Driven by digitisation, connectivity, and collaborative ecosystems, many industries are seeing long-standing boundaries blurring or dissolving altogether. The art of the possible is expanding, opening the door to entirely new business models. Treasury needs to adapt to the impacts on liquidity, funding, and risk management needs as new business models change the company. This has already been happening in some industries and seems set to become even more pervasive.
Meanwhile, treasury departments are always pressed to be more efficient and effective. Many treasury teams are focusing on what is being made possible by emerging technologies, such as robotic process automation (RPA), big data, artificial intelligence (AI), machine learning (ML), and distributed ledger technology (DLT). This is also a time of change in financial services, with a wide and growing range of emerging options such as instant payments and application programming interfaces (API).
As more and more financial flows move to ‘real time’, treasury leaders will need to take a fresh look at how they organise and manage treasury functions - from liquidity management and financial risk mitigation, to better preparation for cyber threats - to ensure investments in technology properly support more highly inter-connected processes.
Opportunities
Treasury teams realise there is much at stake in the outcome. A recent survey conducted by Citi, Digitization for Corporates revealed that, from a digital readiness perspective, 64% of companies have a formal digital strategy at the enterprise level. Just under a fifth are formulating a strategy at the treasury level. The most common focus areas are transformative improvements in automation and efficiency, and in data-driven insights for more effective decisions. Perhaps unsurprisingly, the biggest hurdles are in integrating systems and getting the right resourcing and staff skill sets.
From a broader finance and treasury functional perspective, survey respondents felt that payments and receivables operations could be most improved over the next three years. In their view, opportunities to improve liquidity management, including cash forecasting, come next.
It is true that use cases are evolving, in many cases fairly quickly. Finance and treasury teams could leverage RPA to simplify repetitive activities such as reporting, post-trade entry and settlement, account position reconciliation, and cash application. In addition, data analytics, together with AI and machine learning solutions could be leveraged to drive better cash flow forecasting, just-in-time funding, spotting of outliers, and to aggregate and analyse forecasts, prices, and market news for better trade decisions in foreign exchange and investing.
On the horizon, treasuries could see a positive impact from the use of APIs. This can start with basic functions, such as real-time transfer of information on intraday balance positions and trade instructions. Ultimately, APIs could drive new machine-to-machine workflows, replacing many legacy processes, and automating functions. Further evolution in the integration of APIs with enterprise resource planning and treasury management system providers will support more radical re-engineering of processes.
Treasury teams could also pursue innovative financing techniques or workflow optimisation by collaborating with banks and fintech providers in areas such as dynamic discounting and cash application, as well as with the SWIFT gpi initiative to enhance transparency in payment flows.
AI could change how treasury understands risks and makes better decisions, make collaboration with banks and technology providers more seamless and frictionless, and power new internal and external marketplaces. This would create increased resource capacity for treasury to be more strategic and focused on adding value to the business.
Whilst there is considerable interest and potential applications for blockchain/DLT, many of the current use cases are focused on company supply chains. For treasury, the maturity of use cases is yet to evolve in terms of technology, scalability and relevance. Potential applications of cryptocurrency seem even further out.
Managing innovation
Technology, through its impact on business models and on finance, may ultimately lead to a radically simpler, faster, and hyper-connected treasury. In this world, Treasury teams would be able to optimise balance sheets in real time, rely on data driven decision-making, automate risk management execution, and collaborate with financial services providers through open banking and APIs. Service providers may include a growing number of alternate sourcing models and marketplaces. All of this would redefine how treasury operates and make tomorrow’s treasury dramatically increase its strategic value.
But to cast our memory to just the recent past - it wasn’t the Internet or the smartphone that transformed how we travel, or listen to music. It took entirely new ways of thinking, and the emergence of new business models, to exploit these new technologies and create the types of companies that have already changed how we listen to music, how we commute, and where we stay on holiday.
It is equally safe to say that the future of treasury will arise not just because of digital technologies. It will arise as innovative and agile treasury organisations embrace new opportunities, while continuing to deliver on their core goal of safeguarding corporate liquidity and mitigating financial risks. Above all, this calls for a flexible mindset, combined with a realistic assessment of near-term versus medium- to long-term priorities.
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