Abstract: A system and method for allowing a user to manage transactions in an online credit card application. The system includes a back-end server operating the online application and including a processor for processing data and information, a communications interface communicatively coupled to the processor, and a memory device storing data and executable code. When the code is executed, the processor can link one or more external bank accounts to the online application, provide a list of transactions that were made using the credit card, enable a user to select one or more of the transactions in the list to be paid independent of the other transactions, and enable the user to pay the selected transactions using the one or more external bank accounts.

Abstract: In embodiments, an Online Software Platform (OSP) is configured to receive datasets having dataset values that represent relationship instance data of relationship instances between a client primary entity and other secondary entities, select digital rules responsive to these dataset values, produce resources for the datasets by applying the selected digital rules to the dataset values, derive a total value of the produced resources, generate a report document that mentions at least derived the total value, and prepare an instantiation that enables viewing a data record that substantiates the derived total value. The OSP may further make this instantiation available for viewing to a domain entity that has access to the report document and wants to confirm the derived total value. For instance, the OSP may provide an access instruction for viewing the instantiation, or even augment the report document itself with such an access instruction.

Abstract: A method for transferring a credit rights certificate is provided, including: generating a target account address according to a debtor account address and a creditor account address in a credit rights certificate transfer request, the target account address being a temporary account address used for storing a credit rights certificate and based on a multi-digital-signature process; transferring a credit rights certificate corresponding to the credit rights certificate transfer request from the debtor account address to the target account address; and transferring the credit rights certificate from the target account address to the creditor account address based on a confirmation instruction from the creditor account address.

Abstract: A testing platform for an auto-decision engine is disclosed. An auto-test database for a decision engine may be accessed and modified by, for example, executing an application programming interface protocol of a third-party computing system. The decision engine may be bypassed, and a simulated auto-decision may be requested based on a unique key corresponding to a scenario in the auto-test database. A graphical user interface displays information regarding the auto-test database on a user computing device, and one or more output data fields in the auto-test database may be modified.

Abstract: An artificial intelligence fraud management solution comprises an expert programmer development system to build trainable general payment fraud models that integrate several artificial intelligence classifiers like neural networks, case based reasoning, decision trees, genetic algorithms, fuzzy logic, and rules and constraints. These are further integrated by the expert programmers and development system with smart agents and associated real-time profiling, recursive profiles, and long-term profiles. The trainable general payment fraud models are trained with supervised and unsupervised data to produce an applied payment fraud model. This then is applied by a commercial client to process real-time transactions and authorization requests for fraud scores.

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: A system described herein may maintain records, in a distributed ledger, that include parameters (e.g., Quality of Service (“QoS”) parameters and/or Multi-Access/Mobile Edge Computing (“MEC”) device management parameters) that are associated with particular applications and/or MEC operator systems. The system may identify a particular record, from the distributed ledger, that is associated with a particular MEC operator system. The particular record may indicate a first set of MEC configuration parameters implemented by the MEC device operator system, and one or more triggers based on which the first set of MEC configuration parameters were implemented by the MEC device operator system. The system may record a set of modified application parameters, that are generated based on the identified first set of MEC configuration parameters and the one or more triggers, to the distributed ledger.

Abstract: A system that allows for channel and platform agnostic automated scheduling. A user that is registered with the system may add an automated assistant into a pre-existing communication thread or channel, such as a short messaging service (“SMS”) conversation between multiple friends. Any user in the thread may interact with the assistant even if not registered with the system. Once present, the assistant analyzes messages sent to the thread for wake words that trigger actions or responses by the system, including automated scheduling actions. When scheduling is invoked, the system will find acceptable times based on top-down and bottom-up availability provided by registered users, and will propose meeting times until one is accepted by some or all of the participants. Once accepted, the system will confirm the meeting, update linked calendars, and provide reminders to attendees.

Abstract: A method includes receiving a request to open an account associated with a customer, information regarding the account, and a mobile device identifier. The mobile device identifier is received from a third-party computing system based on a first wireless communication between the mobile device and the third-party computing system. The method includes validating the mobile device as belonging to the customer based on the received mobile device identifier and binding the mobile device identifier to the customer based on the validation. The method includes establishing the account for the customer based on the received information regarding the account and generating a token for the account. In response to establishing the account and generating the token, the token is provided to the third-party computing system and provisioned to the validated mobile device via a second wireless communication between the mobile device and the third-party computing system.

