Fund mobility analysis method and equipment based on operation process, and medium

Abstract

The embodiment of the invention discloses a fund liquidity analysis method and device based on an operation process and a medium, and relates to the technical field of data analysis, the method comprises the steps that fund liquidity analysis demand information triggered by a user is acquired, and the fund liquidity analysis demand information comprises a target analysis organization and a target analysis timestamp; based on the fund mobility analysis demand information, a corresponding subject balance table intermediate table and a financial voucher entry intermediate table are matched, and the subject balance table intermediate table comprises operation node information; according to the subject balance table intermediate table and the financial voucher entry intermediate table, determining multi-dimensional financial index data corresponding to each operation node according to a plurality of preset financial index dimensions; and performing sand table modeling according to the multi-dimensional financial index data through a preset node index value table and an operation node connection line table, generating a fund flow sand table model corresponding to a plurality of operation nodes, and performing fund flow prediction risk analysis based on the fund flow sand table model.

Description

Technical Field

[0001] This specification relates to the technical field of data analysis, and in particular, to a method, device, and medium for analyzing the capital liquidity based on the operation process. Background Art

[0002] With the development of the digital economy, the management of working capital is the core of corporate financial management. All walks of life attach more and more importance to the analysis and display of data, and it is particularly important to analyze the collected data by appropriate methods. The capital liquidity management of some enterprises is facing the dual challenges of the complexity of data dimensions and the acceleration of risk transmission.

[0003] Traditional capital liquidity analysis technologies are mostly constructed based on the static financial statement system. By collecting the data of the accounting subject balance sheet to generate a fixed analysis template, the timeliness of the data is limited by the financial accounting cycle and cannot be connected to the real-time data stream of the business system, resulting in the risk warning lagging behind the actual business changes. In addition, the visualization presentation method is limited to the two-dimensional statement structure, lacking the dynamic flow display between data. Therefore, in the traditional working capital management process, it usually relies on static display methods and fixed analysis templates, and the analysis of each node in the operation process is relatively fragmented, unable to meet the capital liquidity analysis needs of enterprises, and there is a problem of lagging risk warning. Summary of the Invention

[0004] One or more embodiments of this specification provide a method, device, and medium for analyzing the capital liquidity based on the operation process, which are used to solve the following technical problems: In the traditional working capital management process, it usually relies on static display methods and fixed analysis templates, and the analysis of each node in the operation process is relatively fragmented, unable to meet the capital liquidity analysis needs of enterprises, and there is a problem of lagging risk warning.

[0005] One or more embodiments of this specification adopt the following technical solutions:

[0006] One or more embodiments of this specification provide a method for analyzing the capital liquidity based on the operation process. The method includes: obtaining the capital liquidity analysis requirement information triggered by the user, where the capital liquidity analysis requirement information includes the target analysis organization and the target analysis timestamp; based on the capital liquidity analysis requirement information, matching the corresponding intermediate table of the account balance sheet and the intermediate table of the financial voucher entries, where the intermediate table of the account balance sheet includes the operation node information, and the intermediate table of the financial voucher entries includes the business type; according to the intermediate table of the account balance sheet and the intermediate table of the financial voucher entries, determining the multi-dimensional financial index data corresponding to each operation node according to a preset plurality of financial index dimensions; through the preset node index value table and the operation node connection line table, performing a sand table modeling according to the multi-dimensional financial index data to generate a capital flow sand table model corresponding to a plurality of operation nodes, so as to perform a capital liquidity prediction risk analysis based on the capital flow sand table model.

[0007] One or more embodiments of this specification provide a device for analyzing the capital liquidity based on the operation process, including:

[0008] At least one processor; and,

[0009] A memory communicatively connected to the at least one processor; wherein,

[0010] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above method.

[0011] A non-volatile computer storage medium provided by one or more embodiments of this specification stores computer-executable instructions, and the computer-executable instructions are set to: execute the above method.

