Business channel compliance multi-dimensional supervision feedback system based on differentiated management and control

Abstract

This invention discloses a multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management and control. It relates to the field of business channel management and control technology and solves the technical problems in existing technologies, such as monitoring relying on data from the business channels themselves, the possibility of terminals circumventing supervision by tampering with data within the platform, and the lack of independent third-party data verification, leading to biased compliance judgments. Specifically, it includes a channel usage scenario analysis unit, which analyzes the usage scenarios of business channels and decides whether they are qualified based on the analysis results, providing feedback optimization; if the analysis is qualified, feedback optimization is performed; if the analysis is unqualified, source tracing and detection are conducted. It also includes a channel anomaly feedback optimization unit, which analyzes and optimizes anomaly feedback of business channels and implements compliance management based on the optimization. Finally, it includes a channel analysis targeted control unit, which performs compliance assessment and control on newly established business channels, filters existing business channels based on the assessment and control, and decides whether to retain the current business channels.

Description

Technical Field

[0001] This invention relates to the field of business channel management technology, specifically a multi-dimensional supervision and feedback system for business channel compliance based on differentiated management. Background Technology

[0002] Business channels are the "pathways" through which enterprises deliver products / services to target customers and realize value delivery. They are the core link connecting enterprises and the market. Their design and management directly affect business efficiency, market coverage, and compliance risk levels, and need to be differentiated by industry characteristics, customer needs, and corporate strategy. The core of this monitoring and feedback system is to adapt to the compliance requirements of different types of business channels through differentiated control strategies, achieve full-process compliance coverage by combining multi-dimensional monitoring mechanisms, and promote the rectification of compliance issues through a closed-loop feedback system, ultimately reducing channel compliance risks and improving management efficiency.

[0003] However, in existing technologies, monitoring relies on data from the business channels themselves (such as orders and reviews). Terminals may evade supervision by tampering with data within the platform. The lack of independent third-party data verification leads to biased compliance judgments. Furthermore, it cannot accurately identify issues by combining usage scenarios. In addition, it cannot perform abnormal feedback analysis and optimization of business data, and it cannot identify the consistency of contract terms and performance records across the entire chain. Although semantic recognition is achieved, a closed-loop verification of marketing-contract-performance is not constructed.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to solve the problems mentioned above by proposing a multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management and control includes a multi-dimensional supervision and feedback platform, which is connected to a channel usage scenario analysis unit, a channel anomaly feedback optimization unit, and a channel analysis targeted control unit.

[0008] The channel usage scenario analysis unit analyzes the usage scenarios of business channels, and decides whether the analysis results are qualified and provides feedback optimization. If the analysis is qualified, feedback optimization is performed; if the analysis is unqualified, source tracing and detection are carried out.

[0009] The Channel Anomaly Feedback Optimization Unit analyzes and optimizes anomaly feedback from business channels, and conducts compliance management based on the anomaly feedback analysis and optimization.

[0010] The channel analysis targeted control unit conducts compliance assessment and control of newly established business channels, screens existing business channels based on the assessment and control, and decides whether to retain the current business channels.

[0011] In a preferred embodiment of the present invention, the operation process of the channel usage scenario analysis unit is as follows:

[0012] Based on the operation of the business channels, log data of the business channels is collected, including transaction order data, product review data, and product advertising data.

[0013] The data includes transaction order data such as transaction time, transaction amount, transaction terminal ID, and delivery address; product review data such as review content text, review time, and review account ID; product advertising data such as details page images and promotional copy; real-time screenshots of the product display on the corresponding terminal and the actual time spent browsing the product on the terminal are obtained based on the transaction terminal; and logistics information of the corresponding products from the business channels is obtained, including logistics trajectory, logistics time, and delivery address; the collected log data is processed; and abnormal values ​​in the log data are removed.

[0014] In a preferred embodiment of the present invention, after data processing is completed, the collected multi-dimensional data is jointly compared:

[0015] Obtain the transaction time node from the transaction order data and the logistics time node from the logistics information, and obtain the delay time of the current transaction order based on the time node comparison, and set it as transaction logistics related data;

[0016] The system obtains the review account ID from the product review data and the corresponding delivery ID from the delivery address in the logistics information. Based on the comparison of the account IDs, it obtains the non-overlapping frequency of IDs within the business channel. Based on the fluctuation of the non-overlapping frequency values, it obtains the frequency growth trend and sets it as the review logistics associated data.

