Optimization method and system based on intelligent outbound system
By using intelligent outbound calling system optimization methods, the risk level of communication lines is calculated and the usage frequency is dynamically adjusted, which solves the problem that traditional outbound calling systems cannot identify high-risk lines, and achieves efficient resource utilization and business continuity.
Patent Information
- Application Number
- CN202511476208.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-16
- Publication Date
- 2026-01-23
AI Technical Summary
Traditional outbound calling systems lack the ability to dynamically perceive and predict risks to communication lines, and cannot effectively identify and avoid high-risk outbound calling behaviors, resulting in a large number of communication lines being blocked, causing waste of outbound calling resources and business interruption.
By collecting and preprocessing risk data, prediction data, and frequency adjustment data through an intelligent outbound call database, the system calculates compliance risk index, account suspension prediction index, and usage frequency adjustment index, dynamically adjusts the usage frequency of low-risk communication lines, and identifies and avoids the use of high-risk lines.
Effectively identify high-risk lines, reduce the overall risk of account suspension, ensure the efficiency of communication resource utilization, and ensure the continuity of outbound calling services.
Smart Images
Figure CN121397141A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent outbound calling technology, and in particular to an optimization method and system based on an intelligent outbound calling system. Background Technology
[0002] Intelligent outbound calling refers to a system that proactively initiates calls to customers, then uses voice recognition and semantic understanding to identify customer intent and guides them according to business rules to independently complete the marketing process or screen potential customers for human intervention before transferring them to a human agent to complete the sales transaction. With the widespread application of intelligent outbound calling systems in customer service and marketing promotion, operators are increasingly tightening their control over nuisance calls. For example, operators commonly employ high-frequency blocking mechanisms (such as 28 calls / day for China Telecom, 26 calls / day for China Unicom, and 30 calls / day for China Mobile) and complaint-based blocking mechanisms (blocking a card after 3 complaints), leading to a severe risk of account suspension for intelligent outbound calling systems.
[0003] However, traditional outbound calling systems lack the ability to dynamically perceive and predict risks in communication lines, cannot effectively identify and avoid high-risk outbound calling behaviors, and cannot adjust outbound calling strategies based on real-time data. As a result, a large number of communication lines are easily blocked due to excessive risk, leading to waste of outbound calling resources and business interruption.
[0004] To address the aforementioned technical deficiencies, a solution is proposed. Summary of the Invention
[0005] The purpose of this invention is to address the problem that traditional outbound calling systems lack the ability to dynamically perceive and predict risks in communication lines, cannot effectively identify and avoid high-risk outbound calling behaviors, and cannot adjust outbound calling strategies based on real-time data. As a result, a large number of communication lines are blocked due to excessive risk, leading to wasted outbound calling resources and service interruptions.
[0006] To achieve the above objectives, the present invention adopts the following technical solution: an optimization method based on an intelligent outbound calling system, comprising the following steps:
[0007] Step 1: Collect risk data, prediction data, and frequency adjustment data generated during the outbound calling process through the intelligent outbound calling database, and preprocess the collected data to improve data quality;
[0008] Step 2: Receive risk data and perform analysis and calculation to obtain the compliance risk index of the communication lines, and classify the communication lines into high-risk communication lines, low-risk communication lines, and risk-free communication lines.
[0009] Step 3: Receive the predicted data and analyze and calculate it in conjunction with the compliance risk index of low-risk communication lines to obtain the account blocking prediction index of low-risk communication lines. The account blocking prediction index is used to reflect the possibility of low-risk communication lines being blocked.
[0010] Step 4: Receive frequency modulation data and analyze and calculate it in conjunction with the number blocking prediction index of low-risk communication lines to obtain the frequency adjustment index of communication lines, and dynamically adjust the frequency of low-risk communication lines according to the frequency adjustment index.
[0011] Furthermore, the preprocessing of the collected data involves standardizing the collected risk data, prediction data, and frequency modulation data using the Min-Max standardization method and the following standardization formula: Where X is the standardized data value, x j Let x be the numerical value of the j-th type of data to be processed. min x is the minimum value of the same type of data. max It represents the maximum value of the same type of data.
