WO2025176597A1 - Système et procédé de traitement de données de commande automatisé - Google Patents

Système et procédé de traitement de données de commande automatisé

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Publication number
WO2025176597A1
WO2025176597A1 PCT/EP2025/054171 EP2025054171W WO2025176597A1 WO 2025176597 A1 WO2025176597 A1 WO 2025176597A1 EP 2025054171 W EP2025054171 W EP 2025054171W WO 2025176597 A1 WO2025176597 A1 WO 2025176597A1
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WO
WIPO (PCT)
Prior art keywords
data
module
controlling
controlling data
processed
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/EP2025/054171
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English (en)
Inventor
Günther HOLZAPFEL
Christian DELLWO
Jürgen Hoffmann
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Aipama & Co Kg GmbH
Original Assignee
Aipama & Co Kg GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Aipama & Co Kg GmbH filed Critical Aipama & Co Kg GmbH
Publication of WO2025176597A1 publication Critical patent/WO2025176597A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/105—Human resources
    • G06Q10/1053—Employment or hiring
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/105—Human resources
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/12—Accounting
    • G06Q40/125—Finance or payroll

Definitions

  • the present invention relates to a system for automated processing of controlling data, which can relate to aspects such as data integrity, data lineage, data quality, and data governance.
  • the present invention further relates to the field of financial data processing, specifically payroll data processing, which is the process of calculating and distributing wages, salaries, bonuses, deductions, taxes, and other payments to employees of an organization.
  • Processing of controlling data may involve various objectives, such as collecting and verifying employee information, calculating gross and net pay, withholding and remitting taxes and other deductions, issuing pay checks or direct deposits, generating payroll reports and records, and filing tax returns and forms. These tasks can be performed manually, using paper forms and calculators, or electronically, using software applications and databases. However, both methods may have drawbacks and limitations that affect the accuracy, efficiency, and security of controlling data processing.
  • Processing of controlling data can be prone to errors, such as miscalculations, misclassifications, omissions, duplications, and/or delays. These errors can result in the issuance of incorrect payments, incorrect tax filings, penalties or fines from authorities, disputes and lawsuits from employees or third parties.
  • Manual processing of controlling data can be time-consuming and labour-intensive, as it may require a lot of manual document processing, calculations, checks, and corrections.
  • manual processing of controlling data can be vulnerable to fraud, theft, loss, or damage of payroll data, as it relies on unprotected storage and handling of documents.
  • Electronic processing of controlling data may need to comply with various laws and regulations that govern the protection and privacy of controlling data, in particular in different jurisdictions and contexts.
  • Each module can define a set of service operations, which are actions that can be performed by, or on, the respective module.
  • the system can use the service operations, that can be defined by service interfaces of the external components, to exchange information and perform actions with these external components.
  • the system can provide an interoperability to transfer data between independent entities which can reduce the cost and increase the reliability of the provided data.
  • the system can define interfaces of the modules that specify how two modules that can be organizationally, physically, and/or electronically separated from one another can interact with each other in a scalable way.
  • the objective of the invention is to provide a method and system for centralized data processing that can receive, convert, and process input data or documents from multiple sources, regardless of the format, readability, or interface of the input data or documents.
  • the invention aims to enable the extraction, analysis, and integration of relevant information from various types of input data or documents, such as digital documents or datasets that are primarily designed for human consumption or interaction, rather than machine processing.
  • the present invention provides a method and system for processing of controlling data that uses decentralized technology to enhance the accuracy, efficiency, security, and compliance of controlling data processing.
  • the present invention can improve the accuracy of processing of controlling data by eliminating human errors and ensuring consistency between different sources of data. Also, the present invention can enhance the efficiency of processing of controlling data by automating and streamlining the tasks and reducing the need for manual interventions and reconciliations.
  • the present invention may increase the security of processing of controlling data by protecting the data from unauthorized access or modification using data protection and authentication techniques and consensus between entities.
  • the present invention may also facilitate the compliance of processing of controlling data by adhering to laws and regulations of different jurisdictions and contexts.
  • the invention relates to a system for automatic processing of controlling data.
  • the system can comprise a data processing module configured to retrieve controlling data, and to process the controlling data to generate processed controlling data.
  • the system can be configured to provide the processed controlling data to an access module and/or to a node module.
  • the controlling data can relate to transactional data, i.e., payroll data.
  • Controlling data may involve different aspects that can be of relevance for embodiments of the present technology such as data integrity, data lineage, data quality, and data governance.
  • Data integrity can be the assurance that data is recorded and maintained exactly as intended and is not corrupted or altered unintentionally.
  • Data lineage can comprise the documentation of how data flows and transforms throughout the system, i.e., from the point of origin to the destination point.
  • Data quality can be the degree to which data meets predetermined expectations and requirements which can be set manually and/or automatically by the system.
  • Data governance can comprise a set of policies, standards, roles, and/or responsibilities that define how data is managed and used
  • Controlling data may involve aspects such as reporting, analysis, planning, and/or compliance that may be of relevance.
  • Reporting can be the process of preparing and presenting statements and/or other information that may reflect performance of the system.
  • Analysis can comprise a process of evaluating and interpreting data to support decision making and problem solving.
  • Planning can be the process of setting goals and objectives, developing strategies and system resource allocation, and/or monitoring and adjusting the strategy as needed.
  • Compliance can comprise the process of ensuring that the system adheres to relevant laws, regulations, standards, and technical practices that govern its processes.
  • the data processing module can be represented by a virtualized process that achieves the advantage of assisting a controller in the process of assessing the validity, correctness, and/or accuracy of the received controlling data.
  • Processing the controlling data may comprise transforming the received controlling data such that the data format of the controlling data is compatible with the data processing module to enable further processing.
  • the access module can be configured to allow users to interact with the controlling data.
  • the access module can be a dashboard, in particular, a web-based dashboard, configured to provide an overview of the available data.
  • the access module can be configured to perform data tasks such as filtering, sorting, grouping, and/or aggregating the data.
  • the access module can also be configured to provide a visual interpretation and/or preparation of the data to increase readability, in particular accessibility of specific data elements.
  • the access module can be configured to display charts, graphs, maps, tables, and/or other visual representations of the controlling data.
  • the access module can be configured to allow editing, formatting, or annotating the controlling data.
  • the access module can comprise a database management component configured to allow users to create and manipulate relational or non-relational databases.
  • the database management component can allow users to create and manipulate relational databases.
  • the access module can be configured to provide a graphical user interface (GUI) that enables users to design and use forms, reports, queries, and/or macros to interact with the controlling data.
  • GUI graphical user interface
  • the access module can comprise a cloud-based business analytics service component configured to create and/or share interactive dashboards and reports.
  • the access module can be configured to connect to web services and/or online applications.
  • the access module may further be configured to process natural language queries, which allow the input of prompts relating to the controlling data and to provide a response based, at least in part, on the controlling data.
  • the access module can comprise a user interface component configured to display the controlling data and to receive a user input.
  • the access module can comprise interface features, e.g., one or more buttons or menus, configured to invoke predefined operations and/or modules. Additionally, the access module can comprise output fields that display textual and/or numerical data excerpts from the controlling data which can be generated according to the operations performed.