[0017] In a preferred embodiment of the present invention, transaction logistics correlation data and evaluation logistics correlation data are analyzed:

[0018] If the transaction logistics associated data exceeds the delay time threshold, or if the transaction time node of the transaction logistics associated data is earlier than the logistics time node, the authenticity of the transaction logistics associated data is determined to be abnormal.

[0019] If the frequency growth span of the corresponding frequency growth trend of the logistics-related data exceeds the set frequency increase span threshold at any time, the authenticity of the logistics-related data is determined to be abnormal.

[0020] When the authenticity is abnormal, a data screening signal is generated and sent to the multi-dimensional supervision and feedback platform. After receiving the signal, the multi-dimensional supervision and feedback platform performs source tracing and detection on the real-time log data of each business channel.

[0021] Conversely, if the transaction logistics-related data does not exceed the delay time threshold, and the frequency increase span at any given time does not exceed the set frequency increase span threshold, then it is inferred that the current business channel's usage scenario analysis is qualified, a usage scenario analysis qualified signal is generated and sent to the multi-dimensional supervision and feedback platform.

[0022] In a preferred embodiment of the present invention, the process of the channel anomaly feedback optimization unit is as follows:

[0023] The marketing data of the business channels is obtained by converting sales calls into text streams through a real-time speech recognition engine and attaching timestamps and corresponding business channel numbers; the historical complaint keyword database is obtained from the customer relationship management system based on the historical business channel execution time periods, from which high-frequency words and their weights are obtained;

[0024] Extract contract data, obtain semantics from contract text, and obtain revision records of clauses within the contract text from contract template; obtain customer performance behavior indicators from customer logs within business channels, i.e., the number of times a customer fails to execute clauses within the contract template.

[0025] As a preferred embodiment of the present invention, the overlapping words of the text stream of the current business channel and the complaint keyword database are obtained, and the proportion of high-frequency words and low-frequency words is obtained according to the frequency type of the overlapping words, and they are marked as marketing parameters.

[0026] At the same operating moment, the contract template where the business channel text stream is located is obtained, and the clause revision record is obtained according to the real-time contract template. If the contract template is not revised in time, the time interval between the timestamp of the revision record and the current contract template generation time is obtained and marked as contract data.

[0027] Based on the currently generated contract, the existing clauses in the contract template are obtained, and the performance behavior indicators of the existing clauses are collected. If the performance behavior indicators do not exceed the set proportion threshold of the current customer volume, the contract template generation time and the adjacent historical clause revision time are collected. The difference between the performance behavior indicators at the corresponding time is calculated to obtain the frequency deviation value, and it is marked as performance data.

[0028] In a preferred embodiment of the present invention, each time node is obtained according to the operation process of the business channel, and obtaining the time node indicates the generation of a new contract; during the operation, marketing parameters, contract data, and performance data are obtained in the order of the time nodes; and marketing parameter trends, contract data trends, and performance data trends are obtained as the number of time nodes increases.

[0029] And perform pairwise trend comparison analysis:

[0030] The overlap duration between the growth trends of marketing parameters and contract data is recorded and marked as a channel characteristic parameter. If the channel characteristic parameter exceeds the set overlap duration threshold, a non-compliance signal is generated and sent to the multi-dimensional supervision and feedback platform.

[0031] If the channel characteristic parameters do not exceed the set overlap duration threshold, a characteristic compliance signal will be generated and sent to the multi-dimensional supervision and feedback platform.

[0032] The system obtains the growth rate of contract data trends and the growth rate of performance data trends, calculates the sum of growth rates based on these rates, and marks it as a channel impact parameter. If the channel impact parameter exceeds the set rate and threshold, a non-compliance constraint signal is generated and sent to the multi-dimensional supervision and feedback platform; if the channel impact parameter does not exceed the set rate and threshold, a compliance constraint signal is generated and sent to the multi-dimensional supervision and feedback platform.

