Liquidity management is at the sharp edge of the AI and ML revolution

Article highlights

• The rapid mainstreaming of AI-related technologies is transforming knowledge-based industries, including liquidity management.
• Machine learning (ML) techniques are revolutionizing liquidity management by enabling the analysis of large volumes of data with speed and precision.
• AI and ML have the potential to transform not only cash and liquidity management but every facet of the banking and finance industries.
• Cloud computing has had a transformative impact on knowledge work, allowing financial institutions to gather, store, and access data sets in new ways.

It’s clear now to even the most casual observer that we are entering a new phase of history. The advent of AI-related technologies and their extremely rapid mainstreaming have meant that almost every knowledge-based industry is changing before our eyes. Rapid step-changes in technology now allow market participants to optimise their liquidity usage in ways that generate new and significant value. Data, and an institution’s ability to capture and understand it, are of paramount importance. Examples of this abound, particularly in liquidity management: consider, for example, J.P. Morgan’s use of virtual accounts to aggregate data and enable centralised liquidity control.

AI and ML: precision, speed, and exponential change

AI is the big story currently, and with good reason. But machine learning techniques have been quietly revolutionising liquidity management for several years already.

ML technology is to thank for our ability to analyse data at the huge volumes to which the financial sector is now accustomed. The ability of ML-enabled technologies to perform pattern recognition tasks already far outstrips that of humans, and the speed with which they can carry out regression analysis and similar processes is far beyond that of even the most advanced non-ML data analysis techniques.

Even in their comparative infancy, the principles of AI and ML are already transforming not only cash and liquidity management but every facet of the banking and finance industries.

We’ll be looking at AI and ML and their role in liquidity management in a dedicated blog, as the impact of these technologies is very significant. But they are not the only game in town. There are many other tech developments that are transforming liquidity management in related and complementary ways.

Scale and flex in the cloud

Cloud computing has had a similarly transformative impact on what we might call ‘knowledge work’ – that is, anything that involves the manipulation or transmission of data. On-demand, cloud data storage has allowed financial institutions of every size to gather, keep, and access data sets in genuinely radical new ways. Cloud computing has reduced the cost of storage, and in some cases processing power, very dramatically, bringing advanced data analysis within reach of virtually every organisation.

In the case of liquidity management, real-time access to data is the key to better outcomes. Cloud computing is an important factor, enabling financial institutions to store, access, and manipulate information quickly and efficiently. In particular, cloud computing enables rapid scalability and the opportunity to ‘flex’ both storage capacities and processing power. In the past, when large institutions each developed their own proprietary data solutions, months of work could be required in order to meet a new business need. Today, distributed storage, cloud-streamed applications, data lakes, cloud-data sharing, and other core principles of cloud computing mean that institutions can be as agile as the markets in which they operate. For liquidity management and monitoring, where the volume of data being ingested and the speed at which that data can be processed are absolutely essential, this becomes all the more important. Access to your real-time liquidity position means better, swifter, more informed decision-making, which in turn creates new value.

Build bridges, not siloes

But of course, technology alone is not particularly useful – and in fact, poorly considered implementation of new tools is one of the most common problems facing any organisation carrying out a process of digital transformation.

There are several key ways that these problems can manifest. Tools may be siloed within specific functions, meaning that their benefit is not felt across organisations. Poor or under-informed buying decisions can lock institutions into sub-optimal vendor relationships. And, crucially, an inability to integrate new tools into an existing technology stack can mean not only that the benefits of the new tool are not realised, but also that new time and opportunity costs are incurred.

Data silos are a challenge for any financial markets firm, due to all number of business and regulatory demands such as segregated business lines, data sovereignty requirements, compliance needs, mergers and acquisitions, etc. Siloing is of particular concern to those responsible for liquidity management. Liquidity issues can have their roots in any part of an organisation, and can then rapidly impact every function. Liquidity crises are felt across an entire firm and are often the result of information visibility issues. Technology plays a key role in breaking down the historical data silos within a firm, providing new access points and aggregation opportunities to consolidate disparate platforms and data sets. By maximising the visibility of key metrics across an institution, managers can ensure they are acting according to the best possible information available.

Olaf Ransome, Liquidity Futurologist at Planixs comments,”Knowing where your collateral – securities and cash – is at any time, as well as their current market price and then being able to monetise securities to get the right amount of money in the right currency, to the right place, at the right time, to settle transactions and payments. That is a function of people, processes and systems.”

Integration is the missing piece

In liquidity management, which relies so fundamentally on joined-up thinking across organisations, the integration of new technology into existing application stacks is of paramount importance. Good liquidity management solutions are those that add value to existing stacks. They act as an ‘aggregating layer’, gathering every piece of relevant data and then performing analysis holistically.

Effective liquidity management hinges on the mindful application of all these technologies into an institution-wide system. Such a system could aggregate data on cash positions and liquidity needs across cash and securities, vital for real-time strategic decision-making in adjusting credit lines or managing interbank lending.

Planixs’s suite of liquidity management tools are based on this core principle of deep integration, enabling banks and FIs to monitor their real-time liquidity position and aggregate data from diverse sources. Crucially, they also help stakeholders ‘close the loop’ between data and action, helping them to generate valuable insights based on the data they are gathering. This approach goes beyond regulatory compliance, identifying liquidity opportunities for enhanced financial performance.