533 results about "Risk profiling" patented technology

Here, we introduce Z-webs, including Z-factors and Z-nodes, for the understanding of relationships between objects, subjects, abstract ideas, concepts, or the like, including face, car, images, people, emotions, mood, text, natural language, voice, music, video, locations, formulas, facts, historical data, landmarks, personalities, ownership, family, friends, love, happiness, social behavior, voting behavior, and the like, to be used for many applications in our life, including on the search engine, analytics, Big Data processing, natural language processing, economy forecasting, face recognition, dealing with reliability and certainty, medical diagnosis, pattern recognition, object recognition, biometrics, security analysis, risk analysis, fraud detection, satellite image analysis, machine generated data analysis, machine learning, training samples, extracting data or patterns (from the video, images, and the like), editing video or images, and the like. Z-factors include reliability factor, confidence factor, expertise factor, bias factor, and the like, which is associated with each Z-node in the Z-web.

By including environment information in a security policy, a security architecture advantageously allows temporal, locational, connection type and / or client capabilities-related information to affect the sufficiency of a given credential type (and associated authentication scheme) for access to a particular information resource. In some configurations, time of access, originating location (physical or network) and / or connection type form a risk profile that can be factored into credential type sufficiency. In some configurations, changing environmental parameters may cause a previously sufficient credential to become insufficient. Alternatively, an authenticated credential previously insufficient for access at a given trust level may be sufficient based on a changed or more fully parameterized session environment. In some configurations, the use of session tracking facilites (e.g., the information content of session tokens) can be tailored to environmental parameters (e.g., connection type or location). Similarly, capabilities of a particular client entity (e.g., browser support for 128-bit cipher or availablity of a fingerprint scanner or card reader) may affect the availability or sufficiency of particular authentication schemes to achieve a desired trust level.

The present invention provides systems, methods and computer program products for authorizing transactions based on, at least in part on, enhanced authorization data. In one embodiment, enhanced authorization data is received in a request for authorization to accept a transaction instrument as payment. Examples of enhanced authorization data include an automatic number identification, an information identifier, an email address, a contact telephone number, a ship-to-name, ship-to-address, an Internet Protocol address, and a seller identification. A risk analysis is performed based, at least in part, on the enhanced authorization data to determine the risk of the request being associated with a fraudulent purchase. The risk may be calculated by comparing the enhanced authorization data with information stored about the transaction instrument or with historical transaction information. Furthermore, the velocity of transactions associated with the enhanced authorization data may be measured in calculating the risk.

The present invention provides investment advice systems. One version of the present invention provides investment advice systems that allow a user to select one or more advisors from a list of investment advisors. According to this version of the invention, the end user can receive advice on a particular transaction either separately from each investment advisor or in consensus. The system offers advice in part on the user's portfolio, tax position and risk profile and in part on the advisors evaluation of current market conditions. Thus, when a user is considering making a transaction, the user can obtain advice that can take into portfolio information including a user's proposed transaction and / or user portfolio information. A user armed with the above-described customized advice can execute a specific transaction and have their portfolio updated to reflect execution of that (those) order(s). In an alternative embodiment, a user's desire to buy or sell a security and / or a need for rebalancing a user's portfolio can generate transaction(s). As a result, the system will generate a buy / sell list (including recommended alternatives) from which a user can select.

Systems and methods for use with a service provider and a consumer electronic device include a trusted remote attestation agent (TRAA) configured to perform a set of checking procedures or mechanisms to help ensure the security status of a consumer electronic device (e.g., a mobile terminal or phone) that holds financial instruments. The checking procedures may include: self-verifying integrity by the TRAA; checking for presence of a provisioning SIM card (one that was present when the financial instruments were enabled on the device); checking that a communication connection between the consumer electronic device and the service provider is available and active; and checking that communication connectivity to a home mobile network is available and active. The frequency of the checking mechanisms may be adjusted, for example, according to a risk-profile of a user associated with the device or the location (e.g., GPS location) of the device. The checks may be used, for example, to temporarily disable or limit the use of the financial instruments from the device.

