CN112217877A - Micro-service architecture based collection and case allocation method and system - Google Patents
Micro-service architecture based collection and case allocation method and system Download PDFInfo
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Abstract
The invention discloses a micro-service architecture based collection and case allocation method and a system, wherein the method comprises the following steps: s1 is used for pushing overdue or pre-overdue data to the server according to the credit and loan information and in combination with third-party data; s2 is used for obtaining overdue orders through the timed task service and distributing different collection urging modes according to different dimensions of the overdue orders; and S3 is used for optimizing the catalytic recovery processes of different catalytic recovery modes. Therefore, the full-flow management and control of collection urging, such as case rapid introduction, flexible case division, timely feedback of collection urging progress, data strategy engine, repayment safety management and the like, can be realized, the automatic and standardized operation of collection urging business is realized, the collection urging business success rate and risk early warning capacity are improved, the strict supervision of a credit agency on the collection urging process is met, the collection urging business safety and standardization are ensured, and the collection urging success rate and efficiency are improved while all departments are coordinated.
Description
Technical Field
The invention relates to the technical field of computer software, in particular to a collection urging and case allocation method and system based on a micro-service architecture.
Background
With the longitudinal development of credit business, the method controls the transaction risk of each link in the credit process, improves the asset quality of enterprises, and becomes an urgent target for internet financial enterprises. Meanwhile, post-loan collection is an important part in risk management, and how to improve the collection efficiency of credit business on the premise of compliance so as to accelerate the rate and speed of money return of credit funds is also very important. The prior art can not meet the strict supervision of credit agencies on the collection urging process, has low safety and standard collection urging service, low coordination capacity of all departments, low success rate and efficiency of collection urging case division, and does not have a collection urging case division method based on a micro-service architecture.
Disclosure of Invention
The invention aims to provide a method and a system for urging collection and case division based on a micro-service architecture.
The invention provides a micro-service architecture based urging collection and case allocation method, which comprises the following steps:
s1 step for pushing overdue or pre-overdue data to service end according to credit and loan information and combining third party data
S2 is used for obtaining overdue orders through the timed task service and distributing different collection urging modes according to different dimensions of the overdue orders;
and S3 is used for optimizing the catalytic recovery processes of different catalytic recovery modes.
The collection prompting mode comprises automatic short message sending, algorithm distribution collection prompting task, IVR (Interactive Voice Response) outbound and AI (Artificial Intelligence) intelligent outbound. The collection urging mode also comprises a step of combining AI (Artificial Intelligence) Intelligence with manual work, and is used for automatically initiating repayment or payment reminding for the customer through an automatic short message or AI (Artificial Intelligence) intelligent outgoing call service before overdue; after overdue, the call center is connected with an Interactive Voice Response (IVR) call center in a manual reception prompting mode, and the whole flow of the reception prompting dialing behavior is monitored. The collection urging mode also comprises a multi-channel integrated collection urging step, which is used for integrating a short message platform, an outbound center and an AI (Artificial Intelligence) intelligent outbound, and intelligently sending short messages, one-key group sending, one-key outbound and AI (Artificial Intelligence) intelligent dialing. The step of optimizing the catalyst recovery process of different catalyst recovery modes by the aid of the S3 includes: s31 is used for the step of real-time voice quality inspection and regulation of the collection process; s32 is used for counting the multi-dimensional data to generate a statistical result; s33 is used for carrying out security reinforcement on the system data. The step of S31 for conforming the catalyst process through real-time voice quality inspection includes: s311, intelligent voice recognition, namely performing intelligent voice recognition on the record of the call-up, and displaying the content of the voice-to-character at the front end; s312, urging to collect voice quality inspection, wherein the voice quality inspection is used for customizing keywords such as required terms and illegal terms and scoring the call according to quality inspection rules; and S313, risk early warning, wherein the risk early warning is used for presetting an early warning scheme by a system and automatically executing early warning operation.
The invention also provides a system for urging collection and case division based on the microservice architecture, which comprises: the module is used for pushing overdue or pre-overdue data to the server according to the credit granting and loan information and by combining third-party data; the module is used for acquiring overdue orders through the timed task service and distributing different collection urging modes according to different dimensions of the overdue orders; and the module is used for optimizing the collection accelerating processes of different collection accelerating modes.
