Discretion management method of ai-based centralized procurement management hub

Abstract

The application relates to the field of procurement governance and artificial intelligence decision support, in particular to a discretionary power governance method of an AI-based centralized procurement governance hub, which carries out discretionary judgment according to business characteristic information of a target business, generates a plurality of discretionary processing paths corresponding to the target business according to the business characteristic information and a preset discretionary rule library in response to a result of the discretionary judgment being that discretion is needed, and carries out path evaluation to obtain a target discretionary path and an evaluation result description. A corresponding permission boundary parameter is configured for the target discretionary path to obtain a target discretionary scheme for governing the target business, and a process of determining the target scheme is recorded and filed for subsequent calling and tracing. The application automatically evaluates whether discretion needs to be started without manual intervention, the evaluation result is objective and has strong reliability. Further, the application automatically carries out business discretion, automatically evaluates and selects a discretionary scheme, improves the discretion efficiency and makes the discretion result interpretable.

Description

Technical Field

[0001] This application relates to the fields of procurement governance and artificial intelligence decision support, and includes, but is not limited to, a governance method for determining discretionary power triggers, selecting discretionary processing paths, and controlling discretionary boundaries for procurement business matters within a centralized procurement governance framework. Background Technology

[0002] In existing centralized procurement governance practices, procurement systems are typically designed around fixed processes to govern standardized and predictable procurement transactions. Elements such as amounts, processes, and approval paths are usually preset using rule parameters and executed automatically within the system. When a transaction conforms to the preset procurement rules, the existing system can effectively control the procurement process; however, when a transaction has unique, urgent, exceptional, or rule-conflicting characteristics, the existing system often cannot directly address the issue and usually requires manual intervention. Related techniques are typically used by business personnel or governance personnel based on experience to determine whether there is a deviation from the standard procurement process; governance is achieved through offline communication, ad-hoc approvals, or post-event supplementary explanations; problems are solved on a case-by-case basis, lacking a reusable system mechanism.

[0003] While the relevant technologies are efficient in governing standardized procurement matters in the aforementioned application scenarios, they suffer from several shortcomings when dealing with special circumstances, exceptions, or rule conflicts. These include a lack of objective judgment mechanisms to trigger discretionary power, a lack of structured generation and evaluation methods for discretionary governance paths, and a lack of authority boundary control and full-process recording for the exercise of discretionary power.

[0004] The lack of an objective judgment mechanism for triggering discretionary power refers to the fact that in existing centralized procurement or organizational decision-making systems, the need to initiate discretionary governance for business matters often relies on human experience or the subjective opinions of governance personnel. Different personnel have inconsistent judgment standards for similar matters, and the lack of unified and reusable judgment rules for triggering discretionary power leads to a highly subjective and error-prone process in initiating discretionary power. The lack of structured generation and evaluation methods for discretionary governance paths is specifically manifested in the fact that when business matters deviate from standard processes, existing technologies typically determine the governance path through manual decision-making or ad hoc judgment, lacking a systematic generation, compliance, and risk assessment mechanism for multiple candidate paths, resulting in low efficiency and poor interpretability in governance path selection. The lack of authority boundary control and full-process recording in the exercise of discretionary power is reflected in the fact that existing systems typically do not systematically constrain the scope of application, monetary range, time window, or frequency of discretionary behavior, nor do they fully record the discretionary triggering conditions, path selection, and execution results. This results in a high risk of unauthorized discretionary behavior and makes post-event auditing, accountability tracing, or rule optimization difficult.

[0005] The aforementioned shortcomings restrict the standardization, controllability, and transparency of centralized procurement governance in complex business scenarios.

[0006] Therefore, the technical problem solved by the embodiments of this application is how to improve the standardization, controllability and transparency of centralized procurement governance in complex business scenarios. Summary of the Invention

[0007] In view of this, the discretionary power governance method of the centralized procurement governance center based on AI provided in the embodiments of this application can automatically determine the business that needs to be discretionary and make the discretionary decision.