[0012] One or more embodiments of this specification adopting the above at least one technical solution can achieve the following beneficial effects: Through the above technical solution, the traditional analysis method relies on a fixed template and is difficult to deeply analyze for specific scenarios. However, one or more embodiments of this specification can accurately focus and locate problems by obtaining the requirement information including the target analysis organization and the timestamp, avoiding the "one-size-fits-all" situation in the traditional method. " one-size-fits-all ”The extensive management mode; in the face of the problem of complex data dimensions, traditional methods only rely on the balance sheet of accounting subjects and cannot comprehensively reflect the dynamic changes of funds. However, the embodiments of this specification match the intermediate table of the balance sheet of subjects and the intermediate table of the entries of financial vouchers, integrating the data of operation nodes and business types. It can not only understand the current status of procurement funds, but also trace the process of fund flow, comprehensively master the dynamic changes of funds in the procurement link, and overcome the defects of isolated data and inability to reflect the overall picture of funds in the traditional way; traditional fund liquidity analysis is limited by fixed analysis templates and it is difficult to deeply analyze the fund status. However, the embodiments of this specification preset multiple financial index dimensions to determine multi-dimensional financial index data. In the current situation of accelerating risk transmission, these indexes can evaluate funds from multiple levels; traditional visualization methods are limited to two-dimensional statements and lack the display of dynamic data flow. However, the embodiments of this specification generate a fund flow sand table model through sand table modeling and present the fund flow in an intuitive graph, solving the dilemma of insufficient data visualization and difficulty in discovering fund flow problems in the traditional way; traditional analysis methods have poor data timeliness and risk warnings lag behind business changes. However, the embodiments of this specification conduct risk analysis based on the sand table model, can simulate different scenarios to predict risks, make up for the defect of lagging risk warnings in the traditional way, and ensure financial stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings described below are only some embodiments recorded in this specification. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. In the drawings:

[0014] Figure 1 It is a schematic flow chart of a fund liquidity analysis method based on an operation process provided by an embodiment of this specification;

[0015] Figure 2 It is a schematic diagram of a fund flow sand table model provided by an embodiment of this specification;

[0016] Figure 3 It is a schematic structural diagram of a fund liquidity analysis device based on an operation process provided by an embodiment of this specification. SPECIFIC IMPLEMENTATION MANNER

[0017] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this specification.

[0018] The embodiments of this specification provide a method for analyzing the liquidity of funds based on the operation process. It should be noted that the execution subject in the embodiments of this specification can be a server or any device with data processing capabilities. Figure 1 The following is a schematic flowchart of a method for analyzing the liquidity of funds based on the operation process provided by the embodiments of this specification, as Figure 1 shown, mainly including the following steps:

[0019] Step S101, obtain the information on the demand for analyzing the liquidity of funds triggered by the user.

[0020] In an embodiment of this specification, the information on the demand for analyzing the liquidity of funds triggered by the user is obtained. Here, the information on the demand for analyzing the liquidity of funds includes the target analysis organization and the target analysis timestamp. It should be noted that the target analysis organization can be an enterprise or a subordinate organization within the enterprise. By setting the target analysis organization, the demand for analyzing the liquidity of funds at different levels within the enterprise can be realized, achieving the effect of targeted analysis. In addition, the target analysis timestamp can be a real-time timestamp or a timestamp of a historical period. When the target analysis timestamp is a real-time timestamp, the analysis of the liquidity of funds is a real-time analysis process, and real-time analysis is carried out along with the real-time transaction situation within the organization; if the target analysis timestamp is a historical timestamp, the analysis of the liquidity of funds refers to the analysis of the flow of funds within the organization at a historical moment. Therefore, the liquidity analysis requirements of different organizations at different times can be met.

[0021] During the operation process of an enterprise, due to different management requirements, the demand for analyzing the liquidity of funds will be triggered, including the target analysis organization (such as a specific subsidiary, department, etc.) and the target analysis timestamp (specific analysis period, such as a certain month, quarter, etc.). By clarifying this information, the scope and time dimension of the analysis can be determined, providing an accurate guidance for subsequent data matching and analysis.

[0022] Step S102, based on the information on the demand for analyzing the liquidity of funds, match the corresponding intermediate table of the account balance and the intermediate table of the financial voucher entries.

[0023] Among them, the intermediate table of the subject balance sheet includes operation node information, and the intermediate table of the financial voucher entry includes business types. The intermediate table of the subject balance sheet and the intermediate table of the financial voucher entry can be automatically generated according to a preset time period according to a preset table structure, for example, automatically generated on an annual basis.

