Abstract: A shared ledger operated by a group of network participants according to a set of consensus rules manages and resolves subrogation claims between a clamant and a defendant with arbitration. Evidence regarding the value of the subrogation claim is sent to the shared ledger by the parties to the subrogation claim such as sending data to a smart contract deployed on the shared ledger. The parties to the subrogation claim or entities that are not parties to the subrogation claim may broadcast data relating to fault to the blockchain. The data relating to fault may be evaluated by the parties or entities acting on the parties' behalf to determine fault. A fault determination may be broadcast to the blockchain based upon the analysis of the data relating to fault. Once the claim is resolved, arbitrator may release funds on the chain to the prevailing party or may accept confirmation that any payments have been made between the parties off-chain.

Abstract: A system may include a processor that may detect one or more loan indicators present in banking data or credit data associated with a user. The processor may then retrieve additional data associated with the user in response to detecting the one or more loan indicators, such that the additional data may include data acquired from a home assistant device, a wearable device, a computing device, or any combination thereof. The processor may then determine a loan probability associated with the user based on the banking data, the credit data, and the additional data. The processor may then determine a pre-approval loan amount based on the banking data and the credit data in response to the loan probability exceeding a threshold and automatically send a notification indicative of a pre-approval loan amount to a computing device associated with the user.

Abstract: Generating an asset ontology. Obtaining current transaction information associated with a current transaction, the current transaction information being obtained in response to the current transaction being processed by a point of sale system. Updating a subscriber profile based on the current transaction information. Selecting one or more subscriber roles based on the updated subscriber profile. Identifying one or more assets based on the one or more subscriber roles and the asset ontology. Selecting one or more incentives based on the one or more assets. Providing the one or more incentives to a subscriber system, thereby causing the subscriber system to present the one or more incentives at substantially the same time as the current transaction is processed by the point of sale system.

Abstract: A method for mobile credit acquisition is disclosed. The method deploys a shopping incentive offer, the shopping incentive offer for a shopping incentive. A device identifier associated with a user's mobile device is received in response to a user responding to the shopping incentive offer on the user's mobile device. In addition, a user identifier is received for the user. The device identifier and the user identifier are used to obtain user specific information useable for a credit prescreen. The shopping incentive is then provided to the user's mobile device. If the user does pass a credit prescreen, a pre-approved credit offer is also provided to the user via the user's mobile device in conjunction with the shopping incentive.

Abstract: A system and method are disclosed in which a user engaging in an online or in-person transaction with a merchant may create automatic expiring transactions for a credit card. The user provides the credit card information to an online interface or a point-of-sale device but specifies an expiration date that is on or before the actual expiration date of the credit card, known as an artificial expiration date. A token for the merchant is generated with the artificial expiration date. The issuing bank will honor the transaction with the artificial expiration date using the merchant-specific token, and the token may continue to be used with the online merchant until the artificial expiration date.

Abstract: A method of determining a Trac score representing an individual's future employment behavior using past and present employment behavior that are unrelated to skills and job match within a job and across multiple jobs of an individual when combined with public and available external records. A method employing a Trac score calculation system comprises at least one processor to execute computer program instructions for obtaining one or more ratings from one or more users through one or more user devices connected to the Trac score calculation system that assigns the credibility to the ratings. A combination of the Trac sub-score obtained by accumulating the ratings weighted by estimated credibility of each rating, and Adjustment sub-score obtained by processing available external records in public and private forms, creates a Trac score which is a numerical and reflects an aggregation of available data weighted by what is believed to affect the employment behavior.

Abstract: One embodiment of the system and method described herein provides a computer system configured to provide an interface for operation by a user at a remote computing device, receive a request from the user for a vehicle history report of a vehicle. The computer system is further configured to prompt the user for interest in a prequalification for a financing offer. The computer system is further configured to receive the indication of the user's interest in the prequalification. The system also includes a data storage module, accessible by the computer system, configured to retrieve data corresponding to the vehicle, store the retrieved data, retrieve data corresponding to a determination regarding the prequalification for the financing offer, and store the retrieved determination. The computer system is further configured to convey the vehicle history report to the user and convey the prequalification determination to the user.

Abstract: A streamline banking system includes a customer kiosk having a photographic element and a processor. The processor is programmed to capture an image with the photographic element and determine that the captured image comprises an image of a machine-readable code. The processor decodes the machine-readable code and extracts customer financial account data therefrom. The customer financial account data is associated with one or more financial institutions. The processor retrieves information associated with one or more financial product offerings offered by the financial institutions. Each of the financial institutions is presented to a customer along with the respective financial accounts and the respective financial product offerings. The customer selects one or more of the financial accounts and the financial product offerings. The customer kiosk then transmits to the customer service computing system the customer selection.

