Patent attributes
Risk scores are generated by systems that use features or inputs from the current transactions, some summary statistics like velocity and some statistics calculated in batch mode which traverse hierarchical classification levels of entities, including classified attribute levels of known transactions, to identify neighborhoods of related entities and related transactions. Corresponding records of transaction information are extracted from or are otherwise generated from neighborhoods of the related transactions associated with the defined neighborhoods of entities/transactions. These records of transaction information are then used by a consortium risk engine to generate composite risk scores associated with information from multiple merchants/entities and that were only identified by traversing the hierarchical classification of the entities and/or the corresponding transactions, which are at least tangentially related to the new transaction(s), and which may be the basis for approving or denying the new transaction(s) and/or sending the new transaction(s) for manual review.