[0033] The data shows the growth value of the fulfillment data trend, corresponding to the order generation time point and the marketing parameter exceeding the set threshold time point. The overlapping time points are obtained by comparing the time points. The overlapping time points indicate that the deviation between the two time points is within the set time range.

[0034] If the overlapping time point occurs when the corresponding order production time point is earlier than the abnormal marketing parameter time point, a marketing non-compliance signal will be generated and sent to the multi-dimensional supervision and feedback platform.

[0035] If the overlapping time point occurs when the corresponding order production time point is later than the abnormal marketing parameter time point, a non-compliance signal is generated and sent to the multi-dimensional supervision and feedback platform. After receiving various types of non-compliance signals, the multi-dimensional supervision and feedback platform will carry out compliance control according to the corresponding link of the signal.

[0036] As a preferred embodiment of the present invention, the process of channel analysis targeted control unit is as follows:

[0037] Select data from the company's existing business channel database that shares at least two of the following similar characteristics with newly established business channels: business type matching degree (e.g., product type, logistics type); same registered region and recent transaction volume (e.g., order volume); mark the selected existing business channels as similar channels, and extract their historical compliance records and operational data; historical compliance records include violation type, frequency, and corresponding transaction volume percentage; operational data includes average daily transaction count and user complaint rate; and mark the types of records with consecutive abnormalities in the corresponding compliance records of similar channels as compliance risk parameters.

[0038] In a preferred embodiment of the present invention, during the real-time business volume increase phase of a newly established business channel, the rising range of the compliance risk parameter is obtained and the set threshold of the same type of parameter corresponding to the current business volume is obtained. The risk parameter fluctuation ratio is calculated based on the ratio. Based on the time period corresponding to the risk parameter fluctuation ratio, the overlap duration between the fluctuation ratio growth phase and the daily average number of transactions of the newly established business channel is obtained, and the rate of increase of the overlap duration is marked as the quantitative value of the risk parameter impact.

[0039] In a preferred embodiment of the present invention, the fluctuation ratio of the risk parameter and the quantified value of the impact of the risk parameter are analyzed:

[0040] If the fluctuation ratio of the risk parameter exceeds the set fluctuation ratio threshold, or if the quantitative value of the risk parameter's impact exceeds the set time increase rate threshold, an establishment control signal will be generated and sent to the multi-dimensional monitoring and feedback platform. After receiving the establishment control signal, the multi-dimensional monitoring and feedback platform will establish control over the business channel, screen the existing business channels, and determine whether to retain the business channel based on the screening results.

[0041] If the risk parameter fluctuation ratio does not exceed the set fluctuation ratio threshold, and the quantitative value of the risk parameter impact does not exceed the set time increase rate threshold, a channel retention signal will be generated and sent to the multi-dimensional monitoring and feedback platform.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] 1. In this invention, existing monitoring relies on data from the business channels themselves (such as orders and reviews). Terminals may evade supervision by tampering with data within the platform, and the lack of independent third-party data verification leads to biased compliance judgments. By combining usage scenario analysis, this invention can accurately identify fraudulent transactions and reviews from various business channels. It can also verify the consistency between the content displayed in product advertisements and the actual products. Through data analysis, it eliminates the risk of tampering with the business channels' own data, avoids data isolation at each stage, and prevents the formation of a collaborative supervision logic, resulting in low regulatory efficiency and a high rate of missed judgments.

[0044] 2. In this invention, abnormal feedback analysis and optimization of business channels are performed. In the prior art, only the sales script is monitored, and the consistency of contract terms and performance records across the entire chain cannot be identified. Although semantic recognition is achieved, a closed-loop verification of marketing-contract-performance is not built. However, the channel abnormal feedback optimization can track the consistency of commitments across links and intercept the progress of business channels in a timely manner to avoid channel transaction abnormalities.

