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: 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: 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: 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 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: 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: 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: 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: A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile device customer feedback indicating that the alert was a false positive or otherwise erroneous. The method also includes inputting the data detailing the financial transaction into a machine learning program trained to (i) determine a reason why the false positive was generated, and (ii) then modify the rules-based engine to account for the reason why the false positive was generated, and to no longer generate electronic fraud alerts based upon (a) fact patterns similar to fact patterns of the financial transaction, or (b) data similar to the data detailing the financial transaction, to facilitate reducing an amount of future false positive fraud alerts.

Abstract: A process for handling interleaved sequences using RNNs includes receiving data of a first transaction, retrieving a first state (e.g., a default or a saved RNN state for an entity associated with the first transaction), and determining a new second state and a prediction result using the first state and an input data based on the first transaction. The process includes updating the saved RNN state for the entity to be the second state. The process includes receiving data of a second transaction, where the second transaction is associated with the same entity as the first transaction. The process unloops an RNN associated with the saved RNN state including by: retrieving the second state, determining a new third state and a prediction result using the second state and an input data based the second transaction, and updating the saved RNN state for the entity to be the third state.

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

Abstract: Automated loan production systems, methods, and media are provided. For example, the disclosed subject matter can provide a point-of-sale platform that sources the borrower, captures the borrower's information in the form of a consumer loan application at a point-of-sale, underwrites the borrower based on criteria provided by lending partners, underwrites one or more merchants for inclusion on the point-of-sale platform, matches multiple loan offers from multiple lending partners based on borrower and lender requirements, presents loan documents of a selected loan for electronic signature between the merchant and the borrower, disburses funds from the lender to the merchant, and provides reporting to merchants, partners, lenders, and other entities through respective portals.

Abstract: A computer-implemented method for predicting interchange charges includes: retrieving a historical transactions set, where each completed transaction in the set includes transaction features, a bank identification number (BIN), and a corresponding true interchange code; transforming all BINs in the set into a corresponding plurality of BIN features that comprise probabilities; creating a first training set including all transaction features, all pluralities of BIN features, and all true interchange codes associated with the historical transactions set; training a random forest model using the first training set and generating a second training set including rounded BIN features, rounded transaction features, discrete ones of the transaction features, and the true interchange codes; training the random forest model using the second training set to generate a trained random forest model for prediction of the interchange codes; and executing the trained random forest model for new transactions to generate corres

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: 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: 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: 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: 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: 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: 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 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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 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: 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: 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: 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: Computer systems and methods for managing resources are described.

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.