Mediation performance data processing method and system and electronic equipment

Abstract

The invention provides a mediation performance data processing method and system and electronic equipment, and relates to the technical field of data analysis, the method can adapt to complex organization structure changes, balance evaluation of quality and quantity is achieved, flexible algorithm configuration can be supported to obtain an accurate quality scoring result, and the accuracy of the quality scoring result is improved. Therefore, the technical problems of low data processing efficiency, inflexible algorithm configuration, single evaluation system, weak organization adaptation capability and the like in traditional mediation performance management are solved.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a mediation performance data processing method, system and electronic equipment. Background Art

[0002] For economic mediation activities such as debt collection and payment collection, mediators need to comprehensively consider various factors such as debt collection, commitment, and repayment in mediation cases. Since most business scenarios are on the mediator's side, it is difficult to make comprehensive considerations when determining the mediator's performance, and a complex performance algorithm needs to be set up for comprehensive evaluation.

[0003] Specifically, traditional mediation performance data management processes still face challenges such as complex data processing, rigid algorithm configuration, and a single evaluation dimension. Existing technologies primarily rely on manual statistics and fixed formulas, making them inflexible and unable to adapt to organizational changes and business development needs. Furthermore, performance evaluations overly focus on quantitative indicators while neglecting quality assessments, making it difficult to develop a comprehensive and objective evaluation system. Furthermore, existing performance evaluation processes generally lack the ability to flexibly adapt to organizational structures, making them difficult to support complex and ever-changing organizational restructuring. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a mediation performance data processing method, system and electronic equipment, which can adapt to changes in complex organizational structures, achieve balanced evaluation of quality and quantity, and support flexible algorithm configuration to obtain accurate quality scoring results, thereby solving technical problems in traditional mediation performance management such as low data processing efficiency, inflexible algorithm configuration, single evaluation system, and weak organizational adaptability.

[0005] In a first aspect, an embodiment of the present invention provides a method for processing mediation performance data, the method comprising: Data preparation steps: Obtain the corresponding payment collection flow data and statement data for the mediation case, as well as the mediator's call data. Based on the mediator's corresponding organizational structure relationship map, determine the evaluation data for the mediation case. Use the evaluation data to update the payment collection flow data and statement data to obtain the collection data corresponding to the mediation case. Data analysis step: obtaining text data corresponding to the call data, determining the emotion recognition results and mediation processing results corresponding to the call data based on the text data, and using the emotion recognition results and mediation processing results to determine the quality score results corresponding to the mediation case; Performance calculation steps: Determine the commission rules corresponding to the mediation cases based on the collected data, and use the commission rules to determine the performance results corresponding to the quality score results; Result application steps: Generate the performance display strategy and performance data archiving strategy corresponding to the mediation case based on the organizational structure relationship map, use the performance display strategy to display the performance results, and use the performance data archiving strategy to store the performance results.

[0006] Optional data preparation steps include: Use the preset financial data collection interface to obtain the financial data corresponding to the mediation case, and obtain the collection flow data and statement data through the financial data; Utilize the preset call data collection interface to obtain the mediator's call times, call duration, and call recordings, and use the call times, call duration, and call recordings to determine the call data; Obtain an organizational structure relationship map based on the mediator's department personnel relationship data, obtain supervisor rating data and customer feedback data corresponding to the mediation case based on the organizational structure relationship map, and determine evaluation data based on the supervisor rating data and customer feedback data; After updating the collection flow data and statement data according to the data cleaning strategy corresponding to the evaluation data, the collected data corresponding to the mediation case is obtained.

[0007] Optionally, after updating the payment flow data and statement data according to the data cleansing strategy corresponding to the evaluation data, the collected data corresponding to the mediation case is obtained, including: Obtaining standard values corresponding to the evaluation data, and determining an abnormal acquisition strategy corresponding to the evaluation data based on the standard values; Determine the outliers contained in the evaluation data according to the anomaly acquisition strategy, and determine the data cleaning strategy corresponding to the evaluation data through the outliers; After using the data cleaning strategy to eliminate the outliers corresponding to the collection flow data and statement data, the collected data corresponding to the mediation case is obtained.

