Abstract: Systems and methods for automatic classification of loan collection actions are disclosed. An example system may include: a data collection circuit to interpret interactions among entities related to at least one transaction of a first set of loans, wherein the at least one transaction involves a first collection action of a set of payments corresponding to the first set of loans; an artificial intelligence circuit to classify the first collection action, wherein the artificial intelligence circuit is trained on the interactions corresponding to the first set of loans; and a robotic process automation circuit that is trained on the interactions and a set of loan collection outcomes corresponding to the first set of loans to implement a second loan collection action on behalf of a party to a second loan.

Abstract: Systems and methods for crowdsourcing data collection for condition classification of bond entities are disclosed. An example system may include a crowdsourcing data collection circuit to collect information about entities involved in a set of bond transactions and a training data set of outcomes related to the entities. The example system may include a condition classifying circuit to classify a condition of a set of issuers using the information from the crowdsourcing data collection circuit and a model, where the model is trained using the training data set of outcomes related to the set of issuers. The example system may also include an automated agent circuit to perform an action related to a debt transaction in response to the classified condition of at least one issuer of the set of issuers.

Abstract: A system and method for automated blockchain custody service for managing a set of custodial assets with block chain authenticity verification is disclosed.

Abstract: Systems and methods for automated servicing of a subsidized loan are disclosed. An example system may include a crowdsourcing services circuit to collect information related to a set of entities involved in a set of subsidized loan transactions and a condition classifying circuit including a model and an artificial intelligence services circuit to classify a set of parameters of the set of subsidized loans based on information from the crowdsourcing services circuit, where the model is trained using a training data set of outcomes related to subsidized loans. The example system may further include a smart contract circuit for automatically modifying a term or a condition of the subsidized loan based on the classified set of parameters from the condition classifying circuit.

Abstract: Financing tools can provide a flexible credit services to customer. A credit service provider can collect personal data from clients that can include a mobile telephone number and a legal name of the client as well as purchase information from a merchant. Based upon the collected data, the system can determine a client credit risk. The system can make a credit decision to offer a client credit to purchase goods or services based upon the credit risk.

Abstract: Verifiable order message handling for electronic auctions. Electronic order messages are received, with at least one message including an order of a predetermined type having sell order information associated with an entity having securities not previously registered for transactions. Requests for participation in an electronic auction are identified from among the messages. The requests include auction-only order information, with at least one request including the order of the predetermined type. It is determined whether the sell order information in the order of the predetermined type meets a predetermined auction condition based on an auction price. When the sell order information meets the predetermined auction condition, the order is permitted to participate in the electronic auction, such that the order is executed in full in the electronic auction. When the sell order information does not meet the predetermined auction condition, the electronic auction is canceled.

Abstract: A payment gateway is configured to directly access a revenue stream and financial information about the revenue stream. A machine learning (ML) model is trained to continuously process the financial information about the revenue stream to continuously analyze and score the revenue stream. A smart contract factory is responsive to the scoring by the ML model to generate at least one smart contract on a distributed, decentralized network. The smart contract is programmed to receive payments in stablecoins with respect to revenue stream.

Abstract: Systems and related methods include an Internet of Things data collection circuit structured to collect information about at least one entity involved in at least one transaction comprising at least one bond, a condition classifying circuit structured to classify a condition of the at least one entity in accordance with a model and based on information from the Internet of Things data collection circuit, wherein the model is trained using a training data set of a plurality outcomes related to the at least one entity, and an event processing circuit structured to undertake an action related to the at least one transaction in response to the classified condition of the at least one entity.

Abstract: Systems and methods for automated digital-property analysis are disclosed. A document representing a digital property may be received and the document, or key elements and/or language characterizations representing the document, may be utilized to search one or more databases for similar documents. The search results may be ranked and displayed for review. If an indication that the search results do not correspond to the document is received, that indication may be utilized to promote registration of the document with a trade-secret registry, for provision of insurance policies, etc. Scheduled auditing may be established and utilized to confirm the digital property has not be disclosed and/or to determine a potential misappropriation event.

Abstract: An example operation includes one or more of capturing message content from messages between a sender and receiver which comprise information about a transfer of value from the sender to the receiver, detecting information about a compliance check within the message content which indicates whether the transfer of value complies with jurisdictional regulations, and recording the message content including the detected information about the compliance check via a blockchain.

Abstract: A system for processing a digital transaction includes a user authenticator, a processor in communication with the user authenticator, and non-transitory computer readable media that stores instruction code. The user authenticator is configured to receive biometric data associated with a user from a sensor. The sensor corresponds to at least one of: an image sensor, a finger print sensor, a motion sensor, a user interaction pattern sensor, and an infrared image sensor. The user authenticator is further configured to receive user identifying information and to determine whether the biometric data associated with the user is associated with the user identifying information to thereby validate the user. If the user is validated, the user authenticator is configured to generate user credentials associated with the user. The instruction code is executed by the processor and causes the processor to receive, from a user terminal, the user credentials.