[0024] In an embodiment of the present specification, an example of the table structure of the intermediate table of the subject balance sheet (TMSAKMYE) is as follows. It is used to store multi-dimensional subject balance data, supports multi-currency accounting (dual-track system of original currency / local currency), includes complete period balance information (beginning of year / accumulated / occurred / end of period), realizes period dimension analysis through AccPeriodID. Through the intermediate table of the subject balance sheet, the capital stock information of each operation node can be obtained, providing a basis for analyzing the occupation of funds in different links.

[0025]

[0026]

[0027] The intermediate table of financial vouchers includes the intermediate table of financial voucher entries TMFACWPZFL and the intermediate table of financial voucher headers TMSACWPZZB, which are used to receive the original voucher data of the financial system. The voucher header table and the entry table are associated through AccDocID, retaining complete accounting dimension information (unit, ledger, period). Among them, the table structures of the intermediate table of financial voucher entries TMFACWPZFL and the intermediate table of financial voucher headers TMSACWPZZB are as follows:

[0028]

[0029]

[0030]

[0031]

[0032] The intermediate table of financial voucher entries covers business type information. The business types record in detail the nature of various economic operations of the enterprise, such as credit purchases, cash sales, manufacturing expense expenditures, etc. These information show the inflow and outflow channels of funds, reflecting the dynamic changes of funds in different business activities. Through the intermediate table of financial voucher entries, the impact of different business activities on the flow of funds and the transfer path of funds between various businesses can be understood.

[0033] According to the target analysis organization and timestamp in the fund liquidity analysis demand information, accurately screen the corresponding intermediate table of the subject balance sheet and the intermediate table of financial voucher entries from the data table. This matching operation combines the operating node information with the business type information, enabling comprehensive analysis from two dimensions: the stock and flow of funds. Through this matching, it is possible to clearly understand the fund status of each operating node and the impact of related business activities on fund flow within a specific organization and time period, laying a solid data foundation for subsequent calculation of multi-dimensional financial indicator data, sand table modeling, and in-depth fund liquidity analysis.

[0034] Step S103: According to the intermediate table of the subject balance sheet and the intermediate table of financial voucher entries, determine the multi-dimensional financial indicator data corresponding to each operating node according to multiple preset financial indicator dimensions.

[0035] According to the intermediate table of the subject balance sheet and the intermediate table of financial voucher entries, determine the multi-dimensional financial indicator data corresponding to each operating node according to multiple preset financial indicator dimensions, specifically including: establishing the association relationship between the intermediate table of the subject balance sheet and the accounting subjects through the operating node subject mapping table and the operating node information in the intermediate table of the subject balance sheet; taking data from the intermediate table of the subject balance sheet according to this association relationship to determine the subject balance data, and obtaining the predefined financial indicator calculation method; determining the multi-dimensional financial indicator data corresponding to the operating node through the subject balance data and the financial indicator calculation method.

[0036] In an embodiment of the present specification, the operating nodes include cash and marketable securities, accounts receivable, accounts payable, inventory, liabilities, fixed assets, other incoming funds, other outgoing funds, etc. The data table structure of the operating node table is as follows:

[0037]

[0038] Through the mapping relationship between JDID (node ID) and KMBH (subject number) in the operating node subject mapping table (TMSAYYJDKMYS), perform an exact match with KMBH in the intermediate table of the subject balance sheet (TMSAKMYE). The data table structure of the operating node subject mapping table is as follows:

[0039]

[0040] Among them, DWID (Unit ID) ensures the consistency of the organizational structure dimension, and AccPeriodID (Accounting Period ID) realizes the alignment of the time dimension. The associated result forms the account balance data corresponding to each operation node. Through the KMBH mapping of TMSAYYJDKMYS, the relevant account data of the corresponding accounts in TMSAKMYE is automatically captured, such as the beginning balance, cumulative amount of transactions, and ending balance. Moreover, the balance direction can be adjusted according to the debit and credit directions to achieve dynamic data extraction of the account balances for each operation node. The calculation methods of financial indicators are predefined. According to the calculation methods of financial indicators, using the account balance data, the multi-dimensional financial indicator data corresponding to the operation nodes is determined.