[0008] Optional data analysis steps include: Obtain the audio file corresponding to the call data, and convert the audio file into text to generate text data corresponding to the call data; Obtaining semantic results of the text data, determining the mediator's professionalism data using a preset professionalism evaluation template and the semantic results, and determining key information data corresponding to the text data based on preset keyword data; Perform emotion recognition on the audio file based on the text data to determine the emotion recognition result corresponding to the call data; The quality score results corresponding to the mediation case are determined based on the emotion recognition results and mediation processing results.

[0009] Optional performance calculation steps include: Determine the dimension parameters and version parameters of the collected data based on the organizational structure relationship map; Use dimension parameters and version parameters to determine the commission rules corresponding to mediation cases, and calculate the financial performance, call quality performance, and manual evaluation performance corresponding to the quality score results based on the commission rules; Performance results are calculated based on financial performance, call quality performance, and human evaluation performance.

[0010] Optionally, performance results are calculated based on financial performance, call quality performance, and manual evaluation performance, including: Determine the first weight, second weight, and third weight corresponding to financial performance, call quality performance, and manual evaluation performance using the dimension parameters; The financial performance, call quality performance and manual evaluation performance are weightedly calculated using the first weight, the second weight and the third weight to obtain a performance result.

[0011] Optional, result application steps include: Use the organizational structure relationship map to obtain the performance dimension parameters corresponding to the mediation case, determine the performance display strategy corresponding to the mediation case based on the performance dimension parameters, and use the performance display strategy to display the performance results; The performance change data corresponding to the mediator is obtained according to the performance display strategy, the performance data archiving strategy corresponding to the mediation case is determined according to the performance change data, and the performance results are stored and processed using the performance data archiving strategy.

[0012] Optionally, after the result application step, the method further comprises: Permission control steps: Determine the configuration adjustment strategy corresponding to the mediation case based on the stored performance results, and use the configuration adjustment strategy to update the data control permissions corresponding to the mediation case and the data access permissions corresponding to the mediator.

[0013] In a second aspect, the present invention provides a mediation performance data processing system, the system comprising: The data preparation module is used to obtain the collection flow data and statement data corresponding to the mediation case, as well as the mediator's call data. Based on the organizational structure relationship map corresponding to the mediator, the evaluation data corresponding to the mediation case is determined. After using the evaluation data to update the collection flow data and statement data, the collected data corresponding to the mediation case is obtained; A data analysis module is used to obtain text data corresponding to the call data, determine the emotion recognition results and mediation processing results corresponding to the call data based on the text data, and use the emotion recognition results and mediation processing results to determine the quality score results corresponding to the mediation case; The performance calculation module is used to determine the commission rules corresponding to mediation cases based on the collected data, and use the commission rules to determine the performance results corresponding to the quality score results; The result application module is used to generate the performance display strategy and performance data archiving strategy corresponding to the mediation case based on the organizational structure relationship map, use the performance display strategy to display the performance results, and use the performance data archiving strategy to store the performance results.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device comprising a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the steps of the mediation performance data processing method provided in the first aspect.

[0015] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the steps of the mediation performance data processing method provided in the first aspect.

[0016] An embodiment of the present invention provides a mediation performance data processing method, system and electronic device. In the process of evaluating the mediation performance data of a mediator, the method first obtains the collection flow data and statement data corresponding to the mediation case and the mediator's call data, determines the evaluation data corresponding to the mediation case based on the organizational structure relationship map corresponding to the mediator, and uses the evaluation data to update the collection flow data and statement data to obtain the collection data corresponding to the mediation case, thereby completing the data preparation step; then obtains the text data corresponding to the call data, determines the emotion recognition result and mediation processing result corresponding to the call data based on the text data, and uses the emotion recognition result and mediation processing result to determine the quality scoring result corresponding to the mediation case, thereby completing the data analysis step; then determines the commission rule corresponding to the mediation case based on the collected data, uses the commission rule to determine the performance result corresponding to the quality scoring result, and completes the performance calculation step; finally, generates the performance display strategy and performance data archiving strategy corresponding to the mediation case according to the organizational structure relationship map, uses the performance display strategy to display the performance result, and uses the performance data archiving strategy to store the performance result. This method can adapt to changes in complex organizational structures, achieve a balanced evaluation of quality and quantity, and support flexible algorithm configuration to obtain accurate quality scoring results, thereby solving technical problems in traditional mediation performance management such as low data processing efficiency, inflexible algorithm configuration, single evaluation system, and weak organizational adaptability.

