Managing intraday liquidity in a disrupted business environment

The need for improved efficiencies heightened by remote working, rapid changes to business models and thrust to optimise liquidity has accelerated the demand for bank treasury to manage its intraday cash and liquidity in an effective manner. For the financial services providers, this means assessing and managing their working capital and credit needs against stressed financial conditions as well as meeting their real-time funding, cash flow forecasting and intraday liquidity reporting needs through advanced technologies.

From a current operating environment perspective and given the regulatory obligations around Basel III and the Basel Committee on Banking Supervision framework(especially BCBS 248), banks need to be able to demonstrate control over their own liquidity as well as the critical understanding of their demand dynamics through the day on a real-time basis. For firms, this essentially means making use of the intraday dataset to understand and optimise intraday liquidity positions and risks. “Amid marked increase in credit and market and operational risks arising from the pandemic, the key for banks is to be able to run liquidity in a business as usual as well as in stress scenario, and to be able to know where their liquidity crunch points are,” said Nadeem Shamim, head of cash and liquidity management at SmartStream. Post the settlement of large-value payments or given the sudden demand for it on a priority basis, banks may additionally experience fully utilised intraday lines for unsettled payments, he added. In case of delayed or missed payments, these events carry significant operational as well as reputational risks.

Shamim opines that while in Asia, majority of banks are managing liquidity on an intraday basis in accordance with regulatory requirements, they are only able to do so manually or on a “reactive basis” through a combination of excel spreadsheets, emails, manual gathering of information, etc. These are not only time-consuming but complex processes that render obsolete the enhancement of effective intraliquidity management systems.

As an answer to a myriad of inefficiencies, he warrants the role of technologies such as artificial intelligence (AI) and machine learning (ML) to enhance monitoring and reporting in a manner that “banks are able to visualise, aggregate, update, and make decisions on the most up to date information or in real-time”. AI and ML coupled with the deployment of data-powered dashboards have the potential to provide real value add for the treasurer and predict the settlement of liquidity at any particular point in time of the day. As a technology solution provider, SmartStream has developed automated solutions for liquidity that aggregates flows from funding, borrowing and lending, as well as support the reporting requirements of a bank. “SmartStream has already developed a proof of concept where it applies ML to create a solution that predicts the settlement time of unsettled cash flows,” explained Shamim.

This will ultimately benefit SmartStream’s bank clients to become aware of and understand where their liquidity profile sits. It will also better predict settlement times of projections that have yet to be cleared through the account, making for more incisive decision-making.

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