[0041] In an embodiment of this specification, the multi-dimensional financial indicator data here includes dimensions such as currency dimension and account dimension. When calculating financial indicators under the currency dimension, the separation calculation of domestic and foreign currency data can be achieved through the CurrencyID field; when calculating financial indicators under the account dimension, the nodes can be associated with accounts based on accurate matching of KMBH. In addition to the calculation of financial indicators under the above dimensions, it can also be the solvency indicator dimension (current ratio, quick ratio, etc.), the operation ability indicator dimension (accounts receivable turnover rate, inventory turnover rate, etc.), and the profitability indicator dimension (gross profit margin, net profit margin, etc.).

[0042] Step S104, through the preset node indicator value table and the operation node connection line table, perform sand table modeling based on the multi-dimensional financial indicator data to generate a fund flow sand table model corresponding to multiple operation nodes, so as to perform fund liquidity prediction risk analysis based on the fund flow sand table model.

[0043] Through the preset node indicator value table and the operation node connection line table, perform sand table modeling according to the multi-dimensional financial indicator data to generate a fund flow sand table model corresponding to multiple operation nodes, which specifically includes: parsing the operation node connection line table to obtain the flow topology rule information corresponding to the fund flow between nodes, where the flow topology rule information includes the flow direction; parsing the node indicator value table to determine the node indicator reference data corresponding to each operation node; according to the node indicator reference data and the multi-dimensional financial indicator data, determining the sand table node display parameters, where the sand table node display parameters include the node size and the node color parameters; performing sand table modeling through the flow topology rule information and the sand table node display parameters to generate a fund flow sand table model corresponding to multiple operation nodes.

[0044] In an embodiment of this specification, relevant tables of nodes are pre-configured, including a node index category table, a node index table, and a node index value table. Taking the operating node corresponding to cash and marketable securities as an example, the node index categories thereof include the upper and lower limits of the fund stock, the node index data thereof includes the absolute upper limit and the absolute lower limit, and the node index value data is used to represent the specific value of the node index. For example, the absolute upper limit is 8,000 and the absolute lower limit is 1,000. The table structures of the node index category table, the node index table, and the node index value table are as follows:

[0045]

[0046]

[0047]

[0048]

[0049] By parsing the node index value table, the node index reference data corresponding to each operating node is determined, that is, the ZBZ field in the node index value.

[0050] Parse the operating node connection line table of this operating node to obtain the flow topology rule information corresponding to the fund flow between nodes, specifically including: matching the operating node connection line table corresponding to each operating node through the operating node identifier corresponding to each operating node; obtaining the source node identifier and the destination node identifier in the operating node connection line table, and determining the flow direction corresponding to the fund flow between nodes according to the source node identifier and the destination node identifier.

[0051] In an embodiment of this specification, the table structure of the operating node connection line table is as follows:

[0052]

[0053]

[0054] Match the operating node connection line table corresponding to each operating node through the operating node identifier corresponding to each operating node, obtain the source node identifier and the destination node identifier in the operating node connection line table through the LYJDID and QXJDID fields, and determine the flow direction corresponding to the fund flow between nodes according to the source node identifier and the destination node identifier. It should be noted that the direction of the connection line is determined according to the source node ID and the destination node ID in the operating node connection line table, and the amount occurred on the connection line is calculated according to the occurrence amount of one of the source node or the destination node to avoid double counting.

[0055] Based on the node index benchmark data and the multi-dimensional financial index data, determine the display parameters of the sand table nodes, specifically including: according to a preset conversion method, convert the multi-dimensional financial index data in terms of capital scale to obtain the actual occurrence scale corresponding to each sand table node, and set the node size through this actual occurrence scale; based on the node index benchmark data and the multi-dimensional financial index data, determine the node deviation index corresponding to each sand table node, and set the node color parameters based on this node deviation index.

