250 results about "Financial data processing" patented technology

The invention relates to the technical field of financial data processing, in particular to a multi-source heterogeneous fund data processing method and system, and the method comprises the steps: recording source information through building a data source registry, and marking a unique identifier for data; performing differential analysis on the fund data in different formats to generate standardized column type storage data; traversing column type storage data to extract statistical characteristics, performing field classification through metadata analysis and financial dictionary matching, analyzing business connotations of fields difficult to classify in combination with a localized large language model, and mapping the business connotations to a header fusion knowledge graph; generating a mapping rule from the source field to the enterprise-level data model by applying a rule engine template on the basis of field classification and semantic recognition results; converting the data structure according to the mapping rule and executing standardization processing; the quality is further optimized through data cleaning; and finally, the data are verified, standardized fund data supporting data traceability are output, and the strict requirements of financial supervision application are met.

The invention discloses a personal credit score real-time early warning system based on behavior chain mining, which relates to the technical field of financial data processing and comprises a data acquisition module, a behavior chain atlas module, a behavior mining module, a collaborative modeling module, a score fusion module, an early warning interpretation module and a safety optimization module. All the modules interact through an end-to-end data flow and a real-time message mechanism, and dynamic evaluation and intelligent early warning of personal credit risks are achieved. According to the method, diversified normal and high-risk virtual behavior chains are automatically simulated and generated through a generative AI technology, a federated learning mechanism is combined, multiple mechanisms are enabled to jointly confront novel fraud and complex risk behaviors, original data does not need to be transmitted during model training, privacy security and model generalization ability are greatly improved, unknown risk behaviors are virtualized through AI, and the method is high in practicability and easy to popularize. The capability of identifying unprecedented risks is improved, and the problems of data islands and privacy leakage are avoided through federal learning.

The invention discloses a financial data generation method and system based on a rule configuration engine, and the method comprises the steps: converting a business demand into structured rule description through a semantic analysis engine according to the financial business demand, dynamically configuring a financial data processing rule through a context-aware rule template library, and generating financial data according to the financial data processing rule. Generating an executable rule configuration set; extracting related data from a plurality of heterogeneous financial data sources according to the rule configuration set, and mapping features of different data sources to a unified high-dimensional vector space by adopting a multi-source data fusion algorithm to generate a fused financial feature matrix; and inputting the fused financial feature matrix into a rule configuration engine, adopting a rule execution optimization model, dynamically adjusting a rule execution sequence and parameters, generating financial data, and performing noise addition processing on the financial data to ensure data privacy security. According to the embodiment of the invention, the financial data can be flexibly and efficiently generated, and the safety and efficiency of overall data processing are improved.

The invention provides a multi-source financial data intelligent classification and automatic accounting optimization processing method and system, and relates to the technical field of enterprise financial management, and the method comprises the steps: carrying out the textualized preprocessing of multi-source enterprise financial data, constructing a transaction scene map, carrying out the scene clustering, forming a transaction classification rule set, and carrying out the classification of transactions, according to the method, labels and accounting subject codes are matched for conventional transaction data, a transaction traceability graph is constructed to analyze the integrity of a transaction link, and an accounting voucher is generated to realize automatic accounting, so that the accuracy and efficiency of financial data processing are improved, the manual intervention cost is reduced, and the traceability of financial data is enhanced.

The invention relates to the technical field of data processing, in particular to an enterprise financial data processing system and method. The method comprises the following steps: obtaining multi-source enterprise financial data, and carrying out dynamic data type identification and structure transcoding to obtain preprocessed enterprise financial data; performing graph embedded structure conversion on the preprocessed enterprise financial data to obtain enterprise financial semantic fusion data; constructing a financial data auditing path according to the enterprise financial semantic fusion data; tense version mapping is carried out on the data format fluctuation characteristics in the financial data auditing path to record the structure change process of various vouchers and asset and liability data in the financial data auditing path, hierarchical file compression is carried out on a tense version mapping result, and a structured financial data auditing path is obtained; and time sequence causal link construction is carried out according to the structured financial data auditing path, and a financial cognitive inference model is obtained. The auditing efficiency and the risk monitoring capability can be improved.

