CN108470228A - Financial data auditing method and audit system - Google Patents

Abstract

The invention discloses a kind of financial data auditing method and audit system, this method includes obtaining financial affair work data, and acquired financial affair work data include at least flow instance data and fixed assets data, will be in the storage to data warehouse of financial affair work data；At least one business diagnosis model is set, and the financial affair work data stored in data warehouse are analyzed by Distributed Calculation big data platform system；The result information that analysis obtains is stored in on-line analysis library, and analysis result is transmitted to and is checked on application server online；Check that analysis result is transmitted to terminal installation by application server by the form of report online.The system includes data acquisition module, big data platform module, data display module, for realizing above-mentioned auditing method.The present invention can reduce the cost of checking of enterprise, and improve the efficiency checked.

Description

Financial data audit method and audit system

technical field

The invention relates to the field of enterprise information management, in particular to a method for auditing enterprise financial data and a device for realizing the method.

Background technique

A large amount of financial data is generated during the operation of the enterprise, such as the operating income and operating expenses of the enterprise, and the profitability of the enterprise, such as profit, can be calculated according to different financial data of the enterprise. Since the amount of original financial data is very large and there are many types of data, it is often necessary to audit financial data, and the financial audit system is a tool commonly used for auditing financial data.

In the financial online audit system, the online automatic retrieval and early warning method through the audit rules has played a great role in financial audit and financial risk prevention. After several years of continuous deepening and application, although the online automatic retrieval early warning method has been continuously optimized and improved In-memory computing, database separation and other technologies are used to improve the performance of audit execution. However, due to the increasing amount of source data audits face and the continuous expansion of source data types, such as original vouchers and text data, the requirements for audit methods are also increasing. constantly improving. Therefore, it is necessary to perfect and improve the existing financial online auditing technology.

The current online financial audit system mainly has the following problems:

First, it cannot meet the processing requirements of big data. Under the conditions of large-scale centralized deployment, financial audit needs to process data in multiple regions in terms of finance and business. The maximum number of records in a single financial table at the database level can reach hundreds of millions. The business is similar to the existing financial audit. After a long time The operation of business data may increase to billions, which requires a very large-capacity server to store these data. With the continuous deepening of financial online audit applications, subsequent data processing of a large amount of semi-structured data and unstructured data is required, so the use of big data technology in financial audits is an inevitable trend.

Second, the current financial online audit method is relatively simple and cannot meet the growing audit needs. Therefore, the financial audit method also needs to adapt to the requirements of the times. Therefore, a new audit theoretical framework and corresponding technical methods are very necessary.

Contents of the invention

The main purpose of the present invention is to provide a financial data auditing method capable of reducing auditing costs and having high auditing efficiency.

Another object of the present invention is to provide a financial data auditing system that can be used more widely and can reduce manual operations.

In order to achieve the above-mentioned main purpose, the financial data auditing method provided by the present invention includes acquiring financial business data, the acquired financial business data at least includes process instance data and fixed asset data, etc., storing the financial business data in the data warehouse; setting at least A business analysis model, and analyze the business data through the distributed computing big data platform system; store the result information obtained from the analysis in the online analysis database, and transmit the analysis results to the online audit application server; finally, the online audit application server The analysis results are transmitted to the terminal device in the form of reports.

A preferred solution is that the obtained financial business data is process instance data and standard process data of the internal control system; the method also includes: after collecting the financial business data, setting the mapping relationship between the standard process and the instance process through the process name and process ID, and The collected data is stored in the distributed computing big data platform system; the business analysis model is the audit rule model, and the process instance data and the standard process data of the internal control system are analyzed according to the audit rule model.

An optional solution is that obtaining financial business data includes setting audit indicators, setting access formulas and obtaining data according to the formulas; setting the execution cycle of indicators, and setting warning levels and warning messages; obtaining instance data of preset indicators, and Obtain data from the report and display the obtained data.

Another optional solution is that the financial business data is profit statement data, user data, and operating income data; the business analysis model is an analytical review model; the analysis of financial business data includes applying the analytical review model to the financial business data. Data analysis, and generate profit trend analysis table and detailed analysis data, and perform multi-dimensional query on business period.

Another optional solution is that the financial business data is financial control account data, and the business analysis model is an aging calculation model; the analysis of financial business data includes data analysis through the aging calculation model and generation of aging analysis data.

