Business outlet post-evaluation method, device, equipment, medium and program product

Abstract

The invention provides a post-evaluation method for a business network. The post-evaluation method can be applied to the fields of cloud computing and Internet of Things. The method comprises the steps of obtaining multi-dimensional index data of a business network in response to a full payback period of the business network; performing differentiation division on the types of the business outlets, and extracting influence factors of the multi-dimensional index data; for different types of business outlets, according to the multi-dimensional index data and the influence factors, calculating an actual accumulated net present value of the business outlets within a preset time width by using a customized post-evaluation model; and carrying out comparative analysis on the actual accumulated net present value and the expected accumulated net present value to obtain an evaluation result of the business network. The invention further provides a device and equipment for post-evaluation of the business outlets, a storage medium and a program product.

Description

Technical Field

[0001] The present disclosure relates to the fields of cloud computing and the Internet of Things, and more specifically to a method, device, equipment, medium, and program product for post-evaluation of business outlets. Background Art

[0002] In the financial industry, the construction of business outlets is an important strategic measure for financial institutions to expand their business and serve customers. However, with the intensification of market competition and the increasing diversification of customer needs, it is difficult to accurately grasp and continuously optimize the operating efficiency of business outlets by relying solely on traditional evaluation methods. In particular, after the outlets have been operating for a period of time, when the investment recovery period expires, a comprehensive and in-depth evaluation of the operating results of the outlets becomes particularly important. At present, the common post-evaluation methods of business outlets often have the following limitations: First, the data dimension is single, ignoring the comprehensive consideration of multi-dimensional information; second, there is a lack of unified management and control, and the data standards, collection methods and analysis methods between different outlets and different departments are different, making it difficult to form a unified and comparable evaluation result; third, the evaluation method is lagging behind, and the post-analysis method is mostly used, lacking the ability to monitor the operation process in real time and dynamically adjust. Summary of the invention

[0003] In view of the above problems, embodiments of the present disclosure provide a method, apparatus, device, medium and program product for post-evaluation of business outlets.

[0004] According to a first aspect of the present disclosure, a method for post-evaluation of business outlets is provided, the method comprising: in response to the full payback period of the business outlets, obtaining multi-dimensional indicator data of the business outlets; performing differentiated classification on the types of the business outlets, and extracting influencing factors of the multi-dimensional indicator data; for different types of the business outlets, calculating the actual cumulative net present value of the business outlets within a preset time window using a customized post-evaluation model based on the multi-dimensional indicator data and the influencing factors; comparing and analyzing the actual cumulative net present value with the expected cumulative net present value to obtain an evaluation result of the business outlets.

[0005] According to an embodiment of the present disclosure, the actual cumulative net present value is compared and analyzed with the expected cumulative net present value to obtain an evaluation result of the business outlet, including: judging whether the actual cumulative net present value is greater than 0; when the actual cumulative net present value is greater than 0, judging whether the actual cumulative net present value is greater than X% of the expected cumulative net present value, where X is a positive number greater than or equal to 0; in response to the actual cumulative net present value being greater than X% of the expected cumulative net present value, judging that the business outlet has met the standards.

[0006] According to an embodiment of the present disclosure, the differentiated classification of the types of the business outlets includes: classifying the types of the business outlets based on the operating hours and facility conditions of the business outlets, wherein the types of the business outlets include at least newly established, relocated and on-site renovated types.

[0007] According to an embodiment of the present disclosure, the method further includes: based on the type of the business outlets, performing differentiated settings on the investment payback period of the business outlets, and performing differentiated calculations on the multi-dimensional indicator data.

[0008] According to an embodiment of the present disclosure, the method also includes: based on the multi-dimensional indicator data of the historical time period of the business outlets, using the pre-trained post-evaluation model to predict the expected cumulative net present value of the business outlets; when the difference between the expected cumulative net present value and the actual cumulative net present value is greater than a first specified threshold, adjusting the parameters and structure of the post-evaluation model until the difference between the output of the post-evaluation model and the actual cumulative net present value is less than or equal to the first specified threshold.

[0009] According to an embodiment of the present disclosure, the extracting of the influencing factors of the multidimensional indicator data includes: performing a sensitivity analysis on the multidimensional indicator data to obtain the influencing factors, wherein the multidimensional indicator data includes operating income, operating expenses, depreciation, amortization, internal management expenses, corporate income tax, discount rate and initial investment amount.