Abstract: A method of facilitating merchant self-service assistance to financing and content support for a marketing event may include receiving a request from a merchant for approval for financing and content generation to support the marketing event and determining whether to approve the merchant based on comparing information provided in the request to approval standards. The method may further include, responsive to approval of the merchant, receiving context information regarding content requested, and providing the content requested to the merchant based on the context information to support the marketing event.

Abstract: Training a machine learning model includes selecting a subset of training transactions from a plurality of training transactions to be used for classifying transactions as either fraudulent or genuine, and classifying transactions as either fraudulent or genuine. Additionally, selecting the subset of training transactions includes clustering the plurality of training transactions into a plurality of clusters based on a similarity measure. Each training transaction includes an indication whether the training transaction is fraudulent or genuine. Further, selecting the subset of training transactions includes selecting a first proportion of the training transactions of a cluster of training transactions for the subset of training transactions if the cluster comprises at least one fraudulent training transaction, and selecting a second proportion of the training transactions of a cluster of training transactions for the subset of training transactions if the cluster is free of fraudulent training transactions.

Abstract: A fraud detection system including at least one processor configured to: calculate a fraud level of a user who uses a service based on a behavior of the user; obtain a determination result as to whether the behavior is actually fraudulent; and calculate accuracy of fraud detection for each user based on the fraud level and the determination result.

Abstract: Systems and methods for model evaluation. A protected class model that satisfies an accuracy threshold is built by using: data sets for use by a modeling system being evaluated, and protected class membership information for each data set. A target for the protected class model is a protected class membership variable indicating membership in a protected class. Each predictor of the protected class model is a predictor of an evaluated model used by the modeling system. A target of the evaluated model is different from the target of the protected class model. Each predictor is a set of one or more variables of the data sets. For each predictor of the protected class model, a protected class model impact ranking value and a modeling system impact ranking value are determined.

Abstract: The disclosure describes an apparatus having programmed instructions that when executed cause the apparatus to receive, via a communication network, information regarding suspicious fraud activity at a first location involving a plurality of transaction cards; monitor changes over a first time interval to received information regarding suspicious fraud activity at the first location; and identify a point-of-compromise (POC) location based on monitored changes surpassing a threshold indicating suspicious fraud activity at the first location over the first time interval.

Abstract: A data processing and analytics system for processing financial related data includes a financial data processing unit that is secured by a security layer. The financial data processing unit and the security layer are embedded in a company native environment. The company has a plurality of data sources for providing raw financial data that is filtered by the security layer prior to transfer to the financial data processing unit. The financial data processing unit includes a raw data storage unit for storing the raw financial data, and a data processing unit for processing the raw financial data via one or more preloaded audit applications. The processed financial data is then employed to generate one or more financial reports that are then transferred to the financial expert externally of the company.

Abstract: An apparatus for security management of application information comprises a processor operable to receive the application information associated with a first entity and to receive entity device information for a first entity device associated with the first entity. The processor is operable to determine that a portion of data fields of the application information associated with the first entity corresponds to a portion of data fields of entity account data associated with a second entity and to determine that a portion of the entity device information associated with the first entity device corresponds to a portion of the entity device information associated with a second entity device that is associated with the second entity. The processor is further operable to determine that the first entity is associated with suspicious indicators, wherein suspicious indicators signal that there is suspicious activity associated with the first entity.

Abstract: A system and method for allowing a user to manage transactions in an online credit card application. The system includes a back-end server operating the online application and including a processor for processing data and information, a communications interface communicatively coupled to the processor, and a memory device storing data and executable code. When the code is executed, the processor can link one or more external bank accounts to the online application, provide a list of transactions that were made using the credit card, enable a user to select one or more of the transactions in the list to be paid independent of the other transactions, and enable the user to pay the selected transactions using the one or more external bank accounts.

Abstract: The system and methods described herein allow users to give their applicant information when seeking to submit an inquiry associated with a product provided by at least one entity, and have various lender microservices run in parallel, segregated by entity, in a jailed and self-contained, autonomous environment. The result of these microservices may be returned as a response to the inquity, being determined autonomously for each respective entity based on one or more respective rule sets or executable logic for each respective entity. Payloads for multiple entities may be combined in a single output from the jailed and self-contained environment due to outputs from the environment being encrypted in a universal format, wherein the outputs are decrypted in a user session in an application, allowing the user to see the results of the respective responses of each of the at least one entity, to their inquiry.

