Parallel Financial Systems: Towards Governable and Sustainable Intelligent Financial Services

Abstract

Contemporary financial systems operate in complex environments marked by volatility, uncertainty, complexity, and ambiguity, which elevates the cost of trial and error and exposes the limits of siloed data and centralized control. Considering the complexity challenges for the legacy financial system, we propose the parallel financial systems, which are grounded in the theory of parallel intelligence and utilizes the ACP (Artificial systems, Computational experiments, and Parallel execution) methodology to conduct financial execution and resource coordination through the interaction and co-evolution of real-world and artificial systems. Based on this paradigm, we construct a corresponding technical architecture that integrates cutting-edge intelligent technologies represented by AI agents with decentralized technologies provided by blockchain, smart contracts and decentralized autonomous organizations (DAOs). To further demonstrate the applicability for the legacy enterprise, we detail the system workflow, from individual operation to group coordination, with an illustrative example of how the parallel financial systems are utilized along a project lifecycle. This work serves as a theoretical basis and design roadmap for verifiable, privacy-preserving, and interoperable financial intelligence.