Abstract: A method and system of providing a service node within a blockchain network. The method includes storing, in a memory of a processing server, a blockchain comprised of a plurality of blocks, wherein each block is comprised of at least a block header and one or more data values, wherein the one or more data values included in a most recent block includes at least one data point associated with services or functions of at least a first service node; receiving, by a receiving device of the processing server, a request from a second service node for the list of services or functions of the at least a first service node within the blockchain network; and validating, by the processing server, the request from the second service node for the list of services or functions of the at least a first service node within the blockchain network.

Abstract: Systems and methods for crowdsourcing information on loan collateral are disclosed. An example system may include a crowdsourcing request circuit to configure at least one parameter of a crowdsourcing request related to obtaining information on a condition of a collateral for a loan; a crowdsourcing publishing circuit to publish the crowdsourcing request to a group of information suppliers; and a crowdsourcing communications circuit to collect and process at least one response from the group of information suppliers, and to provide a reward to at least one of the group of information suppliers in response to a successful information supply event.

Abstract: Aspects of the present disclosure include an electronic ticket processing system that enables the management of a venue with auction-based, during event, peer-to-peer electronic ticket exchanges. The peer-to-peer during event ticket exchange can be limited by the location of the electronic device of a user and can allow the event attendees enhancement of their experience (e.g. by upgrading their seat location or rights to access). In some embodiments, the during event peer-to-peer ticket exchange can be encouraged or controlled by the venue in accordance to broadcasting aspects, crowd control, analytics, to encourage consumer spending, memberships, and/or other real time updates (e.g. weather, game scores, security concerns).

Abstract: According to an aspect, a system for automating pricing desk operations is described. The system includes an input module configured to receive a proposed offer in relation to a financial product and associated context information; a machine learning module trained to classify offers according to positive or negative client; a processing module configured to optimize the proposed and an output module configured to transmit the optimized offer for communication to the client. According to additional aspects, a corresponding computer-implemented method, non-transitory computer-readable medium, and systems and methods for training a machine learning module are also described.

Abstract: Systems and methods for automatic loan classification are disclosed. An example system may include a data collection circuit to collect a training set of interactions from at least one entity related to at least one loan transaction; an automated loan classification circuit trained on the training set of interactions to classify at least one loan negotiation action; and a robotic process automation circuit trained on a training set of a plurality of loan negotiation actions classified by the automated loan classification circuit and a plurality of loan transaction outcomes to negotiate terms and conditions of a new loan on behalf of a party to the new loan.

Abstract: Systems and methods for crowdsourcing information on a guarantor for a loan are disclosed. An example system may include a crowdsourcing request circuit to configure at least one parameter of a crowdsourcing request related to obtaining information on a condition of a guarantor for a loan; a crowdsourcing publishing circuit to publish the crowdsourcing request to a group of information suppliers; and a crowdsourcing communications circuit to collect and process at least one response from the group of information suppliers, and to provide a reward to at least one of the group of information suppliers in response to a successful information supply event.

Abstract: A tracking liquidity order and related market center and process are disclosed which allow posting market centers (e.g. exchanges) to fill routable, smaller orders that would have otherwise routed off the posting market center. Such tracking liquidity orders increase the liquidity of that posting market center and allow it to execute more orders internally, without having to route them to an away market center.

Abstract: A system that varies the terms and conditions of a subsidized loan includes a blockchain service circuit structured to interpret a plurality of access control features corresponding to a plurality of parties associated with a loan; a data collection circuit structured to interpret entity information corresponding to a plurality of entities related to a lending transaction corresponding to the loan; a smart contract circuit structured to specify loan terms and conditions relating to the loan; and a loan management circuit structured to interpret loan related events in response to the entity information, the plurality of access control features, and the loan terms and conditions, wherein the loan related events are associated with the loan; and implement loan related activities in response to the entity information, the plurality of access control features, and the loan terms and conditions, wherein the loan related activities are associated with the loan.

Abstract: A system and method of smart contract and distributed ledger platform with blockchain authenticity verification includes a blockchain service circuit structured to interface with a distributed ledger; a data collection circuit structured to receive data related to a set of items of collateral that provide security for a loan: a smart contract circuit structured to create a smart lending contract for the loan and assign at least a portion of the set of items of collateral to the loan, thereby creating an assigned set of items of collateral; wherein the blockchain service circuit is further structured to record the assigned set of items of collateral to a loan-entry in the distributed ledger, and wherein each of the blockchain service circuit, the data collection circuit, and the smart contract circuit further comprise a corresponding application programming interface (API) component structured to facilitate communication among the circuits of the system.