System and method for blockchain transaction risk management using machine learning

A method comprising:

• receiving digital on blockchain information and digital off blockchain information, wherein the receiving includes a digital asset intake engine;
• extracting digital data from the digital on blockchain information and the digital off blockchain information;
• contextualizing relationships based on the digital data and the digital off blockchain information and the digital on blockchain information, the contextualizing including an entity knowledge base;
• analyzing the digital data and transforming the digital data to an identified behavior category, thereby creating classified risk data, wherein the analyzing and transforming includes a risk classification engine including a machine learning model;
• analyzing the classified risk data and assigning a risk score to each classified risk data, wherein the analyzing and assigning includes a risk scoring regression engine and machine learning;
• analyzing the classified risk data and determining if any deviations from rules or standards have or will occur, wherein the analyzing and determining includes a risk policy engine that is a rules based engine;
• and
• taking an action on the digital on blockchain information and digital off blockchain information based on the assigned risk score and any deviations from rules or standards, wherein taking the action includes a security control system, wherein the action includes:
• on condition the risk score is high:
• at least one of blocking a blockchain transaction, freezing user assets, or suspending user accounts related to the blockchain transaction;
• and
• on condition the risk score is normal:
• approving the blockchain transaction.