[0010] According to an embodiment of the present disclosure, for the different types of business outlets, based on the multidimensional indicator data and the influencing factors, a customized post-evaluation model is used to calculate the actual cumulative net present value of the business outlets within a preset time window, including: determining the weight of each influencing factor in the post-evaluation model based on the degree of influence of each influencing factor on the multidimensional indicator data; adjusting the post-evaluation model based on the multidimensional indicator data and the influencing factors and their weights; inputting the multidimensional indicator data, the influencing factors and the corresponding weights into the adjusted post-evaluation model to obtain the actual cumulative net present value of the business outlets within the preset time window.

[0011] A second aspect of the present disclosure provides a device for post-evaluation of business outlets, the device comprising: an acquisition module, for acquiring multi-dimensional indicator data of the business outlets in response to the full investment payback period of the business outlets; a classification module, for performing differentiated classification of the types of the business outlets and extracting influencing factors of the multi-dimensional indicator data; a calculation module, for calculating, for different types of the business outlets, the actual cumulative net present value of the business outlets within a preset time window according to the multi-dimensional indicator data and the influencing factors, using a customized post-evaluation model; and an evaluation module, for comparing and analyzing the actual cumulative net present value with the expected cumulative net present value to obtain an evaluation result of the business outlets.

[0012] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above method.

[0013] The fourth aspect of the present disclosure further provides a computer-readable storage medium having a computer program or instructions stored thereon, which implements the steps of the above method when the above computer program or instructions are executed by a processor.

[0014] The fifth aspect of the present disclosure further provides a computer program product, including a computer program or instructions, which implement the steps of the above method when the above computer program or instructions are executed by a processor.

[0015] According to the method, device, equipment, medium and program product for post-evaluation of business outlets provided by the embodiments of the present disclosure, the net present value analysis method is used to measure the input-output situation of the business outlets, and multi-dimensional indicator data is introduced to more comprehensively understand the operating conditions of each outlet. At the same time, differentiated treatment is performed for different types of business outlets, and the key influencing factors of each type of outlet in operation are identified, so that differentiated management strategies can be implemented for different types of outlets, and more accurate measurement of business outlets is achieved. In addition, the post-evaluation model is used, combined with multi-dimensional indicator data and its influencing factors, to calculate the actual cumulative net present value within the preset time window, which can more accurately reflect the actual operating results of the business outlets. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0017] Figure 1 A diagram schematically shows an application scenario of the method, device, equipment, medium and program product for post-evaluation of business outlets according to an embodiment of the present disclosure;

[0018] Figure 2A flowchart schematically shows a method for post-evaluation of business outlets according to an embodiment of the present disclosure;

[0019] Figure 3 Schematically showing a flow chart of post-evaluation of different types of business outlets according to an embodiment of the present disclosure;

[0020] Figure 4 A structural block diagram schematically shows a device for post-evaluation of business outlets according to an embodiment of the present disclosure; and

[0021] Figure 5 A block diagram of an electronic device suitable for implementing a method for post-evaluation of a business outlet according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0022] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0023] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0024] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0025] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0026] It should be noted that the method and device for post-evaluation of business outlets determined in the present disclosure can be used in the financial field, information security and cloud computing fields, and can also be used in any field other than the financial field. The application field of the method and device for post-evaluation of business outlets determined in the present disclosure is not limited.

[0027] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0028] In the technical solution of the present disclosure, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0029] In the scenario of using personal information for automated decision-making, the methods, devices, and systems provided by the embodiments of the present disclosure provide users with corresponding operation portals for users to choose to agree or reject the automated decision-making results; if the user chooses to reject, the expert decision-making process will be entered. The expression "automated decision-making" here refers to the activity of automatically analyzing and evaluating a person's behavioral habits, interests and hobbies, or economic, health, credit status, etc. through computer programs, and making decisions. The expression "expert decision-making" here refers to the activity of making decisions by people who specialize in a certain field, have specialized experience, knowledge and skills, and have reached a certain level of professionalism.

[0030] Embodiments of the present disclosure provide a method, apparatus, device, medium, and program product for post-evaluation of business outlets.

[0031] Figure 1 The application scenario diagram of the method, apparatus, device, medium and program product for post-evaluation of business outlets according to an embodiment of the present disclosure is schematically shown.

[0032] like Figure 1 As shown, the application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0033] The user can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0034] The first terminal device 101, the second terminal device 102, and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0035] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0036] It should be noted that the business outlet post-evaluation method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the business outlet post-evaluation device provided in the embodiment of the present disclosure can generally be set in the server 105. The business outlet post-evaluation method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the business outlet post-evaluation device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0037] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0038] First, the technical terms described in this article are explained and described as follows.

[0039] Outlet: refers to an institution in the financial industry that provides financial services to the outside world.