Abstract: Techniques for a modeling platform associated with simulating risk models. According to certain aspects, systems and methods include simulating the risk model over time. The risk model may include a hierarchical tree formed of component assumption objects associated with distribution functions. The systems and methods may apply a time function to generate time-adjusted values for the component assumption objects corresponding to defined distribution functions. The systems and methods may then combine the time-adjusted values to generate time-adjusted values for parent assumption objects.

Abstract: A method including training a machine-learning model, based on historical data, with a maximization problem and one or more minimization problems to improve one or more fairness metrics. The method also can include receiving real-time data. The method additionally can include generating a risk score based on the machine-learning model, as trained, and the real-time data. Other embodiments are described.

Abstract: Distributed ledger-based networks (DLNs) employ self-executing codes, also known as smart contracts, to manage interactions occurring on the networks, which may result in the generation of a massive amount of DLN state data representing the interactions and participants thereof. The instant disclosure discloses systems, apparatus and methods that allow interactions to occur on the DLNs without modification to stored data, thereby improving the storage capabilities of the networks.

Abstract: A system for managing a financial account in a low cash mode. The system may include a memory storing instructions, and a processor configured to execute the instructions to perform operations. The operations may include providing an interface; providing a notification to a user when a balance in the first account is deemed to be in low cash mode; presenting, when the first account balance is deemed to be in low cash mode, an option for a transfer request; receiving, a selection of the option for the transfer request to connect the first account with a second account; transferring funds from the second account to the first account; notifying the user that funds have been transferred from the second account to the first account; and further notifying the user that the balance in the first account is greater than the threshold value.

Abstract: Provided are systems and methods for configuring and implementing a loan repayment based on transactions output from a merchant POS terminal. In one example, the method may include receiving point-of-sale (POS) transactions from a merchant POS terminal, receiving, via an application programming interface (API), a request to allocate a portion of the POS transactions from the merchant POS terminal to a lender payment account, depositing the POS transactions received from the merchant POS terminal into a merchant payment account during a settlement process, and automatically triggering a payment transaction that pushes the portion of the POS transactions from the merchant payment account to the lender payment account.

Abstract: Methods and systems, including computer programs encoded on a computer storage medium, implement compliance testing to evaluate controls used to protect assets of a target system. A respective first score is generated for each control based on compliance tests performed to detect each of the controls at the target system. A compliance model is generated that integrates machine-learning algorithms to classify inputs corresponding to a compliance test and to enable predictive analytics of the compliance model using the classified inputs. The compliance model derives a negative compliance test (nCT) for each of the compliance tests by applying the predictive analytics to a data set that includes the first score for each control. An nCT is performed for each control detected at the target system and a second score is generated for each nCT. An assurance score characterizing effectiveness of the control is generated based on the first and second scores.

Abstract: A system for presenting operational data is disclosed. The system includes a storage element to store a plurality of insurance policies and a product designer module to: maintain an insurance product model that specifies possible configurations of insurance policy products associated with the plurality of insurance policies; obtain operational data pertaining to a set of existing insurance transactional data associated with the insurance policies; and present to be displayed: at least a portion of the insurance product model comprising a set of insurance product model elements and at least some of the operational data corresponding to the set of insurance product model elements.

Abstract: A communication system enabling a first wireless subscriber in need of an instant credit line to use a creditee module on a portable wireless communication device to request credit from a second subscriber that has available credit at a financial institution. The second subscriber uses a creditor module on their device to generate rules for the extension of a credit line guaranteed by the financial institution of the second subscriber. If the rules are met, a credit authorization code is generated by the system and forwarded to the creditee module of the first subscriber's device such that the code can be subsequently used to complete a transaction initiated by the first subscriber to pay a vendor. The vendor may then employ a vendor's module to access the issued credit as prescribed by the creditor module.

Abstract: Techniques are described for determining a value metric for each of a plurality of payment cards, and recommending payment card(s) based on their respective value metrics. Implementations provide a recommendation engine that analyzes user data and card data, and recommends payment card(s) that may be suitable for a user. The engine consumes usage data and credit score and uses that information, along with characteristics of various available cards, to develop a value metric for each payment card that indicates how valuable owning the card would be to the particular user, such as how much money the user can expect to make or lose every year if they use the card as indicated, given the card's interest rate, rewards, fees, and so forth. The engine can rank the cards according to their value metrics, and the top-ranked card(s) are presented to the user as recommendations in a user interface.