Abstract: Systems and methods are provided for identifying and compiling information relating to an entity for investigative analysis. The system may comprise one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to search, in one or more data sources, with a plurality of known characteristics of an entity to obtain a first plurality of records, identify from the first plurality of records a subset of records that match the known characteristics with a substantial confidence, compile the subset of records to form a unified record representing the entity and conduct a second search with information from the unified record to obtain a second plurality of search results.

Abstract: Machine learning techniques are disclosed that allow device contact list information to be leveraged in building better models that provide more accurate assessment of user transaction risks. A computing device may receive a contact list that includes a first set of user device identifiers and generates a contact graph for that user by associating the user device identifier with the first set as first-degree contacts. The computing device may then determine that a portion of the first set of the user device identifiers are stored in a contact database (e.g. on a server) and generate a user score based on user information associated with the first set, the contact graph, and a contact graph model. The computing device may provide the user score to a transaction assessment service as in input for the transaction assessment service deciding whether particular electronic transactions are approved for processing by an electronic service provider.

Abstract: A computer-based credit evaluation system is described that uses a machine learning-based credit risk model with an adverse action methodology to assess applicant credit profiles and identify adverse action factors for credit request denials. The credit risk model is trained to assess an applicant's credit profile based on characteristics. In the case of a denial, the system compares applicant values of the characteristics against anchor values for the characteristics determined based on values from a top scoring credit profile. The system uses the credit risk model to calculate a replacement score for each of the characteristics by replacing the applicant value for the characteristic with an anchor value for the characteristic. The system ranks the characteristics based on the replacement scores, and identifies the top ranked characteristics as the adverse action factors for the denial.

Abstract: Systems and methods for verifying a digital title of an asset transferred via a math-based currency transaction. The method includes receiving a digital title request regarding an asset, creating a digital title for the asset in a digital title database, receiving, from a financial institution computing system, an asset transfer request regarding the asset that is the subject of the math-based currency transaction, verifying that an identity of a seller in the math-based currency transaction matches the identity of the owner of the asset. Then, responsive to the verification that the identity of the seller in the math-based currency transaction matches the identity of the owner of the asset, the method includes transmitting, to the financial institution computing system, a positive title verification and updating the identity of the asset of the digital title for the asset to match an identity of a buyer in the math-based currency transaction.

Abstract: One or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to receive a request to hold a meeting in a building, the request including an individual, retrieve, from the request, contact information for the individual, transmit a request for identifying information to the individual using the contact information, determine a purpose of the individual based on the identifying information, generate a virtual ticket for the individual based on the purpose of the individual, identify a presence of the individual at the building based on the identifying information and image data, and control access control devices in response to identifying the presence of the individual to grant the individual access to the building.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for payment services are provided.

Abstract: This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive a customer identifier. The system may determine financial data associated with the customer identifier and vehicle data associated with a vehicle. The system may determine loan information associated with the customer identifier and the vehicle. The system may determine a product or service associated with the vehicle. The system may determine a first value indicative of a probability that the customer will purchase the vehicle and the product or service based on the loan information. The system may determine a second value indicative of a profitability of a purchase of the vehicle and the product or service based on the loan information. The system may determine respective indications of the vehicle, the product or service, and the loan information to a user device for presentation.

Abstract: A system and method of a smart contract and distributed ledger platform with blockchain custody service includes a blockchain service circuit structured to interface with a distributed ledger; a data collection circuit structured to receive data related to items of collateral or data related to environments of the items of collateral; a valuation circuit structured to determine a value for each of the plurality of items of collateral based on a valuation model and the received data; and a smart contract circuit structured to interpret a smart lending contract for a loan, and to modify the smart lending contract by assigning, based on the determined value for each of the items of collateral, at least a portion of the items of collateral as security for the loan such that the determined value of the items of collateral is sufficient to provide security for the loan.

Abstract: The system and methods described herein allow users to apply for a purchase of a good from multiple providers using provider specific methodologies for generating offers for the product. For example, the system described herein may include a multi-layer architecture that includes interactive micro-services that communicate together in a bi-directional manner to create a normalized process for the purchase of a good, such as commercial goods/products (e.g. a vehicle) or real property. The micro-services may assess prequalification for a loan or financing for a good, followed by determining eligibility of the good for financing, and further followed by calculating pricing details for loans (e.g. for financing purchase of the good) that would be offered for a consumer's particular financial credentials, for each of a plurality of lenders. Prequalification and pricing may be performed on a good by good basis, or for a plurality of goods near or substantially simultaneously.