[0056] In an embodiment of this specification, when analyzing the capital liquidity of an enterprise, the form of the multi-dimensional financial index data may be relatively complex, making it difficult to intuitively reflect the actual scale of the capital. The preset conversion method will be designed according to specific business requirements and data characteristics. For example, it may convert the multi-dimensional financial index data into the actual occurrence scale according to the conversion relationship between the financial index and the actual amount of funds. Set the size of the sand table nodes through the actual occurrence scale. Nodes with a large occurrence scale are displayed with a larger size in the sand table, and nodes with a small occurrence scale have a smaller size, facilitating users to intuitively judge the differences in the capital scale of each node. The node index benchmark data represents the index reference values of each node in the ideal state or normal operation of the enterprise. By comparing and analyzing the multi-dimensional financial index data with the node index benchmark data, determine the node deviation index. This deviation index can reflect the degree of deviation of the actual financial status of each sand table node from the ideal or normal state. Set the node color parameters based on this deviation index. For example, when the node deviation index is within a reasonable range, the node can be displayed in green, indicating that the operation status of this node is good; when the deviation index exceeds a certain range, it may be displayed in yellow or red, representing different degrees of risk respectively, facilitating the intuitive identification of nodes with risks.

[0057] In an embodiment of this specification, when conducting capital liquidity analysis, use the pre-set node index value table and operating node connection line table, and combine the multi-dimensional financial index data to construct a capital flow sand table model. First, parse the operating node connection line table to obtain the flow topology rule information of the capital flow between nodes from it, including the flow direction of the capital. Then, parse the node index value table to determine the node index benchmark data corresponding to each operating node. Subsequently, based on the obtained node index benchmark data and the multi-dimensional financial index data, further determine the display parameters of the sand table nodes, including the node size for reflecting the capital scale and the node color parameters for reflecting the node status. Finally, comprehensively use the flow topology rule information and the sand table node display parameters to complete the sand table modeling work, and then generate a capital flow sand table model corresponding to multiple operating nodes, which can intuitively present the capital flow situation in the enterprise operation process. Figure 2 It is a schematic diagram of a capital flow sand table model provided by an embodiment of this specification. As Figure 2As shown, the generated fund flow sand table model can display the working capital data flow of the current unit in the current month according to the unit dimension and time dimension, or can be customized for the period. In addition, it can also obtain real-time data of six indicators, namely asset-liability ratio, interest-bearing liability ratio, current ratio, quick ratio, ratio of two funds to current assets, and cash turnover days, so as to timely understand the asset-liability situation and debt repayment ability of the enterprise, timely avoid the risk of insufficient enterprise fund turnover, and meet the scenario requirements of displaying the occurrence values of purchase limit, credit purchase, manufacturing expenses, management expenses, depreciation / amortization, credit sales, and cash sales of the unit in the current period. In addition, each indicator can be drilled down for joint query to display the specific data composition. By setting upper and lower limits for each indicator, warning display is realized after exceeding the set values of the upper and lower limits.

[0058] In addition, in an embodiment of the present specification, a header indicator table is also preset, which is used to store the summary indicators required for visual display. It can be stored according to the unit organization (DWID) and time (SJRQ) dimensions. The XH field controls the display order, and through a timed calculation task, it supports real-time data refresh.

[0059]

[0060] After generating the fund flow sand table models corresponding to multiple operation nodes, the method further includes: determining at least one risk operation node of the fund flow sand table model, and determining the risk accounts according to the risk operation node and the preset mapping table of operation node accounts; performing financial voucher matching in the preset intermediate table of financial voucher entries with the risk account identifiers corresponding to the risk accounts to determine the risk financial vouchers, and tracing the node risks of the risk operation node.

[0061] In an embodiment of the present specification, in the generated fund flow sand table model, risk operation nodes are identified based on preset risk judgment criteria (such as indicator thresholds for abnormal fund turnover, excessive debt ratio, insufficient cash flow, etc.). The risk judgment criteria can be comprehensively set according to factors such as the historical data of the enterprise, the industry average level, and the financial strategic goals of the enterprise itself. By analyzing the multi-dimensional financial indicator data of each operation node in the sand table model, those nodes that deviate from the normal range or reach the risk warning threshold are screened out and determined as risk operation nodes. The preset mapping table of operation node accounts records the corresponding relationships between each operation node and specific accounting accounts. When a risk operation node is determined, by looking up this mapping table, the accounting accounts related to this risk operation node can be clarified, and these accounts are the risk accounts. For example, if there is a risk of capital backlog in a certain operation node, it may be found through the mapping table that " Inventory ” and other related accounts correspond to it, then " Inventory ”It becomes a risk subject. In the pre-set intermediate table of financial voucher entries, detailed financial voucher information of all business operations of the enterprise is stored. Using the risk subject identifier corresponding to the risk subject as the retrieval condition, a matching operation is performed in this table. In this way, all financial vouchers involving the risk subject are found, and these vouchers are the risk financial vouchers. For example, if the risk subject is "accounts receivable" ” , then search in the intermediate table of financial voucher entries for all vouchers involving " accounts receivable ” subject. These vouchers may record situations such as the failure to recover funds in a timely manner in sales operations. By analyzing the risk financial vouchers, it is possible to deeply understand the specific business activities and transactions that lead to risks in the risk operation nodes. The financial vouchers detail information such as the occurrence time, amount, and transaction object of the business. By sorting out this information, the source of the risk can be traced. If it is found that a certain risk financial voucher records a large-scale credit sales business and the funds have not been recovered for a long time, resulting in an increase in accounts receivable and thus triggering a capital risk in the relevant operation node, then this credit sales business is an important source of the risk.