[0045] 3. In this invention, compliance assessment and control of newly established business channels is beneficial to the accuracy of compliance analysis of newly established business channels. It avoids the inability to accurately guarantee the accuracy of compliance analysis of business channels when historical data is lacking, and also avoids compliance assessment bias caused by low data volume of business channels, thereby improving the analysis accuracy of business channels. Attached Figure Description

[0046] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0047] Figure 1 This is a system principle block diagram of the present invention;

[0048] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0049] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0051] Please see Figure 1 As shown, the business channel compliance multi-dimensional supervision and feedback system based on differentiated management and control includes a multi-dimensional supervision and feedback platform. This platform communicates with a channel usage scenario analysis unit, a channel anomaly feedback optimization unit, and a targeted channel analysis control unit. For detailed system execution flow, please refer to [link / reference]. Figure 2 As shown;

[0052] The multi-dimensional monitoring and feedback platform generates channel usage scenario analysis signals and sends them to the channel usage scenario analysis unit.

[0053] After receiving the channel usage scenario analysis signal, the channel usage scenario analysis unit performs usage scenario analysis on the business channels;

[0054] In existing technologies, monitoring relies on data from the business channels themselves (such as orders and reviews). Terminals may evade supervision by tampering with data within the platform, and the lack of independent third-party data verification leads to biased compliance judgments. By combining usage scenario analysis, it is possible to accurately identify fraudulent transactions and fake reviews across various business channels. It can also verify the consistency between the content displayed in product advertisements and the actual products. Data analysis can eliminate the risk of tampering with the business channels' own data, avoid data silos at each stage, prevent the formation of collaborative supervision logic, and result in low regulatory efficiency and a high rate of missed detections.

[0055] Based on the operation of the business channels, log data of the business channels is collected, including transaction order data, product review data, and product advertising data.

[0056] The transaction order data includes transaction time, transaction amount, transaction terminal ID, and shipping address; the product review data includes review content text, review time, and review account ID; and the product advertising data includes details page images and promotional copy.

[0057] The data collection process involves obtaining real-time screenshots of product displays on the corresponding transaction terminals and the actual duration of product browsing on those terminals. This type of data collection can be performed using a standalone web crawler.

[0058] And obtain the logistics information of the corresponding products in the business channels, including logistics trajectory, logistics time and delivery address;

[0059] Perform data processing on the collected log data;

[0060] Remove abnormal values ​​from the log data, specifically: orders with a transaction amount of zero and review texts with consecutively repeated reviews;

[0061] After data processing is completed, the collected multi-dimensional data is jointly compared:

[0062] Obtain the transaction time node from the transaction order data and the logistics time node from the logistics information, and obtain the delay time of the current transaction order based on the time node comparison, and set it as transaction logistics related data;

[0063] Obtain the review account ID from the product review data and the corresponding delivery ID from the delivery address in the logistics information. Based on the comparison of account IDs, obtain the non-overlapping frequency of IDs within the business channel. Based on the fluctuation of the non-overlapping frequency values, obtain the frequency growth trend and set it as the review logistics associated data.

[0064] And analyze the transaction logistics correlation data and the evaluation logistics correlation data:

[0065] If the transaction logistics associated data exceeds the delay time threshold, or if the transaction time node of the transaction logistics associated data is earlier than the logistics time node, the authenticity of the transaction logistics associated data is determined to be abnormal.

[0066] If the frequency growth span of the corresponding frequency growth trend of the logistics-related data exceeds the set frequency increase span threshold at any time, the authenticity of the logistics-related data is determined to be abnormal.

[0067] When the authenticity is abnormal, a data screening signal is generated and sent to the multi-dimensional supervision and feedback platform. After receiving the signal, the multi-dimensional supervision and feedback platform performs source tracing and detection on the real-time log data of each business channel.

[0068] Conversely, if the transaction logistics-related data does not exceed the delay time threshold and the frequency increase span at any time does not exceed the set frequency increase span threshold, it is inferred that the current business channel's usage scenario analysis is qualified, a usage scenario analysis qualified signal is generated and sent to the multi-dimensional supervision and feedback platform.

[0069] The multi-dimensional monitoring and feedback platform generates channel anomaly feedback optimization signals and sends them to the channel anomaly feedback optimization unit.