[0012] Furthermore, the risk data includes the number of complaints against the communication line within a preset statistical period, the number of times the communication line is blocked within a preset statistical period, and the total number of calls initiated in violation of regulations. The prediction data includes the number of calls made by the communication line in the current month and the number of times the communication line is blocked in historical statistical periods. The frequency modulation data includes the number of ongoing calls on the communication line and the usage frequency of the communication line.
[0013] Furthermore, the calculation process for the compliance risk index of communication lines is as follows:
[0014] S11. Obtain and analyze data on the number of complaints against the communication line within a preset statistical period, the number of times the communication line is blocked within a preset statistical period, and the total number of times the user initiates calls in violation of regulations.
[0015] S12. Calculate the compliance risk index CR of the communication line according to the following formula:
[0016]
[0017] Wherein, CPT represents the number of complaints received regarding the communication line within a preset statistical period. max AS represents the maximum number of complaints across all communication lines, where AS is the number of times a communication line has been blocked within a preset statistical period. max N represents the maximum number of times an account has been blocked across all communication lines, and N is the total number of calls initiated in violation of laws, regulations, industry standards, or operator directives within the time period during which outbound calls are prohibited. eThe standard number of calls initiated proactively and compliantly within the compliant period is defined as follows: a is the preset complaint weight coefficient, b is the preset account suspension weight coefficient, and c is the preset weight coefficient for illegal calls, and a+b+c=1.
[0018] S13. Obtain the preset compliance risk lower limit threshold CR low and compliance risk cap threshold CR top When compared with the compliance risk index CR, when CR <CR low If the communication line used to make outbound calls complies with laws, regulations, and industry standards, it is classified as a risk-free communication line.
[0019] S14, when CR∈[CR] low CR top If the number of calls made is 0, it indicates that a small number of communication lines that make outbound calls do not comply with legal and regulatory requirements and industry standards. These lines are classified as low-risk communication lines, and the prediction index for account blocking of low-risk communication lines is analyzed and calculated.
[0020] S15, When CR>CR top If this occurs, it indicates that a large number of communication lines used for making outbound calls do not comply with laws, regulations, and industry standards, and are therefore classified as high-risk communication lines. Intelligent outbound calls will then be suspended through these high-risk communication lines.
[0021] Furthermore, the calculation process for the prediction index of account suspension for low-risk communication lines is as follows:
[0022] S21. Obtain the number of calls made by low-risk communication lines in the current month and the number of accounts blocked in the historical statistical period, and analyze and calculate them in conjunction with the compliance risk index of low-risk communication lines.
[0023] S22. Calculate the blocking prediction index (FCT) for low-risk communication lines using the following formula:
[0024]
[0025] Where CR is the compliance risk index of the communication line, and n is the number of calls made by the communication line in the current month. max The maximum number of calls allowed per month for a pre-defined communication line, where m is the number of historical statistical periods for the communication line, and P is the maximum number of calls allowed per month. i Let P be the blocking rate of the communication line in the i-th historical statistical period. max P represents the maximum number of blocked accounts for the communication line across all historical statistical periods. minThe minimum blocking rate for a communication line across all historical statistical periods is used to reflect the likelihood of a low-risk communication line being blocked. The higher the value of the blocking prediction index, the higher the likelihood of a low-risk communication line being blocked.
[0026] Furthermore, the calculation process for the frequency adjustment index of communication lines is as follows:
[0027] S31. Obtain the number of ongoing calls on the communication line and the usage frequency data of the communication line, and analyze and calculate them in combination with the number blocking prediction index of low-risk communication lines.
[0028] S32. Calculate the frequency adjustment index k of the communication line according to the following formula:
[0029]
[0030] Where FCT is the prediction index for account suspension of low-risk communication lines, and call is the number of ongoing calls on the communication line. max The maximum number of calls that can be carried on a communication line is α, which is a preset frequency adjustment conversion coefficient. The frequency adjustment index is used to adjust the frequency used by low-risk communication lines.
[0031] S33. Calculate and analyze the adjusted usage frequency f of the low-risk communication line based on the following formula: Among them, f e The preset standard operating frequency for the communication line is denoted by k, where k is the frequency adjustment index for the communication line.