[0017] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flowchart of a method for processing mediation performance data provided by an embodiment of the present invention; Figure 2 A flowchart of the data preparation step S101 in a mediation performance data processing method provided in an embodiment of the present invention; Figure 3 A flowchart of step S204 in a mediation performance data processing method provided by an embodiment of the present invention; Figure 4 A flowchart of the data analysis step S102 in a mediation performance data processing method provided in an embodiment of the present invention; Figure 5 A flowchart of the performance calculation step S103 in a mediation performance data processing method provided in an embodiment of the present invention; Figure 6 A flowchart of step S503 in a mediation performance data processing method provided by an embodiment of the present invention; Figure 7 A flowchart of the result application step S104 in a mediation performance data processing method provided in an embodiment of the present invention; Figure 8 A flowchart of another method for processing mediation performance data provided by an embodiment of the present invention; Figure 9 A schematic diagram of the structure of a mediation performance data processing system provided by an embodiment of the present invention; Figure 10 A data flow diagram of a first mediation performance data processing system provided by an embodiment of the present invention; Figure 11 A data flow diagram of a second mediation performance data processing system provided by an embodiment of the present invention; Figure 12 A schematic structural diagram of an electronic device provided by an embodiment of the present invention.

[0021] icon: 910-Data Preparation Module; 920-Data Analysis Module; 930-Performance Calculation Module; 940-Result Application Module; 101 - processor; 102 - memory; 103 - bus; 104 - communication interface. DETAILED DESCRIPTION

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0023] For economic mediation activities such as debt collection and payment collection, mediators need to comprehensively consider various factors such as debt collection, commitment, and repayment for mediation cases. Since most of the business scenarios are on the mediator's side, it is difficult to make comprehensive considerations when determining the mediator's performance, and a complex performance algorithm needs to be set up for comprehensive evaluation. The management process of traditional mediation performance data still has problems such as complex data processing, rigid algorithm configuration, and single evaluation dimension. The existing technology mainly relies on manual statistics and fixed formula calculations, which cannot flexibly adapt to organizational changes and business development needs. Moreover, performance evaluation focuses too much on quantitative indicators and ignores quality assessment, making it difficult to form a comprehensive and objective evaluation system. In addition, the existing performance evaluation process generally lacks the ability to flexibly adapt to the organizational structure and is difficult to support complex and changeable organizational structure adjustments. Based on this, the present invention provides a mediation performance data processing method, system and electronic equipment. The method can adapt to complex organizational structure changes, achieve a balanced evaluation of quality and quantity, and support flexible algorithm configuration to obtain accurate quality scoring results, thereby solving technical problems such as low data processing efficiency, inflexible algorithm configuration, single evaluation system, and weak organizational adaptability in traditional mediation performance management.

[0024] To facilitate understanding of this embodiment, a mediation performance data processing method disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, the method includes: Data preparation step S101: Obtain the collection flow data and statement data corresponding to the mediation case and the mediator's call data, determine the evaluation data corresponding to the mediation case based on the organizational structure relationship map corresponding to the mediator, use the evaluation data to update the collection flow data and statement data, and obtain the collection data corresponding to the mediation case.

[0025] The data preparation step integrates and dynamically updates multi-source data, involving data collection, evaluation data generation, and collected data output. Specifically, data collection includes the following data: Payment collection data: Extract the actual repayment records of debtors in mediation cases, including the amount, time, payment method, and associated case number of each repayment, to ensure that the data corresponds to the case; Statement data: Collect original debt certificates provided by creditors (such as contract amount, overdue days, interest calculation rules, etc.) to verify repayment progress and debt accuracy; Call data: Collect audio or text records (after desensitization) of calls between mediators and parties, including basic information such as communication frequency, duration, and key conversation content.

[0026] The evaluation data generation process involves mapping the organizational structure. By constructing a tree structure encompassing mediators, team leaders, and departmental hierarchies, and linking mediators' historical performance, client reviews, training records, and other data, a multi-dimensional evaluation framework (e.g., mediation success rate, client satisfaction, and compliance records) can be formed. Furthermore, a data update mechanism can be included, using evaluation data to revise raw business data. For example, if a mediator's historical compliance score is low, the system will automatically flag their case's payment flow for manual review. If the team's overall mediation efficiency is above average, the timeliness calculation rules in the billing data will be dynamically adjusted to improve data accuracy.

