190 results about "CreditCard" patented technology

An example operation may include one or more of training a large language model (LLM) to learn credit card data via execution of the LLM on content from one or more credit card documents, executing the LLM to generate a sequence of prompts which are output to a user via a chatbot within a chat window of a software application, receiving responses to the sequence of prompts for the user via the chat window of the software application, and retraining the LLM model to further learn credit card data via execution of the LLM on a combination of the sequence of prompts and the received responses.

1. The name of the product of this design: magnetic card holder. 2. Purpose of the product of this design: used to hold items such as banknotes and credit cards. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: Stereoscopic diagram 1.

A cybersecurity data loss prevention service stops users from stealing, or exfiltrating, sensitive data. An endpoint cybersecurity agent coordinates the installation of a browser extension. The browser extension adds content scripts to a web browser that monitor for exfiltration events. The exfiltration events represent a user's browser inputs (such as cut-n-paste or drag-n-drop) that can be used to exfiltrate usernames, passwords, credit card numbers, company secrets, and any other sensitive data. When the browser extension detects any exfiltration event, the browser extension intercepts and synchronously blocks the exfiltration event from the web browser. Moreover, the browser extension sends a duplicate copy of the exfiltration event to the cybersecurity agent for evaluation. If the cybersecurity agent determines that the user's browser inputs should have been allowed, then the browser extension is instructed to trigger the duplicate copy. The web browser thus asynchronously processes the user's browser inputs, albeit slightly delayed.

The embodiment of the invention provides a consumption scene preference prediction model training method and device, equipment and a medium. The method comprises the following steps: acquiring historical multi-dimensional information of a user; according to the historical multi-dimensional information, determining a consumption scene preference score of the user in a predefined consumption scene; screening out a target consumption scene with the maximum consumption scene preference score from the consumption scenes; constructing a model training sample according to the historical multi-dimensional information and the target consumption scene; and training based on the model training sample to obtain a consumption scene preference prediction model for consumption scene preference prediction. According to the embodiment of the invention, the marketing effect and the user satisfaction are improved, operation and resource configuration are optimized, precise marketing is realized, and numerous key scenes of credit card customer operation and marketing are covered.

In some examples, a method is included for converting and exchanging loyalty points. The method includes generating, by a computing system, records that include relationship information linking a credit card of a credit card issuer to loyalty rewards program entities. The method includes converting card issuer points of the issuer to loyalty rewards program points of one loyalty rewards program entity of the program entities according to a point conversion rule. The loyalty rewards program points can be issued by the one loyalty rewards program entity to a corresponding loyalty rewards program account of a cardholder of the card after the conversion and according to the point conversion rule. And, the conversion of the card issuer points to the loyalty rewards program points can include a two-step conversion including converting the card issuer points to intermediate points and then converting the intermediate points to the loyalty rewards program points.

A neck scarf or shawl formed of a cylindrical of fabric. The transverse width and the circumference of the tubular body are sized to permit the scarf to be worn by an adult person and to cover the upper arms and upper body of the person in a fully deployed position. The cylinder of fabric has upper and lower circular edges with first and second elastic sections. A closeable pouch is secured on the inside of the fabric cylinder between the elastic edge sections. An open pocket may be provided on the surface of the pouch. The elastic sections allow the pouch and its contents to be secured by twisting the panel so that the pouch it is secured inside a double-wrapped layer of fabric. The pouch may be lined with RFID blocking material to prevent surreptitious reading of credit cards or other magnetic data media inside the pouch.