The invention relates to the technical field of financial data processing, in particular to a financial index real-time analysis method and system, and the method comprises the following steps: extracting financial fields, constructing a mapping chain, matching an archiving path, judging whether to switch, analyzing historical cycle data, establishing a trend chain, merging a state chain, and generating a real-time analysis result. According to the method, through structural acquisition of income, expenditure, asset and liability fields in the financial statement and deep-level analysis of type distribution, sequence density and crossing frequency, construction of the field chain composition density is realized, and data structure characteristics can be accurately mastered at the initial stage of index identification; and the matching deviation risk caused by heterogeneous field distribution is effectively avoided. On the basis, clustering comparison between a field chain structure and archiving path nodes is adopted, an error graph is constructed, fine measurement of path node similarity is achieved, and the reasonability of archiving path selection can be improved through a path error minimum matching mechanism.

The invention discloses a financial data processing method and system based on machine learning, and a storage medium. The method comprises the following steps: encrypting customer credit data of a financial institution through Paillier homomorphic encryption and extracting a risk feature vector; performing secret sharing segmentation on the local gradient parameters and then safely aggregating the local gradient parameters into global gradient parameters through a BGW protocol; on the basis of the privacy level, global gradient parameter differential privacy noise is injected and subjected to federal training to obtain a cross-institution credit evaluation result; calculating risk characteristics and evaluation results through homomorphic encryption to obtain an encrypted credit score, and performing secure multi-party calculation and decryption to generate a customer credit report; and block chain supervision compliance verification is carried out to generate an audit record, and a privacy budget optimization scheme is dynamically adjusted according to the business emergency degree. The technical problems that in an existing financial data processing method, information is incomplete due to data islands, data leakage risks are caused by insufficient privacy protection mechanisms, and an effective supervision compliance verification mechanism is lacked are solved.

The invention belongs to the field of big data, and relates to a financial data processing method, which comprises the following steps: acquiring enterprise end financial data and government end financial data of a target project; performing data integration on the enterprise end financial data and the government end financial data by adopting a preset data warehouse to obtain a comprehensive financial data set; receiving a report request of a user, determining an accounting criterion based on the report request, and loading accounting processing logic corresponding to the accounting criterion from a pre-established accounting module; and based on the accounting processing logic, performing financial analysis processing on the comprehensive financial data set, and generating a financial statement corresponding to the target project. The invention further provides a device, equipment and a medium. The financial data processing efficiency can be improved.

The invention discloses an automatic financial data collection system based on a web crawler technology. The system comprises an intelligent crawler collection module, a financial data processing module and a data collection module. The intelligent crawler acquisition module comprises a dynamic scheduling crawler cluster unit, a multi-format capture engine and a metadata marking unit; the dynamic scheduling crawler cluster configures a routing algorithm based on reinforcement learning, and dynamically adjusts an IP proxy strategy through an anti-crawling feature matrix; the multi-format capture engine is integrated with a PDF / HTML / JSON heterogeneous data analysis channel; the metadata marking unit generates a data source label by adopting multi-layer coding conversion; and the financial data processing module comprises a cross-format analyzer, a data cleaning pipeline and a structured storage unit. According to the scheme, through innovative designs such as multi-modal data analysis, self-adaptive anti-creeping confrontation, dynamic resource scheduling and intelligent association analysis, the core problems of low heterogeneous data integration efficiency, weak dynamic anti-creeping confrontation capability and the like are solved.

The invention discloses a cross-institution financial data federated learning modeling system and a privacy compliance verification method, and relates to the technical field of financial data processing, the system comprises a federated aggregation module used for a server to align financial time sequence characteristics of each institution through a timestamp hash alignment strategy, and a privacy verification module used for verifying the privacy compliance of each institution; aggregating the aligned financial time sequence characteristics by using a federated time convolutional network, and generating time sequence model parameters for capturing cross-mechanism global time sequence dependence; the federation reasoning module is used for generating a minimum spanning tree representation of a global enterprise association relationship based on a security multi-party computing strategy by the server side on the basis of a local sub-graph of the enterprise association relationship constructed by each institution client side; the server performs cross-mechanism graph reasoning by using a federated graph attention network and an aggregation graph embedding vector and combining minimum spanning tree representation, and constructs graph model parameters for identifying enterprise associated risks; and the model joint training module is used for the server to fuse the time sequence model parameters and the graph model parameters so as to determine global model parameters.