[0070] After receiving the channel anomaly feedback optimization signal, the channel anomaly feedback optimization unit performs anomaly feedback analysis and optimization on the business channel. In the existing technology, only the sales script is monitored, and the consistency of contract terms and performance records across the entire chain cannot be identified. Although semantic recognition is achieved, a closed-loop verification of marketing-contract-performance is not built. In contrast, the channel anomaly feedback optimization can track the consistency of commitments across links and intercept the progress of business channels in a timely manner to avoid channel transaction anomalies.

[0071] The marketing data of the business channels is obtained by converting sales calls into text streams through a real-time speech recognition engine (such as an ASR system) and attaching timestamps and corresponding business channel numbers.

[0072] Based on the historical business channel execution period, the customer relationship management system was used to obtain a historical complaint keyword database, from which high-frequency words and their weights were obtained.

[0073] Extract contract data, obtain semantics from the contract text, and obtain information such as the revision record, revision time, and reviser of the contract text based on the contract template;

[0074] Obtain customer performance metrics from customer logs within the business channels, namely the number of times a customer fails to execute the terms in the contract template;

[0075] Obtain overlapping words between the text stream of the current business channel and the complaint keyword database, and obtain the proportion of high-frequency words and low-frequency words based on the frequency type of the overlapping words, and mark them as marketing parameters.

[0076] At the same operating moment, the contract template where the business channel text stream is located is obtained, and the clause revision record is obtained according to the real-time contract template. If the contract template is not revised in time, the time interval between the timestamp of the revision record and the current contract template generation time is obtained and marked as contract data.

[0077] Based on the currently generated contract, the existing clauses in the contract template are obtained, and the performance behavior indicators of the existing clauses are collected. If the performance behavior indicators do not exceed the set proportion threshold of the current customer volume, the contract template generation time and the adjacent historical clause revision time are collected. The difference between the performance behavior indicators at the corresponding time is calculated to obtain the frequency deviation value, and it is marked as performance data.

[0078] The time nodes are obtained based on the operation of the business channels, and the time nodes indicate the generation of new contracts.

[0079] During operation, marketing parameters, contract data, and performance data are acquired in sequence according to time nodes; trends in marketing parameters, contract data, and performance data are obtained as the number of time nodes increases.

[0080] And perform pairwise trend comparison analysis:

[0081] The growth trend of marketing parameters and the growth trend of contract data are compared and overlapped for a certain duration, and this overlap is marked as a channel characteristic parameter. If the channel characteristic parameter exceeds the set overlap duration threshold, it indicates that the compliance analysis of the current business channel is abnormal, generating a characteristic non-compliance signal and sending it to the multi-dimensional supervision and feedback platform.

[0082] If the channel characteristic parameters do not exceed the set overlap duration threshold, it indicates that the compliance analysis of the current business channel is normal, and a characteristic compliance signal is generated and sent to the multi-dimensional supervision and feedback platform. It should be noted that the overlap duration comparison is based on the premise that the growth trend of the marketing parameter trend and the growth trend of the contract data trend are both lower than the set trend duration threshold.

[0083] The system acquires the growth rates of contract data trends and performance data trends, calculates the sum of these growth rates, and marks it as a channel impact parameter. If the channel impact parameter exceeds the set speed and threshold, it indicates that the contract formulation impact of the business channel is abnormal, generating a non-compliance constraint signal and sending it to the multi-dimensional monitoring and feedback platform. If the channel impact parameter does not exceed the set speed and threshold, it indicates that the contract formulation impact of the business channel is normal, generating a compliance constraint signal and sending it to the multi-dimensional monitoring and feedback platform.

[0084] The data shows the growth value of the fulfillment data trend, corresponding to the order generation time point and the marketing parameter exceeding the set threshold time point. The overlapping time points are obtained by comparing the time points. The overlapping time points indicate that the deviation between the two time points is within the set time range.

[0085] If the corresponding order production time is earlier than the abnormal marketing parameter time when the overlapping time point occurs, it indicates that the marketing of the business channel is abnormal, generates a marketing non-compliance signal and sends it to the multi-dimensional supervision and feedback platform.