[0040] Post-business outlet evaluation: refers to the input-output measurement of the project in the initial stage of business outlet establishment, and the verification of operating results after the investment recovery period is completed.

[0041] Discount rate: refers to the rate of return on capital in the annual comprehensive operating plan.

[0042] Net Present Value: refers to the difference between the present value of future cash inflows (income) and the present value of future cash outflows (expenditure).

[0043] Cumulative net present value: refers to the accumulated net present value of different years.

[0044] Cash inflow: refers to all capital income generated by an investment project.

[0045] Cash outflow: refers to all capital expenditures incurred by an investment project.

[0046] The following will be based on Figure 1 The scene described by Figure 2 and Figure 3 The method for post-evaluation of business outlets in an embodiment of the present disclosure is described in detail.

[0047] Figure 2 The flowchart of the method for post-evaluation of business outlets according to an embodiment of the present disclosure is schematically shown.

[0048] like Figure 2 As shown, the business outlet post-evaluation method of this embodiment includes operations S210 to S240.

[0049] In operation S210, in response to a business outlet reaching a full payback period, multi-dimensional indicator data of the business outlet is obtained.

[0050] In an embodiment of the present disclosure, before obtaining the multi-dimensional indicator data of the business outlets, the consent or authorization of the person in charge (user) of the business outlets may be obtained. For example, before operation S210, a request to obtain the multi-dimensional indicator data of the business outlets may be sent to the person in charge. When the user agrees or authorizes that the multi-dimensional indicator data of the business outlets can be obtained, the operation S210 is performed.

[0051] In operation S220, the types of the business outlets are differentiated and the influencing factors of the multi-dimensional indicator data are extracted.

[0052] In operation S230, for different types of business outlets, the actual cumulative net present value of the business outlets within a preset time window is calculated using a customized post-evaluation model based on the multi-dimensional indicator data and the influencing factors.

[0053] In operation S240, the actual cumulative net present value is compared and analyzed with the expected cumulative net present value to obtain an evaluation result of the business outlet.

[0054] In the embodiments of the present disclosure, a corresponding operation portal may be provided for the user to choose to agree or reject the automated decision result. That is, before the actual cumulative net present value is compared and analyzed with the expected cumulative net present value for processing / decision making, an instruction for agreeing or rejecting the processing / decision making inputted by the user through the corresponding operation portal may be obtained. If the user agrees to make the processing / decision making, the actual cumulative net present value is compared and analyzed with the expected cumulative net present value for processing / decision making, i.e., step S240 is executed. If the user rejects the processing / decision making, the expert decision making process is entered.

[0055] In some exemplary embodiments, sufficient multi-dimensional indicator data is first collected to comprehensively evaluate the operating status of the business outlets and provide a data basis for subsequent analysis. In addition, to ensure the accuracy, completeness and consistency of the data, the outliers in the multi-dimensional indicator data are processed, and the data from different sources are integrated into a unified analysis platform or database. At the same time, since different types of business outlets (such as flagship stores, community stores and online platforms, etc.) differ in terms of operating models, target customer groups and resource investment, the types of business outlets are differentiated, and the influencing factors with different degrees of influence on the multi-dimensional indicator data are extracted. Then, a reasonable analysis time period is determined based on factors such as business cycles and changes in the market environment, that is, a preset time window (such as 1 year, 2 years, 5 years, etc.), and the actual cumulative net present value of the business outlets within the preset time window is calculated using the post-evaluation model constructed according to different types of business outlets to evaluate the economic benefits of the business outlets in a specific time period and reflect their return on investment. Finally, the actual cumulative net present value is compared and analyzed with the expected cumulative net present value to evaluate whether the actual operating results of the business outlets have achieved the expected goals, and to conduct in-depth analysis of the reasons for the differences, such as changes in the market environment, internal management problems, and improper resource allocation.

[0056] It is understandable that the disclosed embodiment provides rich and comprehensive data support for the evaluation by introducing multi-dimensional indicator data and influencing factors related to the multi-dimensional indicator data. At the same time, the differentiated classification of business outlets helps to more accurately grasp the characteristics and needs of various types of outlets, thereby formulating more targeted evaluation standards and optimization measures, and improving the pertinence and effectiveness of the evaluation. In addition, the actual cumulative net present value of the business outlets is calculated through the post-evaluation model, and the expected cumulative net present value is predicted, which realizes a more accurate evaluation of the performance of the business outlets and promotes the reasonable prediction of the income and cost of the outlets by financial institutions.