[0062] Through the above technical solution, from the complex enterprise operation data, layer by layer, accurately find the specific business and subjects that lead to risks in the operation nodes, providing a clear direction for solving the capital risk problem, avoiding blind investigation when the enterprise faces risks, and saving a large amount of human, material, and time costs; through node risk tracing, the weak links in the enterprise's capital management and business operation processes can be clearly recognized.

[0063] After generating the capital flow sand table models corresponding to multiple operation nodes, the method further includes: under the specified trigger of the user for the target risk operation node, screening the specified associated operation nodes with inflow and outflow relationships in this capital flow sand table model; according to the inflow and outflow relationships between the specified associated operation nodes and the target risk operation node, conducting a risk flow tracing display of the risk source and risk flow.

[0064] In an embodiment of this specification, when the user designates a target risk operation node in the capital flow sand table model, other operation nodes with inflow and outflow relationships are screened based on the pre-set node connection relationships and capital flow logics in the model. In the sand table model of the enterprise's capital operation, each operation node is interconnected through the flow of funds. Once the target risk operation node is determined, the system will quickly retrieve the nodes with direct or indirect capital transactions with it, and these retrieved nodes are the specified associated operation nodes.

[0065] After screening out the specified associated operating nodes, the sources and flows of risks will be further sorted out and presented based on the inflow and outflow relationships between these nodes and the target risk operating nodes. By analyzing the flow paths of funds and relevant business data, it is clarified from which associated nodes the risks flow into the target risk operating nodes, and to which other nodes the risks of the target risk operating nodes will flow. The visual display method of risk flow traceability greatly improves the efficiency of an enterprise in identifying and handling risks. Compared with the traditional method of manually analyzing and checking risks, it can locate the risk source and the possible scope of influence faster, saving a large amount of time and labor costs.

[0066] Based on this fund flow sand table model, fund liquidity prediction analysis is carried out, specifically including: obtaining target prediction information, where the target prediction information includes a target operating node and index adjustment data corresponding to the target operating node; in the fund flow sand table model, obtaining the target associated accounts corresponding to the target operating node, adjusting the specified values of the target associated accounts according to the index adjustment data, and performing propagation prediction along the connection lines of the target operating node in the fund flow sand table model to determine predicted fund flow data.

[0067] In an embodiment of this specification, when carrying out fund liquidity prediction analysis, first, the goals and relevant adjustment information of the prediction need to be clarified. The target operating node in the target prediction information is a specific operation link node selected by the enterprise according to its own focus of attention. The index adjustment data is the change setting of the relevant indexes of the target operating node based on factors such as enterprise business strategy adjustment and market environment change. The fund flow sand table model details the corresponding relationships between each operating node and accounting accounts. After determining the target operating node, the corresponding target associated accounts can be quickly obtained. These associated accounts reflect the fund income and expenditure items involved in this operating node. Subsequently, according to the obtained index adjustment data, the specified values of the target associated accounts are adjusted. Funds flow between each operating node of the enterprise according to a certain logic and path, and this flow relationship is reflected by the connection lines in the fund flow sand table model. After adjusting the values of the target associated accounts, the impact of the adjustment will spread in the model along the connection lines of the target operating node. According to the preset fund flow rules and algorithms, simulate the flow process of the adjusted funds between each node, comprehensively consider factors such as the fund inflow and outflow relationships and turnover time of each node, predict the fund status of each operating node at different time points after the adjustment, and finally determine the predicted fund flow data.