[0032] The present invention also provides an optimization system based on an intelligent outbound calling system, including a data acquisition unit, a risk analysis unit, a number blocking analysis unit, a frequency modulation analysis unit, and a frequency modulation control unit;
[0033] The data acquisition unit is used to collect risk data, prediction data and frequency modulation data generated during the process of making outbound calls through the intelligent outbound call database, and to preprocess the collected data. Then, the preprocessed risk data is sent to the risk analysis unit, the prediction data is sent to the account blocking analysis unit, and the frequency modulation data is sent to the frequency modulation analysis unit.
[0034] The risk analysis unit is used to receive risk data and perform analysis and calculation to obtain the compliance risk index of the communication line, and classify the communication line into high-risk communication line, low-risk communication line and risk-free communication line.
[0035] The account blocking analysis unit is used to receive prediction data and combine it with the compliance risk index of low-risk communication lines to perform analysis and calculation, and to obtain the account blocking prediction index of low-risk communication lines. The account blocking prediction index is used to reflect the possibility of low-risk communication lines being blocked.
[0036] The frequency modulation analysis unit is used to receive frequency modulation data and analyze and calculate it in conjunction with the number blocking prediction index of low-risk communication lines to obtain the frequency adjustment index for the use of communication lines.
[0037] The frequency modulation control unit is used to dynamically adjust the operating frequency of low-risk communication lines according to the frequency adjustment index.
[0038] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:
[0039] This invention relates to an optimization method and system based on an intelligent outbound calling system. By calculating a compliance risk index and classifying communication lines into risk levels, it can effectively identify high-risk lines and promptly stop their use, thereby effectively avoiding the risk of account suspension due to violations. Simultaneously, it focuses on optimizing low-risk lines, significantly reducing the overall risk of account suspension. Furthermore, by combining the compliance risk index with historical data to calculate an account suspension prediction index, it predicts the likelihood of account suspension for low-risk lines, providing a forward-looking basis for line scheduling. Additionally, based on the account suspension prediction index and real-time call data, it calculates a usage frequency adjustment index, enabling dynamic adjustment of the usage frequency of low-risk lines. This effectively avoids account suspension caused by high-frequency calls, ensuring both efficient utilization of communication resources and the continuity of outbound calling services. Attached Figure Description
[0040] Figure 1 A schematic diagram of the method flow of the present invention is shown;
[0041] Figure 2 A schematic diagram of the system flow of the present invention is shown. Detailed Implementation
[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.
[0043] Example 1:
[0044] like Figure 1 As shown, an optimization method based on an intelligent outbound calling system includes the following steps:
[0045] First, the intelligent outbound calling database collects risk data, prediction data, and frequency modulation data generated during the outbound calling process. The collected data is then preprocessed to improve data quality. Risk data includes the number of complaints against the communication line within a preset statistical period, the number of times the communication line is blocked within a preset statistical period, and the total number of calls initiated in violation of regulations. Prediction data includes the number of calls made by the communication line in the current month and the blocking rate of the communication line in historical statistical periods. Frequency modulation data includes the number of ongoing calls on the communication line and the usage frequency of the communication line.
[0046] The preprocessing of the collected data involves standardizing the collected risk data, prediction data, and frequency modulation data using the Min-Max standardization method and the following standardization formula: Where X is the standardized data value, x j Let x be the numerical value of the j-th type of data to be processed. min x is the minimum value of the same type of data. max It represents the maximum value of the same type of data.
[0047] Then, risk data is received and analyzed to obtain the compliance risk index of the communication line, and the communication line is divided into high-risk communication line, low-risk communication line and risk-free communication line.
[0048] The calculation process for the compliance risk index of communication lines is as follows:
[0049] S11. Obtain and analyze data on the number of complaints against the communication line within a preset statistical period, the number of times the communication line is blocked within a preset statistical period, and the total number of times the user initiates calls in violation of regulations.
[0050] S12. Calculate the compliance risk index CR of the communication line according to the following formula:
[0051]
[0052] Wherein, CPT represents the number of complaints received regarding the communication line within a preset statistical period. max AS represents the maximum number of complaints across all communication lines, where AS is the number of times a communication line has been blocked within a preset statistical period. max N represents the maximum number of times an account has been blocked across all communication lines, and N is the total number of calls initiated in violation of laws, regulations, industry standards, or operator directives within the time period during which outbound calls are prohibited. eThe standard number of calls initiated proactively and compliantly within the compliant period is defined as follows: a is the preset complaint weight coefficient, b is the preset account suspension weight coefficient, and c is the preset weight coefficient for illegal calls, and a+b+c=1.