Another option is that the financial business data is fixed asset data; the analysis of financial business data includes the use of a comprehensive sampling method for fixed assets, sampling and analysis through sampling algorithms, sample sizes, and unit information, and generating corresponding sampling data; analysis The results are presented in the form of graphs.

In order to achieve the above-mentioned another purpose, the financial data auditing device provided by the present invention includes a data acquisition module for acquiring financial business data, and the acquired financial business data includes at least process instance data, fixed asset data, etc.; big data platform module , for storing financial business data in the data warehouse, and setting at least one business analysis model, and analyzing the financial business data stored in the data warehouse through the distributed computing big data platform system, and storing the result information obtained from the analysis In the online analysis library, the analysis results are transmitted to the online audit application server; the data display module is used to transmit the analysis results to the terminal device in the form of reports.

A preferred solution is to further include a security control module for performing security authentication during data collection, storage, calculation, and analysis. Security authentication includes at least identity verification, authorization process and input verification.

A preferred solution is to further include a configuration management module, which is used to monitor cluster operation and maintenance, service monitoring, resource monitoring and abnormal alarm of the big data environment.

A preferred solution is to further include a service scheduling module for performing task scheduling, and the task scheduling includes at least the scheduling of data collection tasks, data calculation tasks, and data analysis tasks.

It can be seen from the above scheme that the financial data audit method and audit system of the present invention can be applied to improve the online audit function, expand and guide the application of online audit business, and play an important role in promoting the deepening application of online audit. Through the method of the present invention, risk audit points are integrated, researched and judged, audit resources are integrated, the amount of on-site audits is reduced, and the efficiency and effect of online audits are improved. Moreover, the present invention can reduce company auditing costs. For example, implementing new auditing methods such as information system inspection method and assessment index monitoring method in actual audit work will greatly reduce various expenses such as organizing on-site auditing.

In addition, the present invention can expand the scope of online auditing. By using new auditing methods such as information system inspection method, assessment index monitoring method, sampling method, recalculation method, and analytical review method, the scope of financial auditing will be extended from the auditing of financial accounting documents. It will expand the coverage of financial audits to various front-end documents, contracts, plans, etc., as well as office affairs documents and tables. In addition, the present invention can also improve the work efficiency of financial audit and reduce the workload of manual audit. By using new information technologies such as intelligent audit technology platform and big data technology platform, and adopting big data processing technology Hadoop and Hive, the audit workload is greatly reduced. In addition, the present invention can also reduce the company's risk loss and internal control loss. Since the present invention changes the existing mode of only auditing risk audit points, it creates a new idea of full-view online audit, and quickly identifies the company's business operation risk points. From a global perspective Comprehensively reduce the company's risk loss and internal control loss.

Description of drawings

Fig. 1 is a structural block diagram of an embodiment of the financial data auditing system of the present invention.

Fig. 2 is a server frame diagram applying the embodiment of the financial data auditing system of the present invention.

Fig. 3 is a schematic diagram of the data flow of the embodiment of the financial data auditing system of the present invention.

The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

Detailed ways

The financial data auditing method of the present invention is applied to auditing the financial data of enterprises, so as to find possible risks in the financial data of enterprises. The method of the present invention is especially suitable for online auditing of financial data. The financial data auditing system of the present invention includes multiple servers for realizing the above financial data auditing method.

Referring to FIG. 1 , the financial data auditing system of the present invention includes a data acquisition module 10 , a data integration module 20 , a big data platform module 30 , a data application module 50 , a configuration management module 60 , a security control module 61 and a service scheduling module 62 .

In this embodiment, the data acquisition module 10 is used to obtain original financial data, such as obtaining financial control data, SAP-ERP data, other business data, and can obtain structured data, semi-structured data and unstructured data, so , the data acquisition module 10 needs to support the integration of multiple data sources, such as supporting the integration of structured data sources of business systems such as financial management and control systems and SAP-ERP package software, preferably, it also supports the integration of semi-structured data such as logs and mails. Integration also supports the integration of unstructured data such as office documents, contracts, pictures, and videos.

The data integration layer 20 includes a big data connector, a data server bus, and a log system, which can obtain structured data (such as relational database records) from external data sources through various technologies such as data warehouse extraction, file adapter, and real-time data collection. Structured data (such as logs, emails, etc.), unstructured data (such as files, videos, audios, network data streams, etc.) and real-time data for specific needs.