[0057] In an embodiment of the present disclosure, extracting the influencing factors of the multidimensional indicator data includes: performing a sensitivity analysis on the multidimensional indicator data to obtain the influencing factors, wherein the multidimensional indicator data includes operating income, operating expenses, depreciation, amortization, internal management expenses, corporate income tax, discount rate and initial investment amount.

[0058] Specifically, sensitivity analysis is performed on the selected multi-dimensional indicator data, such as analyzing the factors that affect operating income. In this process, a series of possible influencing factors are first selected, such as product sales, sales price, market share, customer satisfaction, and sales channel efficiency, and the time range of the analysis is set to ensure the timeliness and pertinence of the analysis results. Then, for the above possible influencing factors, detailed historical data and current data are collected, and a series of change scenarios are set. These scenarios can include individual changes in a single factor (such as a 10% increase in product sales) or combined changes in multiple factors (such as a 10% increase in product sales and a 5% decrease in sales price). By simulating these change scenarios, the change trend of operating income under different circumstances is observed. Then, statistical software or modeling tools are used to perform sensitivity analysis on the set change scenarios, calculate the change range and change rate of operating income under each scenario, quantify the degree of influence of each influencing factor on operating income, and finally identify and determine the influencing factors that have a key impact on operating income.

[0059] In some exemplary embodiments, the collected multi-dimensional indicator data include but are not limited to operating income, operating expenses, depreciation, amortization, internal management fees, corporate income tax, discount rate and initial investment amount. Among them, depreciation refers to the cost of systematically allocating the accrued depreciation amount according to a determined method within the service life of a fixed asset. Amortization refers to the cost of allocating the purchase cost of other operating assets that can be used for a long time in addition to fixed assets according to their useful life. Internal management fees refer to various expenses incurred in an enterprise for organizing and managing production and business activities. Corporate income tax is an income tax levied on production and business income and other income of enterprises and other organizations that obtain income in China. Operating expenses refer to all expenses incurred by circulation enterprises in the course of operation except operating costs. Operating income refers to a kind of income obtained by commodity producers and operators in production, operation and management activities, including net interest income, net handling fees and commission income, and other non-interest income. Initial investment amount: refers to the cost invested in the initial preparation of business outlets, including the cost of purchasing, decorating and supporting equipment of real estate.

[0060] It is understandable that the results of sensitivity analysis and the identification of key influencing factors are crucial to the formulation of effective management strategies and resource allocation decisions. In addition, multi-dimensional indicator data provides a rich source of information for the comprehensive evaluation of business outlets. Through in-depth analysis of these data, the operating status, profitability, cost control capabilities, development trends and potential problems of the outlets can be more accurately grasped, thereby providing strong data support for subsequent differentiated processing strategies and accurate evaluation decisions.

[0061] Furthermore, the differentiated classification of the types of the business outlets includes: classifying the types of the business outlets based on the operating hours and facility conditions of the business outlets, wherein the types of the business outlets at least include newly established types, relocated types, and on-site renovation types.

[0062] Specifically, the types of business outlets can be divided according to the dimensions of geographical location, target customers, business scale, product / service types, and operation mode. In the process of division, statistical methods such as cluster analysis and decision trees can be used, combined with expert opinions, to determine the optimal classification scheme.

[0063] For example, based on the operating time and facility conditions, outlets are divided into newly established, relocated and renovated outlets. Newly established outlets are those that have been recently established; relocated outlets refer to outlets that have changed their business addresses; and renovated outlets refer to outlets that have undergone overall renovation at their original business addresses.

[0064] It is understandable that different types of business outlets have significant differences in terms of input costs, operating cycles and expected returns. Through differentiated classification, the initial investment, renovation costs, relocation costs and operating and maintenance costs of each type of outlet can be estimated more accurately, so that these differences can be taken into account when calculating the net present value, making the evaluation results more accurate and reliable. In addition, after the post-evaluation of business outlets, targeted measures can be formulated for different types of business outlets to improve resource utilization efficiency and reduce unnecessary waste.

[0065] In an embodiment of the present disclosure, the method further includes: based on the type of the business outlets, performing differentiated settings on the investment payback period of the business outlets, and performing differentiated calculations on the multi-dimensional indicator data.

