Commodity Trade Finance Platform using Distributed Ledger Technology: Token Economics in a Closed Ecosystem using Agent Based Modeling

Distributed Ledger Technology (DLT) creates a decentralized system for trust and transaction validation using executable smart contracts to update information across a distributed database. This type of ecosystem can be applied to Commodity Trade Finance to alleviate critical issues of information asymmetry and the cost of transacting which are the leading causes of the Trade Finance Gap (ie. the lack of supply of capital to meet total trade finance demand). The possibility of scaling up such ecosystems with a number of Institutional Investors and micro small medium enterprises (MSME) would be advantageous, however, it brings up its own set of challenges including the stability of the system design. Agent-based modeling (ABM) is a powerful method to assess the financial ecosystem dynamics. DLT ecosystems model well under ABM, as the agents present a clearly defined taxonomy. In this study, we use ABM to assess the Aquifer Institute Platform - a DLT-based Commodity Trade Finance system, in which a growing number of participating parties is closely related to the circulation of utility tokens and transaction flows. We study the system dynamics of the platform and propose an appropriate setup for different transaction loads.