A purchase receipt data system is provided. The purchase receipt data system includes at least one user device. Each user device is capable of connecting to a network. A server is also connected to the network and includes a storage unit and a computer-readable medium. The computer-readable medium is designed to execute an application. The application performs a number of steps, including gathering a set of purchase data, categorizing the set of purchase data, organizing the set of purchase data into a database, and organizing the database into a graphical user interface.

Embodiments of the invention are directed to systems, methods and computer program products for dynamic resource interaction allocation based on geographic positioning and usage category information associated with a resource interaction system. The invention receives a base positional location and category of usage for a resource interaction system. The invention determines a set of parameters to be used for interactions having characteristics meeting the determined base positional location and category of usage information. When it receives a proposed interaction from a requesting system containing geographic information and usage category information associated with the proposed interaction, it determines whether the geographic information and usage category information associated with the proposed interaction correspond to the base positional location and category of usage for the resource interaction system. If the information matches, the invention applies the set of parameters to the interaction to thereby process the interaction.

Embodiments of the invention are directed to systems, methods and computer program products for dynamic resource interaction allocation based on geographic positioning and usage category information associated with a resource interaction system. The invention receives a base positional location and category of usage for a resource interaction system. The invention determines a set of parameters to be used for interactions having characteristics meeting the determined base positional location and category of usage information. When it receives a proposed interaction from a requesting system containing geographic information and usage category information associated with the proposed interaction, it determines whether the geographic information and usage category information associated with the proposed interaction correspond to the base positional location and category of usage for the resource interaction system. If the information matches, the invention applies the set of parameters to the interaction to thereby process the interaction.

Techniques are provided for authorizations in a virtual computing infrastructure using a federation token service. The techniques may include receiving a request for a launch plan from a user for launching instances in a plurality of sites, determining object permissions required for actions to be performed to launch one or more of the instances at each site of the plurality of sites, contacting an authorization caching service to obtain authorization tokens for each of the determined object permissions required for the actions, receiving the authorization tokens for each of the determined object permissions required for the actions, and forwarding the request to each site of the plurality of sites with an authentication token and the authorization tokens for each of the determined object permissions required for the actions to be performed to launch the one or more of the instances at each site of the plurality of sites.

In embodiments, diagnostics are electronically determined and provided as to why historical resource values differ from resource values determined according to more-trusted ways. Historical relationship instance data regarding a plurality of historical relationship instances between a primary entity and a plurality of secondary entities are received along with a plurality of historical resource values, in which each historical relationship instance of the plurality of historical relationship instances is associated with a respective historical resource value of the plurality of historical resource values. The system produces a respective trusted resource values based on the respective historical relationship instance. Based on differences between the respective trusted resource value and the respective historical resource value associated with the dataset, the system outputs one or more diagnostic comments associated with the detected difference.

In embodiments, diagnostics are electronically determined and provided as to why historical resource values differ from resource values determined according to more-trusted ways. Historical relationship instance data regarding a plurality of historical relationship instances between a primary entity and a plurality of secondary entities are received along with a plurality of historical resource values, in which each historical relationship instance of the plurality of historical relationship instances is associated with a respective historical resource value of the plurality of historical resource values. The system produces a respective trusted resource values based on the respective historical relationship instance. Based on differences between the respective trusted resource value and the respective historical resource value associated with the dataset, the system outputs one or more diagnostic comments associated with the detected difference.

Described herein are improved systems and methods for overcoming technical problems associated with the use of Monte Carlo simulation methods, such as problems associated with applications of Monte Carlo simulation methods that are searching for more definite answers. In some embodiments described herein, improved systems and methods overcome the technical problem of the results of Monte Carlo simulations providing approximations and/or non-optimal results (or at least non-enhanced results). Thus, such embodiments can provide more enhanced answers to limiting risks; and in some cases, such embodiments can even provide optimal answers to limiting risks. In some embodiments, machine learning can be used to provide more enhanced answers to limiting risks; and in some cases, such embodiments can use machine learning to provide optimal answers to limiting risks discovered through Monte Carlo simulations.

In some implementations, a user device may receive, via an application, object information associated with an object, wherein the object information identifies a value associated with the object and a location of the object. The user device may determine an adjustment factor that is associated with transactions performed in a region of the location. The user device may determine, based on the value and the adjustment factor, an adjusted value associated with the object. The user device may generate, based on the adjusted value, an arrangement of tokens for a transaction involving the object and the tokens. The user device may output, via a user interface of the application, an indication of the arrangement of tokens to assist a user with engaging in the transaction.

In some implementations, a user device may receive, via an application, object information associated with an object, wherein the object information identifies a value associated with the object and a location of the object. The user device may determine an adjustment factor that is associated with transactions performed in a region of the location. The user device may determine, based on the value and the adjustment factor, an adjusted value associated with the object. The user device may generate, based on the adjusted value, an arrangement of tokens for a transaction involving the object and the tokens. The user device may output, via a user interface of the application, an indication of the arrangement of tokens to assist a user with engaging in the transaction.

A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability. Once a user gives explicit confirmation, the engine modifies the database entry.