Methods for an electronic token-based payment system includes providing a deferred-payment service by a network-accessible deferred-payment server that performs the steps of processing authorization of digital content purchases for a user account without requiring payment at time of purchase, monitoring a total outstanding purchase balance associated with the user account, and transmitting a settlement request signal to a computer server associated with the financial institution having a credit card account associated with the user for settlement of at least a part of the total outstanding purchase balance when the total outstanding balance exceeds at least one of a predetermined threshold amount and / or accrued over a time that exceeds a predetermined time interval. The transmitted settlement request signal includes information indicative of the total outstanding purchase balance owed, and the electronic token associated with the user of the user account. The electronic token being obtained from a user information database containing electronic tokens associated with corresponding respective user accounts, each token being unique with respect to both a user account of the deferred-payment service for a user, and with respect to a credit card account issued by the financial institution for such user. The token including encrypted information of a characteristic of a user who is associated with the user account, in absence of any information of the user account identification or the credit card account identification, wherein the deferred-payment service has not been provided with, nor has access to, the credit card account identification.

A garment or article of clothing made of a resilient / elastomeric material includes at least a waist portion, a first leg portion, and a second leg portion. The waist portion further includes a pocket on the rear of the garment, where the pocket is defined by a backing panel, a first flap, and a second flap. The first flap is at least partially disposed over the second flap to secure contents between the backing panel and the second panel, and thus, within the pocket. When the waist portion is stretched, the tensile forces imparted onto the waist portion by the resilient / elastomeric material causes the first flap to at least partially overlie the second flap. The pocket is sized and shaped to receive smartphones and other small personal items, such as keys, money, credit cards, identifications, etc.

To provide an information processing device, an information processing method, and a program capable of appropriately selecting affiliated stores that permit the use of a prepaid card. [Solution] An information processing device comprising: an acquisition unit that acquires at least a credit card payment history performed at one or more credit card affiliated stores; and a generation unit that generates, based on the payment history, list information that identifies affiliated stores among the one or more affiliated stores that will or will not allow the use of a prepaid card that performs payment processing using the electronic money balance of an electronic payment service charged by the user.

A methodological technical approach is proposed herein that utilizes historical data to employ a heuristic optimization algorithm for data message routing. While not specifically limited to the banking sector and financial institutions, as a practical example, the approach can utilize historical data relating to patterns of transactions for analyzing customer behavior and detecting fraudulent activities. For example, trajectory mining can be used to analyze the transaction patterns of credit card users, or behavioural patterns of mobile banking users, such as checking account balance, transferring funds and paying bills.

To provide a system for detecting the illicit use of a credit card on the basis of authorization data, in which a determination as to the illicit use is made by taking an action of a user not linked with the authorization data into consideration.SOLUTION: A payment management device for offering an electronic payment service to a user in cooperation with an application program which operates in a terminal device of the user, includes an acquisition unit that acquires, from the application program, operation information about an operation performed on the application program by the user, and a detection unit that detects a particular operation performed on the application program on the basis of the operation information. When detecting that the particular operation has been performed on the application program, the detection unit transmits information for recording the occurrence of the particular operation to a credit payment management device that manages a credit card recorded in the application program.SELECTED DRAWING: Figure 12

The invention discloses a credit card transaction anomaly detection method and device and a medium, and the method comprises the steps: obtaining credit card transaction data, and executing data preprocessing and spatial-temporal feature coding; based on a variational auto-encoder, constructing a reference mode of normal transaction through unsupervised learning, and analyzing credit card transaction data to obtain a corresponding reconstruction error; and based on a deep reinforcement learning model, optimization is carried out through a trial and error learning optimization detection strategy, credit card transaction data is analyzed, and abnormal actions are marked. The dynamic adaptability is enhanced, autonomous discovery of a novel fraud mode is realized, and a traditional method depends on a static rule or a fixed model and is difficult to deal with quickly evolved fraud means (such as zero-day attack and cross-border collaborative fraud fraud). Through the DRL-VAE collaborative architecture, the unsupervised reconstruction error of the variational auto-encoder is used as an internal reward signal, and the reinforcement learning agent is driven to actively explore the unknown abnormal mode.

A tamperproof diamond package comprises a package body; at least one chip embedded in the package body and at least one antenna configured to enable communication with the chip; anti-counterfeiting visual impressions on the package body; a diamond pouch formed at a predetermined section within the package body; and one or more diamonds located inside the diamond pouch and an outer covering encasing the package body and configured to reveal any tampering with the one or more diamonds located in the diamond pouch. The diamond package can be credit card shaped and also contains serial number and website information and be provided in nominal dollar values. An associated diamond exchange system utilizes the diamond packages and provides a registration server which stores unique identifying information that enable interrogating the individual diamond packages and checking their authenticity with the registration server.

