Abstract: Enhanced authentication at resource event apparatuses of a card device and, in some instances, the user of the card device. Card device-specific Non-Fungible Tokens (NFTs) are generated and, in some instance, user credential-specific NFTs are generated. The NFTs are stored within a distributed ledger of a distributed trust computing network, which provides verification as the uniqueness and authenticity of the NFTs. Once a resource event is initiated at a resource event apparatus, card device-related information and, in some instance, user credential-related information is received, and the information is compared to the corresponding NFT as a means of authenticating the card device and, in some instances, the card device and the linked user of the card device. As a result, the use of imitation card devices is prevented and, in some instances, the identity of the user of the card device is authenticated and deemed to be linked to the card device.

Abstract: Methods and systems for user definable prioritization of market information are disclosed. An example method to prioritize market information displayed in a window within a trading interface includes updating the market information displayed in the window at a first frequency, wherein the first frequency is to correspond to a first window priority. The example method also includes, based on a trigger activation, assigning a second window priority to the window, wherein the second window priority is to cause the market information displayed in the window to update at a second frequency, the second frequency different from the first frequency.

Abstract: A fraud prevention server that includes an electronic processor and a memory. The memory includes an online application origination (OAO) service and a plurality of OAO models, each of the plurality of OAO models differentiates between a behavior of a normal user and a behavior of a nefarious actor during a submission of the online application on a device. When executing the OAO service, the electronic processor is configured to receive form data from a client server, determine a best OAO model from a plurality of OAO models with deep-learning, determine a fraud score of the online application based on the best OAO model, and control the client server to approve, hold, or deny the online application based on the fraud score that is determined.

Abstract: An electronic tax assistant for assisting a user in preparing for a tax return preparation process, wherein the electronic tax assistant performs the following steps: determine a trigger based upon a data input, wherein the trigger is indicative of a potential tax implication; determine a data request based at least in part on the data input, wherein at least one of the data input and the data request is associated with an external device; receive a response based upon the data request, wherein the response is indicative as to whether the trigger is indicative of an actual tax implication; and provide, upon determining the actual tax implication, information in indicative of the data input and the response to an external repository associated with a tax preparation system.

Abstract: Aspects of the disclosure relate to machine learning based automated management of a user account. A computing platform may determine, via a computing device and based on historical user activity of a user, a pattern of the user activity. Subsequently, the computing platform may detect a deviation from the pattern of the user activity. Then, the computing platform may identify an anticipated transaction of the user. Then, the computing platform may retrieve, from a repository of user data, one or more user-defined preference rules associated with the anticipated transaction. Then, the computing platform may determine whether the one or more preference rules apply to one or more attributes of the anticipated transaction. Subsequently, the computing platform may trigger, based on a determination that the one or more preference rules apply to the one or more attributes of the anticipated transaction, an action associated with the anticipated transaction.

Abstract: Aspects described herein may use a machine learning model to identify transactions likely to be remembered by a user and that may be used to generate challenge questions to authenticate the user. An individual may request an action related to a financial account. In response to the request, the machine learning model may determine a likelihood an authorized user of the financial account will remember one or more recent transactions. The likelihood of each candidate transaction may be compared to a predetermined threshold to determine a subset of recent transactions. Information relating to the subset of recent transactions may be used to generate one or more challenge questions to pose to the user. The user's responses to the challenge questions may be used to evaluate whether the user is the authorized user of the financial account or is a fraudster or imposter.

Abstract: Systems and methods for issuer-specified domain control on a payment instrument are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for issuer-specified domain controls on a payment instrument may include: (1) receiving, from an issuer of a financial instrument, an identification of a domain control or restriction on a payment token for the financial instrument, the domain control or restriction to be applied by the issuer; (2) requesting generation of the payment token with a pass-through indicator from a token service provider; (3) receiving, from the token service provider, the payment token; and (4) storing an association of the domain control or restriction and the payment token.

Abstract: A system and method for ensuring the authenticity of imaged documents by embedding data into the images of such documents. The embedded data can then be extracted and decoded, and used to determine whether a particular document may be fraudulent. The documents may be checks, money orders, contracts, invoices, titles or other legal documents that may need to have their authenticity confirmed to prevent, for example, forged or otherwise false documents from being accepted as genuine.

Abstract: A planning engine for a financial planning system including at least one processor is provided. The at least one processor is programmed to receive user profile data and account data, assign an asset class weight to each of a plurality of asset classes associated with the account data, and retrieve an expected asset class return, an asset class standard deviation, and an asset class covariance. The processor is also programmed to generate a portfolio data object for each of the plurality of future years wherein the portfolio data object calculates (i) an expected portfolio return across the plurality of asset classes and (ii) a portfolio standard deviation across the plurality of asset classes. The processor is further configured to pass the portfolio data object to a monte carlo return object, receive, from the monte carlo return object, a matrix, and return an account projection derived from the matrix.

Abstract: A digital token has a programmable field in which token type is specified. A method of creating, routing, and performing operations on digital tokens is carried out in a network having a plurality of nodes, wherein each node of the network has code executed therein to enforce rules associated with different types of the digital tokens. The method includes the steps of: creating a digital token having a programmable field from asset data and specifying a token type of the digital token in the programmable field of the digital token; routing the digital token having the specified token type through the nodes of the network to a destination node according to the rules associated with the specified token type; and when the digital token arrives at the destination node, performing an operation on the digital token and updating a record maintained at the destination node according to the operation performed.

