Digitally Enabling Risk Management Objectives: Accelerating to Smart Treasury

FX Risk Management Solutions Quarterly | Issue 127 | July 2020 | Trending 3 The remainder of this article describes one such initiative mobilized at Citi, which aims to: • Provide a continuous validation that treasury policy is sufficient to meet its objectives, thereby building resilience into the treasury’s response at a time of stress. • Offer the necessary set of actions needed by treasury to realize those policy objectives. • Realize the recommended actions through the intelligent automation of trade execution. The flow diagram below breaks out the logical steps involved. Firstly, treasury policy is validated and combined with forecasted currency position (and variance) fed into a prescriptive analytics engine to determine appropriate hedging action. Secondly, recommended actions are inferred, providing decision support to treasury risk managers. Thirdly, what follows is extending to offer auto-execution of the prescribed actions, with feedback loops to support machine learning through subsequent iteration. The result delivers AI-enabled currency risk management. Policy validation moving from an infrequent manual response to a more frequent continuous digitized process offers resilience to allow for market disturbances and consequential currency exchange volatilities. Transitioning to a model of continuous validation of policy sufficiency Let us start by defining what we mean by continuous validation of policy sufficiency: • The availability of a toolkit to deliver against policy objectives. • Sufficient visibility, connectivity and machinery for continuous monitoring of the suitability of deployed instruments. Together, these ensure policy flexibility sufficient to meet the prescribed risk mitigation action. Before we describe how such continuous validation can be brought about, let us briefly remind ourselves how treasury can create a risk management policy today and what characterizes best practice. A successful program relies on identifying and quantifying risk, consistent with a risk-based approach. Treasury and the business are closely aligned in setting hedge objectives and setting risk tolerances. They design an optimal hedge solution to reduce corporate-wide earnings-at-risk to acceptable levels. And they have established a high level of resources and technological infrastructure around risk management often Figure 3: Logical flow diagram depicting the buildup of smart treasury processes. The target state will vary by the customer’s risk appetite (trust in machines) and the need to automate for future operational treasury resilience Descriptive Analytics Predictive Analytics Prescriptive Analytics Artificial Intelligence Digital Treasury Objectives/Maturity Currency Instrument Notional Duration Publish Treasury Policy Measure Currency Risk Determine Hedging Action Execute Hedging Strategy Validate Policy Objectives Currency Hedging Policy Objective Approved Currency Hedging Instruments Forecast of Currency Risk with Variance Counterparty Liquidity Channel Price ERP1 ERP2 TMS Back Testing Simulations Iterative Refinement Hedge Effectiveness Reporting