[0008] The discretionary power governance method for the centralized procurement governance center based on AI provided in this application embodiment is implemented as follows: One aspect of this application provides a discretionary power governance method for a centralized procurement governance center based on AI, the method comprising: Make discretionary judgments based on the business characteristics of the target business; In response to the result of the discretionary determination that discretion is required, multiple discretionary processing paths corresponding to the target business are generated based on business characteristic information and a preset discretionary rule base. Each discretionary processing path is evaluated to obtain the target discretionary path and an explanation of the evaluation results. Configure the corresponding permission boundary parameters for the target discretionary path to obtain the target discretionary scheme, which is used to govern the target business. The process of determining the target discretionary plan should be recorded and archived for future reference and traceability.

[0009] In one possible implementation, the method also includes: If the decision is that no discretion is required, proceed with the target business.

[0010] In one possible implementation, discretionary judgment is made based on the business characteristics information of the target business, including: Based on the business characteristics information of the target business, a judgment is made according to the preset discretionary judgment rules to obtain a first judgment result, which includes discretion required, no discretion required, and uncertainty.

[0011] In one possible implementation, discretionary judgment is made based on the business characteristics information of the target business, including: If the first determination result is that discretion is required or not, then the first determination result shall be determined as the result of the discretionary determination.

[0012] In one possible implementation, making discretionary judgments based on the business characteristics of the target business also includes: If the first judgment result is uncertain, the corresponding discretionary confidence level is determined according to the discretionary judgment model; The result of the discretionary judgment is determined based on the relationship between the discretionary confidence level and the discretionary threshold.

[0013] In one possible implementation, the business characteristic information of the target business includes at least one of the following: business amount characteristics, time urgency characteristics, standard procurement rule matching characteristics, and historical similar business characteristics.

[0014] In one possible implementation, path assessment includes at least one of the following assessment components: compliance assessment, efficiency assessment, and risk assessment.

[0015] In one possible implementation, the method also includes: The target business is governed according to the target discretionary plan, and the corresponding discretionary governance results are obtained; Record at least one of the following: business characteristic information, discretionary judgment results, target discretionary plan, and discretionary governance results.

[0016] In one possible implementation, the discretionary rule base includes permission boundary parameters for constraining discretionary schemes, which include at least one of the following: applicable amount range, time window, and applicable frequency.

[0017] In one possible implementation, the method also includes: Upon receiving a query request that includes the target business identifier, output at least one of the following: business characteristic information, discretionary judgment result, target discretionary plan, and discretionary governance result.

[0018] In this embodiment, the method makes a discretionary determination based on the business characteristics of the target business. In response to the result of the discretionary determination indicating that discretion is required, multiple discretionary processing paths corresponding to the target business are generated based on the business characteristics and a preset discretionary rule base, and the paths are evaluated to obtain the target discretionary path and an evaluation result description. Corresponding permission boundary parameters are configured for the target discretionary path to obtain a target discretionary scheme for governing the target business. The process of determining the target scheme is recorded and archived for subsequent invocation and traceability. This embodiment automatically evaluates whether discretion needs to be initiated based on the characteristics of the target business. This evaluation method requires no manual intervention, and the evaluation results are objective and highly reliable. Simultaneously, when discretion is required, business discretion is automatically performed, and a suitable discretionary scheme is selected by automatically evaluating the schemes obtained from the business discretion, improving discretionary efficiency and making the discretionary results interpretable. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating a discretionary power governance method for an AI-based centralized procurement governance center according to an embodiment of this application is shown. Figure 2 This diagram illustrates the discretionary governance process of an AI-based centralized procurement governance center according to an embodiment of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the specific technical solutions of this application will be further described in detail below with reference to the accompanying drawings of the embodiments of this application. The following embodiments are used to illustrate this application, but are not intended to limit the scope of this application.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0023] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0024] It should be noted that the terms "first, second, third" used in the embodiments of this application are used to distinguish similar or different objects and do not represent a specific order of objects. It can be understood that "first, second, third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0025] The discretionary power governance method of the AI-based centralized procurement governance center in this application embodiment can be executed by any electronic device, including but not limited to mobile phones, wearable devices (such as smartwatches, smart bracelets, smart glasses, etc.), tablets, laptops, in-vehicle terminals, PCs (Personal Computers), etc. The functions implemented by this method can be achieved by the processor in the electronic device calling program code. Of course, the program code can be stored in a computer storage medium. Therefore, the electronic device includes at least a processor and a storage medium.

