Pattern recognition, machine learning, robotic process automation and true artificial intelligence will all be part of common treasury processes in the near future, and some already are.
So what should treasurers be doing now to ensure that they are running an “intelligent” or “smart” treasury?
If you’re not up to speed on these seven developments, you probably should be.
1. Intelligent payments
AI algorithms are ideally suited to resolving some of the key problems in payments because they can learn from previous experience and behaviour patterns. This allows them to build up a picture of good and bad credits, early and late payers, fraudulent activity and even message repair and exception handling.
In its early stages, AI will help treasurers achieve more complete automation in processing what are currently paper-based payments and remittance information. Going forward, the pioneers believe that treasurers can look forward to systems with built-in, intelligent, self-optimizing and dynamic collection and payment strategies with intelligent parsing of customer importance. And it is possible to see how algorithmic invoice discounting could be used to build intelligent supply-chain finance solutions to adapt to specific customers, times of year or points in the business cycle.
Given the many inefficiencies that still exist in AP/AR, treasurers need to keep on top of developments here.
2. AI for cash forecasting and FP&A
Accurate forecasting requires the intelligent evaluation of a large number of internal and external variables; the weighting of those variables; historical patterns; the incorporation of real-time data from the business, procurement and elsewhere; and a view on how good business units themselves are at understanding their situation.
At even a small company, this process involves far more data points than a human, even equipped with Excel, can accurately model. At any firm with international subsidiaries or even a regional supply chain, AI is an obvious approach for the financial planning and analysis (FP&A) function as well as treasury.
An AI-based solution ‘stack’ might include a system to analyse global information sources to assess external political and economic risk, a system to extract key observations from the mass of structure and unstructured data generated by the business, and one to model the concrete financial data. Overlaying all this might be another system able to weigh how each of these sets of predictions impact real business drivers.
Will it make better predictions? No-one knows – but given how digitalisation is driving up data volumes, will treasury have any choice?
(If you are joining Eurofinance in Barcelona 4-6 October for our flagship treasury event, we will be featuring real life case studies of corporate treasury churning out really accurate forecasts using AI-driven solutions.)
3 and 4. Smart hedging
Money managers, hedge funds and banks have been using algorithms to determine trading for some time. The key to the newer systems is that they are not static, statistical models – they don’t increasingly underperform when trends shift or market context changes. AI-based systems get better the more data they analyse and the more experience they accumulate.
So should treasurers have similar systems in place to run their hedge programs?
There are two sides to this.
First, the more accurate the entire forecasting mechanism is in the business and across cash management, the more accurate the numbers treasurers plug in to any hedge programme.
Second, can AI help in creating a more dynamic, accurate FX hedge program better aligned with actual business goals – an intelligent, active currency overlay? At the moment, the development seems to be on the bank and investment management side.
Clearly though treasurers need to watch this space.
5. Welcome to the robo-SSC
Up till now, treasury automation has been of the old-fashioned kind - get machines to do existing tasks again and again more quickly than humans.
Next-generation shared-service centre automation will be different. It will be intelligent.
Robotic process automation is the use of software ‘robots’ to automate administrative processes by replicating the actions of human operators of computer systems. The software robot is ‘trained’ to execute the actions of a human operator, rather than programmed and can manipulate data, set off responses, and communicate to other computer systems. It can also adapt to changes in its operating environment as a human can and may soon be able to review reports and flag problems.
Since treasurers are always being asked to do more with less and this software costs about a third of an offshore employee and can work around the clock with minimal errors, they will need to follow the existing early adopters sooner rather than later.
(Our Barcelona event also features a number of corporate case studies on shared services and their evolution.)
6. Automatic treasury compliance
New York-based Droit Financial Technologies has just secured $16m to accelerate marketing of its software, which automates compliance with complex regulations in the derivatives market introduced in the wake of the financial crisis, focusing on MIFID II.
What’s this got to do with corporate treasury?
Well, AI in RegTech is a potential saviour from the current tsunami of regulation that treasurers say is one of the key challenges they face, from KYC in trade finance and supply chain to simply dealing with their banks on a day-to-day basis.
AI can replace the present combination of scattered humans and fragmented legacy technology to ensure that trades, customers and the business are compliant. Even a medium-sized firm may have to evaluate hundreds of tax and legal updates a week across an international network and techniques such as natural language processing and machine learning are being used to “understand” the law, map compliance needs and even analyse the costs of compliance.
By treating regulations as data, software will dynamically help ensure compliance and bring compliance into the enterprise risk environment, enabling treasurers to take a genuinely risk-based view of regulatory compliance
7. "I'm sorry Dave, I'm afraid I can't do that"
It’s clear that the various technologies that comprise artificial intelligence will have an increasingly significant impact on core treasury processes, structures and staff. But they will also transform the larger systems in which treasury, and the whole business, effectively sits: ERP solutions.
AI-enabled ERP solutions will combine intelligent data analytics, smart automation, smart data gathering and sensor technology with deep learning, natural language processing and the technology to respond appropriately to changing situations in real-time.
We are only at the beginning of this process, but companies like SAP are already deploying these technologies and corporates will need to re-organize all IT- and data-reliant processes to incorporate the changes. The impact on staff and organizational structure is hard to overstate.
Is the day approaching where an ERP (or TMS) system will refuse a treasurer’s instructions on the grounds that they are sub-optimal?
These topics and more will be discussed, debated and presented as panels, round tables, innovation labs and corporate case studies at EuroFinance’s 26th annual treasury event.