[0066] Specifically, in order to more accurately count the input-output situation of business outlets, differentiated treatment is implemented for different types of business outlets. In terms of differentiated calculation of multi-dimensional indicator data, for newly established business outlets, since they are in the initial stage, the operating income and operating expenses can be directly taken from the data of the outlet in that year. For outlets that have been relocated or renovated at the original site, since they have inherited the original business and customer base to a certain extent, it is necessary to adopt an incremental method when calculating operating income and operating expenses. Specifically, the operating income needs to deduct the net interest income (or other related income) of the base period to reflect the additional income brought by the relocation or renovation, and the operating expenses also need to deduct the operating expenses of the corresponding year to reflect the additional expenses during the relocation or renovation process. In addition, the payback period is an important indicator to measure the time required for an investment project to recover the initial investment cost. For different types of business outlets, due to differences in their investment scale, operation model, market environment and other factors, their payback periods should also be different. For example, since the establishment of new outlets usually requires a large initial investment, including site rental, decoration, equipment purchase and personnel training, and it takes a certain amount of time to accumulate customers and develop business in the initial stage, its investment recovery period is relatively long. Although relocation outlets also involve certain relocation costs and possible decoration costs, their investment recovery period is relatively short due to the relative stability of their original customer base and service processes. For outlets that are fully renovated at the original site, their investment is mainly concentrated on decoration and facility upgrades, and the impact on daily operations is relatively small. Therefore, their investment recovery period may be between that of new and relocated outlets. It should be noted that the business department can also personalize the investment recovery period according to specific circumstances to better adapt to market changes and internal management needs.

[0067] It is understandable that setting different payback periods for different types of outlets can more accurately reflect their economic benefits and payback speed, avoid a "one-size-fits-all" evaluation method, and improve the accuracy and scientificity of the evaluation. In addition, the differentiated calculation of multi-dimensional indicator data takes into account the operating characteristics and data features of different types of outlets, thus being closer to actual operating conditions and further improving the accuracy of the evaluation results.

[0068] Furthermore, the comparing and analyzing of the actual cumulative net present value with the expected cumulative net present value to obtain the evaluation result of the business outlets includes: judging whether the actual cumulative net present value is greater than 0; when the actual cumulative net present value is greater than 0, judging whether the actual cumulative net present value is greater than X% of the expected cumulative net present value, where X is a positive number greater than or equal to 0; in response to the actual cumulative net present value being greater than X% of the expected cumulative net present value, judging that the business outlets meet the standards.

[0069] Figure 3The flowchart of post-evaluation of different types of business outlets according to an embodiment of the present disclosure is schematically shown.

[0070] like Figure 3 As shown in the figure, for different types of business outlets, after the outlets have completed their payback period, the actual cumulative net present value within the preset time window of the outlets is first calculated based on the actual data, and then compared with the expected cumulative net present value predicted by the financial institution. In this process, the process will make a preliminary judgment on the actual cumulative net present value to determine whether the outlet has achieved profitability. If it has not achieved profitability (that is, the actual cumulative net present value is less than or equal to 0), the evaluation ends. If the actual cumulative net present value is greater than 0, the process will further compare whether it exceeds the expected cumulative net present value by X%. When the outlet meets all the above conditions, the subsequent evaluation results are considered to meet the standards.

[0071] It should be noted that X% is a flexibly set threshold that can be adjusted according to different business strategies, market environments and branch types to achieve a more accurate assessment.

[0072] It can be understood that by comparing whether the actual cumulative net present value is greater than 0 and whether it exceeds the expected cumulative net present value by X%, this dual judgment standard not only takes profitability into account, but also emphasizes the importance of exceeding expectations, thereby enabling a more comprehensive evaluation of the operating performance of the outlets.

[0073] Furthermore, for the different types of business outlets, according to the multidimensional indicator data and the influencing factors, a customized post-evaluation model is used to calculate the actual cumulative net present value of the business outlets within a preset time window, including: determining the weight of each influencing factor in the post-evaluation model based on the degree of influence of each influencing factor on the multidimensional indicator data; adjusting the post-evaluation model based on the multidimensional indicator data and the influencing factors and their weights; inputting the multidimensional indicator data, the influencing factors and the corresponding weights into the adjusted post-evaluation model to obtain the actual cumulative net present value of the business outlets within the preset time window.

[0074] Specifically, the identified influencing factors are quantified using historical data, market research or expert opinions, and converted into calculable values ​​or ratios. Then, based on the quantification results, reasonable weights are assigned to each influencing factor. According to factors such as the business type and data characteristics of the business outlets, a suitable evaluation model is selected, such as a cash flow discount model or an economic profit model, that is, a customized post-evaluation model is selected according to the type of business outlets. After the selection is completed, the selected evaluation model is customized and adjusted according to the determined multi-dimensional indicators and influencing factors and their weights to ensure that the model can accurately reflect the actual situation of the business outlets. Finally, the weighted influencing factors are used as part of the model input, combined with the multi-dimensional indicator data, and jointly input into the adjusted post-evaluation model to obtain the actual cumulative net present value of the business outlets.

