Abstract: A financial services system that utilizes a user device and a blockchain having a blockchain ledger includes. a host database having a non-transitory computer-readable medium including code and a host controller that executes the code. The host controller enables communication between a first digital wallet on the user device and one of a local currency account and a digital currency account to initiate a deposit via one of the currency accounts. The deposit can be assigned a transaction ID that is recorded to the blockchain ledger. The transaction ID can include a deposit currency value.

Abstract: Using exported data of a machine learning model and a model training environment specification, a resource usage specification and a code module usage specification of the model are identified. A code module installation specification is determined from a code module requirements specification and a target execution environment specification. The code modules specified by the code module installation specification are caused to be installed in the target execution environment. Using data of the updated target execution environment, the updated target execution environment is validated for execution of the model. Execution of the model in the updated target execution environment is simulated. The model is deployed in the updated target execution environment responsive to the simulating being successful.

Abstract: Provided is a method for detecting group activities in a network. The method may include receiving interaction data associated with a plurality of interactions. For each account identifier associated with at least one interaction, a value may be determined for each of a first set of categories, and a vector may be generated based on the value for each category. The length of each vector may be determined. At least one relational graph may be generated based on the interaction data. Each relational graph may be associated with a respective category of a second set of categories. At least one cluster of nodes may be determined based on the relational graph(s). A score for each cluster may be determined based on the length of the vector associated with the account identifier of each node of the cluster of nodes. A system and computer program product are also disclosed.

Abstract: A query operation is performed to obtain information for a select entity of a computing environment. The information includes boost information of one or more boost features currently available for the select entity. The one or more boost features are to be used to temporarily adjust one or more processing attributes of the select entity. The boost information obtained from performing the query operation is provided in an accessible location to be used to perform one or more actions to facilitate processing in the computing environment.

Abstract: The disclosure herein describes a virtual commute experience system. In some examples, the virtual commute experience includes receiving a plurality of information from one or more different programs; in response to a trigger event, launching a virtual commute experience; in response to the launch of the virtual commute experience, displaying a first portion of the plurality of information from the one or more different programs; receiving a first user interaction; in response to receiving the first user interaction, displaying a second portion of the plurality of information; receiving a second user interaction; outputting a prompt to continue or end the virtual commute experience; and in response to receiving a response to the prompt to end the virtual commute experience, pausing notifications generated by one or more different programs via the user interface until another trigger event.

Abstract: Methods, systems, and media for providing a networking platform for dynamically aggregating and routing loan inquiries are provided.

Abstract: Machine-learning prediction of occupancy status of real property. In an embodiment, ground-truth data, comprising property records, are received. The property records are normalized and augmented with property-specific data. Feature vectors, which are labeled with a known occupancy status, are generated from the normalized and augmented property records and used to train a machine-learning model to predict occupancy status based on a plurality of features.

Abstract: This technology relates generally to data assembly and analytics, as can be used in the personal finance and banking field, and more particularly to the field of lending and credit notification methods and systems. Embodiments of this technology provide systems and methods for creating objects which can be used in multiple implementations to generate scores.

Abstract: A computer-implemented method for determining a reward associated with one or more transactions of a user may comprise obtaining travel data of the user via a device associated with the user, wherein the travel data includes travel dates of the user; obtaining, via one or more processors, exchange rate data based on the travel data of the user; determining, via the one or more processors, a value of the reward associated with the one or more transactions of the user during the travel dates based on the exchange rate data; transmitting, to the user, a notification indicative of the reward associated with the one or more transactions; and causing the reward associated with the one or more transactions to be directed to a financial account associated with the user.

Abstract: A method for authenticating a user identity linked to a user account may include receiving information that asserts a user identity including a user identifier, accessing external data stores to receive data rows that are associated with the user identity, and accessing monitoring systems to receive data vectors. The monitoring systems may monitor transmissions to receiving systems, the data vectors may include numerical target values for the receiving systems, and the data vectors may be accessed using the user identifier. The method may also include determining whether the data rows can be matched to the data vectors, and based on that determination, authenticating the user identity.

