PIONEERING SELF-ADAPTIVE AI ORCHESTRATION ENGINES FOR REAL-TIME END-TO-END MULTI-COUNTERPARTY DERIVATIVES, COLLATERAL, AND ACCOUNTING AUTOMATION: INTELLIGENCE-DRIVEN WORKFLOW COORDINATION AT ENTERPRISE SCALE

Abstract

Self-Adaptive AI orchestration engines support enterprise-scale multi-counterparty derivatives, collateral, and accounting processes through real-time end-to-end automation and intelligent management of disruptive workflows. In the real-time, multi-counterparty domains, three key characteristics are Architectural: Analytical underpinning for real-time, multi- counterparty deployment of Self-Adaptive AI orchestration en- gines; Intelligence-driven coordination of automated workflows; and Support for real-time process integration and risk-aware collaboration across multiple counterparties. The need for end- to-end immersion and latency independence of trade capture and processing has long been recognized but remains unfulfilled, especially for collateral optimization and margin. When operating with a relatively small number of counterparties, however, it is sometimes possible to bypass this challenge by engineering and adapting separate processes for each counterparty. Such engineered collated workflows then require only to be made visible to the self-adaptive orchestrator engine.