[0075] In some exemplary embodiments, if only multi-dimensional indicator data is considered, the post-evaluation model uses the net present value analysis method to calculate the input-output situation of the business outlets. The actual NPV (net present value) calculation formula is as follows:

[0076]

[0077] Among them, CI is the capital inflow, CO is the capital outflow, i c is the discount rate, t is the year, and (CI-CO) is the net cash flow in the tth year.

[0078] The specific calculation is as follows:

[0079] NPV in the first year = [operating income - operating expenses + depreciation + amortization - internal management fees - corporate income tax] / (1 + discount rate) - initial investment amount

[0080] NPV in the second year = [operating income - operating expenses + depreciation + amortization - internal management fees - corporate income tax] / (1 + discount rate) / (1 + discount rate)

[0081] NPV in the third year = [operating income - operating expenses + depreciation + amortization - internal management fees - corporate income tax] / (1 + discount rate) / (1 + discount rate) / (1 + discount rate)

[0082] NPV in the fourth year = [operating income - operating expenses + depreciation + amortization - internal management fees - corporate income tax] / (1 + discount rate) / (1 + discount rate) / (1 + discount rate) / (1 + discount rate)

[0083] …

[0084] NPV in year t = [operating income - operating expenses + depreciation + amortization - internal management fees - corporate income tax] / (1 + discount rate) / (1 + discount rate) / (1 + discount rate) / (1 + discount rate) / ...

[0085] Cumulative NPV = NPV of the first year + NPV of the second year + NPV of the third year + NPV of the fourth year + … + NPV of the tth year

[0086] It should be noted that the net present value calculation method provided in the embodiment of the present disclosure takes operating income, depreciation and amortization as the capital inflow in the tth year, operating expenses, internal management expenses and corporate income tax as the capital outflow in the tth year, and converts the capital inflow in the tth year into present value. At the same time, the initial investment amount is deducted only from the NPV in the first year during the calculation.

[0087] It is understandable that the net present value calculation method of the embodiment of the present disclosure not only comprehensively uses multi-dimensional indicator data, so that the calculation process comprehensively considers various factors that affect the operating results of the outlets, but also converts the net cash flow of each time period to the starting point of the preset time window according to the discount rate, ensuring that the cash flow of different time periods can be reasonably compared and summarized, and finally accurately quantifying the actual operating results of the business outlets within the preset time window, accurately reflecting the profitability of the outlets. In addition, by incorporating influencing factors into the net present value calculation model, the method of the embodiment of the present disclosure can more comprehensively capture the subtle differences and potential risks that affect the operating results of the business outlets.

[0088] In an embodiment of the present disclosure, the method also includes: based on the multi-dimensional indicator data of the business outlets in the historical time period, using the post-evaluation model to predict the expected cumulative net present value of the business outlets; when the difference between the expected cumulative net present value and the actual cumulative net present value is greater than a first specified threshold, adjusting the parameters and structure of the post-evaluation model until the difference between the output of the post-evaluation model and the actual cumulative net present value is less than or equal to the first specified threshold.

[0089] Specifically, based on the multi-dimensional indicator data of the business outlets in the historical time period, a post-evaluation model is pre-trained using machine learning or statistical learning methods. The model can predict the expected cumulative net present value of the business outlets in the future period according to the changing trends and laws of historical data. At the same time, in order to ensure the accuracy of the prediction, the output of the post-evaluation model (i.e., the expected cumulative net present value) is compared and analyzed with the actual cumulative net present value calculated later. When the difference between the two is greater than the first specified threshold, it indicates that the post-evaluation model may have deviations or deficiencies. At this time, the parameters and structure of the post-evaluation model are adjusted according to the feedback results, including but not limited to reselecting the algorithm, adjusting the hyperparameters, and introducing new feature variables, until the difference between the output of the model and the actual value is reduced to an acceptable range (i.e., less than or equal to the first specified threshold), thereby optimizing the model.

[0090] Furthermore, after post-evaluating the business outlets based on the expected cumulative net present value predicted by the post-evaluation model and the actual cumulative net present value, targeted improvement measures and development plans are formulated according to the evaluation results, such as optimizing resource allocation, adjusting market strategies or improving service quality. At the same time, the strategies are converted into specific action plans, and a monitoring mechanism is established to regularly evaluate the implementation effects and adjust the strategies in a timely manner.

[0091] It is understandable that using the post-evaluation model to predict the expected cumulative net present value of business outlets, in this process, constantly adjusting the parameters and structure of the post-evaluation model to make it more in line with the changing patterns of actual data, can significantly improve the accuracy of predicting the future cumulative net present value, thereby helping financial institutions to more accurately grasp the operating conditions and profitability of business outlets and improve the scientificity and rationality of decision-making.