  • the access module can comprise a connector, specifically interface connectors and/or virtual connectors configured to establish communication with a data source.
  • the data source can be the data processing module which can comprise a transformer configured to transform the controlling data into a suitable format for processing and can further comprise an operator configured to perform calculations, comparisons and/or logical operations on the controlling data.
  • the access module can comprise a generator configured to provide a visual representation of the controlling data and/or the results of the operations based on predefined or user-defined parameters.
  • the access module can simplify and streamline the process of accessing and processing the controlling data by providing a user-friendly and intuitive interface.
  • the access module can also enhance and increase the efficiency of the understanding and communication of the controlling data, in particular by providing options for visualizing and presenting the controlling data.
  • Processed controlling data can refer to the data that has undergone a series of processing steps to ensure its quality and usability.
  • the processing steps may include reading, evaluating, and transforming the data into a homogenized database entry or set of entries that follow a standard format and structure.
  • the processed controlling data can be cross-referenced to other data entries, such as employee provided data, external data, or other sources of information, to check for consistency and completeness.
  • the cross-referencing may also achieve the advantage of the data processing module identifying any errors, gaps, and/or anomalies in the controlling data that may need to be corrected or resolved.
  • Processed controlling data can be provided for decision making, reporting, analysis, or other purposes that require accurate and reliable data.
  • Retrieving the controlling data can comprise receiving the controlling data as an external data stream.
  • the data reception can either be prompted by the data processing module or the controlling data can be received via an established communication or interface link, in particular configured for periodic data transfers.
  • retrieving the controlling data can relate to prompting an external data interface to provide the controlling data or capture a data output of an external data interface, preferably a data provision interface, and extracting the controlling data from the data output.
  • Retrieving can further comprise a data transformation, e.g., between formats, and/or an extraction from a machine and/or manually readable data source.
  • the system can comprise the data provision interface.
  • the data provision interface can be configured to provide the controlling data. This can achieve the advantage that the controlling data can be provided to the data processing module in a directly readable format, in particular without the need of a data retrieval step via the software interface module.
  • the data provision interface can comprise an application programing interface (API) configured to directly access and provide controlling data.
  • API application programing interface
  • the data provision interface can provide access to a salary management module configured to define and modify salary types, i.e., basic salary, allowances, bonuses, deductions, etc.
  • the data provision interface may provide gross and net wages as well as tax and social security contributions for each wage type.
  • the system can comprise the salary management module, preferably in the form of an operation control module.
  • the operation control module can be configured to disburse salaries.
  • the data provision interface can provide access to an employee management module configured to record and update employee data, such as name, address, bank details, tax class, health insurance, etc.
  • employee data such as name, address, bank details, tax class, health insurance, etc.
  • the data provision interface may provide working hours, vacation days, sick days, type of contract, duration of employment etc.
  • the data provision interface can also provide access to a payroll generation module configured to generate individual and/or group payrolls, in particular for each payroll period.
  • the data provision interface may be configured to generate pay slips for employees and/or to post documents for financial accounting.
  • the data provision interface may provide access to a payroll tax filing module configured to submit payroll tax return to the tax office and/or to pay payroll tax to the tax office.
  • the data provision interface may also be configured to create annual payroll tax statement, in particular for each employee.
  • the data provision interface may provide access to a social insurance notification module configured to transmit social insurance notifications, in particular to health insurance companies and/or to disburse payment of the social insurance contributions to the health insurance companies.
  • the data provision interface can also be configured to create an annual social insurance certificate for each employee.
  • the software interface module can be configured to retrieve the controlling data from the data provision interface without a direct data interface, in particular without accessing an API-interface. This can achieve the advantage that the software interface module can retrieve data that may be manually readable but may not be configured to be machine readable. Thus, the system can achieve a high compatibility to sources of controlling data independent of the data format and/or independent of the method by which data is provided.
  • the data processing module can be configured to generate at least one notification based on the processed controlling data.
  • the notification can comprise at least one of the following: indicator of a discrepancy of a data element within the controlling data in reference to an expected value of the data element; notification relating to a discrepancy in the received controlling data; deadline relating to the processing of the received controlling data, in particular that any uncorrected discrepancies will form the basis of the processed controlling data.
  • the indicator of a discrepancy of a data element within the controlling data in reference to an expected value of the data element can be generated when the controlling data is processed and checked against data elements pertaining to the present set of controlling data and data derived from previous controlling data and/or data available to the data processing module from other sources.
  • the data processing module can achieve a cross-platform or cross-interface comparability to increase data homogeneity, i.e., that each data set is based on the same ground truth facts. For example, that salary data, employment data, and/or employee data are consistent over all data processing instances, respectively all interfaces.
  • the indicator may also serve the function that a discrepancy can be indicated where an automatic correction cannot be performed, i.e., when the data source, for example the data provision interface, may not provide a function to correct the respective data element (i.e., read-only).
  • a notification relating to a discrepancy in the received controlling data can be generated.
  • the notification can relate to a single data element or a plurality of data elements.
  • the notification can indicate the discrepancy and a possible solution to resolve the discrepancy.
  • a solution can indicate the basis for the discrepancy, i.e., a data conflict.
  • the data processing module can generate a corrected data element to mitigate the discrepancy.
  • the corrected data element can be generated based on data available to the data processing module from a source outside of the data provision interface.
  • the data processing module can be configured to correct the discrepancy to yield an error-free dataset.
  • the level of automation can be customized such that the data processing module may provide a recommendation for the data correction or perform the data correction based on correction criteria, i.e., that the correction is based on data exceeding a confidence threshold, in other words, that the data on which the correction is performed can be considered correct.
  • the confidence can be increased by previous verification of the data on which the correction is based.
  • the data processing module can perform the correction automatically when a confidence threshold of the base data used for correction is exceeded.
  • the data processing module may generate a notification relating to the correction.
  • the recommendation for data correction can be transformed into a correction should the deadline be exceeded.
  • uncorrected data can be provided when the confidence threshold is not exceeded or automatic correction is not selected.
  • the data processing module can be configured to provide the processed controlling data to an initial data source of the controlling data.
  • the initial data source can be the data provision interface or a data receiving component associated with a system comprising the data provision interface.
  • Providing the processed controlling data can achieve the advantage that receiving, processing, and re-entering the controlling data can be automated. Preferably, a manual processing of the controlling data can be avoided.
  • the data processing module can be configured to generate a control action data based on the processed controlling data.
  • the control action data can comprise an instruction, wherein the instruction is generated by the data processing module and relates to the type of processing performed by the data processing module.
  • the control action data can comprise information relating to modification, verification and/or review of the controlling data.
  • Modification of the controlling data can relate to determining, assessing, and fixing or highlighting an error in received controlling data.
  • Verification can relate to comparing data elements extracted from the controlling data being compared to corresponding data elements available to the data processing module and checking that the data elements are identical, congruent with one another and/or in a logically correct relation to one another. These assessments can be performed by the data processing module.
  • Reviewing controlling data can relate to a consistency check of the controlling data, i.e., the data is related to itself to check consistency, in particular without reference to further data sources.
  • the type of controlling data can be checked against a template form, i.e., the data processing module can determine whether the controlling data adheres to a specific data type, data structure and/or whether relevant data entries are present, i.e., that a value is assigned to each element of the data structure.