Abstract: Aspects of the disclosure provide techniques for using behavior based information for providing and restricting access to a secure website, or computer network and its assets to a user. Components of the system may include the following. Client remote computing device, network and browser unique attribute data collection and fingerprinting. Method for capturing user habits and fingerprinting with ability to detect abnormalities through AIML using mobile and wearable device applications. System for detection of normality of user behavior based on habits, and cyber transactions, device access and determining a confidence score associated with each transaction. Method for calculating individual transaction risk based on contextual factors such as user behavior, device, browser and the network traffic and request for authentication by account owner when risk greater than allowed threshold.

Abstract: A device may receive information identifying a plurality of requests and identifying a plurality of targets for the plurality of requests. The device may generate respective routes for the plurality of targets, where a route, of the respective routes, for a target, of the plurality of targets, identifies a set of transformations to be applied to a corresponding request of the plurality of requests. The device may apply the respective routes to the plurality of requests to generate processed requests, and may communicate with at least one of the plurality of targets based on the processed requests. The device may receive results based on communicating with the at least one of the plurality of targets, wherein the results are based on the processed requests, and may provide information based on the results.

Abstract: Determining an entity's cybersecurity risk and benchmarking that risk includes non-intrusively collecting one or more types of data associated with an entity. Embodiments further include calculating a security score for at least one of the one or more types of data based, at least in part, on processing of security information extracted from the at least one type of data, wherein the security information is indicative of a level of cybersecurity. Some embodiments also comprise assigning a weight to the calculated security score based on a correlation between the extracted security information and an overall security risk determined from analysis of one or more previously-breached entities in the same industry as the entity. Additional embodiments include calculating an overall cybersecurity risk score for the entity based, at least in part, on the calculated security score and the weight assigned to the calculated security score.

Abstract: Attribute features associated with a geographical location are obtained at a terminal device, and the plurality of attribute features are determined based on geographical and residential information data of the geographical location that is collected from one or more remote devices. For each particular attribute feature, a score value and a weight value corresponding to the particular attribute feature are determined. An attribute value for the geographical location that corresponds to each particular attribute feature is calculated using the score value and the weight value corresponding to the particular attribute feature. Display of the attribute value is initiated using a graphical user interface on a computer display device.

Abstract: Systems and methods for using social network data to validate a loan guarantee are disclosed. An example system may include a social networking input circuit to interpret a loan guarantee parameter; a social network data collection circuit to collect data using a plurality of algorithms that is configured to monitor social network information about an entity involved in a loan in response to the loan guarantee parameter; and a guarantee validation circuit to validate a guarantee for the loan in response to the monitored social network information.

Abstract: Described are a system, method, and computer program product for optimizing a predictive condition classification model and automatically enacting reactive measures based thereon. The method includes receiving event data representative of a plurality of events. The method also includes receiving the predictive condition classification model configured to categorize each event as satisfying a condition or not. The predictive condition classification model is configured to order the plurality of events by likelihood of satisfying the condition. The method includes generating a performance evaluation dataset and plotting data configured to cause a visual display to represent at least two model performance metrics of the performance evaluation dataset on a same output plot. The method includes automatically rejecting a top percent of the plurality of events for suspected satisfaction of the condition, determined at least partially from a customized rejection algorithm or a preset rejection algorithm.

Abstract: An information management method and system for managing consent for and use of information using a blockchain are provided. The information management method comprises: receiving a request to store a user agreement to the processing of the user's information from a service provider providing a service to the user; recording the user agreement on a blockchain; providing the service provider a response to the request to store the user agreement; receiving a third-party certification request for the provision of information from the user, regarding the information provided to the service provider; and providing a third-party certification for the provision of information to the user.

Abstract: A system for data collection and loan activities is disclosed. The system may include a data collection circuit to receive data relating to a status of a loan and a set of items of collateral acting as security for the loan. The system may further include a blockchain service circuit to maintain a secure historical ledger of events related to the loan, and to interpret a plurality of access control features corresponding to parties associated with the loan. The system may further include a loan evaluation circuit to determine a loan status based on the received data, a smart contract circuit to create a smart lending contract for the loan, and an automated agent circuit to perform a loan action based on the loan status, wherein the blockchain service circuit is further structured to update the secure historical ledger of events with the loan action.