[0092] Based on the above-mentioned business outlet post-evaluation method, the present disclosure also provides a business outlet post-evaluation device. Figure 4 The device is described in detail.

[0093] Figure 4 The structural block diagram of the device for post-evaluation of business outlets according to an embodiment of the present disclosure is schematically shown.

[0094] like Figure 4 As shown, the device 400 for post-evaluation of business outlets in this embodiment includes an acquisition module 410 , a division module 420 , a calculation module 430 and an evaluation module 440 .

[0095] The acquisition module 410 is used to acquire multi-dimensional indicator data of the business outlet in response to the business outlet reaching the full investment payback period. In one embodiment, the acquisition module 410 can be used to perform the operation S210 described above, which will not be described in detail here.

[0096] The classification module 420 is used to differentiate the types of the business outlets and extract the influencing factors of the multi-dimensional indicator data. In one embodiment, the grouping module 420 can be used to perform the operation S220 described above, which will not be repeated here.

[0097] The calculation module 430 is used to calculate the actual cumulative net present value of the business outlets within a preset time window according to the multi-dimensional indicator data and the influencing factors for different types of business outlets using a customized post-evaluation model. In one embodiment, the loading module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0098] The evaluation module 440 is used to compare and analyze the actual cumulative net present value with the expected cumulative net present value to obtain the evaluation result of the business outlet. In one embodiment, the comparison module 440 can be used to perform the operation S240 described above, which will not be repeated here.

[0099] According to an embodiment of the present disclosure, the evaluation module 440 is specifically used to: determine whether the actual cumulative net present value is greater than 0; when the actual cumulative net present value is greater than 0, determine whether the actual cumulative net present value is greater than X% of the expected cumulative net present value, where X is a positive number greater than or equal to 0; in response to the actual cumulative net present value being greater than X% of the expected cumulative net present value, determine that the business outlets meet the standards.

[0100] According to an embodiment of the present disclosure, the classification module 420 is specifically used to classify the types of the business outlets based on the operating hours and facility conditions of the business outlets, wherein the types of the business outlets at least include newly established types, relocated types, and on-site renovation types.

[0101] According to an embodiment of the present disclosure, the division module 420 may also be used to: perform differentiated settings on the investment payback period of the business outlets based on the types of the business outlets, and perform differentiated calculations on the multi-dimensional indicator data.

[0102] According to an embodiment of the present disclosure, the evaluation module 440 can also be used to: based on the multi-dimensional indicator data of the historical time period of the business outlets, use the post-evaluation model to predict the expected cumulative net present value of the business outlets; when the difference between the expected cumulative net present value and the actual cumulative net present value is greater than a first specified threshold, adjust the parameters and structure of the post-evaluation model until the difference between the output of the post-evaluation model and the actual cumulative net present value is less than or equal to the first specified threshold.

[0103] According to an embodiment of the present disclosure, the division module 420 can also be used to: perform sensitivity analysis on the multi-dimensional indicator data to obtain the influencing factors, wherein the multi-dimensional indicator data includes operating income, operating expenses, depreciation, amortization, internal management expenses, corporate income tax, discount rate and initial investment amount.

[0104] According to an embodiment of the present disclosure, the calculation module 430 is specifically used to: determine the weight of each influencing factor in the post-evaluation model based on the degree of influence of each influencing factor on the multidimensional indicator data; adjust the post-evaluation model based on the multidimensional indicator data and the influencing factors and their weights; input the multidimensional indicator data, the influencing factors and the corresponding weights into the adjusted post-evaluation model to obtain the actual cumulative net present value of the business outlets within a preset time window.

[0105] According to an embodiment of the present disclosure, any multiple modules of the acquisition module 410, the partition module 420, the calculation module 430 and the evaluation module 440 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the acquisition module 410, the partition module 420, the calculation module 430 and the evaluation module 440 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in any appropriate combination of any of them. Alternatively, at least one of the acquisition module 410, the partition module 420, the calculation module 430 and the evaluation module 440 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0106] Figure 5 A block diagram of an electronic device suitable for implementing a method for post-evaluation of a business outlet according to an embodiment of the present disclosure is schematically shown.