The collection urging mode comprises an automatic short message sending submodule, an algorithm distribution collection urging task submodule, an Interactive Voice Response (IVR) outbound submodule and an Artificial Intelligence (AI) intelligent outbound submodule. The collection urging mode also comprises an AI (Artificial Intelligence) intelligent combined Artificial submodule which is used for automatically initiating repayment or payment reminding for the customer through an automatic short message or an AI (Artificial Intelligence) intelligent outgoing call service before overdue; after overdue, the call center is connected with an Interactive Voice Response (IVR) call center in a manual reception prompting mode, and the whole flow of the reception prompting dialing behavior is monitored. The collection urging mode also comprises a multi-channel integrated collection urging sub-module which is used for integrating a short message platform, an outbound call center, an AI (Artificial Intelligence) intelligent outbound call, intelligent short message sending, one-key group sending, one-key outbound call and AI (Artificial Intelligence) intelligent dialing. The module for optimizing the collection process of different collection modes comprises the following modules: a submodule for coordinating the collection process through real-time voice quality inspection; a submodule for counting the multi-dimensional data to generate a statistical result; and the submodule is used for carrying out security reinforcement on the system data. The sub-modules for compliance with the catalyst process via real-time voice quality inspection include: the intelligent voice recognition unit is used for carrying out intelligent voice recognition on the record of the call-up, and the front end displays the content of the converted voice into the text; the voice quality inspection prompting unit is used for customizing keywords such as required terms, illegal terms and the like and scoring the call according to quality inspection rules; and the risk early warning unit is used for presetting an early warning scheme by the system and automatically executing early warning operation.
The invention provides a collection and case distribution method and system based on a micro-service architecture, which can realize the full-flow management and control of collection such as quick case introduction, flexible case distribution, timely feedback of collection progress, data policy engine, repayment safety management and the like, realize the automatic and standardized operation of collection service, and improve the success rate of collection service and the risk early warning capability; the collection and case distribution system has the characteristics of good stability, expandability, data safety and the like, meets the strict supervision of credit agencies on the collection process, guarantees the safety and the standard of collection service and the coordination of all departments, and simultaneously improves the success rate and the efficiency of collection.
Drawings
Fig. 1 and 2 are schematic diagrams illustrating a procedure of a micro-service architecture-based catalytic proposal allocation method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating the step S3 of optimizing the catalyst recovery process according to different catalyst recovery modes according to an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating the step of S31 for performing the real-time voice quality inspection-based verification process according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
As shown in fig. 1 and 2, the present embodiment provides a collection and case allocation method based on a micro-service architecture, which includes the following steps:
s1 step for pushing overdue or pre-overdue data to service end according to credit and loan information and combining third party data
S2 is used for obtaining overdue orders through the timed task service and distributing different collection urging modes according to different dimensions of the overdue orders;
and S3 is used for optimizing the catalytic recovery processes of different catalytic recovery modes.
Those skilled in the art can understand that the VBS pushes overdue or pre-overdue data of the client to the post-loan collection system according to the credit and loan information of the client in each product under the company flag and in combination with a third-party data source. The system distributes correct receiving-urging mode for the order and provides a receiving-urging report form according to different dimensions of the overdue order, such as overdue stage, product type and the like.
The collection urging case distribution method based on the micro-service architecture is based on the micro-service architecture with leading industry, can realize full-flow management and control of collection urging, such as case rapid import, flexible case distribution, timely feedback of collection urging progress, a data policy engine, repayment safety management and the like, realizes automatic and standardized operation of collection urging service, and improves the success rate of collection urging service and risk early warning capacity; the collection urging case division method has the characteristics of good stability, expandability, data safety and the like, meets the strict supervision of credit agencies on collection urging processes, guarantees the safety and the standard of collection urging services, and improves the success rate and the efficiency of collection urging while all departments coordinate.
Further, the collection prompting mode includes automatic short message sending, algorithm distribution collection prompting task, Interactive Voice Response (IVR) outbound and Artificial Intelligence (AI) intelligent outbound.
Further, the collection urging mode also comprises a step of combining AI (Artificial Intelligence) Intelligence with manual work, and is used for automatically initiating repayment or payment reminding for the customer through an automatic short message or AI (Artificial Intelligence) intelligent outbound call service before overdue; after overdue, the call center is connected with an Interactive Voice Response (IVR) call center in a manual reception prompting mode, and the whole flow of the reception prompting dialing behavior is monitored.
As can be understood by those skilled in the art, the repayment reminding method can automatically initiate the repayment reminding for the client before overdue, and can remind the client of repayment or payment in time; the whole flow of the call prompting behavior is monitored, the whole flow management of the call prompting behavior is realized, and the call prompting efficiency is improved.
Further, the collection urging mode further comprises a multi-channel integrated collection urging step, which is used for integrating a short message platform, an outbound center and an AI (Artificial Intelligence) intelligent outbound, intelligently sending short messages, one-key group sending, one-key outbound, AI (Artificial Intelligence) intelligent dialing, highly integrating the short message platform, the outbound center and the AI (Artificial Intelligence) intelligent outbound, and having stable lines, so that the collection urging success rate is high.