Abstract: An information management system-implemented systems and methods for the continuous or near-continuous access to the real-time, near real-time or most recently available scientific characteristics inherent in existing catastrophic events, planet Earth's oceans, weather and environment, and the weather and the activity of our solar system, comprising methods for the continuous weighing, grading, prioritizing of the scientific characteristics, the calculation and quantification of such dynamic risks to humanity, assets, asset classes, infrastructure, and geographic locations, the application and implementation of artificial intelligence or machine learning to systems and methods, the presentation of such risks to a plethora of adapted computer terminals and devices, the exchange of such risk, and the system enterprise management architecture comprising the configurations and functions for the governance, implementation, and execution of systems and methods.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. In response to receiving a request from a client device for an overall score for an entity, the program retrieves a first set of data associated with the entity and a second set of data associated with the entity. The program further uses a first computational model to generate a first score based on the first set of the data. The program also uses a second computational model to generate a second score based on the second set of data. The program further determines the overall score for the entity based on the first score and the second score.

Abstract: A system includes an intermediate mortgage integration platform as a service (MiPaas). Specifically, an MiPaas layer may facilitate integration between a loan origination system (LOS) and supporting services. The MiPaas layer may provide integration flexibility by enabling integration of the supporting services with each other and with different LOSs. Indeed, a number of MiPaas integration formats (e.g. REST API, OpenAPI, GRPC, GraphQL, Industry Standard interface, etc. may be provided to facilitate ease of integration between the LOS and the supporting services. Further, the MiPaas may provide processing efficiencies by adapting workflows based upon particular retrieved data. In this manner, efficient processing may be performed in an intermediate data processing layer, resulting in more efficient turnaround times and reduced processing requirements at traditionally over-burdened systems.

Abstract: Systems and methods for distributed risk analysis are discussed.

Abstract: An apparatus, system, and method, each of which: stores in a memory information relating to a plurality of forms each issued by a first user; receives, from a first terminal of the first user, a request for applying a service based on a particular form of the plurality of forms, and an identifier of the particular form; and transmits a request for applying the service and the identifier of the particular form to a second terminal.

Abstract: Systems, methods, and computer-readable storage media to calculate an update characteristic value for a capacity plan having multiple sub-ledgers. One system can include a communication network interface, a memory, and one or more processors. The memory can store a ledger to broadcast exchanges associated with the capacity plan. The one or more processors can identify a predetermined capacity plan characteristic value indicating a minimum update per cycle value for the capacity plan or a time period for completion of an update of a value of the capacity plan to zero. The one or more processors can calculate an update characteristic value for updating the value of the capacity plan to zero. The one or more processors can transmit, via the communication network interface, a record comprising the update characteristic value.

Abstract: Systems for securing transactions based on merchant trust score are disclosed. The system may receive information identifying a merchant from a user device and, in response, retrieve transaction data associated with the merchant and receive website data in response to receiving information identifying the merchant. The system may use a machine learning model to generate a merchant trust score for the merchant, and determine whether the merchant trust score is less than a predetermined threshold. The system may also generate or retrieve an alternative payment method and provide related information or a recommendation to the user device.

Abstract: The present disclosure involves systems, software, and computer-implemented methods for providing assisted channel credit application completion for customers, where approval of the credit application results in an automatic integration of payment credentials into a corresponding digital wallet. One example method includes receiving, via an assisted channel user terminal, a request to apply for a new credit account for a customer. Input into a digital credit application is input by an employee or teller on behalf of the customer. A credit adjudication process is performed on the application, and, in response to approval, a new credit account associated with the customer and corresponding payment information is created. A system to which the set of payment information is to be provided is identified, and the set of payment information associated with the new credit account is transmitted to those systems to be automatically integrated into those systems' digital wallets.