[0053] S13. Obtain the preset compliance risk lower limit threshold CR low and compliance risk cap threshold CR top When compared with the compliance risk index CR, when CR <CR low If the call is successful, it means that the communication line used for making outbound calls complies with laws, regulations and industry standards, and is classified as a risk-free communication line. It can continue to make intelligent outbound calls according to the preset standard frequency of the communication line.
[0054] S14, when CR∈[CR] low CR top If the number of calls made is 0, it indicates that a small number of communication lines that make outbound calls do not comply with legal and regulatory requirements and industry standards. These lines are classified as low-risk communication lines, and the prediction index for account blocking of low-risk communication lines is analyzed and calculated.
[0055] S15, When CR>CR top If this occurs, it indicates that a large number of communication lines used for making outbound calls do not comply with laws, regulations, and industry standards, and are therefore classified as high-risk communication lines. Intelligent outbound calls will then be suspended through these high-risk communication lines.
[0056] Afterwards, the predicted data is received and analyzed in conjunction with the compliance risk index of low-risk communication lines to obtain the account blocking prediction index of low-risk communication lines. The account blocking prediction index is used to reflect the possibility of low-risk communication lines being blocked.
[0057] The calculation process for the number blocking prediction index of low-risk communication lines is as follows:
[0058] S21. Obtain the number of calls made by low-risk communication lines in the current month and the number of accounts blocked in the historical statistical period, and analyze and calculate them in conjunction with the compliance risk index of low-risk communication lines.
[0059] S22. Calculate the blocking prediction index (FCT) for low-risk communication lines using the following formula:
[0060]
[0061] Where CR is the compliance risk index of the communication line, and n is the number of calls made by the communication line in the current month. max The maximum number of calls allowed per month for a pre-defined communication line, where m is the number of historical statistical periods for the communication line, and P is the maximum number of calls allowed per month. i Let P be the blocking rate of the communication line in the i-th historical statistical period.max P represents the maximum number of blocked accounts for the communication line across all historical statistical periods. min The minimum blocking rate for a communication line across all historical statistical periods is used to reflect the likelihood of a low-risk communication line being blocked. The higher the value of the blocking prediction index, the higher the likelihood of a low-risk communication line being blocked.
[0062] Finally, the frequency modulation data is received and analyzed in conjunction with the number blocking prediction index of low-risk communication lines to obtain the frequency adjustment index of communication lines. The frequency of use of low-risk communication lines is then dynamically adjusted according to the frequency adjustment index.
[0063] The calculation process for the frequency adjustment index of communication lines is as follows:
[0064] S31. Obtain the number of ongoing calls on the communication line and the usage frequency data of the communication line, and analyze and calculate them in combination with the number blocking prediction index of low-risk communication lines.
[0065] S32. Calculate the frequency adjustment index k of the communication line according to the following formula:
[0066]
[0067] Where FCT is the prediction index for account suspension of low-risk communication lines, and call is the number of ongoing calls on the communication line. max The maximum number of calls that a communication line can carry is α, which is a preset frequency adjustment conversion coefficient determined based on a large number of experiments. The frequency adjustment index is used to adjust the frequency used by low-risk communication lines.
[0068] S33. Calculate and analyze the adjusted usage frequency f of the low-risk communication line based on the following formula: Among them, f e The preset standard operating frequency for the communication line is denoted by k, where k is the frequency adjustment index for the communication line.
[0069] This invention effectively identifies high-risk lines and promptly stops their use by calculating a compliance risk index and classifying communication lines into risk levels, thereby effectively avoiding the risk of account suspension due to violations. Simultaneously, it focuses on optimizing low-risk lines, significantly reducing the overall risk of account suspension. Furthermore, by combining the compliance risk index with historical data to calculate a suspension prediction index, it predicts the likelihood of account suspension for low-risk lines, providing a forward-looking basis for line scheduling. Additionally, based on the suspension prediction index and real-time call data, it calculates a usage frequency adjustment index, enabling dynamic adjustment of the usage frequency of low-risk lines, effectively avoiding account suspension caused by high-frequency calls. This ensures both efficient utilization of communication resources and the continuity of outbound calling services.