[0026] The AI-based discretionary power governance method for centralized procurement governance centers in this application can be applied to any centralized procurement scenario where discretion is possible. Examples include centralized procurement scenarios of large enterprises or group centralized procurement centers, centralized procurement scenarios of government / public institution procurement platforms, and centralized procurement scenarios in heavily regulated industries such as financial institutions, energy, and healthcare.

[0027] The following describes in detail the discretionary governance scheme of the AI-based centralized procurement governance center according to the embodiments of this application, with reference to the accompanying drawings.

[0028] Figure 1 A flowchart illustrating a discretionary power governance method for an AI-based centralized procurement governance center according to an embodiment of this application is shown. Figure 1 As shown, the discretionary power management method of the AI-based centralized procurement governance center in this application embodiment may include the following steps S10-S50.

[0029] For ease of description, the discretionary power management method of the AI-based centralized procurement governance center in this application embodiment is described using an electronic device as the execution subject. It should be understood that the execution subject in this application embodiment can also be a manager or chip in an electronic device, and this application embodiment does not impose any limitations.

[0030] Step S10: Make a discretionary judgment based on the business characteristics information of the target business.

[0031] In one possible implementation, the target business is acquired via electronic devices. This target business is a business matter at any stage of the centralized procurement process, including initiation, approval, or execution. The target business can be uploaded through human-computer interaction between the business execution personnel and the electronic devices. At different stages, the business execution personnel may include procurement applicants, procurement executors, approvers, etc.

[0032] Optionally, the target business has corresponding business characteristic information, used to characterize the characteristics of the target business in a structured data manner. This business characteristic information may include at least one of the following: business amount characteristics, time urgency characteristics, standard procurement rule matching characteristics, and historical similar business characteristics. The aforementioned characteristic information can be uploaded by the user, matched against a preset procurement rule base based on the content of the target business, or obtained through electronic devices.

[0033] For example, in the case where the target business is "The core controller of production line A is damaged, and the estimated downtime loss is 100,000 yuan per hour. The existing supplier's standard delivery time is 15 days, which cannot be met," the business characteristic information can be determined as follows: the business amount characteristic is a purchase amount of 80,000 yuan; the time urgency characteristic can be a requirement for delivery and installation within 24 hours (extremely high urgency); the standard procurement rule matching characteristic is low; and the historical similar business characteristic can be that the system has retrieved 3 similar "emergency equipment repair procurement" records in the past 6 months, all of which were managed through the "emergency procurement report" discretionary strategy.

[0034] In some embodiments, after acquiring the business characteristic information of a target service, the electronic device determines whether the target service requires discretion based on the business characteristic information. This discretionary approach can be implemented through two discretionary strategies, such as sequential discretion through a rule engine and a discretionary judgment model. For example, the electronic device can first determine the target service's business characteristic information based on preset discretionary judgment rules to obtain a first judgment result, which includes whether discretion is required, not required, or uncertain. If the first judgment result indicates that discretion is required or not required, the first judgment result is determined as the discretionary judgment result. If the first judgment result is uncertain, the corresponding discretionary confidence level is determined according to the discretionary judgment model. The discretionary judgment result is then determined based on the relationship between the discretionary confidence level and the discretionary threshold.

[0035] For example, after acquiring the business characteristic information of the target business, the electronic device can first perform a first round of hard judgment through a rule engine based on preset discretionary judgment rules to obtain at least one first judgment result among "discretionary action required," "discretionary action not required," and "uncertain." For instance, the discretionary judgment rules may include determining that discretionary action is required when the business amount characteristic in the business characteristic information is greater than a threshold, the time urgency characteristic is "urgent" or "emergency," and the standard procurement rule matching characteristic is "conflict with bidding cycle rules." Conversely, determining that discretionary action is not required when the business amount characteristic in the business characteristic information is less than or equal to a threshold, the time urgency characteristic is "normal," and the standard procurement rule matching characteristic is "no conflict with bidding cycle rules." This first round of hard judgment is a simple and rigid judgment process based on rules, and this judgment process is efficient. In cases where the first judgment result is either an absolute result requiring discretionary action or not requiring discretionary action, the first judgment result can be directly taken as the result of the discretionary judgment.