[0068] By simulating the cash flow under different business strategies (such as adjusting product prices, expanding production scale, expanding new markets, etc.), we can intuitively see the impact of these decisions on cash flow, evaluate the feasibility and potential risks of decisions, and make more scientific and reasonable strategic choices; when deciding whether to launch a new product, using this predictive analysis technology, we can know in advance the capital demand and recovery of new product research and development, production, and sales, and judge whether the company's funds can support the project, avoiding blind decisions that lead to a break in the capital chain.

[0069] Through the above technical solution, the traditional analysis method relies on fixed templates and is difficult to conduct in-depth analysis for specific scenarios. However, the embodiment of this specification can accurately focus and locate the problem by obtaining the demand information including the target analysis organization and timestamp, thus avoiding the traditional method. " One size fits all ” The extensive management mode; in the face of the problem of complicated data dimensions, the traditional method only relies on the balance sheet of accounting subjects, which cannot fully reflect the dynamics of funds. The embodiment of this specification matches the intermediate table of the balance sheet of accounts and the intermediate table of financial voucher entries, integrates the data of operation nodes and business types, and can not only understand the current status of procurement funds, but also trace the process of fund flow, and fully grasp the dynamic changes of funds in the procurement link, overcoming the defects of isolated data and inability to reflect the full picture of funds in the traditional method; the traditional fund liquidity analysis is limited to fixed analysis templates, and it is difficult to deeply analyze the fund situation, while the embodiment of this specification presets multiple financial indicator dimensions to determine multi-dimensional financial indicator data. At the moment when risk transmission is accelerating, these indicators can evaluate funds from multiple levels; the traditional visualization method is limited to two-dimensional reports, lacking the dynamic flow display between data, while the embodiment of this specification generates a fund flow sandbox model through sandbox modeling, presents the fund flow with intuitive graphics, and solves the dilemma of insufficient data visualization and difficulty in discovering fund flow problems in the traditional method; the traditional analysis method has poor data timeliness, and risk warning lags behind business changes, while the embodiment of this specification conducts risk analysis based on the sandbox model, which can simulate different scenarios to predict risks, make up for the defects of the lag of risk warning in the traditional method, and ensure financial stability.

[0070] The present specification also provides a fund liquidity analysis device based on the operation process, such as Figure 3 As shown, the device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above method.

[0071] The embodiments of the present specification also provide a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured to execute the above method.

[0072] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the embodiments of devices, equipment, and non-volatile computer storage media, since they are basically similar to the method embodiments, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the method embodiments.

[0073] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] The devices and media provided by the embodiments of this specification correspond one-to-one with the methods. Therefore, the devices and media also have beneficial technical effects similar to those of their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be elaborated here.

[0075] Those skilled in the art should understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, this specification can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0076] This specification is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0077] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes Figure 1 or blocks of one or more processes and / or Figure 1 blocks or blocks of one or more blocks.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, such that a series of operational steps are performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes Figure 1 or blocks of one or more processes and / or Figure 1 blocks or blocks of one or more blocks.

[0079] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0080] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

[0081] Computer-readable media includes permanent and non-permanent, removable and non-removable media implemented by any method or technology for information storage. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0082] It should also be noted that the terms " include ” , " contain ”Or any other variation is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, article, or apparatus. Without more limitations, a statement " comprising an ……” element defined does not preclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0083] The foregoing is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A method for analyzing the capital liquidity based on the operation process, characterized in that, The method includes: Obtaining the information on the demand for capital liquidity analysis triggered by the user, where the information on the demand for capital liquidity analysis includes the target analysis organization and the target analysis timestamp; Based on the information on the demand for capital liquidity analysis, matching the corresponding intermediate table of the account balance sheet and the intermediate table of the financial voucher entries, where the intermediate table of the account balance sheet includes operating node information, and the intermediate table of the financial voucher entries includes business types; According to the intermediate table of the account balance sheet and the intermediate table of the financial voucher entries, determining the multi-dimensional financial index data corresponding to each operating node according to a preset plurality of financial index dimensions; Through the preset node index value table and the operating node connection line table, performing sand table modeling according to the multi-dimensional financial index data to generate a capital flow sand table model corresponding to a plurality of operating nodes, so as to perform capital liquidity prediction risk analysis based on the capital flow sand table model.

