A method for pooling and retrieving block rewards in a reward pool including an operator node and a set of member nodes in a distributed network extending a proof-of-space-based blockchain includes: submitting a transaction configured to generate a singleton in a set of singletons, the singleton including: an outer puzzle hash linking the singleton to a singleton puzzle hash; and an inner puzzle hash defining a pool address associated with the reward pool; generating a block including a proof-of-space and a block reward allocated to the singleton puzzle hash; detecting the block reward allocated to the singleton puzzle hash; identifying the singleton linked to the singleton puzzle hash; and submitting a transaction configured to: remove the singleton from the set of singletons; and transfer the block reward from the singleton puzzle hash to the pool address.

Embodiments of present disclosure provide methods and systems for increasing transaction approval rate. Method performed includes accessing transaction features and determining via fraud model and approval model, first and second set of rank-ordered transaction features. Method includes computing difference in ranks of transaction features and determining set of utilized and unutilized transaction features and generating simulated authorizing model and computing simulated transaction approval rate and simulated fraud transaction rate for simulated authorizing model. Method includes generating plurality of proxy authorization models. Method includes computing transaction approval rates and fraud transaction rates for each of plurality of proxy authorization models and computing an increase in transaction approval rate and change in fraud transaction rate for each of plurality of proxy transaction approval models. Method includes determining one or more recommended transaction features from set of unutilized transaction features and transmitting one or more recommended transaction features to authorizing entity.

A serverless computing framework is secured against malicious payload injection. A series of functions can be strung together to perform a workflow in response to a triggering event. A validator can be included with a function that verifies that an input payload originated from a trusted source. A validation value, such as a hash, can be computed based on the result payload in combination with the source code of the function that produced the result payload. A downstream function can receive the result payload and the hash and utilize the result payload and a copy of the upstream source code to produce another hash. The received and generated hashes can then be compared and utilized to control execution of the downstream function. Execution can be prevented when there is a mismatch between the hashes.

The disclosed embodiments include computer-implemented systems and methods that dynamically profile behavior using trained machine-learning or artificial-intelligence processes. For example, an apparatus may obtain a data element associated with an exchange of data, and based on an application of a trained machine-learning or artificial-intelligence process to an input dataset associated with the data element, the apparatus may generate behavioral profile data that includes a range of expected deviations from an expected value of the parameter during a temporal interval. Based on a determination that the range of expected deviations fails to include the first parameter value, the apparatus may perform operations that prioritize the position of the data element within the alert queue, and transmit, to a device, a notification that includes the data element and information characterizing the prioritized position of the data element within the alert queue.

Methods and systems are provided for utilizing interactive UI dialogs to resolve issues that may arise during the real-time ordering and activation of wireless products and services while a user is engaged during their session. The interactive UI dialogs may provide a customer with an opportunity to provide information, make decisions or trigger additional steps during the real time order.

Systems and methods for facilitating a transaction between a first entity and a second entity using a digital currency are described. In some aspects, a computing node participates in a private distributed ledger for a financial institution and stores one or more transaction blocks representing transactions in a digital currency. The digital currency is issued by the financial institution and is fixed with respect to a fiat currency. The computing node is configured to receive a transaction for transferring an amount of digital currency from a first entity to a second entity, generate a new transaction block representing the transaction, transmit the new transaction block to other computing nodes participating in the private distributed ledger, receive an indication of validity of the new transaction block, and insert the new transaction block into the private distributed ledger.

Payment platforms such as point of sale terminals can send test transactions to an acquirer processor certification and analytics system for certification of the payment platform's readiness to perform financial transaction processing with payment networks. A payment platform sends a test transaction to an acquirer processor and receives a unique request identifier. The request identifier and a test identifier associated with the test transaction are sent to an analytics engine that retrieves data associated with the test transaction from the acquirer processor, and expected values based on the test identifier. The analytics engine performs a comparison and determines a certification result for the payment platform based on the comparison. Based on certification results, authorization or licenses can be granted to payment platforms to use payment networks of the acquirer processor.

A computer-implemented method includes receiving, from a mobile device, a deposit request including a first check image for funds to be deposited into a user account, determining a risk level associated with the deposit request, requesting a second check image having a restricted endorsement based on the risk level, receiving the second check image having the restricted endorsement, determining a confidence level based on the restricted endorsement, and transferring the funds to the user account based on the confidence level.

Account information for a plurality of accounts and transaction information for a plurality of transactions conducted among the plurality of accounts are analyzed. A transaction volume threshold is determined based on the analysis. A first subset of the accounts is identified. The first subset of account each corresponds to an amount of conducted transactions below the transaction volume threshold. A second subset of the accounts is identified. The second subset of the accounts each corresponds to an amount of conducted transactions above the transaction volume threshold. In response to the identification of the first subset and the second subset of the accounts, the account information and the transaction information are stored into an electronic database collectively for the first subset of the accounts, and the account information and the transaction information are stored into the electronic database separately for the second subset of the accounts.

Various embodiments described herein are generally directed to techniques for managing fraud rules and generating authentication directions according to location data from one or more client devices. Embodiments may include using a payment server informed by a client device application to manage and/or apply fraud rules for transactions. In embodiments, fraud rules may be managed based on location data provided by a client device application and/or location data associated with at least one transaction system. In some embodiments, fraud rules may be managed based on location data provided by multiple client device applications and/or location data associated with at least one transaction system. In some embodiments, rules may be managed for an individual authorization request according to information from at least one client device application and location data for a transaction system associated with the authorization request.