Abstract: A distributed enhanced payment processing system includes a merchant point of sale (POS) terminal system and a remote payment management system. The POS terminal system initiates a transaction that includes receiving a payment amount, a purchaser account identifier, a virtual electronic payment indicator, and a merchant ID via a payment client. Subsequently, the POS terminal system outputs the transaction to the remote payment management system which generates a token for the transaction. The payment management system then provides the purchaser account identifier, a merchant account identifier, and the payment amount to a remote virtual electronic payment (VEP) entity system. Upon receiving a VEP entity system response, the payment management system outputs the response and token to the POS terminal system.

Abstract: Systems and methods for dynamic detection of security features based on self-supervised natural language extraction from unstructured data sets are disclosed. The system may receive an unstructured data array including a full text of financial narrative. The system may serialize the unstructured data array to form one or more first data arrays including portions of the full text as discrete financial risk narratives. The system may build a tokenization dictionary and determine condensed summaries for each portion of the full text. The system may determine a relevancy score and a sentiment score for each condensed summary and calculate an overall relevancy score as a weighted average of the relevancy score and the sentiment score. When the overall risk score exceeds a predetermined threshold, the system may execute one or more security actions.

Abstract: A method for executing and evaluating financial services technology solutions in a secured testing environment during a regulatory approval process includes receiving, by a first computing device, via a user interface, a regulatory process application from a second computing device. The first computing device receives an application programming interface call providing an instruction for use in executing, within a secured testing environment, a software application identified within the regulatory process application. The first computing device executes the software application within the secured testing environment. The first computing device provides access to the software application executing within the secured testing environment to a user of a third computing device, during at least one phase of a regulatory approval process. The first computing device receives a result of the at least one phase of the regulatory approval process.

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: Computer systems and methods for managing resources are described.

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: A method, a system, and a computer program product for generating an interpretable set of features. One or more search parameters and one or more constraints on one or more search parameters for searching data received from one or more data sources are defined. The data received from one or more data sources is searched using the defined search parameters and constraints. One or more first features are extracted from the searched data. The first features are associated with one or more predictive score values. The searching is repeated in response to receiving a feedback data responsive to the extracted first features. One or more second features resulting from the repeated searching are generated.

Abstract: Methods and systems described in this disclosure are directed to electronically generating narratives and tracking a user's actions in responses to receiving the narratives. The disclosed system can rank narratives for effectiveness of a narrative based on the responses. In some embodiments, the narratives can be classified into categories based on criteria pertaining to user population data or user-specific data.

Abstract: System and methods for the integration of dental practice management systems are disclosed herein. The systems and methods may generate models (including schedule models and financial models) from the data provided by a plurality of dental practices. These models can be used to quantitatively evaluate the efficiency and other operating characteristics of a particular dental practice, and can identify operational issues within the practice. Further, the systems and methods can evaluate metrics of the dental practice against goal metrics and/or standard metrics, and recommend and implement solutions based on the comparison.

Abstract: Disclosed are example machine-learning approaches for determining maturity metrics of chatbot users. One or more datasets with words used during past conversations between a chatbot and a set of users with known maturity metrics are generated. A machine learning model is trained by applying machine learning to the one or more datasets such that the machine learning model is trained to output maturity metrics based on words received as inputs. A set of words or phrases spoken or written by the user during a conversation is fed to the machine learning model to determine a maturity metric of the user. A response is identified based on the determined maturity metric, and the response is presented during the conversation with the user. Words and phrases of a user conversing with a chatbot are used to determine the user's age or another maturity metric to generate responses that enhance the user experience.

Abstract: Various embodiments of the present disclosure are generally directed to processing conversions of digital assets to fiat currency. An example method includes obtaining a conversion rate for a digital asset via an API, providing the conversion rate via a client device, receiving a digital asset conversion request and executing a digital asset conversion within a configurable time period. Executing the digital asset conversion includes causing digital asset units to be debited from the digital asset user account and causing fiat currency units to be credited to a fiat currency user account. The method further includes dynamically providing a notification of execution of the digital asset conversion via the client device, updating account balance data objects associated with the digital asset user account and the fiat currency user account, and subsequent to executing the digital asset conversion, executing a fiat currency transaction (e.g., a settlement) with a digital asset exchange system.

Abstract: Systems and methods are disclosed for providing an account holder with an incentive-consent matrix at a point-of-sale device of a merchant. The account holder can provide consent to store transaction related data and obtain an incentive in exchange. The incentive out be a coupon or other offering associated with the merchant. Varying levels of consent can be offered, with each level associated with an incentive having a different relative value. The transaction data can subsequently be provided to a recipient in accordance with the consent received from the account holder.

Abstract: A computer-implemented method for authenticating an online user with an access control server (ACS) is provided.