2. The method for analyzing the capital liquidity based on the operation process according to claim 1, wherein According to the intermediate table of the account balance sheet and the intermediate table of the financial voucher entries, determining the multi-dimensional financial index data corresponding to each operating node according to a preset plurality of financial index dimensions, specifically including: Establishing the association relationship between the intermediate table of the account balance sheet and the accounting subjects through the pre-constructed operating node subject mapping table and the operating node information in the intermediate table of the account balance sheet; Taking data from the intermediate table of the account balance sheet according to the association relationship to determine the account balance data, and obtaining the predefined financial index calculation method; Determining the multi-dimensional financial index data corresponding to the operating node through the account balance data and the financial index calculation method.

3. The method for analyzing the capital liquidity based on the operation process according to claim 1, characterized in that Through the preset node index value table and the operating node connection line table, performing sand table modeling according to the multi-dimensional financial index data to generate a capital flow sand table model corresponding to a plurality of operating nodes, specifically including: Parsing the operating node connection line table to obtain the flow topology rule information corresponding to the capital flow between nodes, where the flow topology rule information includes the flow direction; Parsing the node index value table to determine the node index reference data corresponding to each operating node; Determining the sand table node display parameters according to the node index reference data and the multi-dimensional financial index data, where the sand table node display parameters include the node size and the node color parameter; Performing sand table modeling through the flow topology rule information and the sand table node display parameters to generate a capital flow sand table model corresponding to a plurality of operating nodes.

4. The method for analyzing the capital liquidity based on the operation process according to claim 3, wherein, Determining the sand table node display parameters according to the node index reference data and the multi-dimensional financial index data, specifically including: Converting the multi-dimensional financial index data into the capital scale according to a preset conversion method to obtain the actual occurrence scale corresponding to each sand table node, and setting the node size through the actual occurrence scale; Determining the node deviation index corresponding to each sand table node according to the node index reference data and the multi-dimensional financial index data, so as to set the node color parameter based on the node deviation index.

5. The method for analyzing the capital liquidity based on the operation process according to claim 3, wherein Parsing the operating node connection line table to obtain the flow topology rule information corresponding to the capital flow between nodes, specifically including: Match the operation node connection line table corresponding to each operation node through the operation node identifier corresponding to each operation node; Obtain the source node identifier and destination node identifier in the operation node connection line table, and determine the corresponding flow direction of the fund flow between the nodes according to the source node identifier and the destination node identifier.

6. The method for analyzing the capital liquidity based on the operation process according to claim 1, wherein Based on the fund flow sand table model, perform risk analysis of fund liquidity prediction, specifically including: Obtain target prediction information, where the target prediction information includes a target operation node and index adjustment data corresponding to the target operation node; In the fund flow sand table model, obtain the target associated account corresponding to the target operation node, adjust the specified value of the target associated account with the index adjustment data, and perform propagation prediction along the connection line of the target operation node in the fund flow sand table model to determine the predicted fund flow data.

7. The method for analyzing the capital liquidity based on the operation process according to claim 1, characterized in that, After generating the fund flow sand table models corresponding to multiple operation nodes, the method further includes: Determine at least one risk operation node of the fund flow sand table model, and determine the risk account according to the risk operation node and the pre-set operation node account mapping table; Match the financial vouchers in the pre-set intermediate table of financial voucher entries with the risk account identifier corresponding to the risk account to determine the risk financial vouchers, and trace the node risks of the risk operation nodes.

8. A method for analyzing the capital liquidity based on the operation process according to claim 1, characterized in that After generating the fund flow sand table models corresponding to multiple operation nodes, the method further includes: Under the specified trigger of the user for the target risk operation node, screen the specified associated operation nodes with inflow and outflow relationships in the fund flow sand table model; According to the inflow and outflow relationships between the specified associated operation nodes and the target risk operation node, perform risk flow traceability display on the risk source and risk flow direction.

9. An equipment for analyzing the capital liquidity based on the operation process, characterized in that, The device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1-8.

10. A non - volatile computer storage medium stores computer - executable instructions, characterized in that, The computer-executable instructions are set to: execute the method according to any one of claims 1-8.

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