As shown in fig. 3, the step S3 of optimizing the catalyst progress in different catalyst modes includes:
s31 is used for the step of real-time voice quality inspection and regulation of the collection process;
s32 is used for counting the multi-dimensional data to generate a statistical result;
s33 is used for carrying out security reinforcement on the system data.
Those skilled in the art can understand that the multidimensional data comprises all outbound dialing records, short message sending records, customer interaction information and customer feedback conditions, and is used for showing all outbound dialing records, short message sending records, customer interaction information and customer feedback conditions and providing a high-quality data base for big data analysis; scientific decision-making provides more comprehensive, rich and flexible data analysis dimension expansion, and provides data support for decision-making and analysis of a collection management layer; based on the latest system architecture, the data of the system is reinforced in a targeted manner, and a system layer, a data layer and an application layer are reinforced by adopting a safe OS (operating system), so that the safety of user information and collection urging data is ensured, and the collection urging progress is ensured.
As shown in fig. 4, the step S31 of normalizing the collection process through real-time voice quality inspection includes:
s311, intelligent voice recognition, namely performing intelligent voice recognition on the record of the call-up, and displaying the content of the voice-to-character at the front end;
s312, urging to collect voice quality inspection, wherein the voice quality inspection is used for customizing keywords such as required terms and illegal terms and scoring the call according to quality inspection rules;
and S313, risk early warning, wherein the risk early warning is used for presetting an early warning scheme by a system and automatically executing early warning operation.
The technical personnel in the field can understand that the embodiment provides a timely and comprehensive early warning scheme, finds potential risks in time and avoids the potential risks in real time, ensures the compliance of the collection urging process and ensures the collection urging progress.
Example two
The present embodiment provides a system for collecting and allocating cases based on a microservice architecture, which includes:
the module is used for pushing overdue or pre-overdue data to the server according to the credit granting and loan information and by combining third-party data;
the module is used for acquiring overdue orders through the timed task service and distributing different collection urging modes according to different dimensions of the overdue orders;
and the module is used for optimizing the collection accelerating processes of different collection accelerating modes.
Those skilled in the art can understand that the VBS pushes overdue or pre-overdue data of the client to the post-loan collection system according to the credit and loan information of the client in each product under the company flag and in combination with a third-party data source. The system distributes correct receiving-urging mode for the order and provides a receiving-urging report form according to different dimensions of the overdue order, such as overdue stage, product type and the like.
The collection urging case division method based on the micro-service architecture is based on the micro-service architecture with leading industry, can realize full-flow management and control of collection urging, such as case rapid import, flexible case division, timely feedback of collection urging progress, a data policy engine, repayment security management and the like, realizes automatic and standardized operation of collection urging service, and improves the success rate of collection urging service and risk early warning capacity; the collection and case distribution system has the characteristics of good stability, expandability, data safety and the like, meets the strict supervision of credit agencies on the collection process, guarantees the safety and the standard of collection service and the coordination of all departments, and simultaneously improves the success rate and the efficiency of collection.
Further, the collection prompting mode comprises an automatic short message sending submodule, an algorithm distribution collection prompting task submodule, an Interactive Voice Response (IVR) outbound submodule and an Artificial Intelligence (AI) intelligent outbound submodule.
Further, the collection urging mode also comprises an AI (Artificial Intelligence) intelligent combined Artificial submodule, which is used for automatically initiating repayment or payment reminding for the customer through an automatic short message or an AI (Artificial Intelligence) intelligent outbound service before overdue; after overdue, the call center is connected with an Interactive Voice Response (IVR) call center in a manual reception prompting mode, and the whole flow of the reception prompting dialing behavior is monitored.
As can be understood by those skilled in the art, the repayment reminding method can automatically initiate the repayment reminding for the client before overdue, and can remind the client of repayment or payment in time; the whole flow of the call prompting behavior is monitored, the whole flow management of the call prompting behavior is realized, and the call prompting efficiency is improved.
Furthermore, the collection urging mode also comprises a multi-channel integrated collection urging sub-module, which is used for integrating a short message platform, an outbound center and an AI (Artificial Intelligence) intelligent outbound, intelligently sending short messages, one-key group sending, one-key outbound, AI (Artificial Intelligence) intelligent dialing, highly integrating the short message platform, the outbound center and the AI (Artificial Intelligence) intelligent outbound, and having stable line, so that the collection urging success rate is high.
Further, the module for optimizing the collection process of different collection modes comprises:
a submodule for coordinating the collection process through real-time voice quality inspection;
a submodule for counting the multi-dimensional data to generate a statistical result;
and the submodule is used for carrying out security reinforcement on the system data.