[0070] Example 2:
[0071] like Figure 2 As shown, an optimization system based on an intelligent outbound calling system includes a data acquisition unit, a risk analysis unit, a number blocking analysis unit, a frequency modulation analysis unit, and a frequency modulation control unit.
[0072] The data acquisition unit is used to collect risk data, prediction data and frequency modulation data generated during the process of making outbound calls through the intelligent outbound call database, and to preprocess the collected data. Then, the preprocessed risk data is sent to the risk analysis unit, the prediction data is sent to the account blocking analysis unit, and the frequency modulation data is sent to the frequency modulation analysis unit.
[0073] The risk analysis unit is used to receive risk data and perform analysis and calculation to obtain the compliance risk index of the communication line, and classify the communication line into high-risk communication line, low-risk communication line and risk-free communication line.
[0074] The account blocking analysis unit is used to receive prediction data and combine it with the compliance risk index of low-risk communication lines to perform analysis and calculation, and to obtain the account blocking prediction index of low-risk communication lines. The account blocking prediction index is used to reflect the possibility of low-risk communication lines being blocked.
[0075] The frequency modulation analysis unit is used to receive frequency modulation data and analyze and calculate it in conjunction with the number blocking prediction index of low-risk communication lines to obtain the frequency adjustment index for the use of communication lines.
[0076] The frequency modulation control unit is used to dynamically adjust the operating frequency of low-risk communication lines according to the frequency adjustment index.
[0077] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.
[0078] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.
[0079] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.
Claims
1. An optimization method based on an intelligent outbound calling system, characterized in that, Includes the following steps: Step 1: Collect risk data, prediction data, and frequency adjustment data generated during the outbound calling process through the intelligent outbound calling database, and preprocess the collected data to improve data quality; Step 2: Receive risk data and perform analysis and calculation to obtain the compliance risk index of the communication lines, and classify the communication lines into high-risk communication lines, low-risk communication lines, and risk-free communication lines. Step 3: Receive the predicted data and analyze and calculate it in conjunction with the compliance risk index of low-risk communication lines to obtain the account blocking prediction index of low-risk communication lines. The account blocking prediction index is used to reflect the possibility of low-risk communication lines being blocked. Step 4: Receive frequency modulation data and analyze and calculate it in conjunction with the number blocking prediction index of low-risk communication lines to obtain the frequency adjustment index of communication lines, and dynamically adjust the frequency of low-risk communication lines according to the frequency adjustment index.
2. The optimization method based on an intelligent outbound calling system according to claim 1, characterized in that, The preprocessing of the collected data involves standardizing the collected risk data, prediction data, and frequency modulation data using the Min-Max standardization method and the following standardization formula: Where X is the standardized data value, x j Let x be the numerical value of the j-th type of data to be processed. min x is the minimum value of the same type of data. max It represents the maximum value of the same type of data.
3. The optimization method based on an intelligent outbound calling system according to claim 1, characterized in that, The risk data includes the number of complaints against the communication line within a preset statistical period, the number of times the communication line is blocked within a preset statistical period, and the total number of calls initiated in violation of regulations. The prediction data includes the number of calls made by the communication line in the current month and the number of times the communication line is blocked within a historical statistical period. The frequency modulation data includes the number of ongoing calls on the communication line and the usage frequency of the communication line.
4. The optimization method based on an intelligent outbound calling system according to claim 1, characterized in that, The calculation process for the compliance risk index of communication lines is as follows: S11. Obtain and analyze data on the number of complaints against the communication line within a preset statistical period, the number of times the communication line is blocked within a preset statistical period, and the total number of times the user initiates calls in violation of regulations. S12. Calculate the compliance risk index CR of the communication line according to the following formula: Wherein, CPT represents the number of complaints received regarding the communication line within a preset statistical period. max AS represents the maximum number of complaints across all communication lines, where AS is the number of times a communication line has been blocked within a preset statistical period. max N represents the maximum number of times an account has been blocked across all communication lines, and N is the total number of calls initiated in violation of laws, regulations, industry standards, or operator directives within the time period during which outbound calls are prohibited. e The standard number of calls initiated proactively and compliantly within the compliant period is defined as follows: a is the preset complaint weight coefficient, b is the preset account suspension weight coefficient, and c is the preset weight coefficient for illegal calls, and a+b+c=1. S13. Obtain the preset compliance risk lower limit threshold CR low and compliance risk cap threshold CR top When compared with the compliance risk index CR, when CR <CR low If the communication line used to make outbound calls complies with laws, regulations, and industry standards, it is classified as a risk-free communication line. S14, when CR∈[CR] low CR top If the number of calls made is 0, it indicates that a small number of communication lines that make outbound calls do not comply with legal and regulatory requirements and industry standards. These lines are classified as low-risk communication lines, and the prediction index for account blocking of low-risk communication lines is analyzed and calculated. S15, When CR>CR top If this occurs, it indicates that a large number of communication lines used for making outbound calls do not comply with laws, regulations, and industry standards, and are therefore classified as high-risk communication lines. Intelligent outbound calls will then be suspended through these high-risk communication lines.