[0027] The data collection and output process integrates and processes the data set, which includes: basic case information, dynamically corrected repayment data, and associated evaluation tags (such as "high risk requiring review" and "efficient mediation team"), forming a standardized data file.

[0028] Data analysis step S102: obtaining text data corresponding to the call data, determining the emotion recognition result and mediation processing result corresponding to the call data based on the text data, and determining the quality score result corresponding to the mediation case using the emotion recognition result and mediation processing result.

[0029] The data analysis process involves intelligent parsing of unstructured data, encompassing three key areas: text data processing, emotion recognition and mediation effectiveness analysis, and a quality scoring system. Specifically, text data processing involves converting call recordings into text using ASR technology, combined with natural language processing (NLP) to extract keywords (e.g., "refuse to repay," "negotiate installments," and "emotionally agitated") to construct a conversation content tag library.

[0030] Emotion recognition results can be used to score text data using sentiment analysis models (such as LSTM neural networks), categorizing sentiment (e.g., positive, neutral, negative), identifying points of conflict (e.g., parties complaining about "the process being too slow"), and automatically generating sentiment trend charts. Mediation results can be used to determine the mediation stage (e.g., initial negotiation, plan development, implementation follow-up) based on the conversation content, identify key actions (e.g., whether a repayment agreement has been reached, whether further communication is required), and compare them with pre-set standardized processes to calculate a process compliance score.

[0031] The construction process of the quality scoring system can integrate dimensions such as emotional stability (30%), process compliance (40%), and problem-solving efficiency (30%), generate a case quality score (such as 85 points / 100 points) through a weighted algorithm, and mark items for improvement (such as "not fully listening to the parties' demands during communication").

[0032] Performance calculation step S103: Determine the commission rules corresponding to the mediation cases based on the collected data, and use the commission rules to determine the performance results corresponding to the quality score results.

[0033] The performance calculation process is a rule-driven, multi-dimensional performance accounting process involving two steps: determining commission rules and generating performance results. Commission rules comprehensively calculate performance across financial data, quality ratings, and manual evaluation. The calculation process uses weighted calculations to determine the final performance results.

[0034] Result application step S104: Generate a performance display strategy and a performance data archiving strategy corresponding to the mediation case based on the organizational structure relationship map, use the performance display strategy to display the performance results, and use the performance data archiving strategy to store the performance results.

[0035] The performance display strategy uses a hierarchical dashboard to present performance data across different dimensions, taking an organizational structure into account. For example, the individual view highlights a mediator's caseload, success rate, and quality rating trends; the team view compares each group's per capita performance, case type distribution, and average process time; and the management view displays global performance achievement rates and risk case alerts (e.g., if the proportion of low-scoring cases exceeds a threshold). Furthermore, the performance display strategy can be enhanced with dynamic interactive features: in real-world scenarios, users can filter by time range, case type, and other conditions, and clicking on a chart will display specific case details and related call transcripts.

[0036] The data archiving strategy categorizes and stores cases by case closing date, mediation type, and performance status (e.g., paid, pending review). Blockchain technology is used to ensure data immutability and meet audit requirements. In specific scenarios, historical performance data can be used to assess mediator competency, analyze training needs (e.g., a team's generally low quality scores trigger specialized communication skills training), and optimize and iterate future commission rules.

[0037] Optionally, the data preparation step S101 is as follows: Figure 2 Shown, including: Step S201: Using a preset financial data collection interface to obtain financial data corresponding to the mediation case, and obtaining payment flow data and statement data through the financial data; Step S202: using a preset call data collection interface to obtain the number of calls, call duration, and call recordings of the mediator, and determining the call data using the number of calls, call duration, and call recordings; Step S203: Obtaining an organizational structure relationship map based on the mediator's department personnel relationship data, obtaining supervisor rating data and customer feedback data corresponding to the mediation case based on the organizational structure relationship map, and determining evaluation data based on the supervisor rating data and customer feedback data; Step S204: After updating the payment flow data and the statement data according to the data cleaning strategy corresponding to the evaluation data, the collected data corresponding to the mediation case is obtained.