The invention relates to the technical field of financial data processing, in particular to a financial data automatic extraction and articulation processing system and method, and the system comprises a financial data obtaining module which is used for obtaining financial image data, audio data and bank API data; and the financial data processing module adopts OCR (Optical Character Recognition), Whisper voice conversion and bank API (Application Program Interface) paging query technologies to carry out standardization processing on the data and extract financial data through an anomaly detection mechanism. And the financial data sorting module classifies and stores the data to different financial databases by adopting a dynamic routing and four-way distribution strategy based on format verification and priority marks. And the financial data articulation module performs verification and difference processing on the data through a cross-library articulation rule to generate a financial analysis report. And the financial data display module monitors the financial analysis result by adopting a data snapshot and rollback mechanism, so that automatic extraction, articulation and visualization of the financial data are realized, and the accuracy and compliance of the financial data are improved.

The invention provides a multi-source financial data intelligent classification and automatic accounting optimization processing method and system, and relates to the technical field of enterprise financial management, and the method comprises the steps: carrying out the textualized preprocessing of multi-source enterprise financial data, constructing a transaction scene map, carrying out the scene clustering, forming a transaction classification rule set, and carrying out the classification of transactions, according to the method, labels and accounting subject codes are matched for conventional transaction data, a transaction traceability graph is constructed to analyze the integrity of a transaction link, and an accounting voucher is generated to realize automatic accounting, so that the accuracy and efficiency of financial data processing are improved, the manual intervention cost is reduced, and the traceability of financial data is enhanced.

The invention belongs to the technical field of financial data processing, and discloses an intelligent financial bookkeeping robot system and method based on the RPA technology, and the system comprises a user interaction unit which provides a system interaction interface for financial staff; the business processing unit comprises a task management module, a data acquisition module, a data processing module, a data verification module, an accounting voucher generation module and an accounting processing module; the RPA execution unit simulates human operation through an RPA worker and executes a financial accounting task; the data storage unit is used for storing data by using a relational database; the report generation unit is used for generating financial statements and checking and submitting the statements; and the exception handling unit is used for detecting various exceptions in real time. According to the invention, financial data, accounting voucher generation and accounting processing are automatically acquired according to preset task configuration through the RPA tool, the task management module can schedule tasks according to preset rules or manual instructions, the task execution sequence can be reasonably arranged, and parallel processing of the tasks is realized.

The invention relates to the technical field of financial data processing, in particular to a financial data security storage method and system, and the method comprises the steps: obtaining salary data of all employees in at least one year of a current month in financial data; calculating the overall salary core degree of each employee according to the salary data; according to the total salaries of the employees in the salary data, sorting all the employees in the current month according to a preset sorting rule to obtain an employee sorting result; calculating the salary similarity between every two employees in each month based on the salary data, the salary overall core degree and the employee sorting result; according to the salary similarity, carrying out clustering processing on the salary data of all employees in each month to obtain a clustering result; and according to a clustering result, carrying out partitioned secure storage on salary data of each month in the financial data. According to the scheme provided by the invention, the distance between the core employee and the surrounding data points can be shortened, the clustering precision is improved, and the storage reliability and safety of the financial data are improved.

The invention discloses a financial data processing method which is applied to processing financial data in the field of finance. In the method, a computational graph comprising nodes and edges is adopted to represent a processing flow of financial data, and the nodes in the computational graph can indicate input financial data, an algorithm model function for processing the financial data and an operation rule function. When the computational graph is executed, a series of processing processes of the financial data can be realized by calling the data or functions indicated by the nodes in sequence, so that the data, an algorithm model and an operation rule are visually combined together, and the interpretability of the financial data processing flow is improved. Moreover, when the financial data processing flow is visually presented on the basis of the computational graph, the financial data processing flow can be changed only by adjusting nodes in the computational graph, and the financial data processing flow can be analyzed and adjusted conveniently.