5. The optimization method based on an intelligent outbound calling system according to claim 1, characterized in that, The calculation process for the number blocking prediction index of low-risk communication lines is as follows: S21. Obtain the number of calls made by low-risk communication lines in the current month and the number of accounts blocked in the historical statistical period, and analyze and calculate them in conjunction with the compliance risk index of low-risk communication lines. S22. Calculate the blocking prediction index (FCT) for low-risk communication lines using the following formula: Where CR is the compliance risk index of the communication line, and n is the number of calls made by the communication line in the current month. max The maximum number of calls allowed per month for a pre-defined communication line, where m is the number of historical statistical periods for the communication line, and P is the maximum number of calls allowed per month. i Let P be the blocking rate of the communication line in the i-th historical statistical period. max P represents the maximum number of blocked accounts for the communication line across all historical statistical periods. min The minimum blocking rate for a communication line across all historical statistical periods is used to reflect the likelihood of a low-risk communication line being blocked. The higher the value of the blocking prediction index, the higher the likelihood of a low-risk communication line being blocked.
6. The optimization method based on an intelligent outbound calling system according to claim 1, characterized in that, The calculation process for the frequency adjustment index of communication lines is as follows: S31. Obtain the number of ongoing calls on the communication line and the usage frequency data of the communication line, and analyze and calculate them in combination with the number blocking prediction index of low-risk communication lines. S32. Calculate the frequency adjustment index k of the communication line according to the following formula: Where FCT is the prediction index for account suspension of low-risk communication lines, and call is the number of ongoing calls on the communication line. max The maximum number of calls that can be carried on a communication line is α, which is a preset frequency adjustment conversion coefficient. The frequency adjustment index is used to adjust the frequency used by low-risk communication lines. S33. Calculate and analyze the adjusted usage frequency f of the low-risk communication line based on the following formula: Among them, f e The preset standard operating frequency for the communication line is denoted by k, where k is the frequency adjustment index for the communication line.
7. An optimization system based on an intelligent outbound calling system, applied to the optimization method based on an intelligent outbound calling system as described in any one of claims 1-6, characterized in that, It includes a data acquisition unit, a risk analysis unit, an account blocking analysis unit, a frequency modulation analysis unit, and a frequency modulation control unit; The data acquisition unit is used to collect risk data, prediction data and frequency modulation data generated during the process of making outbound calls through the intelligent outbound call database, and to preprocess the collected data. Then, the preprocessed risk data is sent to the risk analysis unit, the prediction data is sent to the account blocking analysis unit, and the frequency modulation data is sent to the frequency modulation analysis unit. The risk analysis unit is used to receive risk data and perform analysis and calculation to obtain the compliance risk index of the communication line, and classify the communication line into high-risk communication line, low-risk communication line and risk-free communication line. The account blocking analysis unit is used to receive prediction data and combine it with the compliance risk index of low-risk communication lines to perform analysis and calculation, and to obtain the account blocking prediction index of low-risk communication lines. The account blocking prediction index is used to reflect the possibility of low-risk communication lines being blocked. The frequency modulation analysis unit is used to receive frequency modulation data and analyze and calculate it in conjunction with the number blocking prediction index of low-risk communication lines to obtain the frequency adjustment index for the use of communication lines. The frequency modulation control unit is used to dynamically adjust the operating frequency of low-risk communication lines according to the frequency adjustment index.