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: A system receives a request for payment of a transaction between a vendor and a consumer, and sends a first request to a database associated with the online service for historical transactions and personal attributes of the vendor concurrently with sending a second request to a number of third-party services for credit information and personal attributes of the consumer. The system receives information responsive to the first and second requests from the database and the third-party services, respectively, and obtains a risk score for the transaction based on an application of one or more risk assessment rules to the received information by a machine learning model trained with at least the historical transactions and the personal attributes of the vendor. In some aspects, the system determines whether to advance funds to the vendor, prior to requesting payment from a consumer account, based at least in part on the risk score.

Abstract: According to one example embodiment, a computer implemented method performed by a funds transfer computing system, includes registering a beneficiary to a rating system. Registering the beneficiary comprises receiving identifying information including at least one of a receiving account, a financial institution associated with the receiving account, a beneficiary location, a beneficiary name, and an authentication factor. An identity of the beneficiary is validated in response to the received identifying information. A trust score for the beneficiary is generated. The trust score is indicative of the beneficiary's likelihood of being approved to receive funds in an international funds transfer between the beneficiary and a payor.

Abstract: A system for generating video content may include a bank database that has a first set of data associated with an account status of an individual. The system may also include a credit provider database that includes a second set of data associated with a credit status of the individual and at least one processor. At least one processor may receive an indication that the credit status of the individual has changed, retrieve the first set of data from the bank database and the second set of data from the credit provider database, generate a personalized financial video associated with the individual based on the first set of data and the second set of data, and transmit the personalized financial video to a computing device associated with the individual.

Abstract: Systems and methods are provided for the problem of automatic, algorithm-guided estimation of insurance loss ratio, claims frequency, the probability of excess claims, and other insurance policy performance characteristics for an individual insured or for groups of insured individuals. A time-series-derived Bayesian power spectrum weight is calculated from the frequency of temporal pattern-specific values in terms of intensities at various frequencies of the power spectrum computed from credit utilization ratio (CUR; outstanding balance of debt, as a percentage of credit line available) time-series obtained by the insurer by ‘soft pull’ inquiries submitted periodically to credit-rating agencies, and provides an opportunity to capture and measure the relative magnitude of frequent or unexpected changes in consumer liquidity.

Abstract: A systems and method facilitates obtaining accountant prepared financial statements associated with a client. A financial statement user initiates the process such as when a client has requested a loan and the financial statement user initiates an underwriting process. An identity of an accountant or client is received at a confirmation system from the financial statement user via the communications network. The identified accountant or client identifies the other party to the confirmation system via the communications network. Financial statements associated with the client are received from the identified accountant via the communications network. The received financial statements include financial information associated with the client. Permissions associated with the financial statements are received from the client via the communications network. The financial statements are provided via the communications network to the financial statement user in accordance with the permissions provided by the client.

Abstract: In some examples, a system receives first transaction data for first transactions processed by a payment service, and uses a first model to determine, based on the first transaction data, that a probability of default for a user of the payment service satisfies a threshold. The system generates, based on a first financing factor, a first offer of credit for the user, and sends the first offer to the user. The system determines, based on third party information, that the user has additional income, and receives, from one or more of the third-party systems, second transaction data indicating the additional income. The system uses a machine learning model included in the first model to determine a second financing factor based on the second transaction data, and generates, based on the first financing factor and the second financing factor, a second offer of credit to send to the user.

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: Systems, methods, and devices provide a user experience capable of integrating robo-advising with human advising based on various inputs that are actively detected. Inputs from a conversation, or multiple conversations separated in time, may be analyzed to determine, based on voice inputs, that live communications should be initiated. Based on triggers identified, a robo-advising session may additionally or alternatively be initiated. Transitions between advising sessions may be facilitated to allow users to more efficiently employ robo-advising until human advising is triggered.

Abstract: A distributed computing system facilitates automatic loan agreements between syndicate participants. The system includes a blockchain comprising circuitry embodying a plurality of blockchain services. A membership service registers participants to the syndicate, generates a unique identifier for each of the participants, and verifies that a respective entity is a node on the blockchain. An oracle service retrievably stores loan terms templates provided by the participants via a centrally managed entity. A smart contracts service receives financial and/or geo-location data associated with the plurality of syndicate participants. A predictive analytics service uses the data to determine whether a first syndicate participant has an excess of funds and whether a second syndicate participant has a lack of funds. A loan service automatically facilitates a loan agreement between the first participant and the second participant.