Abstract: The EMERGENCY RESPONSE MANAGEMENT APPARATUSES, METHODS AND SYSTEMS (“ERMS”) transform emergency related inputs and sensor information into a threat indication category, which is distributed to individuals and/or first responders for managing the threat. In one implementation, the method includes an emergency management processor-implemented method that receives sensor readings from one or more sensor devices and generates risk factors for the at least one sensor device. The generated risk factors are then curve fitted to a plurality of statistical distribution curves including both non-extreme and extreme statistical distributions, wherein each of the statistical distribution curves is indicative of a threat category. The threat category is then determined based on the generated risk factors that provide a best fit with one of the plurality of statistical distribution curves.

Abstract: A system for interfacing with a decisioning service from a third-party domain. A backend system may receive a request to interface with the decisioning service to generate a prequalification result for a user for a specified product, in response to the actuation of a button included in a third-party web domain rendering a product. The backend system may execute a call on a website of the decisioning service. The backend system may receive the product information from the button. The backend system may generate the website within the third-party domain, including a request for information about the user, in response to executing the call to the website. The backend system may transmit a request for generating prequalification result for the product to the decisioning service. The backend system may receive the prequalification result from the decisioning service.

Abstract: A computer-implemented system, method and computer program product for detecting fraud. The system and method receives data representing transacting parties where a party transacts with another party to define a relationship therebetween. The received data is incorporated into a relationship network graph comprising nodes that capture data about transacting parties and corresponding information associated with each transaction. A risk model is run that is configured to determine a risk weight for the relation between nodes associated with the transacting parties based on the data captured in the relationship network graph. Then there is determined a degree of a party's association score based on risk scores of nodes associated with the party and a defined relationship with another suspicious party. The system then dynamically updates the risk weight of the relation based on the party's association score.

Abstract: Systems and methods are described for automatically processing data stored in one or more databases using machine learning to detect entities (such as health care providers, health care plan members, patients, pharmacies, and so forth) associated with health care claims that are suspected of fraudulent, wasteful, and/or abusive activity. The techniques may further or alternatively involve generating and presenting, for a set of suspected entities, natural language explanatory information explaining how and/or why each of the respective suspected entities is considered to be suspected of fraudulent, wasteful, and/or abusive activity. Feedback provided by fraud analysts and/or other subject matter experts in the misuse detection space is used to facilitate misuse detection and misuse detection presentation.

Abstract: Aspects of the disclosure relate to data feed meta detail categorization for confidence. A computing platform may retrieve source data from a source system and identify a first set of patterns associated with the source data. The computing platform may retrieve, from a target system, partially transferred data associated with an ongoing data transfer from the source to the target system and identify a second set of patterns associated with the partially transferred data. The computing platform may evaluate integrity of the partially transferred data by comparing the first set of patterns with the second set of patterns. The computing platform may detect whether the first set of patterns falls within an expected deviation from the second set of patterns based on the comparison and halt the ongoing data transfer based on detecting that the first set of patterns falls outside the expected deviation from the second set of patterns.

Abstract: Decentralized computer systems and methods are disclosed for analyzing transaction attributes and dispute information using blockchain. One method includes: receiving a first transaction information of a first transaction, wherein the transaction information includes attributes of the first transaction; generating a blockchain entry that stores the received attributes in a shared ledger to participants of the blockchain; receiving an input of a selection of an attribute of the first transaction from a participant of the blockchain to analyze other transactions having the selected attribute; compiling a list of other transactions having the selected attribute; receiving transaction information for each transaction of the list of other transactions; and generating, on a user interface, an analytics report of the attributes of the other transactions.