[0086] If the overlapping time point occurs when the corresponding order production time point is later than the abnormal marketing parameter time point, it indicates that the contract terms of the business channel are non-compliant, generating a non-compliance signal and sending it to the multi-dimensional supervision and feedback platform.

[0087] After receiving various types of non-compliance signals, the multi-dimensional supervision and feedback platform will carry out compliance management according to the corresponding links of the signals;

[0088] Simultaneously, channel analysis-specific control signals are generated and sent to the channel analysis-specific control unit;

[0089] After receiving the channel analysis targeted control signal, the channel analysis targeted control unit performs compliance assessment and control on the newly established business channels. This is beneficial to the accuracy of compliance analysis of the newly established business channels, avoids the inability to accurately guarantee the accuracy of compliance analysis of business channels when historical data is lacking, and also avoids compliance assessment bias caused by low data volume of business channels, thereby improving the analysis accuracy of business channels.

[0090] Select data from the company's existing business channel database that shares at least two of the following similar characteristics with newly established business channels: business type matching degree (e.g., product type, logistics type); same registered region; and recent transaction volume (e.g., product order volume).

[0091] The selected existing business channels are marked as similar channels, and their historical compliance records (type of violation, frequency, and corresponding transaction volume percentage) and operational data (average number of transactions per day, user complaint rate) are extracted from the similar channels.

[0092] Based on the types of records that show continuous abnormalities in the compliance records of similar channels, they are marked as compliance risk parameters, such as the frequency of violations exceeding the set frequency threshold, or the average number of transactions per day not exceeding the set range for the current stage;

[0093] During the period of increased real-time business volume in newly established business channels, the rise range of compliance risk parameters is obtained and the set threshold of the same type of parameter corresponding to the current business volume is used to calculate the risk parameter fluctuation ratio.

[0094] Based on the corresponding time period of the risk parameter fluctuation ratio, obtain the overlap duration between the growth phase of the fluctuation ratio and the decline phase of the average daily transaction volume of the newly established business channels, and mark the rate of increase of the overlap duration as the quantitative value of the impact of the risk parameter.

[0095] Analyze the fluctuation ratio of risk parameters and the quantitative value of the impact of risk parameters:

[0096] If the fluctuation ratio of the risk parameter exceeds the set fluctuation ratio threshold, or if the quantitative value of the risk parameter's impact exceeds the set time increase rate threshold, it is inferred that the newly established business channel has non-compliance risks. An establishment control signal is generated and sent to the multi-dimensional supervision and feedback platform. After receiving the establishment control signal, the multi-dimensional supervision and feedback platform will implement establishment control on the business channel, screen the existing business channels, and determine whether to retain the business channel based on the screening results.

[0097] If the fluctuation ratio of the risk parameter does not exceed the set fluctuation ratio threshold, and the quantitative value of the impact of the risk parameter does not exceed the set time increase rate threshold, then it is inferred that the newly established business channel is compliant, a channel retention signal is generated and sent to the multi-dimensional supervision and feedback platform.

[0098] In use, this invention includes a channel usage scenario analysis unit that analyzes the usage scenarios of business channels, determines whether the analysis results are qualified, and performs feedback optimization. If the analysis is qualified, feedback optimization is performed; if the analysis is unqualified, source tracing and detection are performed. A channel anomaly feedback optimization unit analyzes and optimizes anomaly feedback of business channels, and performs compliance control based on the anomaly feedback analysis and optimization. A channel analysis targeted control unit performs compliance assessment and control on newly established business channels, screens existing business channels based on the assessment and control, and decides whether to retain the current business channels.

[0099] Thresholds, preset values, preset ranges, etc. are set for result comparison and analysis to determine whether they are good or bad. The value of these thresholds is determined by a combination of large-scale model analysis of sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influences.

[0100] Furthermore, the settings for weighting ratios, influence factors, etc., are based on the magnitude of each parameter's influence on the results. The specific values ​​are allocated to ultimately reflect the impact on the results. The settings for input and storage are also determined by a combination of large-scale model analysis of sample data and human experience. Appropriate adjustments can also be made based on seasonal or rational influence conditions.