Abstract: In some aspects, a verification exchange system transforms consumer data (e.g., employment or income data) from different contributor computing systems to a standardized format and stores this standardized data in a consumer-status verification repository. The verification exchange system can selectively provide portions of the consumer data to authorized client system via a security portal to a public network. For example, the verification exchange system can use standardized consumer data to service verification queries requesting confirmation of employment or income level for consumers. The verification exchange system can do so by ensuring that a verifier system from which the query is received has provided a valid credential.

Abstract: Intelligent application of reserves to transactions are described. In an example, server(s) associated with a payment processing service receive, from a point-of-sale (POS) device operated by a merchant, transaction data associated with a payment transaction between the merchant and a customer. Based on a predictive model, the server(s) can determine a level of risk associated with the merchant and/or the payment transaction and can determine a portion of the transaction to withhold from a settlement amount of the payment transaction based at least in part on the level of risk. The portion can be deposited into a reserves account associated with the payment processing service to satisfy costs associated with chargeback requests.

Abstract: The system and methods described herein allow users to apply for a purchase of a good from multiple providers using provider specific methodologies for generating offers for the product. For example, the system described herein may include a multi-layer architecture that includes interactive micro-services that communicate together in a bi-directional manner to create a normalized process for the purchase of a good, such as commercial goods/products (e.g. a vehicle) or real property. The micro-services may assess prequalification for a loan or financing for a good, followed by determining eligibility of the good for financing, and further followed by calculating pricing details for loans (e.g. for financing purchase of the good) that would be offered for a consumer's particular financial credentials, for each of a plurality of lenders. Prequalification and pricing may be performed on a good by good basis, or for a plurality of goods near or substantially simultaneously.

Abstract: Systems and methods for detecting digital abuse or digital fraud that involves malicious account testing includes implementing a machine learning threat model that predicts malicious account testing using misappropriate accounts, wherein a subset of a plurality of learnable variables of an algorithmic structure of the machine learning threat model includes one or more learnable variables derived based on feature data indicative of malicious account testing; wherein implementing the machine learning threat model includes: (i) identifying event data from an online event that is suspected to involve digital fraud or digital abuse, (ii) extracting adverse feature data from the event data that map to the one or more learnable variables of the subset, and (iii) providing the adverse feature data as model input to the machine learning threat model; and computing, using the machine learning threat model, a threat prediction indicating a probability that the online event involves malicious account testing.

Abstract: Groups of architecturally connected files may incur and accumulate high maintenance costs as architectural debts. To quantify such debts, architectural debt, which is a term used herein, may be identified, quantified, measured, and modeled. A history coupling probability matrix for this purpose may search for architecture debts through the lens of 4 patterns of prototypical architectural flaws shown to correlate with reduced software quality. Further, a new architecture maintainability metric—Decoupling Level (DL)—measures how well the software can be decoupled into small and independently replaceable modules. The DL metric opens the possibility of quantitatively comparing maintainability between different projects, as well as monitoring architecture decay throughout software evolution.

Abstract: Techniques for disambiguating a blockchain in order to extend, modify, and/or approve a capital loan offer is described. A serving computing device may use a blockchain address to reconstruct and analyze a blockchain wallet. The serving computing device may transmit a capital offer to a device associated with the blockchain wallet, where the terms specified by the capital offer may be based on characteristics of the reconstructed wallet determined by the analysis. The serving computing device may further modify and/or approve a former capital offer, based on the characteristics of the reconstructed wallet.

Abstract: An intelligent data matching and validation system, and associated methods, are disclosed. The system includes various processors, databases, and immutable ledgers for analyzing data such as, but not limited to, loan data. The system leverages intelligent resources such as Bayesian inference networks for determining high correlation events representative of likely outcomes based on data parameters. The system automatically updates the Bayesian inference network's weighted coefficients in response to processing loan data and corresponding target events, such as repurchase requests. The system stores outcomes from the Bayesian inference networks, as well as loan histories and associated loan data, in a ledger that is accessible to third parties via a unique cryptographic token.

Abstract: A system and method for optimizing the frequency of market information updates in an electronic trading environment are described herein. According to one example embodiment, by optimizing the frequency of market information updates, the burden on the client device to update the graphical user interface may be reduced, while still providing an accurate portrayal of the market to the user. An example method includes associating different precedence levels with messages comprising market information. Messages containing market information related to the inside market may be associated to a higher precedence level. Whereas messages containing market information relating to the quantities at prices outside the inside market may be associated with a lower precedence level. Based on the precedence level associated with a message, a client device may update the graphical user interface or the message may be stored in a data structure until a pre-defined condition is satisfied.