Abstract: A method using one or more mobile devices for transporting information from an automated teller machine (“ATM”) to a central server when the ATM does not support a network connection and, upon return of the one or more mobile devices to the ATM, updating the ATM may be provided. The method may include transporting electronic transaction data processed locally at the ATM, via a mobile device, to a location where a network connection between the mobile device and the central server may be established. When in a location including network connection, the method may include transmitting the electronic transaction data to the central server. When the mobile device is detected to have returned to be within the pre-determined range of the ATM, the method may include transmitting a data packet to the ATM, the data packet received from the central server, thereby updating the ATM of the transmittal.

Abstract: A framework for interpreting machine learning models is proposed that utilizes interpretability methods to determine the contribution of groups of input variables to the output of the model. Input variables are grouped based on correlation with other input variables. The groups are identified by processing a training data set with a clustering algorithm. Once the groups of input variables are defined, partial dependent plot (PDP) tables for each group are calculated and stored in a memory, which are used for calculating scores related to each group of input variables for a given instance of the input vector processed by the model. Furthermore, Shapley Additive Explanations (SHAP) values for each group can be calculated by summing the SHAP values of the input variables for a given instance of an input vector per group. These scores can then be sorted, ranked for each interpretability method, and then combined into one hybrid ranking.

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: Aspects of the disclosure relate to data feed meta detail categorization for confidence. A computing platform may retrieve source data from a source system and identify a first set of patterns associated with the source data. The computing platform may retrieve, from a target system, transferred data associated with a data transfer from the source system to the target system and identify a second set of patterns associated with transferred data. The computing platform may evaluate integrity of the transferred data by comparing the first set of patterns with the second set of patterns. The computing platform may detect whether the first set of patterns falls within an expected deviation from the second set of patterns based on the comparison. The computing platform may send one or more notifications based on detecting that the first set of patterns falls outside the expected deviation from the second set of patterns.

Abstract: A method for providing pre-data breach monitoring provides information to businesses that is useful to predict portions of the company data that may not be secured well enough and other risks associated with data breaches, such as employees that may not be trustworthy.

Abstract: A dynamic banner may be displayed in a merchant check out page sourced from a merchant server that may be customized to a particular user and/or merchant. The dynamic banner may be provided by a transaction account provider server and may invite the user to select an offer. In response to the user's interaction with the offer, the characteristics of the merchant check out page may be changed, for example, a product may be discounted, and/or a new transaction account may be issued to the user by the transaction account provider server and used to complete the checkout process via cross document messaging and cross domain scripting. In this manner, the merchant server and the transaction account provider server may interact with a user within a single web page.

Abstract: A Software as a Service (SaaS) management platform (SMP) is provided, the SMP configured to perform a method including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: An integrated computerized system, method, and non-transitory computer readable media oriented to mobile computerized devices such as tablet computers and Smartphones, for assisting users in conducting site visits and tours to various real properties of interest. The method comprises various software modules, including software modules to assist in various numeric comparative property evaluation schemes, modules to automatically present building floor plans and other information at defined tour locations, and modules to show images or CAD drawings of proposed property modifications (often using augmented reality techniques). Other modules may additionally help manage the tour, including semi-automatic notification of tour itinerary changes, management of tour route instructions, and audio or text narration during selected portions of the tour.

Abstract: A computer implemented system, method, or computer readable medium for providing a interactive digital tool that permits users to investigate and evaluate financial, trade, and business-related risks. The system, method, or computer readable medium can be configured to include a software engine that identifies risk subgraphs or other subgraph features in accordance with automated traversal based on a set of rules.

Abstract: In one or more embodiments, one or more loan origination systems can obtain, from a credit reporting system, credit report data for a mortgage loan applicant. The one or more loan origination systems can determine that the mortgage loan applicant does not qualify for a mortgage loan product based on the credit report data obtained from the credit reporting system. The one or more mortgage loan origination systems can obtain data representing a non-mortgage loan product for which the mortgage loan applicant qualifies based on the credit report data. The one or more loan origination systems can generate a modified version of the mortgage loan applicant's credit report data based on the non-mortgage loan product and determine that the mortgage loan applicant would qualify for the mortgage loan product based on the modified version of the credit report data.