[0036] If the initial judgment result is uncertain, the electronic device determines the corresponding discretionary confidence level by invoking a pre-trained discretionary judgment model. This discretionary judgment model can be an artificial intelligence model. Its input can be business characteristic information, and its output is the discretionary confidence level. This discretionary confidence level characterizes the probability that the target business requires discretion. The electronic device can pre-set a discretionary threshold. If the discretionary confidence level is greater than the threshold, the result is determined to be that discretion is required; if the discretionary confidence level is less than or equal to the threshold, the result is determined to be that discretion is not required. This discretionary judgment process can accurately and objectively determine whether the target business requires discretion through a dual-judgment strategy. The entire judgment process is systematic, transparent, and measurable. The artificial intelligence model can be any neural network model capable of classification, such as support vector machines, convolutional neural networks, or large language models.

[0037] Step S20: In response to the result of the discretion determination that discretion is required, generate multiple discretion processing paths corresponding to the target business based on the business feature information and the preset discretion rule library.

[0038] In one possible implementation, after the electronic device makes a discretionary determination on the target business, it obtains a result indicating whether discretion is required or not. Specifically, if the electronic device determines that discretion is not required, no special strategy is needed to execute the target task through discretionary means; the target business is executed normally. This normal execution process can determine the corresponding business execution parameters from a pre-set procurement rule base to execute the target business.

[0039] Optionally, if the discretionary determination result indicates that discretion is required, the electronic device can determine that the procurement rules do not match the target business or that there is a conflict between the procurement rules and the target business. It then needs to generate multiple candidate discretionary solutions corresponding to the target business based on business characteristic information and a pre-set discretionary rule library. The discretionary rule library includes at least one discretionary rule used for emergency contingency planning for the target business. This rule includes permission boundary parameters constraining the discretionary solutions. The permission boundary parameters include at least one of the following: applicable amount range, time window, and applicable frequency. The amount range may include a single applicable amount upper limit and a single applicable amount lower limit; the time window may include a procurement operation window or a post-event remedial period; and the applicable frequency may be, for example, a quarterly limit for the same supplier / category. Alternatively, the permission boundary parameters may also include other boundary conditions such as object boundaries, process boundaries, and risk boundaries.

[0040] In some embodiments, the electronic device can first generate multiple discretionary processing paths for discretionary purposes on the target business based on business characteristic information and a preset discretionary rule base, and then further generate candidate discretionary schemes corresponding to each discretionary processing path based on the discretionary processing paths.

[0041] Step S30: Perform path evaluation on each of the discretionary processing paths to obtain the target discretionary path and an explanation of the evaluation results.

[0042] In one possible implementation, the electronic device can also acquire multiple discretionary processing paths when it is determined that discretion is required for the target business, and further evaluate each discretionary processing path to obtain the target discretionary path from the discretionary processing paths based on the path evaluation results. Simultaneously, the electronic device also generates an evaluation result description corresponding to the target discretionary path based on the path evaluation process, explaining the reasons for selecting the target discretionary path. The evaluation of the discretionary processing path by the electronic device can include at least one of the following: compliance evaluation, efficiency evaluation, and risk evaluation. Any evaluation process can be implemented through preset evaluation rules or through a pre-trained evaluation model. Optionally, each of the aforementioned discretionary processing paths is a predefined, standardized, and special process that is compliant within specific boundaries.

[0043] Optionally, compliance assessment evaluates whether the corresponding discretionary action path conforms to or compensates for the breached standard procurement rules, as well as the legality of its own procedures. Efficiency assessment evaluates whether the corresponding discretionary action path addresses the immediate needs of the target business in terms of speed and cost-effectiveness. Risk assessment evaluates the potential secondary problems, losses, or governance loopholes that the corresponding discretionary action path may cause. Each of the above assessment methods can yield an assessment score for the discretionary action path, and then a final score for the discretionary action path can be obtained by calculating a weighted sum, etc., to determine the discretionary action path with the highest assessment score as the target discretionary action path.

[0044] In some embodiments, the electronic device can generate a corresponding evaluation result description while determining the target discretionary path. This evaluation result description may include the evaluation score for the target discretionary path and the evaluation scores for other discretionary processing paths. For example, it may include: discretionary path A is recommended, with a comprehensive evaluation score of 7.2, significantly better than other discretionary paths (discretionary path B: 6.5, discretionary path C: 5.8). Optionally, the evaluation result description may also include other content, such as the basis for explaining the applicability of the target discretionary path to the target business and the probability of similar historical businesses choosing the target discretionary path.