[0107] like Figure 5As shown, the electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 to a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include an onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0108] In RAM 503, various programs and data required for the operation of electronic device 500 are stored. Processor 501, ROM 502 and RAM 503 are connected to each other via bus 504. Processor 501 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 502 and / or RAM 503. It should be noted that the program can also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0109] According to an embodiment of the present disclosure, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to the bus 504. The electronic device 500 may further include one or more of the following components connected to the input / output (I / O) interface 505: an input portion 506 including a keyboard, a mouse, etc.; an output portion 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 508 including a hard disk, etc.; and a communication portion 509 including a network interface card such as a LAN card, a modem, etc. The communication portion 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage portion 508 as needed.

[0110] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0111] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 502 and / or RAM 503 described above and / or one or more memories other than ROM 502 and RAM 503.

[0112] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the method for post-evaluation of business outlets provided in the embodiment of the present disclosure.

[0113] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 501. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0114] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 509, and / or installed from the removable medium 511. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0115] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the processor 501, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0116] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0117] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0118] It will be appreciated by those skilled in the art that the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations or combinations are not explicitly described in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0119] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for post-evaluation of business outlets, characterized in that: The method comprises: In response to a business outlet reaching a full payback period, obtaining multi-dimensional indicator data of the business outlet; Differentiate the types of the business outlets and extract influencing factors of the multi-dimensional indicator data; For different types of business outlets, the actual cumulative net present value of the business outlets within a preset time window is calculated using a customized post-evaluation model based on the multi-dimensional indicator data and the influencing factors; The actual cumulative net present value is compared and analyzed with the expected cumulative net present value to obtain the evaluation result of the business outlet.

2. The method according to claim 1, characterized in that The comparison and analysis of the actual cumulative net present value and the expected cumulative net present value to obtain the evaluation result of the business outlets includes: Determine whether the actual cumulative net present value is greater than 0; When the actual cumulative net present value is greater than 0, determining whether the actual cumulative net present value is greater than X% of the expected cumulative net present value, where X is a positive number greater than or equal to 0; In response to the actual cumulative net present value being greater than X% of the expected cumulative net present value, it is determined that the business outlet meets the requirements.

3. The method according to claim 1, characterized in that The differentiated classification of the types of the business outlets includes: Based on the operating hours and facility conditions of the business outlets, the types of the business outlets are divided, wherein the types of the business outlets at least include newly established types, relocated types, and original site renovation types.

4. The method according to claim 3, characterized in that The method further comprises: Based on the type of the business outlets, differentiated settings are made for the investment payback period of the business outlets, and differentiated calculations are made for the multi-dimensional indicator data.

5. The method according to claim 1, characterized in that The method further comprises: Based on the multi-dimensional indicator data of the business outlets in the historical time period, using the post-evaluation model, predicting the expected cumulative net present value of the business outlets; When the difference between the expected cumulative net present value and the actual cumulative net present value is greater than a first specified threshold, the parameters and structure of the post-evaluation model are adjusted until the difference between the output of the post-evaluation model and the actual cumulative net present value is less than or equal to the first specified threshold.

6. The method according to claim 1 or 4, characterized in that: The extracting of the influencing factors of the multi-dimensional indicator data includes: Perform a sensitivity analysis on the multi-dimensional indicator data to obtain the influencing factors, wherein the multi-dimensional indicator data includes operating income, operating expenses, depreciation, amortization, internal management expenses, corporate income tax, discount rate and initial investment amount.

7. The method according to claim 6, characterized in that For the different types of business outlets, according to the multi-dimensional indicator data and the influencing factors, using a customized post-evaluation model to calculate the actual cumulative net present value of the business outlets within a preset time window includes: Determining the weight of each of the influencing factors in the post-evaluation model based on the degree of influence of each of the influencing factors on the multi-dimensional indicator data; Adjusting the post-evaluation model based on the multi-dimensional indicator data and the influencing factors and their weights; The multi-dimensional indicator data, the influencing factors and the corresponding weights are input into the adjusted post-evaluation model to obtain the actual cumulative net present value of the business outlets within a preset time window.

8. A device for post-evaluation of business outlets, characterized in that: The device comprises: An acquisition module, configured to acquire multi-dimensional indicator data of a business outlet in response to the business outlet reaching a full investment payback period; A classification module, used to differentiate the types of the business outlets and extract the influencing factors of the multi-dimensional indicator data; A calculation module, for calculating the actual cumulative net present value of the business outlets of different types within a preset time window using a customized post-evaluation model according to the multi-dimensional indicator data and the influencing factors; The evaluation module is used to compare and analyze the actual cumulative net present value with the expected cumulative net present value to obtain an evaluation result of the business outlet.

9. An electronic device, comprising: one or more processors; a storage device for storing one or more computer programs, It is characterized in that when the one or more programs are executed by the one or more processors, the one or more processors execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having executable instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor executes the method according to any one of claims 1 to 7.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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