Abstract: A system may include one or more detectors configured to generate detector data based on signals received from one or more tags integrated in or disposed on one or more items. The system may include a processor configured to: receive the detector data; determine a first set of identification information corresponding to a first item of the one or more items based on the detector data; receive a list of tagged items for a first location, and the list of tagged items comprises a second set of identification information corresponding to the one or more items; identify a theft incident for the first item based on a comparison of the first and second sets of identification information; automatically send a notification relating to the theft incident to one or more devices; and determine one or more insurance policy decisions for the first item based on the theft incident.

Abstract: Methods and systems described in this disclosure are directed at developing a life planner for a user based on data collected from various data sources. The life plan is displayed using a timeline that includes events generated from the collected data. As additional data is received, the timeline is updated to reflect the changes or additions to the data. In some embodiments, the life plan includes recommendations and predictions pertaining to a financial plan for the user based on his or her expenses and income.

Abstract: A system for system for dynamic card identifier based transactions is disclosed. The system may receive a transaction authentication request. The system may generate a first dynamic card identifier (DCID) in response to the transaction authentication request. The system may authenticate a transaction based on the first DCID. The system may execute the transaction in response to the authenticating. In various embodiments, the system may generate a second DCID in response to executing the transaction.

Abstract: A wearable device, system and method. The wearable device comprises a frame portion and a body portion. The frame portion is formed from a metallic material and the body portion is formed from a non-metallic material. The frame portion is configured to partially surround the body portion. The body portion supports at least one passive or active tag thereon such that the tag is operable through an opening in the frame portion.

Abstract: The present disclosure includes an account binding method. In the method, an account addition page is presented in a first application that is currently logged into using an application account of the first application. Information acquisition instruction carrying user identity information in an encrypted form is transmitted to an account provider system, in response to an account addition instruction triggered. A to-be-bound account that is associated with the user identity information and acquired and fed back by the account provider system is received. The received to-be-bound account is displayed on a gateway page of the account provider system. Also, binding between the application account of the first application and the to-be-bound account is performed, when the displayed to-be-bound account is confirmed by a user operation of the gateway page.

Abstract: An example operation may include one or more of receiving, by a blockchain node of a permissioned blockchain network, a request to transfer an asset from an asset provider to an asset requester, determining the request is valid, and in response validating one or more of an asset requester and an asset provider associated with the request, determining a risk exposure associated with the request is acceptable and generating a blockchain transaction to a public blockchain network to transfer the asset.

Abstract: Example embodiments of systems, methods, and computer-accessible mediums for identity verification and transaction authentication are provided. An exemplary system can comprise an application, a user device, and a server. The application can prompt a removal of a card chip, prompt an insertion of the card chip into the user device, determine an orientation of the card chip after the insertion of the card chip into the user device, and transmit, to the card chip, a first message. The card chip can encrypt the first message via one or more authentication protocols to generate an encrypted first message, transmit, to the server, the encrypted first message. The server can decrypt the encrypted first message, verify the decrypted first message, and transmit a second message to the application, wherein the application is configured to display a verification notification in response to the second message.

Abstract: The present invention discloses systems and methods for facilitating a public offering for a company on an immutable blockchain. The disclosed systems and methods provide hosting indications of interest on a blockchain for potential, initial or secondary future offerings proposed by a company and provided to interested investors on a first-come, first-serve basis. After qualified investors establish their interest in a public offering by returning their indications of interest, a list of prioritized members eligible to invest in the company based upon the recorded time and date of the indication of interest is established, and a fair distribution flow of the public offering is created by providing prioritized members a fair distribution of securities.

Abstract: In one aspect, the present invention provides a computing system for effecting an optimised condition for one or more booking requests in a venue having one or more spaces, comprising an allocation module executing on a processor and arranged to retrieve the booking requests from a database containing a plurality of booking requests, the booking requests including requestor constraint information regarding one or more constraints provided by the booking requestor including a predefined service period, and retrieve venue constraint information from a database, the venue constraint information including venue spatial information and furniture spatial information, wherein the allocation module executes an allocation algorithm that utilises the booking information and the venue constraint information to assess the capacity of the one or more venues and allocate a portion of space for each booking request to satisfy the optimised condition utilising the assessment, to derive an optimised allocation instruction set

Abstract: An exemplary system, method, and computer-accessible medium for recommending a model(s), can include, for example, receiving a plurality of test models including the model(s), determining if each of the test models has at least one verifier associated therewith, and recommending the model(s) based on the determination. An indication of a stake associated with each of the test models can be received. The stake can be a financial stake or a reputation stake. The financial stake can be a cryptocurrency. At least one of the test models can be analyzed using a machine learning procedure, which can be a convolutional neural network or a recurrent neural network. At least one of the test models can be analyzed using an empirical Bayes procedure. A particular model can be removed if the particular model(s) does not have a verifier(s) associated therewith.

Abstract: A user is provided with a GUI that may allow the user to change functionality associated with a non-powered card, a powered card or other device (e.g., a mobile telephonic device). The functionality associated with the device may be displayed by the GUI as a list of third-party applications that may be executed when the user's card or other device is used to complete a purchase transaction. The GUI allows the user to receive and view notifications sent from the third-party application developer via a remote facility that may, for example, allow the third-party application developer to promote the third-party application.

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: 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: 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 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.