Tomorrow’s Treasury Today: AI in Financial Management

Artificial Intelligence has dominated the conversation this year, splitting opinions with some people embracing the new technology and others sceptical about the prospect of technological unemployment and AI’s influence on industries including treasury.

A recent publication by Insider delved into the jobs that could be most affected by AI, particularly ChatGPT. This includes roles like software engineers, coders, journalists and traders which are among those most at risk of being replaced in the coming years.

While it might seem like a shiny and seemingly novel concept, machine learning research dates back to the mid-20th century. The concept was discussed in the 1930s. Despite its 93-year history, awareness and concerns about its impact on job roles have risen with the emergence of tools like ChatGPT hitting the mainstream, raising questions about job security.

BT Group CEO, Philip Jansen, recently cited AI as an influencing factor in the cutting of 55,000 jobs by 2030 replacing at least 10,000 of them with AI technology, helping to reduce business costs considerably.

The growing integration of new AI into current software reflects society’s growing demand for instant gratification. As we increasingly depend on technology for daily tasks, AI will advance. This prompts the question: how will AI’s ascent affect the treasury market?

Treasury Technology

One of the most significant concerns surrounding the growth of AI pertains to how it’s going to affect our jobs. Every profession has undergone a transformation as they adjust to advancements in technology, and treasury is no different. 

Since its inception, the treasury function and its technology have evolved significantly, with tools developed independently to accommodate and streamline necessary services. However, changes in inflation, international exchange regulations and the wider global economy at the back end of the 20th century forced treasury professionals to come up with new techniques and strategies to maintain stability and further business development. Globalisation has also influenced companies to seek more comprehensive treasury solutions across business units globally. 

From the introduction of spreadsheet software to the development of financial systems such as Bloomberg, the treasury technology market has seen continual development and significant improvements in functionality, allowing for better connectivity between banks, vendors, and companies as it strives to keep up with increasing business requirements.

How is AI being used in treasury today?

As an industry, treasury serves as a pillar of a business’s digital ecosystem. Already utilising a variety of software like treasury management systems (TMS), SEPA, Bloomberg, and SWIFT, to name but a few. The pandemic only accelerated the digitisation of treasury operations.

A recent study by Deloitte saw most treasurers surveyed placing digital transformation and technology advancements high on their agenda of required improvements. Inadequate systems infrastructure is prolonging and disrupting fundamental areas of treasury including liquidity management, foreign exchange, and forecasting and the treasurers included in the survey believe digital transformation will only enhance their capabilities.   

The survey found 78% of treasurers are already using technology to assist with accounting practices, 64% are employing technology to help with cash management functions and cash flow forecasting technology is employed by 50% of survey respondents.

Implementing new AI-powered technology or upgrading legacy systems can be a major undertaking for many businesses and has the potential to restructure entire teams, with many jobs being reduced to a reporting or supervisory role. 

A study by investment giant, Goldman Sachs, estimated a 7% rise in global GDP as a result of AI, predicting a potential global AI market value of $150 billion. However, this is not without consequences, as the report cited that potentially 300 million full-time jobs could be replaced by varying degrees of automation in the future.

Evidence of AI technology currently being used in treasury management can be seen in two primary areas.

  1. TMS –AI is being increasingly integrated into TMS to enhance these capabilities and provide more data-driven insights. This system centralises cash, liquidity, risk and reporting management. AI can identify hidden patterns, enhance cash optimisation, risk assessment, fraud detection, trading and regulatory compliance.
  2. RPA – Robotic Process Automation allows treasurers to apply automations to key tasks, creating an algorithm that can streamline processes, improve efficiency, and execute fundamental business processes.

These systems are used to automate tasks, consolidate data, analyse risks, and make predictions. As digital software and technology become more interconnected, the data this provides allows treasury professionals to make quicker, more accurate decisions.

AI’s role in treasury operations is becoming increasingly pronounced and while the benefits of machine learning can be seen through the streamlined efficiency of key tasks, cost saving and business growth, the impact it has on the treasury market is emblematic of the broader changes rippling through industries. We must take time to consider the pitfalls of AI and what impact this software could have on the future treasury workforce and hiring practices.

In part 2 of this blog, we look at the potential negative impacts AI could have on the treasury market. 

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