay on top of the ever-shifting internal and external liquidity factors. 

With predictive analytics, a bank no longer needs a large team of analysts to forecast its liquidity. This AI-powered technology can do a better job than the most skilled analysts — in a fraction of the time.  

That’s because predictive analytics algorithms can: 

• Continuously adjust forecasts based on changes in real-time data 
• Take into account hundreds of parameters 
• Run complex simulations for multiple scenarios in a matter of seconds 
• Analyze current risks and extrapolate them to predict future ones 
• Forecast settlement times and probability of failure 
• Account for external factors that may impact banking liquidity — seasonality trends, foreign exchange (FX) rates, monetary policy indicators and more 
• Continuously scan for and warn about cash flow irregularities and other issues 

Predictive analytics allows for unlocking the full potential of gigabytes of data and hundreds of indicators that banking liquidity depends on. 

Banks need real-time data to make the most out of all the liquidity management strategies above. After all, there’s no longer a substantial time lag between sending and receiving payments in banking. Now, any client, business or not, can send instant payments domestically. 

This means cash inflows and outflows can change quickly within a day. Therefore, banks should closely monitor them on an intraday basis. This is where real-time liquidity management comes in. 

To implement real-time liquidity risk management in banks, banks need a tool that will automatically collect and continuously analyze mountains of data from multiple sources. 

But what makes a software solution the right one? In our experience, it should fit the following bill: 

• Cloud-based infrastructure to ensure scalability and top-notch performance at all times 
• Predictive analytics to power forecasting and detect irregularities 
• Rapid deployment to go live with minimum friction 
• High performance to continuously process millions of transactions and data changes 
• Flexibility in customization to adapt the solution to match the client’s needs to the letter 

To transition to a real-time liquidity management solution, banks need to approach it comprehensively and thoroughly. This means: 

• Bringing on board all stakeholders, from treasury teams to C-level executives, to map out the transition 
• Identifying the data types the solution needs to pull in and analyze 
• Carrying out the transition in phases, from a migration test to step-by-step infrastructure moves 

If you don’t have the in-house expertise for the transition, consider turning to a reliable partner for system integration. 

• Reduced liquidity buffer and funding costs 
• Improved operational risk management 
• More accurate end-of-day funding 
• Automated regulatory compliance 
• Reduced cost of capital 
• Automated netting across accounts

Reviewing the bank’s current liquidity management strategy — and upgrading it with the help of new technology — is necessary to: 

Sound liquidity management allows for predicting future liquidity positions precisely. This gives banks more control over the cash available at a given time. 

Accurate cash forecasting helps minimize buffer costs and correctly calculate the liquidity funding required. So, the top management can commit cash to other expenditures with peace of mind. This drives the organization forward without risking liquidity issues or insolvency. 

Streamlining and standardizing liquidity management helps in avoiding these scenarios, which  can include: 

• Overcommitting capital to fund contingency and buffer costs 
• Not being able to mobilize funds fast enough due to legal restrictions 
• Incurring substantial costs when moving funds or transforming assets into cash 
• Payments getting stuck in transit due to insufficient transaction data provided by the recipient or sender 

Liquidity management strategies should also account for trapped cash scenarios if they do occur. Again, this improves the bank’s resilience. 

The more precise the current liquidity assessment and forecasting are, the less likely the bank is to find itself unable to meet its financial obligations without substantial losses. This means decreasing the risk of having to sell relatively illiquid assets at a loss (like SVB had to) or defaulting on the debt altogether. 

Apart from that, solid liquidity management should address operational risks, like human error or fraud. It should also include contingency plans for sudden large expenditures, lower-than-expected cash inflows and external factors that may cause a run on deposits. 

Comprehensive liquidity risk management mitigates the insolvency risk and ensures the institution’s financial health in the long run. 

If a bank has a solid, up-to-date liquidity management strategy, it becomes a more attractive prospect for investors. That’s because comprehensive and detailed liquidity data, along with multi-scenario forecasting, can demonstrate its financial health. 

What’s more, solid liquidity management can improve the perception of the bank in the eyes of its business partners, creditors and clients. The reason is the same — it ensures the organization’s resilience and demonstrates its financial health. 

And let’s not forget about the regulators and their requirements toward key liquidity indicators. Comprehensive and efficient liquidity management ensures compliance without over-the-board resource spending. 

With our decades-long expertise in banking modernization and digital transformation DXC can take your liquidity management to another level.