Abstract: A computer system accesses electronically stored data pertaining to a consumer's current and historical credit reports from a plurality of credit bureaus. Errors in the reports are identified by the computer system, which can then create dispute letters detailing the errors with text customized for each error. The computer processes the data to identify errors within a single report and between multiple reports, both current and historical. The errors can relate to multiple accounts on a given report duplicating the same debt with the same or differing status, and reports from different credit bureaus reporting the same debt with differing status. The status can include the debt being open or closed, and the date the status of the debt changed. The errors are presented on a display with which particular errors can be selected to be included in the report.

Abstract: An apparatus for customization and utilization of target profiles, the apparatus comprising: a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive a data set comprising a plurality of target data, determine a validity status of the plurality of target data within the data set, modify the data set as a function of the validity status, determine one or more protection gaps within the modified data set using a gap finder module, generate one or more target profiles as function of the modified data set, the one or more protection gaps, and a user input, and modify a graphical user interface as a function of one or more target profiles.

Abstract: A system and method are described which attempt to connect merchants with phone numbers that are known to be associated with fraudulent users.

Abstract: Methods and systems are disclosed that identify and locate debt settlement candidates based on credit data associated with the consumer. For example, candidacy may be based on a debt score, generated by an assessment of the consumer's credit data. Credit data may include the consumer's credit score rank, credit score, revolving credit to debit ratio, credit available, delinquent accounts, negative accounts, instances of negative information on their credit report, public record data, average account age, debit, or a combination thereof.

Abstract: Systems and methods are described to facilitate an efficient on-boarding experience for users joining a financial institution, while maintaining the integrity of certain operations to determine whether the users are eligible for certain financial products based on the personal information of the users. For instance, a first server may perform an approval process by receiving a request to verify an identity of the user using a digital identity service, sending to a second server a request to obtain one or more categories of personal information about the user, receiving personal information associated with the one or more categories selected by or authorized by the user, determining, based on at least some of the received personal information, that the user is approved for a payment card, and sending information associated with the payment card to a mobile device.

Abstract: A system and computer-implemented method for approving a dynamic mortgage application using a blockchain. In one aspect, the method may include determining a customer is approved for a mortgage (“mortgage ready”) and determining a real estate property is mortgage ready. The method may include comparing a calculated amount in which the customer is approved for a mortgage loan with a calculated appraisal value of the real estate property, and approving the mortgage application of the customer when the calculated amount the customer is approved for the mortgage loan is equal to, or exceeds, the calculated appraisal value of the real estate property, reducing a processing time and closing time of the mortgage.

Abstract: A Software as a Service (SaaS) management platform (SMP) is provided, the SMP configured to perform a method including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: Methods and systems are disclosed for providing approved financing in advance of a purchase to a buyer of an item, such as an automobile, and allowing the prospective buyer to maintain control over the financing throughout the sales process. According to disclosed embodiments, a financial service system configures a financing website for the buyer, and receives personal information as well as information relating to the desired item. The financial service system approves loan parameters for the buyer, and provides the user with a link to access the financing website on a mobile device while at a dealership. Financing parameters can thus be edited throughout the process until the final sales agreement, providing the buyer with confidence and flexibility in the buying process.

Abstract: In an example, a computer implemented method includes obtaining respective transactional data from each financial data source of a plurality of financial data sources, where the respective transactional data is each associated with a posting time. The method also includes determining a net liquidity amount from the respective transactional data based on the posting time of each of the respective transactional data. The method also includes outputting net liquidity data that is representative of the determined net liquidity amount.