[0045] Step S40: Configure the corresponding permission boundary parameters for the target discretion path to obtain the target discretion scheme.

[0046] In one possible implementation, after determining the target discretionary path, the electronic device further configures the target discretionary path according to the permission boundary parameters used to constrain the discretionary scheme included in the preset discretionary rule base, thereby obtaining the target discretionary scheme. The permission boundary parameters include at least one of an applicable amount range, a time window, and an applicable frequency. The amount range may include an upper limit and a lower limit for a single applicable amount; the time window may include a procurement operation window or a post-event remedial period; and the applicable frequency may be, for example, a quarterly limit for the same supplier / category. Alternatively, the permission boundary parameters may also include other boundary conditions such as object boundaries, process boundaries, and risk boundaries.

[0047] The constraints of these authority boundary parameters are used to prevent the exercise of discretionary power beyond its scope or frequency in the corresponding discretionary processing path. Simultaneously, they provide a governance basis for discretionary power auditing and accountability tracing, and offer a discretionary power constraint mechanism for the centralized procurement governance center.

[0048] In some embodiments, the electronic device can generate a corresponding target discretionary scheme based on business characteristic information and a discretionary rule base. The target discretionary scheme is an optional, structured exception governance scheme automatically generated by the electronic device based on the discretionary rule base.

[0049] For example, based on different application scenarios, electronic devices can generate corresponding target discretionary schemes based on a discretionary rule base. These may include special processes such as emergency procurement - post-procurement supplementary bidding process, competitive negotiation process, and direct procurement process with special approval from senior management. Each target discretionary scheme also has corresponding permission boundary parameters. For instance, a candidate discretionary scheme for the emergency procurement - post-procurement supplementary bidding process could be: allow immediate procurement from pre-qualified suppliers to meet urgent needs, but a complete bidding process must be completed within a specified period afterward, and this procurement must be included in subsequent contracts. This candidate discretionary scheme also has corresponding permission boundary parameters: amount range: 100,000 to 500,000 yuan; time window: supplementary bidding must be initiated within 30 days after procurement; applicable frequency: no more than once per quarter for the same supplier / same product category.

[0050] Step S50: Record and archive the process of determining the target discretionary scheme.

[0051] In one possible implementation, after the electronic device determines the target discretionary scheme for the target business, it can record and archive the process of determining the target discretionary scheme for subsequent invocation and tracing.

[0052] Optionally, the target business can be managed according to the target discretionary scheme to obtain the corresponding discretionary management result. For example, if the target discretionary scheme is a discretionary management path, the electronic device can automatically select the discretionary management path corresponding to the target discretionary scheme to manage the target business. Alternatively, the electronic device can also send or display the content of the target discretionary scheme to the corresponding user, and after the user confirms, manage the target business according to the discretionary management path corresponding to the target discretionary scheme.

[0053] Furthermore, in this embodiment, the electronic device can also record at least one of the following after completing the target business through discretion: business characteristic information, discretion judgment result, target discretion scheme, and discretion governance result. The aforementioned data can be stored in a structured manner, and the discretion judgment result can further include each candidate discretion scheme and its corresponding evaluation score. The storage of this end-to-end data of the target business can serve as the basis for subsequent business discretion, and can be used for the optimization of discretion rules and as basic data for model training. Simultaneously, it can be reviewed later when needed to prove that the administrator's operation was within the authorized scope and the process was standardized. That is, the record of discretion execution is used to form discretion execution record data that can be invoked by subsequent governance rules and models regarding the exercise of discretionary power. Upon receiving a review request including the target business identifier, at least one of the following is output: business characteristic information, discretion judgment result, target discretion scheme, and discretion governance result.

[0054] Figure 2 This diagram illustrates the discretionary governance process of an AI-based centralized procurement governance center according to an embodiment of this application. Figure 2 As shown, users can input business items for a target service and extract corresponding business feature information through human-computer interaction with the electronic device. Further, the electronic device determines whether the target service requires discretion based on both rule-based judgment and model reasoning. If discretion is required, it generates at least one candidate discretionary scheme, evaluates each, and then confirms the target discretionary scheme. The target service is then governed according to the target discretionary scheme, and the entire process is recorded and audited.