The invention provides an account reimbursement method and device based on an OCR and a Transform decoder and electronic equipment, and belongs to the technical field of financial data processing. The method comprises the following steps: scanning a bill to obtain a bill image, preprocessing the bill image, performing text recognition on the preprocessed bill image by adopting OCR (Optical Character Recognition), and outputting a text recognition result; classifying the text recognition results based on a preset financial business rule, generating financial data information and storing the financial data information; converting the financial data information into an input format corresponding to a Transform decoder, inputting the financial data information into the Transform decoder, and outputting structured reimbursement information; performing compliance verification on the structured reimbursement information based on financial business rules; and filling the verified structured reimbursement information into a reimbursement bill template in the financial reimbursement system, and generating a reimbursement bill. The full-process automatic processing from bill scanning to bill generation can be realized, the reimbursement efficiency and accuracy are obviously improved, and meanwhile, the requirement of manual intervention is reduced.

The invention discloses a financial data anomaly analysis system and method based on artificial intelligence, and relates to the technical field of financial data. The method comprises the following steps: collecting and cleaning various financial data in real time through docking with an enterprise financial system; processing data extraction features; analyzing the feature data by using the trained deep neural network model, marking abnormal data, and setting a reasonable index threshold to further confirm an abnormal condition; deeply analyzing the financial items marked as abnormal by using an optimization algorithm, and obtaining financial optimization target data to generate specific adjustment suggestions; and financial data are collected again for monitoring again and abnormal type analysis, and a project set is constructed to calculate an association index to find potential problems in the business process, and an early warning report is generated. According to the method, automation and intelligentization of financial data analysis are realized, the detection precision and efficiency are improved, optimization suggestions with strong pertinence are provided, and enterprises are helped to deal with financial risks in time.

The present invention provides an intelligent financial data processing and analysis system, which belongs to the technical field of financial data processing and analysis. The intelligent financial data processing and analysis system includes a data acquisition module, which can accurately collect and verify various types of financial data through multiple interfaces; a data processing module, which uses algorithms to clean, classify, and integrate data to establish logical associations; an analysis module, which performs multi-dimensional analysis, such as financial ratio analysis and cost structure analysis, and generates intuitive charts and reports; an early warning module, which monitors key data based on preset thresholds, and promptly pops up windows and sound warnings when abnormalities occur, prompting teaching knowledge points. The system solves many problems existing in traditional financial data processing in accounting teaching, improves teaching quality and effect, promotes students' understanding and mastery of financial knowledge, and provides efficient and intelligent data processing and analysis tools for accounting teaching.

The invention relates to the technical field of data processing, in particular to a financial data processing system based on a block chain, which comprises an access chain authorization module, a write-in arbitration scheduling module, a voucher path identification module, a structure back adjustment point module and a chain type result output module. According to the method, the stability score is calculated according to the field calling sequence difference, the calling interval time difference and the calling return content consistency of the node access behavior log, the nodes with stable access behaviors are screened, and block access permission mapping is formed; a sorting label is constructed based on a transaction timestamp and a fund transaction amount to realize sorting of concurrent transaction priorities, dynamic matching judgment is performed through a public key address list and a multi-signature access threshold, and link access path redirection is formed, so that the possibility that a node tampers data is reduced, and the transaction efficiency is improved. And according to the chain segment block height, the relay node confirmation state and the tail end data field variation value, sequence verification and index tracing are carried out, so that the tracing capability of the financial transaction data is obviously improved.

The invention is suitable for the technical field of data processing, and particularly relates to a financial data processing and classification method, system and equipment based on verifiable computing, and the method comprises the steps: obtaining on-chain transaction data verified by a block chain consensus node storage and risk-related index data verified by an under-chain oracle machine; the problems that the authenticity of traditional financial data is difficult to verify and the data is split are solved; calling a risk assessment model through an intelligent contract deployed on a block chain, and placing an assessment process in a decentralized block chain network; performing verifiable calculation through an intelligent contract to determine a total performance score and a risk index, and realizing whole-course tracing and verification of a calculation process by utilizing the characteristics of verifiable calculation of a block chain; the total performance score and the risk index are stored in the block chain as non-tampering records, and the risk rating groups are automatically divided according to the fixed rating rule on the chain through the smart contract, so that the authenticity, objectivity, verifiability and fairness of financial data processing are guaranteed.