  • the data processing module can provide feedback relating to the processing of the controlling data such that further data processing structures can evaluate the processing and/or such that a manual evaluation or supervision can be employed.
  • the control action data can further comprise an instruction relating to the further processing of the controlling data, wherein this instruction can indicate a processing status and which further processing steps may be performed.
  • the controlling data can be labeled as having a specific predetermined status relating to the processing such that either further processing can be performed or that the controlling data is final.
  • the controlling data can be labelled as being ready for transmission, ready to be input into the next controlling step or the respective negatives, which can prompt further processing.
  • finalized controlling data can be considered as equivalent to being checked by a payroll accountant, or being sufficient to be submitted to an authority, e.g., a tax authority.
  • the further processing of the controlling data can be performed by the data provision interface.
  • the control action data can further relate to actions to be performed in view of the controlling data and/or in response to the processed controlling data.
  • the data processing module can be configured to include executable instructions and/or parameters pertaining to an executable instruction.
  • the data processing module can mark specific functions as ready for execution after processing the controlling data. For example, duties for salary and wage accounting, reporting, and paying, contributions to social security and pension insurance institutions and the relevant tax office, and/or maintenance of employee master data and/or person master data can be triggered by the control action data.
  • master data can relate to a single, up-to date database considered to comprise the ground truth.
  • the software interface module can be configured to provide the processed controlling data and/or the control action data to the data provision interface. This achieves the advantage that the data provision interface can receive, process and perform relevant steps based on the processed controlling data and/or the control action data. Specifically, the data provision interface can be configured to interpret the control action data to execute a corresponding function.
  • the system can comprise an operation control module.
  • the operation control module can be configured to perform an action according to the control action data, in particular to initiate object transfers, in particular to a plurality of instances.
  • the operation control module can be a salary disbursement module configured to disburse a salary according to the processed controlling data, wherein the processed controlling data indicates an amount to be disbursed and/or comprises salary data indicating the basis for the salary to be disbursed, i.e., compensation (contractual, monthly, travel, bonus etc.).
  • the operation control module can also be configured to provide access to a resource according to the controlling data.
  • access to specific data can be controlled or access to physical objects can be controlled, i.e., access to salary disbursement parameters and/or the salary itself, i.e., in form of an electronic payment.
  • the software interface module can be configured to retrieve a plurality of instances of controlling data from a plurality of corresponding data provision interfaces. At least two of the plurality of corresponding data provision interfaces can differ in access conditions. Each data provision interface can be an autonomous instance which is separate from the other data provision interfaces.
  • the software interface module can receive controlling data from each data provision interface.
  • the data processing module can be configured to generate a combined database comprising the controlling data from each data provision interface.
  • the data processing module can be configured to process the controlling data across different data provision interface origins. This achieves the advantage that statistical data and insights can be acquired across a plurality of data sources.
  • a plurality of divisions can report controlling data which can be centralized at the data processing module to produce a combined overview of all data provision interfaces, respectively the divisions they represent.
  • a division can be a company, company module, technical instance, or device and/or a sub-group of devices.
  • Access conditions can be met by the data processing module to access the controlling data.
  • access conditions can relate to an application programming interface (API) between the data provision interface and the data processing module.
  • API application programming interface
  • the access conditions can relate to the data formatting of the controlling data, such that a specific format is provided by the data provision interface and that the data processing module is configured to process the provided data format.
  • the access conditions can relate to operating rules, i.e., the rules and relations in which framework the controlling data is generated and/or provided by the data provision interface.
  • operating rules can relate to technical rules, laws and/or regulations.
  • the operating rules can relate to the jurisdiction (district, authority, area etc.) of the origin of the controlling data.
  • the data provision interface can be configured to provide data elements in the controlling data which are specific to the access conditions. Thereto controlling data from different origins may comprise different data elements. The data elements may have a degree of similarity (e.g. employment data may comprise similar core data attributes, but taxation or official recordation may vary).
  • the data processing module can be configured to process the respective controlling data in such a way that data differences based on access conditions are removed, respectively converted to a common format. This can increase comparability of the different controlling data sets.
  • the access conditions can generally relate to aspects of data retrieval and may define access of the data processing module, preferably via the data provision interface, to the controlling data. For example, access can be limited to specific data elements, e.g., in agreement with data privacy regulations.
  • the data processing module can be configured to generate a set of expected values for the processed controlling data based on the retrieved controlling data and/or previously retrieved controlling data. This can achieve the advantage that the efficiency and/or accuracy of detecting false or modified values in the controlling data can be improved.
  • Expected values can be assigned a confidence interval such that a slight deviation from the expected value may only prompt a marking of the respective data or, with a substantial deviation (that may, for example, be implemented as a deviation exceeding a threshold value), a flagging as erroneous.
  • the confidence interval can decrease when an expected value was met in previous submissions of the controlling data.
  • the data processing module can be configured to compare the set of expected values against the processed controlling data and to generate corrected controlling data based on the processed controlling data and the outcome of the comparison. Comparing the processed controlling data with the set of expected values can achieve the advantage of detecting and subsequently being able to correct anomalies in the processed controlling data, such as values that are too high or too low, values that are missing or duplicated, or values that have different formats or units. For example, if the expected value for a sensor is a positive integer in Celsius, and the processed controlling data shows a negative decimal in Fahrenheit, the data processing module can flag this as an error and generate a corrected value based on the expected value or other sources of information. Alternatively, false deductions or taxations in payroll data can be detected.
  • the data comparison can also achieve the advantage of monitoring and optimizing the performance of the controlled system, such as a system that controls a technical system parameter. For example, if the expected value for the respective technical parameter is optimal according to a predetermined criterion, and the processed controlling data shows a value that is too high or too low, the data processing module can mark this as a deviation and generate a corrected value based on the expected value or other factors that affect the system. This can increase the efficiency of processing of payroll data evaluation and speed up disbursement. Also, the risk of false transactions can be reduced, which can cause fines or interest payments.
  • the data comparison can further be used to provide feedback and recommendations to operators or users of the controlled system, such as a payroll accounting system that controls payroll information and disbursement data.
  • the data comparison can be used to detect and correct errors in the financial data, such as incorrect calculations, misclassifications, or fraud. For example, if the expected value for the net income is based on the revenue and expenses, and the processed controlling data shows a value that is inconsistent with the accounting principles, the data processing module can flag this as an error and generate a corrected value based on the expected value or other financial records.
  • the data comparison can also be used to monitor and optimize the financial performance of the organization, such as a company, a non-profit, or a government. For example, if the expected value for the tax liability is based on the income and deductions, and the processed controlling data shows a value that is too high or too low, the data processing module can mark this as a deviation and generate a corrected value based on the expected value or other tax regulations.
  • the data comparison can further be used to provide feedback and recommendations to managers or employees of the organization, such as a system that controls the salary and wage management. For example, if the expected value for the salary or wage is based on the job description, performance, and market rate, and the processed controlling data shows a value that is inaccurate, the data processing module can generate a corrected value based on the expected value or other human resource policies and provide suggestions on how to improve the employee satisfaction and retention.