A determination is made as to whether there is a correlation between a user's security risk profile and a personalized threat profile of an actual or spreading threat. If there is a correlation, a personalized reactive alert is issued in the case of an actual threat. The personalized reactive alert informs the user of specific suspected data that may have been compromised by the threat and the specific non-computer related action that the user should take. Further, if there is a correlation, a personalized proactive alert is issued and / or personalized proactive protective action taken in the case of a spreading threat. The personalized proactive alert informs the user of the spreading threat that the user and / or the user's host computer system is particularly susceptible to. Further, the personalized proactive protective action taken provides automated risk mitigation.

Security policy changes can be implemented for a user or a user group based on behaviorally-derived risk information. A behavior-receiving module receives information about user behaviors for the user across various clients with which the user interacts. An attribute-receiving module receives one or more user attributes identified for a user. A profile-generating module generates a user risk profile for the user based on the received information about the user behaviors and the received user attributes. A user scoring module assigns the user a user risk score based on an evaluation of the user risk profile for the user. Similarly, groups of users can be given group risk scores, or users can have combined group / user scores. Finally, a remediation module automatically establishes a security policy requiring remediative actions for the user (or user group) based on the user risk score or combined score (or group score).

Systems and methods are presented for determining risk levels for consumer-to-consumer (C2C) transactions on brokering websites. The risk levels can be based on payment processing network (e.g. Visa) account data as well as external data, such as geo-location using IP addresses, fraud bureau data, and star ratings. The buying and selling consumers can have multiple risk scores for each transaction, such as a fraud, credit, return / chargeback, dissatisfaction, product misuse, nonreturnable, and defect risk scores. The buying and selling consumers can trade their risk levels before proceeding with the transaction.

Here, we introduce Z-webs, including Z-factors and Z-nodes, for the understanding of relationships between objects, subjects, abstract ideas, concepts, or the like, including face, car, images, people, emotions, mood, text, natural language, voice, music, video, locations, formulas, facts, historical data, landmarks, personalities, ownership, family, friends, love, happiness, social behavior, voting behavior, and the like, to be used for many applications in our life, including on the search engine, analytics, Big Data processing, natural language processing, economy forecasting, face recognition, dealing with reliability and certainty, medical diagnosis, pattern recognition, object recognition, biometrics, security analysis, risk analysis, fraud detection, satellite image analysis, machine generated data analysis, machine learning, training samples, extracting data or patterns (from the video, images, and the like), editing video or images, and the like. Z-factors include reliability factor, confidence factor, expertise factor, bias factor, and the like, which is associated with each Z-node in the Z-web.

A system and method for defining the value of a corporation by its categories of values, and determining the risk profile of the corporation by the relationship between the categories of value, termed the “Risk Signatures.” The system provides for the determination of the “Relative Values” of corporate enterprises, with the capability of dynamically monitoring and measuring the financial performance of an enterprise through the use of artificial intelligence and data mining techniques.

A method of providing for a secure financial transaction, the method including the steps of: (a) formulating the documentation associated with the financial transaction, including security for the transaction; (b) dividing the transaction into a series of segments, each segment having an associated expected risk profile and security profile; (c) for each segment, creating an indicative token describing the segment, including associated expected risk profile and security profile; (d) providing a block chain environment for storage of the indicative tokens.

A computerized monitoring system and corresponding method of monitoring the status and health of a blowout preventer. The system includes a graphics display at which a graphical user interface (GUI) displays the health of various sealing elements and control systems by way of “traffic light” indicators. The health indicators are evaluated, by the monitoring system, based on a risk profile for each of the indicated elements and control systems. The risk profiles are evaluated based on inputs such as measurement inputs, feedback signals, mechanical positions, diagnostic results, drilling conditions, and other status information of the blowout preventer at a given time and based on levels of redundancy and levels of deviation from normal conditions. The GUI includes recent history of changes in operating condition, and alarm indications such as poor health, along with the times of those events.

