Abstract: A multidimensional recursive and self-perfecting process used to discover dyadic or multi-counterparty relationships between parties, the process comprising: (a) collecting information from a plurality of data sources; (b) discovering dyadic or multi-counterparty relationships between the parties from the collected information; (c) clustering the parties to infer the dyadic or multi-counterparty relationships between the parties based on common or partially intersecting attributes between the parties, thereby forming clustered parties; (d) evaluating the clustered parties for business linkage potential by integrating the collected information and contextually assessing indicia from the data sources to detect and measure consistency and inconsistency for a given party or dyadic or multi-counterparty relationship; (e) positing and evaluating relationship type and role said party plays in each relationship; and (f) assessing the confidence level regarding the likelihood that the dyadic or multi-counterparty rela

Abstract: A multidimensional recursive and self-perfecting process used to discover dyatic or multi-counterparty relationships between parties, the process comprising: (a) collecting information from a plurality of data sources; (b) discovering dyatic or multi-counterparty relationships between the parties from the collected information; (c) clustering the parties to infer the dyatic or multi-counterparty relationships between the parties based on common or partially intersecting attributes between the parties, thereby forming clustered parties; (d) evaluating the clustered parties for business linkage potential by integrating the collected information and contextually assessing indicia from the data sources to detect and measure consistency and inconsistency for a given party or dyatic or multi-counterparty relationship; (e) positing and evaluating relationship type and role said party plays in each relationship; and (f) assessing the confidence level regarding the likelihood that the dyatic or multi-counterparty rela

Abstract: A method and system for determining an entity's future commercial viability which comprises: (a) using a first predictive modeling, determining a future commercial viability of the entity, the first predictive modeling is derived by identifying patterns in data and relating to predictive attributes, thereby generating a viability score; (b) using predictive modeling to generate a relative ranking of the entity against its peer group, thereby generating a comparative viability score (i.e.

Abstract: There is provided a method that includes employing a computer to perform operations of (a) receiving, from a data source, by way of an electronic communication, a descriptor of a business, (b) matching said descriptor to data in a database, thus yielding a match, wherein said data includes a unique identifier of said business, (c) saving to a log, a signal that includes said unique identifier, (d) counting a quantity of signals that include said unique identifier in said log, thus yielding a number of said signals for said unique identifier, and (e) calculating a credit score for said business, based on said number of signals. There is also provided a system that performs the method, and a storage device that controls a processor to perform the method.