  • the corrected controlling data can comprise the processed controlling data modified to comprise expected values for the processed controlling data.
  • the data processing module can be configured to modify the processed controlling data to comprise expected values for the processed controlling data.
  • the corrected controlling data can further comprise a reference to base data on which the generation of the expected values is based. This can achieve the advantage that further review can determine the correctness and/or validity of the expected values, in particular based on the correctness or validity of the referenced base data.
  • the data processing module can be configured to provide the corrected controlling data according to a machine learning model.
  • the machine learning model can be trained to process the controlling data and modify data elements according to a highest likelihood for generating a ground truth correct result.
  • previous modifications, the validity of these corrections, data entry age, trust level of the base data used for the modification can be used to generate a likelihood value.
  • the data processing module can be configured to replace the original processed values with the expected values.
  • the data processing module can be configured to amend the processed controlling data to comprise the expected values.
  • the expected values may provide an indication with respect to the processed controlling data.
  • the expected values may not replace values in the processed controlling data, but may only flag values in the processed controlling data that may need review.
  • the data processing module can be configured to receive confirmation data relating to the corrected controlling data and to provide the corrected controlling data and/or processed controlling data, in particular uncorrected controlling data.
  • Confirmation can be the process of verifying the accuracy and validity of the corrected controlling data. Confirmation can be done by either correction, manual validation, or third-party system validation. Correction may comprise checking and/or fixing any errors or inconsistencies in the corrected controlling data. Manual validation may involve prompting the user or the data provision interface to confirm or reject the corrected controlling data. Third- party system validation may involve comparing the corrected controlling data with a trusted external source, e.g., a node module or any other reliable data source. Corrected controlling data that passes the confirmation process is considered verified and can be used for further processing or analysis. Uncorrected controlling data can be marked as processed and/or verified when the data processing module did not discover any errors, discrepancies or prompt for any correction to the received controlling data.
  • a trusted external source e.g., a node module or any other reliable data source.
  • the data processing module can be configured to generate confirmed controlling data based on the confirmation data, wherein the confirmed controlling data is confirmed for distribution of funds and/or official controlling record filing.
  • the confirmed controlling data is based on the corrected controlling data and in particular can comprise confirmation data.
  • the system can comprise a node module configured to provide user data, in particular a set of user data elements.
  • the data processing module can be configured to generate the at least one notification based on the user data, in particular at least one of the user data elements, and wherein the node module is configured to provide the at least one notification back to the user, in particular via the node module.
  • Input via the node module can achieve the advantage that data provided via the node module that specifically relates to a user can be considered a ground truth for processing the data.
  • the user can provide user data on which the user has data sovereignty.
  • user data such as address, bank account details, contact information, insurance data can be considered valid when provided by the user.
  • the data processing module may provide a prompt for confirmation should the received user data deviate from existing data, i.e., change of address etc.
  • the data processing module can be configured to generate the processed controlling data based on the user data.
  • controlling data received from the data provision interface is processed taking the user data into account.
  • data elements within the controlling data can be modified, in particular updated in relation to the user data.
  • the data processing module can realize a confluence of data, where accounting, contractual and/or salary data is provided to the data processing module by the data provision interface and user data is provided to the data processing module via the node module to allow for centralized processing of combined data received from the data provision interface and node module.
  • the system can comprise a control module configured to provide the confirmation data and/or to receive and process a notification.
  • the control module can operate independent from the data processing module, independent of the type of data provision interface.
  • the control module can be configured to perform data harvesting to receive controlling data from the data provision interface independent of the interface between data provision interface and control module, data structure and format of the provided data and/or language of the data elements.
  • Data harvesting can comprise transforming received controlling data into a universal data format used by the components of the system to achieve cross-platform and/or cross-jurisdiction compatibility.
  • the control module may comprise a communication interface configured to provide a communications link to the data processing module, wherein the control module is configured to provide base data.
  • Base data can relate to data elements that can be considered constants and/or may only be changed intermittently. Specifically, base data can be differentiated from controlling data that can be generated continuously, in particular automatically.
  • Base data can be a system identifier of a user.
  • base data can relate to a person and can comprise any information that can identify or be linked to a specific individual. This can include direct identifiers, such as name, identification number, or location data, as well as indirect identifiers, such as system identifiers, cookie IDs, company IDs, and/or factors related to the physical, mental, or social identity of a person.
  • Examples of data elements that only change intermittently are: date of birth, place of birth, nationality, marital status, educational level, medical history. These data elements may be stable and not change frequently, unless there are exceptional circumstances, such as a change of citizenship. Data elements that may change more frequently can be: sick days, compensation, work load, performance evaluation, contact information, health status. These data elements can be part of the controlling data which can be processed by the control module in reference to the base data.
  • the controlling data may relate to accounting data that can be based on a body of financial data that backs an accounting statement.
  • the controlling data specifically the processed controlling data, can be used to generate, verify, and/or audit the financial statements of a business or an organization.
  • the accounting data can comprise data from at least one of the following data categories:
  • Payment transaction data can relate to the records of money received or paid by a business for goods or services. They include invoices, receipts, bank statements, and cash registers.
  • Time tracking can relate to the process of measuring and recording the amount of time spent by employees on various tasks or projects. Time tracking can form the basis to calculate wages, bill clients, and monitor productivity. Time tracking can be done manually or automatically.
  • employment status can relate to the classification of workers according to their contractual relationship with the employer. It determines the rights and obligations of both parties, such as taxes, benefits, and labor laws. Employment status can be full-time, part-time, temporary, casual, contract, or self-employed.
  • bonuses can relate to additional payments made to employees, in particular as a reward for achieving predetermined goals or targets. Bonuses can be based on individual, team, or organizational performance. Bonus payments can be in the form of cash, stock options, or other benefits. Each aspect of a bonus can be indicated in the controlling data.
  • the data processing module can be configured to generate processed controlling data based on the base data. This achieves the advantage that the data processing module can check the controlling data against the base data.
  • the base data can form a basis for evaluating the controlling data.
  • the data processing module can be configured to determine data elements of the controlling data that conflict with the base data.
  • the data processing module can be configured to check the base data for logical consistency as part of validating the data. This can improve the quality, validity, and relevance of base data for integration into the controlling data and/or as a reference point for processing the controlling data.
  • the data processing module can be configured to verify that the base data provided or stored in the system is coherent with a set of predetermined expectation rules and/or constraints of the data domain. For example, the system may collect data on employees that may be employed at a specific company and the employment and/or accounting data may not be congruent with the base data, or when basing the accounting on the provided base data a different result may be obtained. Such checks can provide the advantage of allowing to identify and correct errors, outliers, missing values, and biases in the data.
  • the data processing module can be configured to check the base data for logical consistency, in particular by comparing the base data from different sources and checking that they are compatible and consistent with each other. For example, a system that integrates data from multiple databases may check that the same entity has the same attributes and values across different tables, or that foreign keys match primary keys of the referenced tables. Such checks can help ensure the integrity and reliability of the data for analysis and decision-making.
  • the data processing module can relate checking the base data and/or controlling data to a set of validation rules, which can be expressions or statements that define the conditions or criteria that the respective data must satisfy.
  • Validation rules can relate to declarative data integrity and/or procedure-based rules.