The big data platform layer 30 includes a data storage module 31, a data calculation module 35, a data analysis module 40, and an analysis result storage module 45, wherein the data storage module 31 is responsible for storing big data, and is provided with a distributed file system 32 and a distributed database 33. For all data types and diverse computing needs, it can store various types of data from various business systems and support advanced applications in the data computing and analysis layers, featuring massive-scale storage and fast query and reading.

The data computing module 35 includes a distributed computing module 36, a memory computing module 37, and a streaming computing module 38. Using distributed computing technology, combined with streaming computing and memory computing technologies required by specific scenarios, the application involves computing task workflow. Reasonable allocation and optimization to achieve timely and effective completion of computing tasks.

The data analysis module 40 provides analysis engines such as data analysis and data mining, so a data analysis engine module 41 and a data mining engine module 42 are provided.

The analysis result storage module 45 is provided with a relational type database 46 for storing analysis and mining results in the relational type database 45 for calling by the data application module 50 .

The data application module 50 is used to support various functional modules involved in the online audit application system, such as storing daily audit data, special audit data, real-time monitoring data, regular audit data, search and analysis data, and the like.

The configuration management module 60 is used to comprehensively monitor the cluster operation and maintenance, service monitoring, resource monitoring and abnormal alarm of the big data environment.

The security control module 61 is used to solve a large number of security issues such as identity verification, authorization process and input verification generated from the process of data collection, storage, calculation, analysis, application, etc. in the big data environment, such as complying with the security policy of the enterprise for protection .

The scheduling service 62 is used to provide a unified task scheduling service, including unified scheduling of data collection tasks, data calculation tasks, and data analysis tasks.

Apply the server frame of financial data auditing system embodiment of the present invention as shown in Figure 2, in the present embodiment, need to set up the Hadoop big data cluster of X86 structure, for example, the data of external system 70, comprise SAP-ERP data, marketing management data The data collected by electricity consumption can be extracted into the operation data storage (ODS) database 75 through the ETL tool, and then the business data in the operation data storage database 75 can be converted and loaded into the Distributed computing big data platform system 74. It can be seen from FIG. 2 that the distributed computing big data platform system 74 includes multiple servers and forms a server cluster.

An online audit result database 77 and a financial control database 76 are set in the data center 72, and the established online audit result database 77 is used to store analysis results. In addition, the algorithm models of five new financial audit methods are established in the distributed computing big data platform system 74, the business data extracted by Hadoop is analyzed by executing the program, and the analysis results are written into the online audit result database 77.

The application server includes a financial management and control application server 78 and an online audit application server 79. In this embodiment, the financial online audit triggers the distributed computing big data platform system 74 to perform analysis and calculation through the scheduling program execution scheduling.

The data flow of the financial data audit method of this embodiment is shown in Figure 3. First, the big data platform cluster 80 first obtains financial business data, so the big data platform cluster 80 receives the financial control database transmitted by the financial control database process instance server 84 Process instance data, and receive the internal control database standard process data transmitted by the internal control database standard process data server 83, and the above data is transmitted to the distributed data warehouse process model database 82. Specifically, relevant business data, such as process instance data and fixed asset data, are cleaned and loaded into the distributed data warehouse process model database 82 of the big data platform cluster 80 through the ETL tool.

Then, the financial data auditing system analyzes the relevant business data in the distributed data warehouse process model database 82 through the business analysis model, such as the sampling model of R language, the process monitoring model, etc., through the Hadoop MapReduce of the big data platform, and analyzes the analyzed data The result information is stored in the online audit OLAP analysis library 85, and finally can be displayed by the front-end report of the online audit application server cluster 81. In this embodiment, the analysis results can be sent to mobile terminals such as mobile phones, or can be sent to Computers and other terminal devices, so that auditors can check the results.

The present invention is based on big data technology and data mining technology to construct five methods of a new financial audit method, namely, information system inspection method, assessment index monitoring method, analytical review method, recalculation method, and sampling method. Through these five methods, Supplement and improve the method system of financial online audit. The above five audit methods will be introduced in detail below.

The application scenario of the information system inspection method is process monitoring. The essence of process monitoring is to detect whether the process instance data generated during the actual information system circulation of the business process meets the requirements of the business standard process. If it does not meet the requirements, it will be regarded as a violation. Therefore, in the financial business data auditing method of the present invention, two process monitoring models need to be established, one is missing steps, and the other is incompatibility of positions.

