This October, Kyriba experts attended the AFP Annual Conference in Boston. After speaking with hundreds of finance and treasury professionals, we continued to hear common challenges that they each were working to resolve: currency volatility, fraud and cybercrime, and the uncertain future of treasury as technology continues to evolve.
These aren’t just challenges for U.S.-based treasury functions. The week prior, I heard the same concerns the prior while attending EuroFinance in Copenhagen. Luckily, each of these challenges has a solution:
The AFP conference took place against the background of looming Brexit uncertainty occurring alongside earnings season for many large corporates. The result was increased emphasis on currency volatility and its impact on bottom line results. This was emphasized by findings from Kyriba’s Currency Impact Report, which showed that North American companies sustained $20+ billion in losses for the third consecutive quarter – the longest such stretch in at least a decade. And currency impacts continue to be a billion-dollar problem for European companies.
I had the fortune of presenting a session at AFP alongside Amazon and World Vision about how treasury defends against geopolitical volatility. My co-presenters discussed how they used Kyriba to capture and identify currency exposures and what they did with that analysis, including creating greater natural hedging offsets to reduce net exposures.
Fortunately, there are solutions for reducing currency risk, which will not only provide CFOs and treasurers the insight to explain currency impacts but also take action to minimize the impact on corporate earnings to predictable levels.
The risk of fraud still keeps treasury teams on alert, especially as “I didn’t think that could happen” stories informally circulated during the AFP conference. The session I presented with SWIFT and Santander at AFP reinforced the continual interest in gathering fraud prevention best practices. Attendees were keen to hear not only the war stories but also basic principles, such as why it is critical to use a second factor of authentication when logging into your treasury systems.
Many were surprised to hear that SWIFT, as part of their Customer Security Program (CSP), is mandating multi-factor authentication technology for any user initiating payments through SWIFTNet. We have always encouraged this practice at Kyriba – not only for the initial login to the cloud platform but also for payment approvers – so this added requirement by SWIFT is a welcome push for better payment security.
We also highlighted the need to implement real-time payment screening, sanctions list screening but also compliance with the company payment policy. While there are rules-based algorithms to automate screening today in many treasury and payments platforms, the impending adoption of machine learning over the next few years will enhance the detection process by making the decision making of what is and isn’t a valid payment more data-driven. This will be a welcome enhancement as payments are projecting to be fully real-time within five years (or less!).
AFP attendees heard loud and clear that artificial intelligence (AI) and machine learning is coming to finance and treasury. Treasury systems will be self-learning robots within a decade, with first versions of AI already starting to appear within many TMS and ERP solutions. AFP just released an executive guide on the emergence of RPA and AI in treasury, with experts suggesting that treasury teams should be ready to embrace these advanced automation technologies.
While that sounds promising, treasury professionals remain concerned about what their jobs will look like in the face of artificially intelligent treasury technology. Some asked me if the next wave of technology is like the movement from spreadsheets to a treasury workstation, where we rarely saw jobs automated away but rather observed a shift to decision making rather than spending most of the day processing data. In that sense, emerging technologies such as robotic process automation will offer a similar jump in automation as the escape from spreadsheets offered treasury.
At the same time, artificial intelligence – specifically machine learning – focuses more on decision making than pure automation of manual tasks. AI-driven treasury systems will observe data and offer contextual decisions. They will require significant amounts of data to do this, but the software will gain experience by learning how decisions around reconciliation or forecasting are made – and then will offer better conclusions for treasury to work with. While for many this may sound like replacement of treasury professionals, I believe treasury will still have a job in an AI-driven world. It will be different, and it will most likely be better, simply because time can be allocated to more in-depth analysis of treasury operations. Treasury software will effectively operate treasury, but treasury professionals will assess the effectiveness of those operations to continually push treasury to deliver greater strategic value for the CFO.
To conclude, AFP always offers a wealth of learning, and at least for those that I talked to, they all found better answers to how treasury can evolve its management of currency exposures, building continued resilience to the threat of payments fraud and continue to deliver strategic value as artificially-intelligent treasury technology begins its infiltration into our professional lives.
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