  • the data processing module can be configured to perform a format check on the base data and/or the controlling data, wherein the format check may comprise a test to verify whether the respective data follows a predetermined format and/or structure.
  • Format checks can provide the advantage of maintaining consistency across data and through time, as well as facilitate data processing and analysis. Format checks can be applied to different types of data, such as dates, numbers, text, codes, or files. Format checks can also be performed using various tools and techniques, such as regular expressions, parsers, validators, or converters.
  • the data processing module can be configured to process the base data to provide processed base data as an input to the data provision interface.
  • Processing the base data can comprise performing a validity check, in particular according to the above- mentioned validity rules.
  • processing the base data can comprise performing a data transformation to change the data format to be compatible with an input interface of the data provision interface.
  • the data provision interface can be configured to receive the processed base data as an input.
  • the data provision interface can be configured to generate processed controlling data based on the processed base data. This can achieve the advantage that when the data provision interface does not provide controlling data to the data processing module, processing of the controlling data, in particular in reference to the base data can be performed by the data provision interface. This may be of advantage, in particular, when access to the controlling data by means of the data provision interface may not be allowed, for example, for data privacy and/or security reasons.
  • the data processing module can be configured to provide processed controlling data to the control module. This achieves the advantage that processed controlling data can be made available by the data processing module, in particular a plurality of sets of controlling data can be provided by the data processing module such that the data processing module can serve as a data hub configured to centralize controlling data, providing a unified access to the controlling data, in particular a plurality of controlling data sets. Controlling data sets may have different origins, i.e., originate from different data provision interfaces.
  • the control module can comprise a database module which is configured to store processed controlling data and to provide access to the processed controlling data to the user.
  • the control module can be configured to limit access to the processed controlling data or a subset of the processed controlling data according to a set of data access conditions. Access, by a user, to the controlling data can be limited to a subset of controlling data pertaining to the user.
  • the data processing module and/or the control module can be configured to extract a subset of controlling data according to the data access conditions. Access to the processed controlling data can be independent of a status of the user, i.e., independent of an employment status. This can achieve the advantage that processed controlling data is available to the user even if an employment status changes.
  • the processed controlling data can be available independent of the status of the initial provider of the controlling data.
  • the status of the initial supplier can change, e.g., a legal entity can be transformed or cease to exist.
  • the control module and/or the data processing module can then still guarantee access to the processed controlling data.
  • the control module can comprise an interface module configured to provide access to data stored in the control module according to a set of access conditions.
  • the interface module can provide an electronic interface and/or an interface interoperable by a human.
  • the set of access conditions can define rights pertaining to the processed controlling data, i.e., read, transfer, modify, in particular to a subset of the processed controlling data.
  • the control module can be configured to define access conditions to the processed controlling data such that the respective business unit receives access to the processed controlling data, in particular the processed controlling data pertaining to the respective business unit.
  • the control module can be configured to control access of the business unit to the processed controlling data with respect to each data element, each type of data elements and/or jurisdictional data access requirements.
  • control module can provide access to data the business unit is legally authorized to access.
  • a rule set can be provided to the control module, wherein the control module is configured to transform the rule set into access conditions pertaining to the processed controlling data.
  • the interface module can be configured for a dedicated access pertaining to a single business unit.
  • the control module can be configured to receive base data pertaining to the single business unit via the interface module. This can achieve the advantage that a dedicated interface for data communication can be established such that cross communication via business units can be controlled, in particular, limited or prevented.
  • the control module can comprise a plurality of interface modules, wherein each interface module of the plurality of interface modules is limited to communication with a corresponding single business unit.
  • the control module can be configured to aggregate base data received from a plurality of interface modules according to a set of aggregation conditions.
  • the aggregation conditions can relate to controlling data relating to connected entities, the same employee, e.g., who is working for at least two entities (business units), aggregation of data relating to business divisions under an umbrella of a parent company, or a single ownership entity.
  • the control module can be configured to digitize processes in preparatory payroll accounting, wherein the data processing module can be configured to perform payroll accounting based on controlling data received from the control module.
  • the control module can be configured for generating and maintaining a personnel file, in particular for each person of a specific group of people, e.g., employees.
  • the control module can be configured to generate the personnel file by extracting personnel data from the controlling data and/or the base data.
  • the control module can be configured to provide feedback, in particular relating to the base data, via the node module.
  • the control module can be configured to provide documents, in particular documents based on the personnel file and/or the controlling data to each person of the specific group of people.
  • the documents can relate to an employment status and/or a salary status or actionable salary data, i.e., a pay slip.
  • the control module and/or the data processing module can be configured to perform processing of the controlling data in relation to an accounting time window, i.e., according to a specific fiscal unit.
  • the control module can be configured to provide an overview across the specific group of people, i.e., statistical information which can be extracted from the controlling data.
  • the control module can be configured to communicate with external modules, in particular modules relating to the processing of payments, invoicing and/or notifications relating to the controlling data.
  • the control module can be configured to instantly provide notifications when during processing of the controlling data a notification is triggered. Thereby, the respective notification recipient, which can also be a module can be informed as soon as possible.
  • the control module can be configured to trigger processing of the controlling data in the data processing module.
  • the trigger can be schedule based and/or event based. This can achieve the advantage that processing can be efficient and the processed controlling data is as recent as possible. Specifically, processing can be triggered when a data completeness threshold is reached or when specific outstanding data is received enabling a successful processing.
  • the control module can be configured to access controlling data from a set of instances, i.e., business modules such that the respective set of controlling data can be processed jointly.
  • the control module can be configured to track controlling data in reference to a particular individual, entity, or unit. Thereby, the control module can be configured to provide aggregated controlling data pertaining to the particular individual, entity, or unit.
  • the node module can be configured to provide base data.
  • the node module can provide access to the data processing module and/or control module. Specifically, the node module can request processed controlling data from the control module, respectively the data processing module.
  • the control module can be configured to process, in particular verify, the base data provided by the node module. This can achieve the advantage that the base data when verified can be used as a comparison database when processing the controlling data.
  • the control module can be configured to push data elements to the node module.
  • the node module can be configured to push data elements to the control module. This can achieve the advantage that the node module can provide data elements, in particular base data independent of a specific request for base data. Therefore, efficiency in processing the controlling data in reference to the base data can be increased as errors due to incorrect base data can be prevented. Thus, a complete loop of determining an error, prompting for updated base data, receiving updated base data, and reprocessing the controlling data can be avoided. Furthermore, pushing data to the node module increases the efficiency in providing processed controlling data.
  • the controlling data can be pushed to the node module as soon as it is marked for distribution, i.e., passes a validation.
  • the node module can be configured to control access of the control module to data elements of the node module, in particular grant or deny access to data available to the node module.
  • the node module can be configured to set and/or modify access conditions for data elements the control module can access.
  • the node module can be configured to provide a plurality of access condition sets, wherein each set comprises access conditions for a specific control module.
  • the node module can provide data to a plurality of control modules and data access can be tailored to each control module.
  • the node module can serve as a data hub, for example a datahub for all data relating to a single entity, and providing subsets of this data to control modules can be efficiently controlled.
  • the node module can comprise personal information and documents relating to an employee and the employee can control access to this data.