The invention belongs to the technical field of financial industry transaction fraud detection, and relates to a self-adaptive label sensing graph neural network credit card fraud detection method, which comprises the following steps: acquiring credit card transaction data and inputting the credit card transaction data into a trained credit card fraud detection model to obtain a fraud detection result; the training process of the fraud detection model comprises the following steps: obtaining a credit card transaction record data set to construct an initial multi-relation heterogeneous graph; inputting the initial multi-relation heterogeneous graph into a plurality of graph aggregation layers which are sequentially connected in series; inputting the node features output by the last graph aggregation layer into a classification module to obtain a fraud detection result; updating model parameters according to a fraud detection result until a training credit card fraud detection model is obtained; according to the method, node features are aggregated for each relationship by using a graph attention mechanism in a graph aggregation layer, and different types of neighbors are further processed by using a conversion module, so that the nodes adaptively adjust information aggregated from the neighbors with different sex and the neighbors with same sex, and the capability of credit card fraud detection tasks is improved.

The disclosed system and method can manage real-time transactions using a blockchain ledger. A processor can create a fractionalized risk pool for a property, comprising asset tokens and an occupancy token. The processor can receive title information and can update the blockchain ledger with this information, a timestamp, and / or a property valuation. Upon receiving a transaction from a credit card network and / or issuing bank, the processor can determine a user's real-time equity.

A system and method for making credit card to credit card payments. The system may include a processor, a network, a general ledger, a staging element with reconcilement capabilities, an institution account, and a clearing house account. The system may complete a credit card to credit card transaction by utilizing the credit available in a credit card account to reimburse funds utilized through the institution account. The clearing house ensures the transaction is satisfied by both the institution account and the credit card account. The operations may include providing an interface; using generative artificial intelligence to generate a prompt specific to an account associated with the interface; and displaying the prompt to a user of the account.

The invention belongs to the technical field of financial industry transaction fraud detection, and relates to a residual aggregation enhanced neighborhood graph sampling credit card fraud detection method, which comprises the following steps: acquiring credit card transaction data and inputting the credit card transaction data into a credit card fraud detection model to obtain a fraud detection result; the training process of the credit card fraud detection model comprises the steps of obtaining credit card transaction data and constructing a multi-relation heterogeneous graph; inputting the multi-relation heterogeneous graph into a plurality of graph aggregation layers which are sequentially connected in series to obtain a multi-relation heterogeneous graph output by each graph aggregation layer; the node features of the multi-relation heterogeneous graph output by each layer are input into a shallow layer residual error aggregation module, and final node features are obtained; inputting the final node feature representation into a classification module to obtain a fraud detection result; updating model parameters according to a fraud detection result until a trained fraud detection model is obtained; according to the method, the node features are updated under each relation type in the graph aggregation layer, and the neighbor information of the node features in various relation types is fully utilized.

To provide a terminal capable of recognizing that settlement cannot be performed in a stage before trying the settlement by a settlement server when a user owns a credit card to be used for the settlement and another credit card in which a part of card face information is the same.SOLUTION: The device 10A includes a determination unit 113 that, when an operation of the user U instructing credit settlement using a first credit card is received, determines whether or not first information identical to first information relating to the first credit card is also stored in a storage device 12A storing first information that is a part of identification information uniquely identifying each of a plurality of credit cards that the user U can use for credit settlement, and a display control unit 114A that, when a determination result of the determination unit 113 is affirmative, displays, on a display, that credit settlement cannot be performed.SELECTED DRAWING: Figure 3

