Digitally Enabling Risk Management Objectives: Accelerating to Smart Treasury

FX Risk Management Solutions Quarterly | Issue 127 | July 2020 | Trending 8 The process steps covered by this intelligent automation are: 1. Required FX hedges generated in the TMS. 2. Transmit FX hedges to the desired execution venue, typically via an API. 3. Log on to the user interface of the execution venue. 4.Review pricing provided, select the respective liquidity provider and transact. 5. Transmit completed FX hedges including both confirmed price and FX counterparty details. Typically as well, the exposures in step 1 are tagged in such a way that the associated hedges in step 5 are identifiable from a hedge-accounting point of view. An increasing number of companies are skipping step 4 in view that best execution is achieved by the multiple liquidity providers bidding for the deal, or that associated costs have been pre-agreed with their respective liquidity providers, in the case of a direct connectivity. As discussed, though, the process that leads up to step 1 is still predominantly manual and cumbersome for a treasury. As risk management gets more prescribed via the real-time algorithms described in this article, hedge determination is made fully automatic. Connecting the results of prescriptive analytics to initiate automated hedges will be the new normal. As forecasts are adjusted on a real-time basis, hedge adjustments will naturally be more frequent but smaller in size. Importantly, treasuries will also look to step away from typical hedge cycles (usually monthly) to one that is happening constantly. The shift of focus for a corporate treasury at this phase will be less on price discovery and more on ensuring that in this new touchless environment, there are ample failsafe mechanisms to ensure that the right people are notified at the right time for any manual intervention. To elaborate further, things can go wrong during auto execution for a multitude of reasons such as lack of credit allotment by the price provider causing rejects, latency in the network causing a lack of response and code errors that result in the duplication or incorrect notional of trades being sent. Prescriptive analytics may provide the most accurate of recommended actions, but poor management in the execution phase can lead to significant losses when issues are not addressed in a timely fashion. Other considerations would also need to be made, such as the impact of liquidity when a company transacts, as attempting to transact large transactions at the wrong time can be costly — particularly with too many liquidity providers. Another example is avoiding concentration risk by ensuring that counterparty exposures are managed evenly between banking partners. Therefore, the algorithms required to be deployed in this phase will need to incorporate these crucial parameters and not just focus on achieving best price. That said, autoexecution is a fairly mature field and already firms have begun the process of shifting parts of their portfolios into a rules-based environment. With the right structured test plan to iron out all foreseeable issues and robust failsafe mechanisms in place, a typical treasury should be able to find sufficient comfort to kick things off. It is therefore not too far away. With the advancements of prescriptive analytics discussed in this article, this final linkage to execution paves the way for the era of Artificial Intelligence in treasury currency risk management with full end-to-end inteligent automation. Towards a smart treasury future The innovations described in this article are some of the key components of the suite of initiatives at Citi targeted to support our clients’ smart treasury aspirations. Future treasury will be defined not only by the automation of repetitive tasks but also by the utilization of prescriptive analytics to determine best next action. Treasury that is sensitive to market fluctuations will be able to offer a more resilient function that is more capable of dynamically adjusting to future shock events. Erik Johnson Director Risk Management Solutions erik.johnson@citi.com Dr. Duncan Cole Director Treasury Advisory Principal, EMEA duncan.cole@citi.com Kelvin Ang Director Treasury Advisory Principal, NAM East and Latam kelvin.any@citi.com Yi Hahn Chin Managing Director EMEA Head of eFX Solutions — Corporates yi.hahn.chin@citi.com Ray Pereira Vice President EMEA eFX Solutions — Corporates ray.pereira@citi.com 1 “Citi: Future-Proofing Treasury for the Decade Ahead”, available at: https://www.citibank.com/tts/insights/articles/article120.html. 2 Treasury Digitization: Market Perspectives, Citi, available at https://www. citibank.com/tts/sa/flippingbook/2020/Treasury-Digitization-Market- Perspectives/2/. 3 Future of Corporate Treasury, Zanders and Citi, available at: https://www. citibank.com/tts/sa/flippingbook/2019/The_Future_of_Corporate_Treasury. 4 “Reviewing FX Hedging Strategy: A Brief for New Treasury Leaders”, A Playbook for Treasury, Citi, Volume 1, available at https://www.citibank.com/ tts/sa/flippingbook/2020/playbook-for-treasury/14. 5 Benchmarking Treasury for Shareholder Value, Citi, available at https:// www.citi.com/tts/sa/flippingbook/2019/Benchmarking_Treasury_for_ Shareholder_Value/index.html. 6 “Algorithmic Forecasting in a Digital World”, Deloitte, available at https:// www2.deloitte.com/us/en/pages/finance-transformation/articles/ algorithmic-analytics-to-improve-forecasting-process.html.