The steps of the information system inspection method are as follows: firstly, set the standard process in the internal control system, generate process instance data in the financial control system, and then collect the process instance data of financial control and the standard process data of the internal control system through ETL tools, and The system stores the collected data in the distributed computing big data platform system through the mapping relationship between the built-in standard process and the instance process through the process name and process ID. Finally, the process data is analyzed through the audit rule model, and the analysis results are stored in the OLAP analysis database 85 .

It can be seen that the method of the present invention monitors the displayed process information that does not conform to the specification, and checks the content of the process monitoring through functional penetration, such as missing steps, which step is missing, the positions are incompatible, and which two positions exist The process is abnormal.

The application scenario of the assessment indicator monitoring method is to incorporate indicators, including peer benchmarking and enterprise person-in-charge assessment indicators, into the online audit module, generate indicator data in real time, and compare it with budget indicators to check for doubts.

The assessment indicator monitoring method includes the following steps: First, establish relevant indicators through the indicator system function, and set the access formula through the indicator function, such as obtaining data from the financial control report. Then, set the execution cycle of the indicator through the indicator policy setting function, such as scheduling frequency by hour, day, month, quarter, etc.; and set the warning level and warning message. The warning message can be email, SMS, system message, etc. Then, the financial business data audit system executes the scheduling program to execute the indicators, and fetches the data from the financial control system report, and finally displays the indicator results through the supervision kanban function.

The application scenario of the analytical review method is to combine the business characteristics of power grid enterprises, conduct time-series trend analysis on the main business income and costs of the power grid, and take the profit analysis of the power grid as the application research of trend analysis. Specifically, the analytical review method may include the following steps: First, collect financial control and profit-related report data, user data, and operating income data through the ETL program, and then conduct data analysis through the analytical review method model to generate profit trend analysis Table and detail analysis data. Then, through the trend analysis function, conduct multi-dimensional queries on power supply units and business periods, and present them in intuitive charts.

It can be seen that this method conducts trend analysis on the main business income and cost of a certain unit in a functional way, and can conduct trend analysis on each large electricity customer and electricity purchase cost, and present it in the form of a chart.

The application scenario of the recalculation method is account aging analysis. In this embodiment, the account aging analysis adopts the first-in-first-out method. Since the account aging is the most important information when analyzing accounts receivable, and accounts receivable are current assets, so Accounts receivable with an aging of more than a reasonable number of turnover days will have a negative impact on the company's operations, and the higher the age, the lower the capital efficiency, the greater the risk of bad debts, and the higher the financial cost.

In this embodiment, the recalculation method includes the following steps: firstly, collecting financial control-related account data through ETL, and then performing data analysis through an account aging calculation model to generate account aging analysis data. Therefore, in this embodiment, the aging data is checked through the intelligent aging calculation function. The aging calculation function supports four statistical dimensions: statistics by transaction unit, statistics by subject, statistics by project, and statistics by aging. You can query by specified date and unit.

Sampling is the implementation of inspection procedures for less than 100% of the items in the relevant population, so that all sampling units have the opportunity to be selected. The application scenario of the sampling method is to sample and analyze fixed assets through stratified sampling and systematic sampling. Specifically, the sampling method includes the following steps: first, collect the fixed asset data of the business system through ETL, and then use the comprehensive sampling function of fixed assets to pass Sampling algorithms, such as stratified sampling, systematic sampling, etc., conduct sampling analysis on sample size, unit and other information, generate corresponding sampling data, and finally present the sampling result information in the form of charts for viewing.

The financial business data auditing method of this patent adopts five new financial auditing method systems, builds the application model of the new financial auditing method, and forms a set of informatization implementation scheme based on intelligent traceability technology and big data technology on this basis, changing In view of the fact that the current financial audit method takes audit rules as the core, new financial audit methods such as information system inspection method, assessment index monitoring method, analytical review method, recalculation method, and sampling method are combined with the information system platform to improve online audit. Accuracy, effectively prevent the business risk of the enterprise, and realize the risk-oriented full-view online audit.

Since the system, norms, standards and intelligent analysis method of the audit method of this patent can be directly applied to improve the online audit function, expand and guide the application of online audit business, and integrate and judge the risk audit points through the new audit method, integrate audit resources, Reduce the amount of on-site audits and improve the efficiency and effectiveness of online audits.