  • a control module can be associated with an employer and the employee can provide data via the node module to the employer.
  • the node module can be configured to control access to data elements of the node module for a plurality of control modules.
  • the node module can comprise a communication interface configured to provide a communications link to the control module.
  • the communication between the data processing module, control module and/or node module can be standardized by a common communications protocol, interface standard and/or communication format standard. This achieves interoperability between the components. Specifically, the data transfer and access according to predetermined conditions can be guaranteed by a standardized interface. Preferably, the interface can be configured to acknowledge when sending and/or receiving data.
  • the system can comprise standardized communication links between the data processing module, the control module and/or the node module.
  • the communication interface can be hardware and/or software component configured to enable data exchange between two or more modules.
  • the communication interface may include, for example, a network interface, a wireless transceiver, a serial port, a parallel port, a USB port, or any other suitable device or protocol.
  • the communication interface can be configured to provide a dedicated communication link. This can be a communication channel that is exclusively reserved for the data exchange between the modules.
  • the dedicated communication link may be physically and/or logically isolated from other communication channels. Isolation can be achieved by using encryption, authentication, and/or addressing schemes.
  • the processed controlling data may include, for example, commands, instructions, parameters, settings, feedback, or any other suitable information relating to the controlling data, base data and/or user data.
  • the dedicated communication link can improve performance and efficiency of the data exchange between the modules. This can in particular comprise measures like increasing the bandwidth and reducing the latency and jitter of the dedicated communication link.
  • Functionality and flexibility of the data exchange between the modules can be increased by enabling bidirectional and asynchronous communication of various types of data.
  • the data processing module can be configured to receive a plurality of sets of controlling data and the data processing module can be configured to determine differences between at least two sets of controlling data of the plurality of sets of controlling data.
  • the data processing module can be configured to select the controlling datasets with differences for comparison.
  • the data processing module can be configured to perform an elementwise comparison of the selected controlling datasets.
  • the selected controlling datasets may differ in dataset-type, wherein the dataset-type is defined by at least one of the following criteria: point of origin of the dataset, geographic or jurisdictional, data structure, data element composition, data readability;
  • the origin of the controlling dataset can relate to the source or method of collecting the data. Additionally, or alternatively, the origin of the dataset can relate to the initial state or format of the data before any manipulation or transformation.
  • a dataset can originate from a database table, a text file, an image, or a web page.
  • the origin of a dataset can also refer to the location or authority that provides the data for access or use.
  • the dataset can originate from a local file system, a remote server, a cloud service, or a web API.
  • the data element composition can relate to the process of defining the structure and attributes of a data element, such as its name, description, data type, domain, format, length, and validation rules.
  • Data element composition can be part of data element specification, that can form the basis for quality and consistency of data elements across different data sources and applications.
  • Data element composition can also relate to combining multiple data elements into a single dataset.
  • Data readability can correspond to a degree to which data can be easily understood by humans or machines, depending on the format and structure of the data.
  • Data readability can be classified into three types: Machine readable data can be data that is encoded that can be processed automatically by a computer system, in particular without human intervention.
  • Human readable data can be data that is encoded in a natural language that can be read by humans without requiring special tools or software.
  • Hybrid readable data can be data that is encoded in a way that can be read by both humans and machines.
  • the data can comprise a markup or metadata to the human readable data.
  • Hybrid readable data can increase semantic meaning and accessibility of the data.
  • System (100) for automatic processing of controlling data comprising a data processing module (101), configured to retrieve controlling data, to process the controlling data to generate processed controlling data.
  • the data processing module is configured to provide the processed controlling data to an access module (103) and/ or to a node module (107).
  • the data processing module comprises a software interface module (102) configured to connect to a data provision interface (104) to retrieve the controlling data.
  • system comprises the data provision interface (DPI), and/or wherein the DPI is configured to provide controlling data.
  • DPI data provision interface
  • the data processing module is configured to generate at least one notification based on the processed controlling data.
  • the notification comprises at least one of the following: indicator of a discrepancy of a data element within the controlling data in reference to an expected value of the data element; notification relating to a discrepancy in the received controlling data; deadline relating to the processing of the received controlling data, in particular that any uncorrected discrepancies will form the basis of the processed controlling data.
  • System comprising an operation control module (105), wherein the operation control module is configured to perform an action according to the control action data, in particular to initiate object transfers, in particular to a plurality of instances.
  • the software interface module (102) is configured to retrieve a plurality of instances of controlling data from a plurality of corresponding data provision interfaces (104-1 - 104-4), wherein at least two of the plurality of corresponding data provision interfaces differ in access conditions (106-1, 106-2).
  • the data processing module (101) is configured to generate a set of expected values for the processed controlling data based on the retrieved controlling data and/or previously retrieved controlling data.
  • node module is configured to provide user data comprising a set of user data elements.
  • System comprising a control module (108), configured to provide confirmation data and/or to receive and process a notification.
  • control module (108) comprises a communication interface (109) configured to provide a communications link to the data processing module, wherein the control module is configured to provide base data.
  • control module (108) comprises an interface module (110) configured to provide access to data stored in the control module according to set of access conditions.
  • control module comprises a plurality of interface modules (110-1 - 110-3), wherein each interface module of the plurality of interface modules is limited to communication with a corresponding single business unit (111-1 - 111- 3).
  • control module is configured to aggregate base data received from a plurality of interface modules according to a set of aggregation conditions.
  • control module (108) is configured to process, in particular verify, the base data provided by the node module (107).
  • control module is configured to push data elements to the node module, and/or wherein the node module is configured to push data elements to the control module.
  • the node module comprises a communication interface (112) configured to provide a communications link to the data processing module, in particular a communication interface of the data processing module, and/or to the control module, in particular to a communication interface of the control module, and/or wherein the communication between the data processing module, control module and/or node module is standardized by a common communications protocol, interface standard and/or communication format standard.
  • control module comprises a further communication module configured to connect with the communication module of the node module.
  • the data processing module is configured to receive a plurality of sets of controlling data and wherein the data processing module is configured to determine differences between at least two sets of controlling data of the plurality of sets of controlling data.
  • the node module comprises a communication interface (112) configured to provide a communications link to any one of the plurality of control modules, in particular to a communication interface of any one of the plurality of control modules.
  • Method for automatic processing of controlling data comprising the steps of retrieving controlling data, processing the controlling data to generate processed controlling data.
  • Method according to the preceding embodiment comprising providing the processed controlling data to an access module.
  • Method according to the preceding embodiment comprising the step of connecting to a data provision interface to retrieve the controlling data.
  • Method according to any of the preceding method embodiments comprising the step of retrieving the controlling data from a controlling data provision interface without a direct data interface, in particular without accessing an API-interface.
  • Method according to any of the preceding method embodiments comprising the step of providing the processed controlling data to an initial data source of the controlling data.
  • Method according to any of the preceding method embodiments comprising the step of generating a control action data based on the processed controlling data.
  • Method according to any of the preceding method embodiments comprising the step of performing an action according to the control action data, in particular to initiate object transfers, in particular to a plurality of instances.
  • Method according to any of the preceding method embodiments comprising the step of retrieving a plurality of instances of controlling data from a plurality of corresponding data provision interfaces, wherein at least two of the plurality of corresponding data provision interfaces differ in access conditions.