The invention relates to the technical field of financial data processing, in particular to a payment and settlement service system based on a big data technology, and the system comprises a data collection module, a user payment behavior recognition module, a payment channel evaluation module, and a payment execution and monitoring module. According to the invention, through deep analysis of transaction data and dynamic user portrait construction, consumption modes and preference trends of users can be captured and analyzed more accurately, and through extraction of periodic purchase behaviors and sudden change preferences, payment experience is highly personalized, customer service quality is greatly improved, payment channel assessment is comprehensive, and user experience is improved. The method includes real-time performance monitoring and cost analysis, guarantees the optimization of the payment process, effectively improves the processing speed and safety, reduces the fraud risk, enhances the transaction safety and transparency through the implementation of full-chain encryption and the real-time tracking of the payment progress, and improves the response speed to potential abnormalities.

The invention provides a financial data encryption transmission system and method based on a circuit board. The system comprises an identity authentication module, a main control circuit module, a secret key processing module and a distributed storage module which are connected in sequence, and a security monitoring module connected with the secret key processing module, the identity authentication module adopts a biological characteristic matching algorithm based on mahalanobis distance to realize identity authentication, the key processing module adopts a key fragmentation technology based on a threshold scheme, a true random number generator realized by combining a ring oscillator ensures key security, the distributed storage module adopts Reed-Solomon coding to realize reliable fragmentation storage, and the distributed storage module adopts a random number generator realized by combining a random number generator realized by combining a random number generator realized by combining a random number generator realized by a random number generator. The safety monitoring module monitors temperature, voltage and physical invasion behaviors in real time; the method can effectively improve the safety and reliability of the financial data transmission process, and is suitable for financial data processing scenes needing high safety guarantee.

A method and system for enhanced financial data processing using large language models (LLMs) to transform PDF statements into structured accounting data. The invention preprocesses statements with line numbering, character position tagging, and data partitioning to overcome LLM context limitations. The system extracts transactions, reconciles them with statement balances, normalizes vendor information, and generates enhanced output files compatible with standard accounting platforms. This enhanced transaction data collapses reconciliation and categorization times in downstream accounting systems. The system creates a robust vendor-transaction database supporting direct analysis or simultaneous application of multiple accounting models.

A financial report analysis system having an intelligent automation unit for selecting from stored financial data the financial data to be processed and automatically scheduling for processing the selected financial data, a conversion unit for converting the selected financial data stored in a storage unit into a selected processing format to form converted financial data, a financial data processing unit for automatically processing the converted financial data to form processed financial data and for generating marked financial data from the processed financial data that includes one or more markings, and a verification unit for verifying an accuracy of the processed financial data by comparing the processed financial data to other financial data, and then highlighting or marking portions of the processed data if the data is inaccurate.

The invention discloses a financial heterogeneous data real-time cleaning and fusion method, and the method comprises the following steps: S1, obtaining multi-source, multi-time-dimension and multi-granularity financial heterogeneous original data, building a data access channel, and executing format standardization processing; and S2, constructing a cross-source, cross-time and cross-granularity financial index consistency constraint space, dynamically learning systematic deviation distribution of each data source in different market states based on the constraint space, and generating an implicit consistency deviation field. According to the financial heterogeneous data real-time cleaning and fusion method, a cross-source, cross-time and cross-granularity financial index consistency constraint space is constructed, systematic deviation distribution of data sources in different market states is dynamically learned based on the space, and an implicit consistency deviation field is generated; the problem of consistency among multi-source heterogeneous data is effectively solved, and the accuracy and reliability of the data are improved.