[0038] In specific scenarios, the preset financial data collection interface can be used to obtain the financial data corresponding to the mediation case, and then the collection flow data and statement data can be obtained from the obtained financial data. The preset call data collection interface can then be used to collect call data such as the number of mediators' calls, call duration, and call recordings. After completing data collection, the organizational structure is synchronized, and the organizational structure relationship map is obtained based on the mediator's department personnel relationship data. Based on the organizational structure relationship map, the supervisor rating data and customer feedback data corresponding to the mediation case are obtained, realizing the aggregation of multi-source data. Finally, the collection flow data and statement data are cleaned and standardized according to the corresponding data cleaning strategy to obtain the collected data corresponding to the mediation case.

[0039] Optionally, after updating the payment flow data and the statement data according to the data cleaning strategy corresponding to the evaluation data, step S204 of obtaining the collected data corresponding to the mediation case is performed, such as Figure 3 Shown, including: Step S301, obtaining a standard value corresponding to the evaluation data, and determining an abnormality acquisition strategy corresponding to the evaluation data based on the standard value; Step S302: determining the outliers contained in the evaluation data according to the outlier acquisition strategy, and determining the data cleaning strategy corresponding to the evaluation data according to the outliers; In step S303, after using the data cleaning strategy to remove the abnormal values corresponding to the collection flow data and the statement data, the collected data corresponding to the mediation case is obtained.

[0040] When using data cleaning strategies to process collection flow data and statement data, the corresponding data cleaning strategy is determined by obtaining the outliers corresponding to the evaluation data, and then the collected original data is standardized to eliminate outliers and ensure data quality.

[0041] Optionally, the data analysis step S102, such as Figure 4 Shown, including: Step S401: obtaining an audio file corresponding to the call data, and converting the audio file into text to generate text data corresponding to the call data; Step S402: obtaining semantic results of the text data, determining the mediator's professionalism data using a preset professionalism evaluation template and the semantic results, and determining key information data corresponding to the text data based on preset keyword data; Step S403, performing emotion recognition on the audio file based on the text data, and determining an emotion recognition result corresponding to the call data; Step S404: determining a quality score result corresponding to the mediation case based on the emotion recognition result and the mediation processing result.

[0042] Data analysis assesses mediation quality based on speech recognition and natural language processing technologies. By acquiring the audio files corresponding to the call data and performing real-time speech recognition on them, the recorded audio is converted into text, resulting in the corresponding text data. The mediator's professionalism is then assessed and analyzed, and the mediator's professional expression ability is evaluated by extracting semantic information from the text data. Specifically, the mediator's professionalism is determined using a pre-set professionalism assessment template and semantic information. Key information related to the text data, such as the promised repayment time, is then determined based on pre-set keyword data.

[0043] The mediator's emotions are then identified and analyzed within the audio file, resulting in comprehensive emotion recognition results. In real-world scenarios, emotion recognition can also be performed on the mediating parties (e.g., debtors), yielding comprehensive emotion recognition results. Finally, a quality assessment report is generated based on the emotion recognition results and the mediation outcome, resulting in a quality score for the mediation case.

[0044] Optionally, the performance calculation step S103 is as follows: Figure 5 Shown, including: Step S501: Determine dimension parameters and version parameters of collected data based on the organizational structure relationship map; Step S502: Determine the commission rules corresponding to the mediation case using the dimension parameters and version parameters, and calculate the financial performance, call quality performance, and manual evaluation performance corresponding to the quality score results based on the commission rules; Step S503: Calculate the performance results based on the financial performance, call quality performance, and manual evaluation performance.

[0045] The performance calculation process is a multi-dimensional calculation that integrates three dimensions: financial data, call quality, and manual evaluation. The multi-dimensional commission rule configuration supports setting commission rules based on multiple dimensions such as collection amount, collection rate, and call quality. The rule can set corresponding rule version management and can switch between different rule versions at any time.

[0046] After determining the commission rules for mediation cases using dimension and version parameters, performance calculation is performed by obtaining the mapping relationship of the organizational structure. The financial dimension primarily calculates performance based on financial indicators such as collection amount and collection rate; the call quality dimension combines call score, call duration, and number of calls; and the manual evaluation dimension integrates manual evaluations such as supervisor evaluations and customer feedback. Ultimately, performance results are calculated based on financial performance, call quality performance, and manual evaluation performance.