An information device includes a dynamically configurable security module in which operational settings are automatically and dynamically configured based on risk profile or computing capacity information, or both.

The invention is directed to providing threat and risk analysis for a network that has a high degree of inter-relationships and interdependencies among the assets comprising it, using a “cut set” enumeration method. The identified cut sets are used as the basis to the threat and risk analysis, since each cut set may affect the traffic between two dependent assets in the network, and thereby affect the security state of the dependent assets themselves. The affected security state may be confidentiality, integrity, availability, or other network or security relevant parameter.

The present invention is applicable in the field of corporate finance, corporate capital investments, economics, math, business risk analysis, simulation, decision analysis, qualitative risk analysis, risk management, quantitative risk analysis, and business statistics, and relates to the modeling and valuation of investment decisions under uncertainty and risk within all companies, allowing these firms to properly identify, assess, quantify, value, diversify, and hedge their corporate capital investment decisions and their associated risks. Specifically, the present invention looks at starting from a comprehensive qualitative risk register and moving the analysis into the realms of quantitative risk modeling, simulation, and optimization.

Devices, systems, methods, and software for providing remote medical diagnosis and therapy to a subject comprising: a module for conducting telecommunications with a telemedicalist; a module for applying a diagnostic or a therapeutic analysis; an apparatus for dispensing one or more medical items from an inventory of medical items, the inventory of medical items risk profiled to a subject, a population, a venue, or a situation; and optionally, a biosensor apparatus.

A tool is provided for designing electronic games of chance such as slot or fruit machine games. Software that runs on a computer or remote server takes user inputs and selections such as game rules, input data, and pointers to or import of files (such as sound and graphics files). The output data of such a tool may be a file or parameters that specify one or more of hit rate, return to player, pay-table, symbol mapping, symbols, game theme, risk profile, rules of game play, denomination, language, currency, display, simulation results, pay methods, triggers for game features or jackpots.

There is provided a computer system having a module for controlling a processor to receive a request via a network for a risk analysis of an investment, pass the request to a risk analysis engine, receive a result of the risk analysis from the risk analysis engine, and send the result to a client device via the network.

A computer implemented method for mining risks includes providing a set of risk-indicating patterns on a computing device; querying a corpus using the computing device to identify a set of potential risks by using a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with the corpus; comparing the set of potential risks with the risk-indicating patterns to obtain a set of prerequisite risks; generating a signal representative of the set of prerequisite risks; storing the signal representative of the set of prerequisite risks in an electronic memory; and aggregating potential risks linked to an entity to an entity risk profile (ERP). A computing device or system for mining risks includes an electronic memory; and a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with a corpus stored in the electronic memory.

The present invention provides traders with a computer-based neural analysis system for trading commodities based on a traders risk profile, particularly equities, by providing a careful selection of the data to analyze and selecting the correct manipulation of that data. The neural analysis component uses initially selected data components or factors, by manipulating them with operators, or asset specific mathematical functions, a fuzzy or Bayesian advisors help to assist in the genetic learning of the system by being reward and punishment based on the correlation to success and failure, or meta-advisors. A contingency notification system implemented either internally or externally examines the real-time data feed to determine if conditions are such that the trader should be notified that conditions have been met, such that the risk profile requires an immediate action.