Abstract: A system and method for defining and processing timed orders are defined. According to one embodiment, a trader may define a timed order by defining an intra-day time trigger or a time period when the timed order should be automatically modified, such as deleted or cancelled/replaced with a new order. In one embodiment, the intra-day time trigger or time period may be dynamically changed to a later time, for example, upon receiving a predetermined user input. Also, the time trigger and time period may be configured to dynamically vary based on any user configurable formula. Also, the timed order may be associated with one or more actions to be taken once the order is deleted, such as sending a new order, for example.

Abstract: The systems and methods described herein allow users to control access to regulated data of the user (stored in a secured third party database) through interaction on a mobile device (or other computing device), such as to provide a touch gesture on the mobile device that causes the users regulated data to be accessible to a third party. The regulated data may include credit data of the user, such as a credit report or credit file. Access rights to the regulated data may be provided in real-time (or near real-time) in response to a request for the data from a third party, for example. The system may allow a user to respond to an alert or notification that is automatically sent to the computing device of the user in response to a request for a secure regulated data of the user.

Abstract: Techniques described herein are directed to, among other things, enabling the use of contactless payment technology when customers and merchant are remote from one another by, for example, authorizing merchants to use payment hardware components residing on customer devices. For example, when a customer requests to purchase an item from a merchant via a ecommerce page of the merchant, a payment-processing service may authorize, at the request of the customer, the merchant to use an NFC reader residing on the customer device to accept payment information from a contactless card of the customer for satisfying a cost of the transaction.

Abstract: The disclosed exemplary embodiments include computer-implemented systems, apparatuses, and processes that dynamically implement and manage hash-based consent and permissioning protocols. By way of example, an apparatus may obtain consent data that identifies one or more elements of data accessible to an application program executed by a device. The apparatus may generate a consent document for the application program based on at least a portion of the consent data, and may compute a consent hash value representative of the consent document. The apparatus may also generate and transmit permissioning data that includes at least the consent hash value to the device. The permissioning data may, for example, include information that instructs the executed application program to store the consent hash value within a local memory of the device and to associate the consent hash value with an access token of the executed application program.

Abstract: The disclosed embodiments provide systems and methods for managing a loan application. In one embodiment, a method is disclosed that may include identifying one or more unfulfilled conditions associated with a loan application of a customer and sending, to a customer device, a request for a loan application document based on the identified one or more unfulfilled conditions. The method may also include receiving, from the customer device, a responsive loan application document. The method may also include identifying a document type for the responsive loan application document and confirming that the responsive loan application document is a valid document. Finally, the method may also include sending loan application status information to the customer device based on the confirmation.

Abstract: A computerized financial risk management system is disclosed that includes risk tolerance test, expectation reality check and real-time risk monitor using graphs of returns and risks. Real-time risks are calculated daily based on a set of rolling short-term, medium-term and long-term time windows and graphs of annualized returns and risks for said set of time windows are provided for analysis.

Abstract: A data processing system communicates with a secure third-party database to obtain information about a user that is usable to determine one or more items associated with the user. The system then coordinates gathering and identification of additional data relevant to the user from other third-party data sources, to potentially update the user's information stored with the secure third-party database. The updated information may then be accessed at the secure third-party database to determine items associated with the user, which may include additional items in view of the additional data.

Abstract: A system and method of a smart contract and distributed ledger platform with blockchain custody service includes a blockchain service circuit structured to interface with a distributed ledger; a data collection circuit structured to receive data related to items of collateral or data related to environments of the items of collateral; a valuation circuit structured to determine a value for each of the plurality of items of collateral based on a valuation model and the received data; and a smart contract circuit structured to interpret a smart lending contract for a loan, and to modify the smart lending contract by assigning, based on the determined value for each of the items of collateral, at least a portion of the items of collateral as security for the loan such that the determined value of the items of collateral is sufficient to provide security for the loan.

Abstract: In some embodiments, a comprehensive computer system and method (See FIGS. 1, 1a, 2) for automating and facilitating the performing and processing of tasks, information transfer, and information storage associated with the home sale (See FIG. 3a), mortgage origination (See FIG. 3b), and settlement process (See FIG. 3c), and the home mortgage refinancing origination and settlement process (See FIGS. 1b, 1c, 2a) (or performing other business processes), over a distributed computing network are disclosed. One aspect of the invention is a greatly simplified process for a home buyer to search for a home and simultaneously receive accurate and competitive bids for mortgages and services from multiple lenders and service providers. The process includes an automated underwriting process which generates complete, accurate information on the costs of buying and owning a home at very beginning of the home buying process. Another aspect of the invention is greatly automating the entire sale, loan and settlement process.