  • Method according to any of the preceding method embodiments comprising the step of generating a set of expected values for the processed controlling data based on the retrieved controlling data and/or previously retrieved controlling data.
  • Method according to any of the preceding method embodiments comprising the steps of receiving confirmation data relating to the corrected controlling data and providing the corrected controlling data and/or processed controlling data, in particular uncorrected processed controlling data.
  • Method according to any of the preceding method embodiments comprising the step of generating confirmed corrected controlling data based on the confirmation data, wherein the confirmed corrected controlling data is confirmed for distribution of funds and/or official controlling record filing.
  • Method according to any of the preceding method embodiments with features of M5, comprising the steps of receiving user data, in particular a set of user data elements, and generating the at least one notification based on the user data, in particular for at least one of the user data elements, and wherein the node module is configured to provide the at least one notification back to the user, in particular via the node module.
  • M16 Method according to any of the preceding method embodiments with features of M15, comprising the step of generating the processed controlling data based on the user data.
  • M17 Method according to any of the preceding method embodiments with features of M5, comprising the step of providing confirmation data and/or receiving and processing a notification.
  • Method according to any of the preceding method embodiments comprising the step of processing the base data to provide processed base data as an input to a data provision interface
  • Method according to any of the preceding method embodiments comprising the step of generating processed controlling data based on the processed base data.
  • Method according to any of the preceding method embodiments comprising the step of storing processed controlling data and providing access to the processed controlling data to the user.
  • Method according to any of the preceding method embodiments comprising the step of providing access to the control module according to a set of access conditions.
  • Method according to any of the preceding method embodiments comprising the step of receiving base data pertaining to the single business unit via the interface module.
  • Method according to any of the preceding method embodiments comprising the step of processing, in particular verifying the base data provided by the node module.
  • Method according to any of the preceding method embodiments with features of M29 comprising the step of selecting the controlling datasets with differences for comparison performing an elementwise comparison of the selected controlling datasets.
  • a computer program product comprising instructions, which, when executed by a system and any of its components according to any of the system embodiments, cause the system and its components to perform the steps, for which the system and/or any of its components are configured.
  • a computer program product comprising instructions, which, when executed by the system and any of its components according to any of the system embodiments, cause the system and its respective components to perform the steps of the method according to any of the method embodiments, which method steps are performed by the system and/or the respective components according to the method.
  • FIG. 1 schematically depicts a drawing of an embodiment of a system for automated processing of controlling data according to the invention
  • Fig. 2 schematically depicts a drawing of an embodiment of a system for automatic processing of controlling data according to the invention.
  • Fig. 1 is a schematic drawing of an embodiment of a control system according to the invention.
  • a first component can be the data processing module 101 which can be configured as a virtual payroll accountant that supports a payroll accounting process and may replace manual work partially or completely.
  • the data processing module 101 may not replace a payroll accounting module but may operate the payroll software, i.e., process its output and provide required input.
  • the data processing module 101 can be configured to execute browserbased in the cloud and can be connected to a payroll accounting workspace via an interface program, i.e., a client software, which can be installed locally on a specific device.
  • the data processing module 101 can provide the following features: It can be independent of the payroll software, the country and the language used.
  • the data processing module can use multiple payroll programs simultaneously.
  • an international payroll office can centrally manage and control all countries with the different payroll programs in the control module.
  • the data processing module can further comprise a document management system, conduct a digital operational audit, perform a data check.
  • This data check can comprise controlling of the created documents for completeness, errors, etc. with subsequent workflows for certain findings and presentation by using easily perceivable indicators (i.e., colored warnings). This check can be performed across companies, incorporate a file archive, communicate with customers, do invoicing, manage appointments per customer and globally.
  • a second component can be the control module 108.
  • the control module 108 can be configured for business units and achieve the effect of increased digitization of processes in the preparatory payroll accounting.
  • the control module 108 can comprise the following features: It is independent of the payroll software, the country and the language used, and can also be independent of the data processing module 101;
  • the control module 108 can comprise the following functions: managing digital personnel files, communicating with employees, providing documents to employees, performing payroll control, providing time tracking, capturing items for the current payroll accounting, performing workflow-supported items (for example, pay out bonus etc.), providing an overview of all items in a predetermined timespan, e.g., within the current month, use a document management system, managing employees, integrating further modules (for example, payment transactions, invoicing, instant notifications), connecting to existing third-party software, prompting the data processing module to automatically start workflows.
  • the connection between the data processing module 101 and the control module 108 can be as follows: they can communicate with each other; the control module 108 may capture items for the current payroll accounting; the controlling data can be transmitted to the data processing module 101; each module can initiate a communication (for example, for inquiries); the controlling data can be transferred automatically to the payroll software; after processing the controlling data, e.g., generating processed controlling data relating to the accounting, documentation pertaining to the processed controlling data can be generated and made available to the control module; automated messages can be sent to the user (for example, payroll accounting reminders and/or deadlines).
  • the node module 107 can provide a digital solution for users, e.g., employees, to store personal data, information, and communicate with their employers, i.e., via the data processing module and/or control module.
  • the node module 107 can be provided and interacted with independent of the payroll software of the employer, the country, and/or the language used by the employer. It can be independent of the control module, and the node module can provide a walled-off data space providing data sovereignty to the user within that data space.
  • the user is enabled to store personal documents and data, exchange documents and data with the employer, e.g., via the control module 108, and transfer data and documents to a different employer, for example, when applying for a new job or starting a new employment.
  • the node module 107 can be configured to be expandable such that additional modules can be integrated, e.g., additional storage space and/or connection to external software modules.
  • the node module 107 can be configured to control the data transfer, specifically the documents to be released to the new employer.
  • the node module 107 can be connected to the control module 108, which can represent a digital solution for employers to manage payroll processes and communication with their employees.
  • the control module 108 can be configured to provide an invitation function, wherein an invite to a user, e.g., a new employee, can be provided, and wherein the invite can comprise a prompt to collect data via a node module 107.
  • new controlling data from the new employer and/or existing data by the user can be provided, in particular to the node module 107.
  • the controlling data can be collected at the node module 107.
  • the employer can also receive and verify changes in personal data from the employee received from the node module 107 to the control module 108.
  • the updated controlling data can be provided to the data processing module 101 for processing.
  • An example of processing controlling data, in particular for payroll accounting can be:
  • the user can provide controlling data, e.g., a new account number, via the node module 107.
  • the controlling data can be transmitted to the control module 108 and verified by the control module 108, e.g., by performing a validity check.
  • the changes can be recorded as an item by the control module 108 and forwarded to the data processing module 101 after completion of the verification.
  • the data processing module 101 can provide the changes to an external payroll module, preferably initiating a trial controlling data, e.g., payroll, processing, checking the trial controlling data processing, and performing the processing of controlling data independently.
  • a trial controlling data e.g., payroll, processing, checking the trial controlling data processing, and performing the processing of controlling data independently.
  • the data and documents can be transmitted to the control module 108 and the node module 107.
  • Notifications can be sent according to the processed controlling data, in particular relating to deficiencies in the data.
  • the data processing module 101 can automatically initiate providing a notification, e.g., an invoice.