A robot safety system configured to protect humans in the vicinity of a working robot (1, 11, 21, 31) against harmful impacts by said robot (1, 11, 21, 31), said safety system comprising a sensor system (3, 13, 23) and a safety controller (4, 14, 24) configured to establish an impact risk profile of the robot (1, 11, 21, 31) and deliver an operating signal to a robot controller (2, 12, 22) based on said impact risk profile, wherein the safety controller (4, 14, 24) is configured to establish the impact risk profile based on stored data and input signals, and that the stored data and input signals comprise stored impact data, stored data related to the path of the robot (1, 11, 21, 31), and signals from the sensor system of events in the vicinity of the robot (1, 11, 21, 31), such as a detected human (P1, P11, P21, P22, P31, P32) in the vicinity of the robot (1, 11, 21, 31).

A method for evaluating a system having at least one portal is provided, wherein the method includes examining the at least one portal to identify at least one accessible portal, performing a qualitative analysis responsive to the at least one accessible portal, performing a quantitative analysis responsive to the qualitative analysis and generating a risk profile responsive to the performing a qualitative analysis and the performing a quantitative analysis.

Embodiments of the present invention are directed to a method and system for automated risk analysis. The method includes accessing host configuration information of a host and querying a vulnerability database based on the host configuration information. The method further includes receiving a list of vulnerabilities and accessing a plurality of vulnerability scores. The list of vulnerabilities corresponds to vulnerabilities of the host. Vulnerabilities can be removed from the list based on checking for installed fixes corresponding to vulnerability. A composite risk score can then be determined for the host and each software product of the host based on the plurality of vulnerability scores. An aggregate risk score can then be determined for the host and each software product of the host based on the plurality of vulnerability scores.

Systems, methods, and apparatus for handling and / or authorizing payment requests by a consumer for a transaction are provided. Challenge questions may be presented from the non-merchant to the consumer after receiving the payment information, thereby allowing a judicious determination of when to ask such challenge questions and allowing complex and probative questions. The time limit for such challenge questions may advantageously be unconstrained, while still preserving security. Also, a risk analysis may be started prior to the consumer submitting payment information, thus allowing an efficient and complex risk analysis. Information about an access device used by the consumer may be obtained at the non-merchant from the access device with code sent to the access device from the merchant, and the device information may be used in the risk analysis.

A system, computer program product, method and algorithm for evaluation of blood glucose variability—one of the most important parameters of diabetes management. An embodiment of the method may use routine self-monitoring blood glucose (SMBG) data collected over a period of 2-6 weeks, for example, based on a theory of risk analysis of blood glucose data. One aspect may include a method, system and computer program product for computing the Average Daily Risk Range (ADRR)—a measure of overall glucose variability. Another aspect may include a method, system, and computer program product for estimating separately the glucose variability in the hypoglycemic range via a Low BG Index (LBGI) and the glucose variability in the high BG range via High BG Index (HBGI) followed by a combination of the two indices into a single variability display.

The CapStratix System operates on a plurality of existing loans (a “designated portfolio”), held by a regulated Lender, using a pool of capital which is available from unregulated Investors, to dynamically re-compute loan packages. The CapStratix System arranges for the disaggregation of a Lender's designated portfolio of Mortgage Loans, each into discrete note amounts, including an A Note and a “RenuNote”, both (or all) secured by the same mortgage lien. This process facilitates the extension of the maturity dates of the loans, at new market pricing, and the restatement of other terms and conditions required for a successful sale of the RenuNote to an Investor, reducing Lender's assets and risk profile, thereby having a positive effect on a Lender's regulatory capital ratios, without requiring a change to the Borrower's ownership structure or risk exposure.

Systems and methods are presented for improved authentication and risk analysis processes using search engine technology. In one potential implementation, an authorization request message is received at a payment processing network as part of a transaction between a user and a merchant. The payment processing network analyzes risk based on a search history associated with the user involved in the transaction with the merchant. A response to the authentication request is made based in part on the risk associated with the user search history. In further embodiments, a user registers with a search engine as part of a service for improved authentication, where the user accepts privacy settings allowing storage of search and transaction data by a search engine server. The search engine server passes search and transaction data to a risk analysis server for creation of risk parameters which may be used to authenticate transactions.