To improve convenience of a user.SOLUTION: An acquisition unit configured to acquire credit settlement information regarding a settlement transmitted in response to a user using a credit card at a member store of a credit card, and identify second user identification information managed in a service that provides a first benefit corresponding to first user identification information for identifying the user included in the credit settlement information; A processing unit configured to specify second member store identification information managed in the service corresponding to first member store identification information for identifying the member store included in the credit payment information, and apply the first privilege to the payment of the credit payment information when the first privilege applied to the payment of the credit card at the member store of the second member store identification information is associated with the second user identification information in the service.SELECTED DRAWING: Figure 1

The application discloses a method for processing data sets in credit card fraud transactions based on clustering down-sampling technology, and relates to the application of artificial intelligence field related algorithm. According to the nature of the transaction, the credit card transaction is divided into normal transaction and fraud transaction, and the K-Means clustering algorithm is used for clustering all normal transactions. For each credit card normal transaction cluster obtained by clustering, a new node is created to represent the cluster, and the new node represents the characteristics of the normal transactions with similar characteristics. These new nodes represent the representatives of normal transaction nodes with similar characteristics, and the new nodes of all clusters constitute a new normal transaction set. Finally, the new normal transaction set and the fraud transaction set are combined into a balanced training data set. The application solves the technical problem that the existing technology cannot effectively extract the characteristics of a specific group due to the imbalance of the data set in the credit card fraud detection, resulting in slow operation efficiency and low accuracy.

To provide a card issuance application system capable of improving the performance of issuing credit cards to people who are qualified to hold credit cards. [Solution] A card issuance application system 1 allows an applicant to apply for the issuance of a credit card from a terminal connected via a network. The system includes a basic information acquisition unit 21 that prompts an applicant terminal 4 to input basic information for screening, a first screening instruction unit 23 that instructs the implementation of a first screening based on the basic information, and an additional information acquisition unit 24 that prompts the applicant terminal to input additional information when the result of the first screening indicates that a rescreening is required.

The embodiment of the invention provides a data processing method, electronic equipment, a storage medium and a program product. The method comprises the following steps: judging which type a target customer to be processed belongs to; according to the type, feature data related to the type of customers is found; and according to the feature data, determining a link in which the target customer is located, and pushing corresponding activity information to the target customer according to an activity pushing strategy of the corresponding link. When the feature data of the target customer is determined, not only are behavior features of the credit card application program considered, but also card use features of the credit card and card use and behavior composite features are considered, so that the determined features can be more comprehensive, and activity information can be pushed to the target customer more accurately.

The invention relates to the field of machine learning, and particularly provides a financial fraud detection method and device, and the method comprises the following steps: S1, obtaining financial transaction transfer related information; s2, performing data preprocessing on the related information to obtain transfer risk feature data; and S3, according to the transfer risk feature data and a Stacking ensemble learning risk identification model, obtaining a corresponding transfer risk identification result in the transfer transaction. Compared with the prior art, the method has the advantages of being high in real-time performance, outstanding in anti-interference capability and good in expandability, and is suitable for financial risk control scenes such as credit card fraud prevention and money laundering prevention.

The invention discloses a credit card management method and device, equipment, a storage medium and a product. The specific scheme is as follows: verifying at least one locking code of a plurality of credit cards according to a preset management constraint condition of a plurality of credit card management levels to obtain a target control parameter corresponding to each credit card; when it is detected that the received target transaction data belongs to credit card transaction, target credit card information is determined, and a target control parameter corresponding to the target credit card information is called; and when the target transaction data and the target control parameter meet a preset condition, returning transaction completion response data indicating that the target transaction corresponding to the target transaction data is completed. According to the method, the locking code and the target control parameter are adopted, effective risk management and control of credit card transaction are realized, and the credit card use experience of a user is improved.

1. Name of the product in this design: Interface main body of a graphical user interface for displaying the rights and interests of electronic devices. 2. Intended use of this design: for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: The overall and partial purpose of this design is to display card benefits information, such as credit card benefits. 7. Human-computer interaction method of graphical user interface: In Design 1, when the user clicks the “Limited-time bonus gift” module in the main view of Design 1, he / she can view the details of the benefits, as shown in the reference figure of the interface usage status of Design 1. The human-computer interaction methods of Designs 2 to 8 are the same as those of Design 1, and will not be described again. 8. Other situations requiring explanation: The text and numerical content in each design interface does not limit the scope of protection of this design. The dashed lines in the interface represent parts that do not require protection.

