A financial digital asset that is a virtual representation of a physical item including model smart structures or environments, manufacturing processes, humans, and a variety of other things. In the context of cryptocurrency and the broad category of digital assets, digital twins include tokens that represent real assets (non-financial assets) or financial assets such as stocks, bonds, and real estate property, but are traded via a tamper-proof and decentralized blockchain network, providing for higher levels of efficiency, transparency and cost savings compared to traditional issues.

Digital twin tokens incorporate blockchains to provide additional layers of trust. An example is a tokenized security that represents an underlying security or financial instruments issued on a different platform (such as a traditional CSD or registrar), where such representation itself meetings the applicable definition of a security/financial instrument under relevant laws.

Other examples of digital twins (digital twin tokens) are tokenized derivative. A tokenized derivative is a digital twin token that represents an underlying derivative instrument issued and recorded on a different platform, where such representation itself meets the definition of a derivative as applicable under a certain code of law.

Blockchains provide trust assurance, specifically in case where multiple parties take part and interact for a certain purpose. In which case, the so-called blockchain digital twins (BDTs) are involved. BDTs do exist and operate within a DT environment (DTE) that consist of multiple DTs of different objects/ actors to enable interactions between these objects/ actors.

A digital twin digitally replicates a physical asset or a financial asset in the virtual environment, including its functionality, features, behavior and performance. It mirrors the actual process or function of the respective asset and keeps a full track of its historical performance. By simulating such assets to predict future performance, digital twins can enable effective decision-making and crafting of strategies to maximize security, reliability, and profitability. The digital twin stores data to determine real-time performance, which can be used and analyzed across the entire lifecycle of an asset for performance of optimization and predictive maintenance.