  • control modules 108a, 108b can be as follows:
  • a first relation between a first control module 108a and the node module 107 for periodic data transfer is terminated.
  • an employment relationship of the employee and a first employer 1 ends.
  • connection between the first control module 108a and the node module 107 can be disconnected.
  • the node module 107 can be configured to provide controlling data directly to a second control module 108b.
  • the second control module 108b can be configured to receive the controlling data via the node module 107 and processing of the controlling data can be initiated between the node module 107 and the second control module 108b.
  • Fig. 2 is a schematic drawing of an embodiment of a control system according to the invention.
  • the system 100 can comprise a data processing module 101, a node module 107.
  • the system 100 can comprise a control module 108, a data provision interface 104, an access module 103, and an operation control module 105.
  • the data processing module 101 can be configured to retrieve controlling data from the data provision interface 104 or from another source, and to generate processed controlling data based on the controlling data and user data provided by the node module 107.
  • the user data can relate to a user identifying characteristic, such as a biometric feature, a personal preference, or a behavioral pattern.
  • the processed controlling data may be used to control or influence the behavior of the node module 107 or the operation control module 105.
  • the node module 107 can be configured to provide user data to the data processing module 101, and to receive processed controlling data from the data processing module 101.
  • the node module 107 may also provide base data relating to a system identifier of a user, such as a username, a password, or a token.
  • the node module 107 may comprise, for example, a sensor, an actuator, a display device, or an input device.
  • the control module 108 can be configured to receive and process a notification from the data processing module 101.
  • the notification may be based on the processed controlling data and/or the user data, and may indicate, for example, a status, an event, an alert, or an error.
  • the control module 108 may also verify the base data provided by the node module 107 and/or the operation control module 105.
  • the data provision interface 104 can be configured to provide controlling data to the data processing module 101, and to receive processed controlling data from the data processing module 101.
  • the controlling data may relate to, for example, a rule, a policy, a regulation, or a requirement.
  • the data provision interface 104 may include, for example, a database, a web service, or an application program interface.
  • control action data may relate to data that can comprise information relating to modification, verification and/or review of the controlling data.
  • the control action data may relate to instructions for providing access to a resource according to the controlling data.
  • the resource may include, for example, a file, a folder, a network, or a device.
  • the system 100 may further comprises a communication interface 112 in the node module 107 and another communication interface 113 in the data processing module 101.
  • a communication link 114-1 between the communication interfaces is provided to transmit processed controlling data and/or user data between the data processing module 101 and the node module 107.
  • the communication link 114-1 is dedicated for data exchange between a first module and the second module, and may be physically isolated, logically isolated, or have a higher priority than other communication channels.
  • the system 100 may comprise more than one node module 107, more than one control module 108, more than one operation control module 105, or more than one data provision interface 104.
  • the system 100 comprises four instances of the data provision interface: 104-1, 104-2, 104-3, and 104-4.
  • An instance of the data provision interface may have access conditions 106-1, respectively 106-2. The access conditions may determine the access rights and privileges of the business unit to the corresponding instance of the data provision interface.
  • the system 100 may comprise more than one communication link 114 between different modules. For example, as shown in FIG. 2, there are three communication links: 114-3 between the node module 107 and the control module 108, particularly a communication interface 109 thereof, 114-2 between the control module 108, particularly a communication interface 109 thereof, and the data processing module 101, and 114-1 between the data processing module 101 and the node module 107.
  • the data processing module 101 may comprise a software interface module 102 that is configured to connect to one or more instances of the data provision interface 104 to retrieve the controlling data.
  • the software interface module 102 may be configured to retrieve a plurality of instances of controlling data from a plurality of corresponding instances of the data provision interface, wherein at least two of the plurality of corresponding instances of the data provision interface differ in access conditions.
  • the data processing module 101 may be configured to generate a set of expected values for the processed controlling data based on the retrieved controlling data and/or previously retrieved controlling data, and to compare the set of expected values against the processed controlling data and generate corrected controlling data based on the processed controlling data and the outcome of the comparison.
  • the corrected controlling data may be provided to the node module 107, the control module 108, the operation control module 105, or the data provision interface 104.
  • the software interface module 102 may be configured to retrieve the controlling data from the data provision interface without a direct data interface, such as by using web scraping, data mining, or natural language processing techniques. Alternatively, the software interface module 102 may be configured to access an API-interface or another suitable interface provided by the data provision interface.
  • the data processing module 101 may be configured to generate at least one notification based on the processed controlling data.
  • the notification may be provided to the node module 107, the control module 108, or another suitable module.
  • the control module 108 can be configured to provide confirmation data and/or receive and process notifications from the data processing module 101.
  • the confirmation data may indicate that the base data and/or accounting data provided by the node module 107 or another suitable module are valid or invalid.
  • the notifications may indicate that an action has been performed or not performed by the operation control module 105 or another suitable module.
  • the data processing module 101 may be configured to generate processed controlling data based on the controlling data, the user data, and/or the base data.
  • the data processing module 101 may also be configured to process the base data and/or accounting data to provide processed base data and/or processed accounting data as an input to the data provision interface 104 or another suitable module.
  • the processed base data and/or processed accounting data may include, for example, aggregated, filtered, sorted, or transformed data.
  • step (X) preceding step (Z) encompasses the situation that step (X) is performed directly before step (Z), but also the situation that (X) is performed before one or more steps (Yl), ..., followed by step (Z).
  • step (Z) encompasses the situation that step (X) is performed directly before step (Z), but also the situation that (X) is performed before one or more steps (Yl), ..., followed by step (Z).

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Abstract

La présente invention concerne un système (100) pour le traitement automatique de données de commande, comprenant un module de traitement de données (101), configuré pour extraire des données de commande, un module de nœud (107) configuré pour fournir des données d'utilisateur relatives à une caractéristique d'identification d'utilisateur au module de traitement de données, dans lequel le module de traitement de données (101) est configuré pour générer des données de commande traitées sur la base des données de commande et des données d'utilisateur, dans lequel le module de nœud comprend une interface de communication (112) et le module de traitement de données comprend (101) une autre interface de communication (113), et dans lequel une liaison de communication (114-1) entre les interfaces de communication est prévue pour transmettre des données de commande traitées et/ou des données d'utilisateur entre le module de traitement de données (101) et le module de nœud (107). L'invention concerne en outre un procédé de traitement automatique de commande de données, comprenant les étapes d'extraction de données de commande, de fourniture de données d'utilisateur relatives à une caractéristique d'identification d'utilisateur; et générer des données de commande traitées sur la base des données de commande et des données d'utilisateur.
PCT/EP2025/054171 2024-02-20 2025-02-17 Système et procédé de traitement de données de commande automatisé Pending WO2025176597A1 (fr)

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7941351B1 (en) * 2006-11-03 2011-05-10 Intuit Inc. Employee-based payroll
WO2016011287A1 (fr) * 2014-07-17 2016-01-21 Square, Inc. Gestion d'informations de liste de salariés

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7941351B1 (en) * 2006-11-03 2011-05-10 Intuit Inc. Employee-based payroll
WO2016011287A1 (fr) * 2014-07-17 2016-01-21 Square, Inc. Gestion d'informations de liste de salariés

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