Therefore, the method of the present invention can reduce the company's audit costs, and implementing new audit methods such as the information system inspection method and the assessment index monitoring method in the actual audit work will greatly reduce various expenses such as organizing on-site audits. Moreover, the method of the present invention can expand the scope of online auditing. By using new auditing methods such as information system inspection method and assessment index monitoring method, the scope of financial auditing will be extended from the auditing of financial accounting documents to various front-end documents, contracts, plans, etc. , and office affairs documents, etc., will expand the coverage of financial audits. Again, the method of the present invention can improve auditing work efficiency and reduce the workload of manual auditing. Because the present invention adopts new information technologies such as intelligent auditing technology platform and big data technology platform, and adopts big data processing technology Hadoop and Hive, it greatly reduces auditing. workload. Finally, the present invention can reduce the company's risk loss and internal control loss. Because the method of the present invention changes the original mode of only auditing risk audit points, it creates a new idea of full-view online audit, quickly identifies business risk points of the enterprise, and analyzes from the overall perspective. From the perspective of comprehensively reducing enterprise risk losses and internal control losses.

Claims (10)

1. The method for auditing financial data, characterized in that it comprises: Acquiring financial business data, the acquired financial business data includes at least process instance data and fixed asset data, and storing the financial business data in a data warehouse; Setting at least one business analysis model, and analyzing the financial business data stored in the data warehouse through a distributed computing big data platform system; Store the result information obtained from the analysis in the online analysis library, and transmit the analysis result to the online audit application server; The online audit application server transmits the analysis result to the terminal device in the form of a report. 2. The financial data auditing method according to claim 1, characterized in that: The acquired financial business data is process instance data and standard process data of the internal control system; The method also includes: after collecting the financial business data, setting the mapping relationship between the standard process and the instance process through the process name and process ID, and storing the collected data in the distributed computing big data platform system; The business analysis model is an audit rule model, and the process instance data and the standard process data of the internal control system are analyzed according to the audit rule model. 3. The financial data auditing method according to claim 1, characterized in that: Obtaining financial business data includes setting audit indicators, setting access formulas and obtaining data according to the formulas; Set the execution cycle of the indicator, and set the warning level and warning message; The instance data of the preset indicator is obtained, and the data is obtained from the report, and the obtained data is displayed. 4. The financial data auditing method according to claim 1, characterized in that: The financial business data are profit statement data, user data, and operating income data; The business analysis model is an analytical review method model; Analyzing the financial business data includes applying the analytical review model to analyze the financial business data, generating profit trend analysis tables and detailed analysis data, and performing multi-dimensional queries on business periods. 5. The financial data auditing method according to claim 1, characterized in that: The financial business data is financial management and control account data, and the business analysis model is an account aging calculation model; Analyzing the financial business data includes performing data analysis through the aging calculation model, and generating aging analysis data. 6. The financial data auditing method according to claim 1, characterized in that: The financial business data is fixed asset data; The analysis of the financial business data includes adopting a comprehensive sampling method for fixed assets, performing sampling analysis through sampling algorithms, sample sizes, and unit information, and generating corresponding sampling data; The analysis results are displayed in the form of graphs. 7. The financial data auditing system is characterized in that it includes: The data acquisition module is used to acquire financial business data, and the acquired financial business data includes at least process instance data and fixed asset data; The big data platform module is used to store the financial business data in the data warehouse, set at least one business analysis model, and analyze the financial business data stored in the data warehouse through the distributed computing big data platform system Perform analysis, store the result information obtained from the analysis in the online analysis library, and transmit the analysis result to the online audit application server; The data display module is used to transmit the analysis results to the terminal device in the form of reports. 8. The financial data auditing system according to claim 7, further comprising: The security control module is used for performing security authentication during data collection, storage, calculation, and analysis, and the security authentication includes at least identity verification, authorization process and input verification. 9. The financial data auditing system according to claim 7, further comprising: The configuration management module is used to monitor the cluster operation and maintenance, service monitoring, resource monitoring and abnormal alarm of the big data environment. 10. The financial data auditing system according to claim 7, further comprising: The service scheduling module is used to execute task scheduling, and the task scheduling at least includes scheduling of data collection tasks, data calculation tasks, and data analysis tasks.