[0055] Based on the aforementioned technical features, this application's embodiments utilize three major mechanisms—rule-based and model-driven collaborative judgment of discretionary triggers, structured generation and evaluation of candidate paths, and full-process access control and record keeping—to transform traditional "rule-by-man" exception governance, which relies on personal experience and ad-hoc decisions, into systematic, transparent, and auditable intelligent governance. Furthermore, while ensuring compliance, this approach significantly improves an organization's agility and standardization in responding to complex and urgent procurement needs, achieving manageable risk flexibility and providing a data-driven decision-making foundation for continuous optimization of procurement rules and governance levels. This drives a fundamental transformation of centralized procurement governance from rigid process control to a smart governance hub.

[0056] It should be understood that although the steps in the above flowcharts are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the above flowcharts may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0057] It should be understood that the phrases "one embodiment," "an embodiment," or "some embodiments" mentioned throughout the specification mean that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this application. Therefore, phrases such as "in one possible implementation," "in one embodiment," or "in some embodiments" appearing throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely for descriptive purposes and do not represent the superiority or inferiority of the embodiments. The descriptions of the various embodiments above tend to emphasize the differences between the various embodiments; their similarities or commonalities can be referred to mutually, and for the sake of brevity, they will not be repeated here.

[0058] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three kinds of relationships. For example, object A and / or object B can represent three situations: object A exists alone, object A and object B exist simultaneously, and object B exists alone.

[0059] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover 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 inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0060] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0061] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0062] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0063] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A discretionary power governance method for a centralized procurement governance center based on AI, characterized in that, The method includes: Make discretionary judgments based on the business characteristics of the target business; In response to the result of the discretion determination that discretion is required, multiple discretion processing paths corresponding to the target business are generated based on the business characteristic information and the preset discretion rule library. Each discretionary processing path is evaluated to obtain the target discretionary path and an explanation of the evaluation results. Configure corresponding permission boundary parameters for the target discretionary path to obtain the target discretionary scheme, which is used to govern the target business; The process of determining the target discretionary scheme is recorded and archived for future reference and traceability.

2. The method according to claim 1, characterized in that, The method further includes: If the result of the discretionary determination is that no discretion is required, the target business is executed.

3. The method according to claim 1, characterized in that, The discretionary judgment based on the business characteristic information of the target business includes: Based on the business characteristics information of the target business according to the preset discretionary judgment rules, a first judgment result is obtained. The first judgment result includes discretionary, no discretionary, and uncertain.

4. The method according to claim 3, characterized in that, The discretionary judgment based on the business characteristic information of the target business also includes: If the first determination result indicates that discretion is required or not, then the first determination result is determined to be the result of the discretion determination.

5. The method according to claim 4, characterized in that, The discretionary judgment based on the business characteristic information of the target business includes: If the first determination result is uncertain, the corresponding discretionary confidence level is determined according to the discretionary determination model; The result of the discretionary judgment is determined based on the relationship between the discretionary confidence level and the discretionary threshold.

6. The method according to claim 1, characterized in that, The business characteristic information of the target business includes at least one of the following: business amount characteristics, time urgency characteristics, standard procurement rule matching characteristics, and historical similar business characteristics.

7. The method according to claim 1, characterized in that, The path assessment includes at least one of the following assessment components: compliance assessment, efficiency assessment, and risk assessment.

8. The method according to claim 1, characterized in that, The method further includes: The target business is governed according to the target discretionary scheme, and the corresponding discretionary governance results are obtained; Record at least one of the following: business characteristic information, discretion judgment result, target discretion scheme, and discretion governance result.

9. The method according to claim 1, characterized in that, The discretionary rule base includes permission boundary parameters for constraining discretionary schemes. The permission boundary parameters include at least one of the following: applicable amount range, time window, and applicable frequency.

10. The method according to claim 8, characterized in that, The method further includes: Upon receiving a query request including the target business identifier, at least one of the following is output: the business characteristic information, the discretionary judgment result, the target discretionary scheme, and the discretionary governance result.

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