1. Name of the design product: bank card. 2. Use of the design product: used as a bank card, such as a credit card or a debit card. 3. Design points of the design product: in the pattern. 4. Picture or photo that best indicates the design points: front view. 5. The design product is a thin product, and the left view, right view, top view, and bottom view are omitted.

The invention relates to the technical field of block chains, and discloses a block chain-based card surface pattern information management method and device, a medium and equipment, and the method comprises the steps: storing a digital file of a credit card surface pattern into a distributed storage system, and obtaining a corresponding content identifier; performing NFT casting by using the smart contract of the block chain, generating an unallocated card surface NFT, and recording the unallocated card surface NFT in the block chain; after the application of the user credit card is passed, the card surface NFT is bound with the user credit card, and then the state of the card surface NFT is updated to be allocated; and making an entity credit card based on the digitized file corresponding to the allocated card surface NFT, and transferring the ownership of the card surface NFT to the block chain address of the corresponding user after the entity credit card is activated. According to the method, the card surface pattern is bound with the life cycle of the credit card, so that the card surface pattern is converted from a static pattern to a digital asset which is synchronous with the physical card state, and the digital value bearing capacity of the credit card is improved.

The application provides a gift recommendation method, device and equipment and a storage medium; the method in the application comprises the following steps: receiving a gift recommendation request, extracting a target user corresponding to the gift recommendation request and user attribute characteristics of the target user; extracting historical user comments of the target user according to the user attribute characteristics, and performing sentiment tendency analysis on the historical user comments to obtain positive user comments; obtaining evaluation commodities corresponding to the positive user comments and target gift categories corresponding to the evaluation commodities, obtaining candidate gifts corresponding to the target gift categories in a preset gift database; obtaining historical gift comments of the candidate gifts, determining target gifts to be recommended according to the historical gift comments and the positive user comments, and recommending the target gifts to the target user. The target gifts that the target user is interested in are determined according to the historical user comments of the target user, and the recommendation accuracy of credit card gifts is improved.

To provide an information processing system, information processing method, and program, which allow for performing processing for making on-behalf-of payments of bills issued by sellers.SOLUTION: An information processing system disclosed herein provides a service that makes on-behalf-of payments of bills issued by sellers. The information processing system comprises a first generation unit for generating first request information input screen information for inputting request information for credit card payment, an output unit for outputting the first request information input screen information, a reception unit for receiving first request information entered by a buyer on a first request information input screen, a determination unit for determining whether on-behalf-of payment by a credit card of the buyer is possible or not based on the first request information, and a second generation unit for generating error notification screen information for notification of an error when the on-behalf-of payment by the credit card of the buyer is determined to be not possible by the determination unit. The output unit outputs the error notification screen information generated by the second generation unit.SELECTED DRAWING: Figure 4

The invention relates to the technical field of credit card interest calculation processing, and particularly discloses a credit card real-time interest calculation method and system based on transaction triggering, and the method comprises the steps: dividing credit card account batch processing into an entry activity and an interest activity; splitting an interest activity into an interest calculation micro-service and an interest posting micro-service; and when a transaction meeting the interest calculation condition occurs, calling an interest activity to calculate the credit card account debt accumulated interest, judging whether the credit card account debt accumulated interest needs to be posted or not, and if so, calling a posting activity to perform posting processing. According to the method, when a transaction meeting an interest calculation condition occurs, the corresponding interest is calculated immediately, and real-time entry of the interest is supported, so that a card holder can clearly know the interest generated by each transaction at any time, and the consumption cost and debt condition of the card holder can be more accurately and timely grasped; the card holder is helped to better plan personal financial and repayment plans, and the card using experience of the card holder is improved.