Abstract: Computer-based systems, platforms, and modules manage and sell securities such as mortgage loans and TBA positions for mortgage loans held by the system user, such as a lender, in the relevant market for such securities. A single system simultaneously negotiates transactions with multiple investors and broker-dealers for such securities. The computer-based systems generate best execution analyses of trades of loans and TBA transactions. The computer-based systems generate hedge recommendations based on the loans and loan commitments owned by the lender and automatically executes those hedge recommendations on a best execution basis without intervention. The computer-based systems allow for lenders to enter into contracts to sell loans to investors who are not qualified investors by locking the spread while allowing for the loan price to fluctuate until a trade is consummated.

Abstract: In some examples, a system may receive first merchant data for a first merchant. For instance, the first merchant data may include one or more merchant characteristics associated with the first merchant. The system may assign the first merchant to a first group of merchants based at least in part on the first merchant sharing at least one of the merchant characteristics with the first group of merchants. The system may use a machine learning model to determine a customized timing at which to provide a loan offer to the first merchant. The customized timing n ay be based at least in part on loan data associated with one or more loans previously offered to the merchants in the first group of merchants. Further, the system may send the loan offer to a computing device of the first merchant based at least in part on the customized timing.

Abstract: A system and computer-implemented method for approving a dynamic mortgage application. In one aspect, the method may include determining a customer is approved for a mortgage and determining a real estate property is mortgage ready, including calculating an appraisal value for the real estate property based upon the information about the real property retrieved from a computer file or memory location/address (such as by using a machine learning or artificial intelligence algorithm). The method may still further include comparing the calculated amount the customer is approved for a mortgage loan with the calculated appraisal value of the real estate property; and approving the mortgage application of the customer for the real estate property when the calculated amount the customer is approved for the mortgage loan meets, or exceeds, the calculated appraisal value of the real estate property.

Abstract: Various embodiments of the present invention describe techniques that perform account registration management operations with respect to an account registration session based on a real-time registration processing output that is generated based on an earlier-generated preliminary risk category, such as a preliminary risk category that is generated before the account registration session is completed. In some embodiments, by generating a component of the real-time registration processing output during the account registration session, the disclosed techniques enable reducing the data processing time associated with generating the real-time registration processing output, thus increasing the speed and operational reliability of an electronic data management system that is configured to perform account registration management operations.

Abstract: The present disclosure relates to methods, devices, and systems for capturing content from a client's transaction related messages on a client's device by a third party. A transaction data processing system, includes a computing device configured to: harvest data from one or more original messages from an account of a seller within seller's email, wherein the original message has a number of elements arranged in a first order, assemble a modified message for each original message wherein the modified message is a customized, uniform format and where all modified messages each have the same elements in the same orientation, but where the orientation of the elements is different than that of the original message, and route the modified messages to one of more team or individual accounts on the client portal access on the client computing devices at a client network.

Abstract: An authentication system for authenticating an asset having an NFC tag is disclosed comprising an authentication server, a controller in communication with the authentication server and an NFC enabled device, the controller is configured to request reading of a tag identification number (ID) from a memory of the NFC tag, generate a tag record of the NFC tag on the authentication server, associated with the tag ID, generate a token (TS) corresponding to the NFC tag, the token is generated by an algorithm based on the tag ID, request writing of the token to the memory, associate the token with the tag ID, wherein, upon a user subsequently validating the asset, the controller is configured to request reading the token from the memory, and verify the token against the tag record comprising comparing said token with the associated token stored in the tag record on the authentication server.

Abstract: A computer system for provisioning automobile financing is described, including: at least one data interface adapted to receive partial or masked pre-approval data set from a backend computing device associated with a financial institution, the partial or masked pre-approval data set configured such that pre-approval data set associated with a potential loan transaction is not independently accessible by the computer system; the at least one data interface adapted to receive, from a customer or a customer device, a corresponding identifier or portion of pre-approval data set that complements the partial or masked pre-approval data set; an integration engine adapted for combining the partial or masked pre-approval data set and the corresponding identifier or portion of pre-approval data set to regenerate the complete pre-approval data set associated with the potential loan transaction; a loan provisioning engine adapted for provisioning the loan transaction in accordance with the complete pre-approval data set