Abstract: Computer implemented methods and systems of processing transactions to determine the risk of transaction convert high categorical information, such as text data, to low categorical information, such as category or cluster IDs. The text data may be merchant names or other textual content of the transactions, or data related to a consumer, or any other type of entity which engages in the transaction. Content mining techniques are used to provide the conversion from high to low categorical information. In operation, the resulting low categorical information is input, along with other data, into a statistical model. The statistical model provides an output of the level of risk in the transaction. Methods of converting the high categorical information to low categorical clusters, of using such information, and other aspects of the use of such clusters are disclosed.

Abstract: Transaction processing of online transactions at merchant sites determines the likelihood that such transactions are fraudulent, accounting for unreliable fields of a transaction order, which fields do not reliably identify a purchaser. A scoring server using statistical model uses multiple profiles associated with key fields, along with weights to indicate the degree to which the profiles identify the purchaser of the transaction.

Abstract: The invention aids an entity to selectively request additional data about a user to serve the needs of the entity without causing the user to have an adverse reaction. The invention helps an entity to determine the condition under which to request additional data so as to reduce the likelihood of causing the user to have an adverse reaction, e.g., terminate the interaction. One embodiment of the invention concerns customers requesting transactions with on-line merchants. More specifically, this embodiment aids merchants by detecting Internet credit card transactions that are likely to be fraudulent, and providing the merchants with mechanisms for managing a suspected transaction as it occurs to obtain additional information that can be useful to reducing the likelihood of fraud.

Abstract: Transaction processing of online transactions at merchant sites determines the likelihood that such transactions are fraudulent, accounting for unreliable fields of a transaction order, which fields do not reliably identify a purchaser. A scoring server using statistical model uses multiple profiles associated with key fields, along with weights to indicate the degree to which the profiles identify the purchaser of the transaction.