Abstract: Systems and methods utilized to protect data. One method includes receiving a trade order and determining a current exchange rate for a plurality of different currency transactions. The method further includes determining a trade sequence, generating a first public and private key pair for the trade order and a second public and private key pair, and transmitting the public key of the first public and private key pair. The method further includes receiving a trade confirmation and updating an account balance entry on an overlay ledger. The method further includes broadcasting the trade order to a plurality of MBC verification nodes and in response to the plurality of MBC verification nodes verifying the trade order, updating a blockchain.

Abstract: Provided is a multi-card having a fingerprint input unit and a payment method using the same, and the multi-card includes a secure element adapted to allow multiple pieces of card information issued to the same card service to match each of a plurality of fingerprints to thus store the matching results therein and a fingerprint input unit for receiving the plurality of fingerprints inputted thereto, wherein the secure element produces transaction response information having one piece of card information activated according to the fingerprint information inputted to the fingerprint input unit.

Abstract: Systems and methods are provided for use in facilitating network messages. An exemplary method includes receiving, at a network, an instruction associated with a first user and specific to a first user account, where the instruction is directed to a second user account associated with a second user. The method also includes compiling a pre-authorization message indicative of the instruction, consistent with a first message standard and including an identifier of the first user account, and transmitting the pre-authorization message to a first institution associated with the first user account.

Abstract: This present disclosure provides a risk assessment method and system for affordable housing application in a smart city based on Internet of Things. The risk assessment method is executed by the management platform, and the risk assessment method includes obtaining a query request for a risk of the affordable housing application from the service platform, wherein the query request is generated by the user platform based on an input of the affordable housing application by an applicant through the user platform; in response to the query request, through a management sub-platform corresponding to the management platform and a service sub-platform corresponding to the service platform, obtaining relevant information of the applicant and his/her related persons thereof, and determining the risk of the affordable housing application of the applicant; and sending the risk of the affordable housing application to the service platform.

Abstract: A computer system including a processor, in communication with a database, programmed to identify a plurality of billers from the database, including biller information, and receive a payee file including payee information identifying a payee which issued a bill to a payor. The processor determines an approximate match score for each of the billers in a first set of billers of the plurality of billers by comparing payee information to biller information and identifies a candidate list of billers from the first set of billers having an approximate match score indicating a likelihood of matching the payee information. The processor adjusts the candidate list of billers by altering the match score of at least one candidate biller by comparing a payee account number of the payee information to an account mask associated with the candidate biller and generates an output file of candidate biller information from the adjusted candidate list.

Abstract: Various methods, apparatuses/systems, and media for implementing a multi-tier intercommunication module (MTIM) for an automatic teller machine (ATM) to prevent fraudulent and forced transactions are provided. A processor within the MTIM verifies whether an anomaly withdrawal transaction is occurring based on analysis of a user's normal banking behavior. When anomaly transactions are detected, the processor transmits a notification to the user's registered Multi-Factor Authentication (MFA) device to verify whether the transaction is fraudulent. Additionally, the MTIM provides a continuous feedback loop of user location data when forced transactions have been triggered. Forced card transactions are allowed completion and the MTIM sends a custom security code (CSC) to the user's registered MFA mobile device.

Abstract: This disclosure relates to systems and methods for processing electronic payments for customer purchases. In some implementations, a mobile computing device receives a payment request identifying a sales transaction between a merchant and a customer. The payment request indicates a purchase amount owed by the customer to the merchant, and carries a set of instructions. The mobile computing device activates a card reader based at least in part on the set of instructions, receives customer authorization for electronic payment of the purchase amount, instructs the card reader to process a credit card for the purchase amount based on receiving the customer authorization, and receives confirmation of payment of the purchase amount from the card reader.

Abstract: Home telematics devices are engineered to identify unique device signatures for all appliances, fixtures, and so on that generate voltage noise, pressure waves, and acoustic responses throughout a property. The device signatures comprise the inventory of devices in the insured's home and are used to create an electronic record of the devices that assists him in filing a claim with an insurer that is quick and easy after a theft or total loss. Using the device signatures provided by home telematics devices' sensing an itemization technology, fraud detection is also possible. Additionally, analytics software predicts possible failure by analyzing the device signatures.

Abstract: A system and method for online payment are described. The method includes receiving, from a vendor server, a payment amount, an identifier of a user and an identifier of a vendor; sending an indication of a payment to a user device associated with the identifier of the user; receiving, from the user device, a confirmation of the payment; receiving, from the user device, supplementary information generated when or after the user confirms the payment; determining legitimacy of the transaction based on the supplementary information; and making the payment from a financial account associated with the user identifier to a financial account associated with the identifier of the vendor if the transaction is legitimate.

Abstract: System, apparatus, user equipment, and associated computer program and computing methods are provided for facilitating efficient decision-making with respect to a subject entity. In one aspect, a labeled training dataset containing N records respectively corresponding to N entities is provided for training a decision engine based on performing supervised learning. Responsive to receiving a plurality of attribute values for the subject entity requiring a decision relative to an estimate of a performance variable based on at least a portion of the attribute values, the trained decision engine is configured to determine a decision score as a function obtained as a set of linearly decomposed constituent components corresponding to the attribute values of the subject entity, thereby effectuating an objective determination of which attributes contribute to what portions of the decision score in a computationally efficient manner.