[0047] Optionally, step S503 of calculating the performance results based on the financial performance, call quality performance and manual evaluation performance, such as Figure 6 Shown, including: Step S601, determining first, second, and third weights corresponding to financial performance, call quality performance, and manual evaluation performance using dimension parameters; Step S602 : performing weighted calculation on the financial performance, the call quality performance, and the manual evaluation performance using the first weight, the second weight, and the third weight to obtain a performance result.

[0048] Specifically, three different types of weights can be set, and weighted calculations can be performed based on the weights of different dimensions to obtain the final performance.

[0049] Optionally, the result is applied in step S104, such as Figure 7 Shown, including: Step S701: using the organizational structure relationship map to obtain performance dimension parameters corresponding to the mediation case, determining the performance display strategy corresponding to the mediation case based on the performance dimension parameters, and displaying the performance results using the performance display strategy; Step S702: Obtain the performance change data corresponding to the mediator according to the performance display strategy, determine the performance data archiving strategy corresponding to the mediation case according to the performance change data, and store the performance results using the performance data archiving strategy.

[0050] The results application step enables multi-dimensional data display and analysis. Data visualization uses charts to intuitively display performance data across various dimensions. Team performance dashboards can also be used to display overall team performance and individual rankings. In practical scenarios, historical trends in individual and team performance can be displayed to facilitate performance trend analysis. Furthermore, performance anomaly monitoring is enabled, automatically identifying unusual fluctuations in performance indicators and providing early warnings.

[0051] Optionally, after the result application step, the method further includes: a permission control step: determining the configuration adjustment strategy corresponding to the mediation case based on the stored performance results, and using the configuration adjustment strategy to update the data control authority corresponding to the mediation case and the data access authority corresponding to the mediator. Figure 8 The flowchart of another mediation performance data processing method is shown. While the details of steps S101-S104 are omitted, the permission management step implements refined permission control through data encryption transmission, access rights verification, and operational behavior auditing, allocating different system access rights based on roles and positions. Furthermore, data access control restricts users to data within their authority scope. Furthermore, sensitive operations can be recorded during the sensitive operation audit process, enabling subsequent tracing and desensitization of sensitive data to protect privacy.

[0052] From the mediation performance data processing method mentioned in the above embodiment, it can be seen that this method can adapt to changes in complex organizational structures, achieve balanced evaluation of quality and quantity, and support flexible algorithm configuration to obtain accurate quality scoring results, thereby solving technical problems in traditional mediation performance management such as low data processing efficiency, inflexible algorithm configuration, single evaluation system, and weak organizational adaptability.

[0053] Corresponding to the mediation performance data processing method provided in the above embodiment, the embodiment of the present invention provides a mediation performance data processing system, such as Figure 9 As shown, the system includes: Data preparation module 910 is used to obtain the collection flow data and statement data corresponding to the mediation case, as well as the mediator's call data, determine the evaluation data corresponding to the mediation case based on the mediator's corresponding organizational structure relationship map, and use the evaluation data to update the collection flow data and statement data to obtain the collected data corresponding to the mediation case; Data analysis module 920, configured to obtain text data corresponding to the call data, determine emotion recognition results and mediation processing results corresponding to the call data based on the text data, and determine a quality score result corresponding to the mediation case using the emotion recognition results and mediation processing results; Performance calculation module 930, for determining commission rules corresponding to mediation cases based on collected data, and using the commission rules to determine performance results corresponding to quality scoring results; The result application module 940 is used to generate a performance display strategy and a performance data archiving strategy corresponding to the mediation case based on the organizational structure relationship map, display the performance results using the performance display strategy, and store the performance results using the performance data archiving strategy.

[0054] like Figure 10 The data flow diagram of the first mediation performance data processing system shown in the figure, the basic data layer corresponds to the data preparation module 910, the intelligent analysis layer corresponds to the data analysis module 920, the multi-dimensional performance calculation model in the business application layer corresponds to the performance calculation module 930, and the performance data visualization platform corresponds to the result application module 940.

[0055] When it comes to permission control steps, such as Figure 11 The data flow diagram of the second mediation performance data processing system shown in FIG. Figure 11 The security and authority control system in the system can realize data encryption, authority control and operation audit process. These modules work together to process data through Figure 10 and Figure 11 The data flow in the system is closed-loop. Specifically, the data collection module (financial / call data) - AI analysis (quality assessment) - performance calculation (comprehensive processing) - and visualization platform (results display) form a complete data closed loop. For example, after cleansing, payment flow data is input into the performance calculation model together with the call quality score obtained through AI analysis.

