Treasury management is currently undergoing a technology driven evolution, that will require a reboot of the entire system. In the past decade treasury management have been tasked with increasing efficiencies through the centralisation of the function, with leaner teams and under the bombardment of regulatory change in an increasingly global environment. The question is how to improve cash management and reduce risk with less resource in an environment of growing complexity. The answer, according to reports and commentators, is technology – and more specifically exponential technologies on offer from the ever expanding fintech marketplace.

Advances within artificial intelligence, distributed ledger technology (DLT), opportunities with cryptocurrencies and big data analytics are all driving treasury managers to look to the benefits of technologies to better their processes.

And the importance of robust treasury management systems is becoming ever clearer. In its 2018 Corporate Priority survey, Back to the Future, Treasury Strategies found that the TMS is now the third highest priority for treasurers, behind only foreign exchange risk management and cash forecasting. Moving up from fifth in 2016 and last year, that puts the management and upkeep of TMS above balance sheet optimisation, operational efficiency, bank relationship management and cyber security, in this year’s concerns among treasury managers.

Yet 41% of treasury departments still rely solely on labour-intensive Microsoft Excel, and as little as 56% of the market currently use any sort of TMS, suggesting many are missing out on the range of functionalities the technologies can offer the treasury function. As the Treasury Strategies report suggest, those not making use of the technological advances may be aware of their own limitations: “For firms without TMS, the acquisition and implementation of a platform may be the issue of the day,” it reads.

But it wasn’t always clear sailing for the TMS market. Such as with any new technology, the first wave of systems to hit the market brought with them limitations. Most were standalone systems that wouldn’t factor into the other parts of the business, or the enterprise resource planning platforms that have become crucial to the smooth running of many organisations. However, as technology has advanced, many TMS products offer state of the art flexibilities and impeccable integration functionalities. With developments in cloud technology and software as a service (SaaS) providing new levels of efficiency gains and speeds of deployment, many treasury managers consider advanced, up to date TMS platforms as crucial to the running of their business.

A wide range of web-based treasury management platforms are now available – and are quick and easy to integrate through the use of application programming interfaces (APIs). And many boast platforms that can be up and running within a day.

For those treasury departments still not using treasury software, consultants working within the field believe those firms may well drop further behind. While many TMS applications focus on specific areas of the treasury system, others offer complete, holistic packages that reshape and restructure the entire treasury function. From cash management to resource deployment and stress testing of capital resources, treasury teams are evolving throughout the course of 2018, stepping out of their comfort zone.

Languishing in the shadows for years, Open Banking and other initiatives have recently pushed API technology into the limelight among financial services and fintech firms. With that wide adoption, the corporate treasury sector has also jumped on the API bandwagon. APIs essentially allow various software systems to communicate with one another, negating the need for potentially crippling system integrations. Now, TMSs can communicate with ERPs, which can then link directly to banking and other financial software. Real time connectivity has begun to allow firms to pull together treasury data like never before, and fintech firms are driving the push to modernise the treasury function.

Within that sphere, many providers have come to adopt artificial intelligence (AI), which, when applied correctly, can apply quantitative modelling to complex corporate treasury planning. Thus going a step further than previous TMS generations, intelligent software allows the treasury function to go much further than simply cash management and into the realm of planning and sophisticated algorithmic resource allocation.

Many TMS providers have made clear the splitting functions within AI. Firstly, robotic process automation (RPA) is the process within which the application is configured to direct it to perform clearly defined steps without the requirement of a complex interface. Crucially, the software can be integrated across multiple platforms, and fully customisable without the need for background, specific programmatic knowledge. From there, programmes build knowledge piece by piece within the system, through pattern and indicator analysis. The second component of AI is the now famous machine learning (ML) construct. Within the TMS world, ML algorithms apply the same iterative concept as RPA to identify correlations in data sets. Using that information, the algorithms then search through previously unassessed data to identify additional trends and to inform strategic decisions. The speed and accuracy of the analysis, coupled with the possibility of previously unidentified knowledge, point to profit maximisation along with risk reduction.