A method and apparatus for fraud detection during transactions using identity graphs are described. The method may include receiving, at a commerce platform system, a transaction from a user having initial transaction attributes and transaction data. The method may also include determining, by the commerce platform system, an identity associated with the user, wherein the identity is associated with additional transaction attributes not received with the transaction. Furthermore, the method may include accessing, by the commerce platform system, a feature set associated with the initial transaction attributes and the additional transaction attributes, wherein the feature set comprises machine learning (ML) model features for detecting transaction fraud. The method may also include performing, by the commerce platform system, a machine learning model analysis using the feature set and the transaction data to determine a likelihood that the transaction is fraudulent, and performing, by the commerce platforms system, the transaction when the likelihood that the transaction is fraudulent does not satisfy a transaction fraud threshold.

A computer-implemented method included receiving a first request to verify a first requested transfer of funds from a first account to a first merchant prior to the first merchant receiving an acceptance of the first requested transfer of funds; identifying a first instance of an application program installed on a first mobile wireless device as being associated with the first account; causing, in response to receiving the first request, a first notification of the first requested transfer of funds to be presented on the first mobile wireless device via the first instance of the application program; determining that the first requested transfer of funds is not approved by a user of the account based on a first message received from the first instance of the application program or a failure to receive a message from the first instance of the application program within a predetermined period of time; and causing use of the first account to be disabled in response to the determination that the first requested transfer of funds is not approved by a user of the account.

Methods and systems are described for setting a risk management limit to be applied to authorized purchase transactions for a payment card account. In an embodiment, a payment card issuer sets a risk management limit to be applied to authorized purchase transactions for a payment card account, receives an authorization request for a first purchase transaction, determines that the payment card account is within a threshold amount of the risk management limit, and transmits a warning message to a mobile telephone of the account holder that the risk management limit is imminent. Next, the payment card issuer computer receives a second authorization request for a second purchase transaction, determines that the payment card account now exceeds the risk management limit and that no contact has been received from the account holder, and then suspends the payment card account pending contact from the account holder.

A method and an apparatus for identifying a transaction risk are disclosed. The method includes obtaining risk identification information of a sub-network to which a node relating to a transaction to be identified belongs; and identifying a risk of the transaction to be identified based on the risk identification information of the sub-network to which the node relating to the transaction to be identified belongs, wherein the sub-network is a network acquired by partitioning a relationship network based on connectivity, the relationship network is a network built up with entities and activities relating to a plurality of transactions. Embodiments of the present disclosure build up entities and activities relating to a transaction to be identified into a relationship network, and identify whether a risk exists in the transaction to be identified using risk identification information of the network which is difficult to be found or changed, and thus are able to identify a transaction risk in a more effective manner.

Embodiments of the invention are directed to methods, apparatuses, computer readable media and systems for providing, along with a token, a token assurance level and data used to generate the token assurance level. At the time a token is issued, one or more Identification and Verification (ID&V) methods may be performed to ensure that the token is replacing a PAN that was legitimately used by a token requestor. A token assurance level may be assigned to a given token in light of the type of ID&V that is performed and the entity performing the ID&V. Different ID&Vs may result in different token assurance levels. An issuer may wish to know the level of assurance and the data used in generating the level of assurance associated with a token prior to authorizing a payment transaction that uses the token.

The present disclosure describes transaction-enabling systems and methods. A system can include a controller and a fleet of machines, each having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement. The controller may include a resource requirement circuit to determine an amount of a resource for each of the machines to service the task requirement for each machine, a forward resource market circuit to access a forward resource market, and a resource distribution circuit to execute an aggregated transaction of the resource on the forward resource market.

A system to authenticate an entity and/or select details relative to an action or a financial account using biometric, behavior-metric, electronic-metric and/or knowledge-metric inputs. These inputs may comprise gestures, facial expressions, body movements, voice prints, sound excerpts, etc. Features are extracted from the inputs and each feature converted to a risk score, which is then translated to a representative value, such as a letter or a number, i.e., a code or PIN that represents the input. For user authentication, the code is compared with a data base of legitimate/authenticated codes. In some embodiments a user selects specific information elements, such as an account or a payment amount using one or more of a biometric, a behavior-metric, an electronic-metric and/or a knowledge-metric input.

Systems and methods for processing machine learning attributes are disclosed. An example method includes: identifying a user transaction associated with a set of transaction attributes and a first transaction status; selecting, based on a risk evaluation model, a first plurality of transaction attributes from the set of transaction attributes; modifying a first value of a first transaction attribute in the first plurality of transaction attributes to produce a first modified plurality of transaction attributes; determining, based on the risk evaluation model, that the first modified plurality of transaction attributes identify a second transaction status different from the first transaction status; and in response to the determining, identifying the first transaction attribute as a risk attribute associated with the user transaction.

A computer-implemented method and apparatus are provided to reduce false fraudulent declines of transactions. Payment processor (PP) systems may be provided with a request acceptor and a replacement transaction generator. The request acceptor receives a notification of a decline of a first transaction attempted by a cardholder with a merchant, for allegedly fraudulent, and a request to determine whether the first transaction was falsely identified as fraudulent, and if so, to remedy the first transaction. The replacement transaction generator generates, in response to a determination that the first transaction was falsely identified as fraudulent, and the merchant is a false fraudulent reduction partner merchant, a replacement second transaction to replace the declined first transaction. The replacement second transaction may include a bypass authorization code, and made available to the cardholder to use to transact with the merchant bypassing the declined first transaction.

Methods and systems of managing or reconciling location-based transactions are disclosed. At least a location attribute related to a virtual coupon is derived from a digital representation of a real-world scene captured at least in part by a mobile device. At least one virtual coupon is generated based on at least the location attribute, wherein the virtual coupon is related to a purchasable item associated with the real-world scene. A reconciliation matrix related to the purchasable item based on at least the location attribute is identified. A transaction for the purchasable item is reconciled among at least one vendor account and at least one consumer account according to the at least one virtual coupon and the at least one reconciliation matrix.