[0056] The flexible algorithm engine provides dynamic configuration for the performance calculation model and organizational structure module. The performance calculation model reads the latest commission rules in real time, and the organizational structure module maps departmental structures to calculation rules. For example, when adjusting the "collection rate weight," the algorithm engine immediately updates the calculation model parameters.

[0057] Performance monitoring implementation process example: 1. The data collection module obtains mediator Zhang San's payment data (amount 100,000) and call recordings in real time; 2. The AI system analyzes the recording to determine its quality score (85 points) and identifies key repayment commitments; 3. The calculation model calculates performance according to the current rules (60% financial weighting + 40% quality weighting); 4. The visualization platform updates the team dashboard in real time and marks abnormal calls (emotional analysis abnormalities); 5. Supervisors can view the performance trend charts of their teams through the permission system.

[0058] This connection realizes a complete performance management closed loop: raw data - intelligent processing - dynamic calculation - visual monitoring, while ensuring system flexibility and data security.

[0059] From the mediation performance data processing system mentioned in the above embodiment, it can be seen that the system can adapt to changes in complex organizational structures, achieve balanced evaluation of quality and quantity, and support flexible algorithm configuration to obtain accurate quality scoring results, thereby solving technical problems in traditional mediation performance management such as low data processing efficiency, inflexible algorithm configuration, single evaluation system, and weak organizational adaptability.

[0060] The mediation performance data processing system provided in the embodiment of the present invention has the same implementation principle and technical effects as the aforementioned mediation performance data processing method embodiment. For the sake of brief description, for matters not mentioned in the system embodiment, please refer to the corresponding content in the aforementioned mediation performance data processing method embodiment.

[0061] This embodiment also provides an electronic device. The structural diagram of the electronic device is as follows: Figure 12 As shown, the device includes a processor 101 and a memory 102; wherein the memory 102 is used to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the steps of the above-mentioned mediation performance data processing method.

[0062] Figure 12 The electronic device shown further includes a bus 103 and a communication interface 104 , and the processor 101 , the communication interface 104 and the memory 102 are connected via the bus 103 .

[0063] The memory 102 may include a high-speed random access memory (RAM) and may also include a non-volatile memory, such as at least one disk storage. The bus 103 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 12 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0064] The communication interface 104 is used to connect to at least one user terminal and other network units through a network interface, and send the encapsulated IPv4 message or IPv4 message to the user terminal through the network interface.

[0065] The processor 101 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by an integrated logic circuit of hardware in the processor 101 or by instructions in the form of software. The above-mentioned processor 101 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present disclosure can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in memory 102, and processor 101 reads information in memory 102 and, in conjunction with its hardware, completes the steps of the method of the aforementioned embodiment.

[0066] An embodiment of the present invention further provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the mediation performance data processing method in the aforementioned embodiment are executed.

[0067] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, equipment and methods can be implemented in other ways. The system embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0068] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0069] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0070] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0071] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A mediation performance data processing method, characterized in that: The method comprises: Data preparation step: Obtain the collection flow data and statement data corresponding to the mediation case, as well as the mediator's call data; determine the evaluation data corresponding to the mediation case based on the organizational structure relationship map corresponding to the mediator; use the evaluation data to update the collection flow data and statement data to obtain the collected data corresponding to the mediation case; Data analysis step: obtaining text data corresponding to the call data, determining an emotion recognition result and a mediation processing result corresponding to the call data based on the text data, and determining a quality score result corresponding to the mediation case using the emotion recognition result and the mediation processing result; Performance calculation step: determining a commission rule corresponding to the mediation case based on the collected data, and using the commission rule to determine a performance result corresponding to the quality score result; Result application steps: Generate a performance display strategy and a performance data archiving strategy corresponding to the mediation case based on the organizational structure relationship map, use the performance display strategy to display the performance results, and use the performance data archiving strategy to store the performance results.

2. The mediation performance data processing method according to claim 1, characterized in that: The data preparation step includes: Using a preset financial data collection interface to obtain the financial data corresponding to the mediation case, and obtaining the payment flow data and the statement data through the financial data; Using a preset call data collection interface to obtain the number of calls, call duration, and call recordings of the mediator, and using the number of calls, call duration, and call recordings to determine the call data; Obtaining the organizational structure relationship map based on the department personnel relationship data of the mediator, obtaining supervisor rating data and customer feedback data corresponding to the mediation case based on the organizational structure relationship map, and determining the evaluation data based on the supervisor rating data and the customer feedback data; After updating the payment collection flow data and the statement data according to the data cleaning strategy corresponding to the evaluation data, the collected data corresponding to the mediation case is obtained.