[0101] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A multi-dimensional monitoring and feedback system for compliance of business channels based on differentiated management and control, characterized in that: This includes a multi-dimensional supervision and feedback platform, whose communication connections include: The channel usage scenario analysis unit performs usage scenario analysis on business channels. Based on the analysis results, it determines whether the analysis is satisfactory and provides feedback for optimization. If the analysis is satisfactory, optimization is performed; if the analysis is unsatisfactory, source tracing and detection are conducted. The operation process of the channel usage scenario analysis unit is as follows: Based on the operation of the business channels, log data of the business channels is collected, including transaction order data, product review data, and product advertising data. The data includes transaction order data such as transaction time, transaction amount, transaction terminal ID, and delivery address; product review data such as review content text, review time, and review account ID; product advertising data such as details page images and promotional copy; real-time screenshots of product display on the corresponding terminal and the actual time spent browsing the product on the terminal are obtained based on the transaction terminal; and logistics information of the corresponding products from the business channels is obtained, including logistics trajectory, logistics time, and delivery address; the collected log data is processed; and abnormal values ​​in the log data are removed. After data processing is completed, the collected multi-dimensional data is jointly compared: Obtain the transaction time node from the transaction order data and the logistics time node from the logistics information, and obtain the delay time of the current transaction order based on the time node comparison, and set it as transaction logistics related data; Obtain the review account ID from the product review data and the corresponding delivery ID from the delivery address in the logistics information. Based on the comparison of account IDs, obtain the non-overlapping frequency of IDs within the business channel. Based on the fluctuation of the non-overlapping frequency values, obtain the frequency growth trend and set it as the review logistics associated data. Analyze transaction logistics correlation data and evaluation logistics correlation data: If the transaction logistics associated data exceeds the delay time threshold, or if the transaction time node of the transaction logistics associated data is earlier than the logistics time node, the authenticity of the transaction logistics associated data is determined to be abnormal. If the frequency growth span of the corresponding frequency growth trend of the logistics-related data exceeds the set frequency increase span threshold at any time, the authenticity of the logistics-related data is determined to be abnormal. When the authenticity is abnormal, a data screening signal is generated and sent to the multi-dimensional supervision and feedback platform. After receiving the signal, the multi-dimensional supervision and feedback platform performs source tracing and detection on the real-time log data of each business channel. Conversely, if the transaction logistics-related data does not exceed the delay time threshold and the frequency increase span at any time does not exceed the set frequency increase span threshold, it is inferred that the current business channel's usage scenario analysis is qualified, a usage scenario analysis qualified signal is generated and sent to the multi-dimensional supervision and feedback platform. The Channel Anomaly Feedback Optimization Unit analyzes and optimizes anomaly feedback from business channels, and conducts compliance management based on the anomaly feedback analysis and optimization. The channel analysis targeted control unit conducts compliance assessment and control of newly established business channels, screens existing business channels based on the assessment and control, and decides whether to retain the current business channels.

2. The multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management and control as described in claim 1, characterized in that, The process of the channel anomaly feedback optimization unit is as follows: The marketing data of the business channels is obtained by converting sales calls into text streams through a real-time speech recognition engine and attaching timestamps and corresponding business channel numbers; the historical complaint keyword database is obtained from the customer relationship management system based on the historical business channel execution time periods, from which high-frequency words and their weights are obtained; Extract contract data, obtain semantics from contract text, and obtain revision records of clauses within the contract text from contract template; obtain customer performance behavior indicators from customer logs within business channels, i.e., the number of times a customer fails to execute clauses within the contract template.

3. The multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management and control as described in claim 2, characterized in that, Obtain overlapping words between the text stream of the current business channel and the complaint keyword database, and obtain the proportion of high-frequency words and low-frequency words based on the frequency type of the overlapping words, and mark them as marketing parameters. At the same operating moment, the contract template where the business channel text stream is located is obtained, and the clause revision record is obtained according to the real-time contract template. If the contract template is not revised in time, the time interval between the timestamp of the revision record and the current contract template generation time is obtained and marked as contract data. Based on the currently generated contract, the existing clauses in the contract template are obtained, and the performance behavior indicators of the existing clauses are collected. If the performance behavior indicators do not exceed the set proportion threshold of the current customer volume, the contract template generation time and the adjacent historical clause revision time are collected. The difference between the performance behavior indicators at the corresponding time is calculated to obtain the frequency deviation value, and it is marked as performance data.