The invention provides a highway toll collection data storage method based on a distributed bookkeeping system, and relates to the technical field of financial data processing, and the method comprises the following steps: obtaining highway toll collection data information, sending the highway toll collection data information to the distributed bookkeeping system for uplink, and carrying out the encryption processing through the distributed bookkeeping system; and storing the encrypted highway toll data information returned by the distributed bookkeeping system into a highway toll data storage server provided by a service provider. According to the information type condition, the secondary encryption is established, the data content is protected by using the symmetric encryption, and then the symmetric key is protected by using the asymmetric encryption, so that the security of the highway toll data is improved. Symmetrical encryption is used for double protection of sensitive information to ensure the safety of data content, in addition, based on a symmetrical encryption algorithm, the requirement for computing resources is low, a symmetrical key can be dynamically generated during data transmission each time, and the risk of long-term storage and key management is reduced.

The invention relates to the technical field of data processing, and discloses a business financial data processing method and system based on a large model and a storage medium, and a converged communication method comprises the following steps: S1, data acquisition and real-time preprocessing; s2, unified semantic space mapping; s3, performing causal analysis and knowledge graph construction; s4, automatically creating and dynamically updating a business-finance mapping rule; s5, risk identification, decision quantification and ROI optimization strategy generation: carrying out risk identification and decision quantification on the industry and financial multi-source data according to the business-financial mapping rule through a decision maker of the industry large model in combination with an expert voting mechanism, identifying a potential loss chain and generating an executable scheme; through cooperative work of the data acquisition module, the cloud computing module and the business and financial decision module, full-process intelligence of business and financial data from acquisition and processing to decision support is realized, and the efficiency and effect of business and financial cooperative management are significantly improved.

The invention discloses a financial data processing method, electronic equipment and a computer readable medium, and the method comprises the steps: carrying out the data cleaning and safety verification of received original financial data, and obtaining pure financial data; semantic analysis is carried out on the pure financial data, and service information, service scenes, sensitive information and semantic relations in the pure financial data are recognized; determining a prompt template matched with the service scene, and generating a basic processing instruction according to the prompt template, the service information, the sensitive information and the semantic relationship; performing transformation processing on sensitive information in the basic processing instruction to obtain a desensitization processing instruction; inputting the desensitization processing instruction into a large-scale language model to obtain a response result output by the large-scale language model; and carrying out restoration processing on the response result to obtain a processing result of the original financial data. The contradictory triangle problem of data privacy, analysis efficiency and system security existing when a large language model is applied in the financial field is solved.

The invention provides a financial management data processing method and system, and relates to the field of financial data processing, and the method comprises the steps: traversing elements in a category data set, and dividing the category data set into at least one representation data chain according to the feature similarity between the elements; calculating data granularity of data items in the representation data chain, and obtaining a mother chain and sub-chain group according to the data granularity; performing hierarchical storage on the mother chain and the sub-chain, constructing an associated index map, and calculating a shortest query path from a mother chain layer to a sub-chain layer; and obtaining the user activeness of each access permission level corresponding to the shortest query path, and comparing the user activeness with the user activeness of each access permission level at the current moment to obtain a target query path at the current moment. According to the method, the activity degree of the user is monitored and the query path is dynamically adjusted, so that the change of user behaviors can be flexibly adapted, and the optimal data search path is found according to the current user request condition.

The invention relates to the technical field of financial information, in particular to an intelligent financial statement automatic generation and auditing method based on an AI learning model, and the method comprises the steps: analyzing an original financial voucher image through a multi-modal AI extraction module, extracting and structuring the sum, a transaction party, a timestamp and voucher type label information, and carrying out the verification of the information; the method comprises the following steps: uniformly correcting time data of different voucher sources based on a timestamp conflict detection model, generating a time alignment data unit set, inputting aligned data into a report to generate an AI model, constructing an amount-subject mapping relation through a long-short-term memory neural network, filling the amount-subject mapping relation into a debt sheet and profit sheet template, and automatically generating a to-be-audited report. Performing node-level compliance verification on the report through the dynamic rule base, marking rule conflict codes and generating an audit mark report; according to the method, automation of complex financial data processing, intelligence of report generation and traceability of audit verification can be realized, and financial efficiency and compliance management capability are remarkably improved.