Abstract: The disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that utilize a machine learning model and a credit value model to generate user interface elements that present credit values and credit value conditions in real time for user accounts. For instance, the disclosed systems can generate an activity score using an activity machine learning model with internal user activity data of a user account. Then, utilizing a credit value model with the activity score and a user activity condition, the disclosed systems can determine a dynamic credit value range for the user account. Indeed, the disclosed systems can display user interface elements with selectable credit values from the dynamic credit value range. Additionally, the disclosed systems can utilize the credit value model to determine and display one or more dynamic credit value conditions for a selected credit value received from the selectable credit values.

Abstract: Systems and apparatus for processing a trade order include a computer configured for receiving market data for a financial asset, receiving pricing parameters and receiving proposed order quantity and price data. The computer is further configured for constructing proposed trades based on the proposed order quantity and price data, and for calculating a theoretical price for the financial asset based on the market data, pricing parameters as well as the proposed order price data. In addition, the computer is configured for comparing the constructed trades with the theoretical price, and displaying market data indicators relative to the theoretical price indicators based on the comparison.

Abstract: A method and system for risk measurement and modeling, which may be used to identify and mitigate information security risks for an information system, and which may improve the efficiency of risk measurement and modeling. Such a system may perform risk modeling based on threat likelihood information, the potential business impacts of particular threats, and data on the effectiveness of particular controls implemented by the operators of the information system, which may be used to calculate residual risk scores for particular risk scenarios that the information system may face.

Abstract: A system and method for replacing a customer's debit card payment with a one-time loan at a point of sale (POS) is disclosed. The method receives, at a POS, a debit card input from a customer to be used as a transaction payment. The POS obtains, from the debit card input, identification information for the customer. A total monetary amount of the transaction payment and the identification information is provided to a one-time loan provider's computer system. The one-time loan provider's system uses the customer identification information to perform a credit screening for the total monetary amount of the transaction payment. The one-time loan provider's system provides to the POS a one-time loan offer for the customer. The one-time loan offer to be used in place of the debit card input to make the transaction payment.

Abstract: The technology disclosed herein provides a blockchain transactions forwarding mechanism that allows for tracking and notification from the originating blockchain through to a last blockchain and back again. An implementation of the system disclosed herein also provides a whitelist mechanism to provide a list of acceptable blockchains or nodes that may receive transactions. Yet another implementation provides a predetermined hop count that may be used as the maximum allowable hop counts that provides the number of times a transaction is allowed to be forwarded.

Abstract: A method for identifying a risk merchant comprises: determining, for each of at least one marked merchant cluster based on a user correlation degree of a merchant to be identified and the each marked merchant cluster, a degree of similarity between the merchant to be identified and the marked merchant cluster, wherein each marked merchant in the each marked merchant cluster is marked with a corresponding risk category by a trained classification model, and the user correlation degree of the merchant to be identified and the marked merchant cluster comprises a user correlation coefficient of the merchant to be identified and the marked merchant cluster and a number of same users of the merchant to be identified and the marked merchant cluster; and determining whether the merchant to be identified is a risk merchant based on the degree of similarity between the merchant to be identified and the each marked merchant cluster.

Abstract: A system and method of an automated agent to automatically implement loan activities includes a data collection circuit structured to receive data related to at least one of a plurality of parties to a loan; a smart contract circuit structured to create a smart lending contract for the loan; and an automated agent circuit structured to automatically perform a loan-related action in response to the received data, wherein the loan-related action is a change in an interest rate for the loan, and wherein the smart contract circuit is further structured to update the smart lending contract with the changed interest rate.

Abstract: A method and device for city-scale nonlinear time-history analysis. The method comprises: acquiring building data; obtaining a model type corresponding to the building data according to the building data; establishing a multiple mass shear series model or a multiple mass shear-flexural parallel model corresponding to the building data according to the model type corresponding to the building data; performing nonlinear history analysis according to time history data of ground motion acceleration from each building through the multiple mass shear series model or the multiple mass shear-flexural parallel model, to obtain a nonlinear history analysis result; obtaining a seismic damage state and an analysis result of each story of each building according to the nonlinear history analysis result.