4. The multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management and control as described in claim 3, characterized in that, Based on the operation of the business channels, we obtain various time nodes, which indicate the generation of new contracts. During the operation, we obtain marketing parameters, contract data, and performance data in the order of the time nodes. The marketing parameter trend, contract data trend, and performance data trend are obtained by increasing the number of time nodes. And perform pairwise trend comparison analysis: The overlap duration between the growth trends of marketing parameters and contract data is recorded and marked as a channel characteristic parameter. If the channel characteristic parameter exceeds the set overlap duration threshold, a non-compliance signal is generated and sent to the multi-dimensional supervision and feedback platform. If the channel characteristic parameters do not exceed the set overlap duration threshold, a characteristic compliance signal will be generated and sent to the multi-dimensional supervision and feedback platform. The system obtains the growth rate of contract data trends and the growth rate of performance data trends, calculates the sum of growth rates based on these rates, and marks it as a channel impact parameter. If the channel impact parameter exceeds the set rate and threshold, a non-compliance constraint signal is generated and sent to the multi-dimensional supervision and feedback platform; if the channel impact parameter does not exceed the set rate and threshold, a compliance constraint signal is generated and sent to the multi-dimensional supervision and feedback platform. The data shows the growth value of the fulfillment data trend, corresponding to the order generation time point and the marketing parameter exceeding the set threshold time point. The overlapping time points are obtained by comparing the time points. The overlapping time points indicate that the deviation between the two time points is within the set time range. If the overlapping time point occurs when the corresponding order generation time point is earlier than the abnormal marketing parameter time point, a marketing non-compliance signal will be generated and sent to the multi-dimensional supervision and feedback platform. If the overlapping time point occurs when the corresponding order generation time point is later than the abnormal marketing parameter time point, a non-compliance signal for the terms will be generated and sent to the multi-dimensional supervision and feedback platform.

5. The multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management and control as described in claim 4, characterized in that, The process of channel analysis and targeted control unit is as follows: From the enterprise's existing business channel database, select data that meets at least two of the following similar characteristics with newly established business channels: business type matching degree (specifically, product type and logistics type); same registered region and recent transaction volume (specifically, product order volume); mark the selected existing business channels as similar channels, and extract their historical compliance records and operational data; historical compliance records include violation type, frequency, and corresponding transaction volume percentage; operational data includes average daily transaction count and user complaint rate; mark the types of records with consecutive abnormalities in the corresponding compliance records of similar channels as compliance risk parameters.

6. The multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management and control as described in claim 5, characterized in that, During the period of increased real-time business volume in newly established business channels, the rise range of compliance risk parameters is obtained and the set threshold of the same type of parameter corresponding to the current business volume is obtained. The risk parameter fluctuation ratio is calculated based on the ratio. Based on the time period corresponding to the risk parameter fluctuation ratio, the overlap duration between the fluctuation ratio growth phase and the daily average number of transactions in newly established business channels is obtained, and the rate of increase of the overlap duration is marked as the quantitative value of the risk parameter impact.

7. The multi-dimensional supervision and feedback system for compliance of business channels based on differentiated management and control as described in claim 6, characterized in that, Analyze the fluctuation ratio of risk parameters and the quantitative value of the impact of risk parameters: If the fluctuation ratio of the risk parameter exceeds the set fluctuation ratio threshold, or if the quantitative value of the risk parameter's impact exceeds the set time increase rate threshold, an establishment control signal will be generated and sent to the multi-dimensional monitoring and feedback platform. After receiving the establishment control signal, the multi-dimensional monitoring and feedback platform will establish control over the business channel, screen the existing business channels, and determine whether to retain the business channel based on the screening results. If the risk parameter fluctuation ratio does not exceed the set fluctuation ratio threshold, and the quantitative value of the risk parameter impact does not exceed the set time increase rate threshold, a channel retention signal will be generated and sent to the multi-dimensional monitoring and feedback platform.

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