3. The mediation performance data processing method according to claim 2, characterized in that: After updating the payment flow data and the statement data according to the data cleaning strategy corresponding to the evaluation data, the collected data corresponding to the mediation case is obtained, including: Obtaining a standard value corresponding to the evaluation data, and determining an abnormality acquisition strategy corresponding to the evaluation data based on the standard value; Determining abnormal values contained in the evaluation data according to the abnormality acquisition strategy, and determining the data cleaning strategy corresponding to the evaluation data through the abnormal values; After using the data cleaning strategy to eliminate the abnormal values corresponding to the collection flow data and the statement data, the collected data corresponding to the mediation case is obtained.

4. The mediation performance data processing method according to claim 1, characterized in that: The data analysis step comprises: Obtaining an audio file corresponding to the call data, and converting the audio file into text to generate the text data corresponding to the call data; Obtaining semantic results of the text data, determining the professionalism data of the mediator using a preset professionalism evaluation template and the semantic results, and determining key information data corresponding to the text data based on preset keyword data; Performing emotion recognition on the audio file based on the text data, and determining the emotion recognition result corresponding to the call data; The quality score result corresponding to the mediation case is determined according to the emotion recognition result and the mediation processing result.

5. The mediation performance data processing method according to claim 1, characterized in that: The performance calculation step includes: Determining dimension parameters and version parameters of the collected data based on the organizational structure relationship map; Determine the commission rule corresponding to the mediation case using the dimension parameter and the version parameter, and calculate the financial performance, call quality performance, and manual evaluation performance corresponding to the quality score result according to the commission rule; The performance result is calculated based on the financial performance, the call quality performance, and the manual evaluation performance.

6. The mediation performance data processing method according to claim 5, characterized in that: Calculating the performance result based on the financial performance, the call quality performance, and the manual evaluation performance includes: Determining a first weight, a second weight, and a third weight corresponding to the financial performance, the call quality performance, and the manual evaluation performance using the dimension parameters; The financial performance, the call quality performance and the manual evaluation performance are weightedly calculated using the first weight, the second weight and the third weight to obtain the performance result.

7. The mediation performance data processing method according to claim 1, characterized in that: The result application step comprises: Using the organizational structure relationship map to obtain performance dimension parameters corresponding to the mediation case, determining a performance display strategy corresponding to the mediation case based on the performance dimension parameters, and displaying the performance results using the performance display strategy; The performance change data corresponding to the mediator is obtained according to the performance display strategy, the performance data archiving strategy corresponding to the mediation case is determined according to the performance change data, and the performance results are stored and processed using the performance data archiving strategy.

8. The mediation performance data processing method according to claim 1, characterized in that: After the result application step, the method further comprises: Authority control step: determining the configuration adjustment strategy corresponding to the mediation case based on the stored performance results, and using the configuration adjustment strategy to update the data control authority corresponding to the mediation case and the data access authority corresponding to the mediator.

9. A mediation performance data processing system, characterized in that: The system comprises: A data preparation module is used to obtain the collection flow data and statement data corresponding to the mediation case and the mediator's call data, determine the evaluation data corresponding to the mediation case based on the organizational structure relationship map corresponding to the mediator, and use the evaluation data to update the collection flow data and statement data to obtain the collected data corresponding to the mediation case; a data analysis module, configured to obtain text data corresponding to the call data, determine an emotion recognition result and a mediation processing result corresponding to the call data based on the text data, and determine a quality score result corresponding to the mediation case using the emotion recognition result and the mediation processing result; a performance calculation module, configured to determine a commission rule corresponding to the mediation case based on the collected data, and to determine a performance result corresponding to the quality score result using the commission rule; A result application module is used to generate a performance display strategy and a performance data archiving strategy corresponding to the mediation case based on the organizational structure relationship map, use the performance display strategy to display the performance results, and use the performance data archiving strategy to store the performance results.

10. An electronic device, characterized in that: It includes a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the steps of the mediation performance data processing method described in any one of claims 1 to 8.

Images