Those skilled in the art can understand that the multidimensional data comprises all outbound dialing records, short message sending records, customer interaction information and customer feedback conditions, and is used for showing all outbound dialing records, short message sending records, customer interaction information and customer feedback conditions and providing a high-quality data base for big data analysis; scientific decision-making provides more comprehensive, rich and flexible data analysis dimension expansion, and provides data support for decision-making and analysis of a collection management layer; based on the latest system architecture, the data of the system is reinforced in a targeted manner, and a system layer, a data layer and an application layer are reinforced by adopting a safe OS (operating system), so that the safety of user information and collection urging data is ensured, and the collection urging progress is ensured.
Further, the sub-module for compliance with the collection process through real-time voice quality inspection comprises:
the intelligent voice recognition unit is used for carrying out intelligent voice recognition on the record of the call-up, and the front end displays the content of the converted voice into the text;
the voice quality inspection prompting unit is used for customizing keywords such as required terms, illegal terms and the like and scoring the call according to quality inspection rules;
and the risk early warning unit is used for presetting an early warning scheme by the system and automatically executing early warning operation.
The technical personnel in the field can understand that the embodiment provides a timely and comprehensive early warning scheme, finds potential risks in time and avoids the potential risks in real time, ensures the compliance of the collection urging process and ensures the collection urging progress.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (12)
1. A micro-service architecture based collection and case allocation method is characterized by comprising the following steps:
s1 step for pushing overdue or pre-overdue data to service end according to credit and loan information and combining third party data
S2 is used for obtaining overdue orders through the timed task service and distributing different collection urging modes according to different dimensions of the overdue orders;
and S3 is used for optimizing the catalytic recovery processes of different catalytic recovery modes.
2. The micro-service architecture based collection and case distribution method of claim 1, wherein the collection and case distribution method comprises automatic short message sending, algorithm distribution collection and case distribution, IVR outbound and AI intelligent outbound.
3. The micro-service architecture based collection and case distribution method of claim 2, wherein the collection and case distribution method further comprises a step of combining AI intelligence with manual work, and is used for automatically initiating a payment or payment reminder to the customer through an automatic short message or an AI intelligence outbound service before overdue; after overdue, the call center is in butt joint with the IVR call center in a manual call-in mode, and the whole flow of call-in and call-out behaviors is monitored.
4. The micro-service architecture based collection and distribution method of claim 2, wherein the collection and distribution method further comprises a multi-channel collection and collection contact step for integrating a short message platform, a call-out center, an AI intelligent call-out, an intelligent short message sending, a one-touch mass texting, a one-touch call-out, and an AI intelligent dialing.
5. The microservice-architecture-based catalyst solution allocation method according to any one of claims 1 to 4, wherein the step of S3 for optimizing catalyst processes of different catalyst modes comprises:
s31 is used for the step of real-time voice quality inspection and regulation of the collection process;
s32 is used for counting the multi-dimensional data to generate a statistical result;
s33 is used for carrying out security reinforcement on the system data.
6. The micro-service architecture based catalytic delivery scheme according to claim 5, wherein the step of S31 for conforming the catalytic delivery process through real-time voice quality inspection comprises:
s311, intelligent voice recognition, namely performing intelligent voice recognition on the record of the call-up, and displaying the content of the voice-to-character at the front end;
s312, urging to collect voice quality inspection, wherein the voice quality inspection is used for customizing keywords such as required terms and illegal terms and scoring the call according to quality inspection rules;
and S313, risk early warning, wherein the risk early warning is used for presetting an early warning scheme by a system and automatically executing early warning operation.
7. A collection and case distribution system based on micro-service architecture is characterized by comprising:
the module is used for pushing overdue or pre-overdue data to the server according to the credit granting and loan information and by combining third-party data;
the module is used for acquiring overdue orders through the timed task service and distributing different collection urging modes according to different dimensions of the overdue orders;
and the module is used for optimizing the collection accelerating processes of different collection accelerating modes.
8. The micro-service architecture based collection and case distribution system of claim 7, wherein the collection and case distribution method comprises an automatic short message sending sub-module, an algorithm distribution collection and case distribution sub-module, an IVR outbound sub-module and an AI intelligent outbound sub-module.
9. The micro-service architecture based collection and distribution system of claim 8, wherein the collection and distribution system further comprises an AI intelligence combined manual submodule for automatically initiating a payment or payment reminder to the customer through an automatic short message or an AI intelligence outbound service before overdue; after overdue, the call center is in butt joint with the IVR call center in a manual call-in mode, and the whole flow of call-in and call-out behaviors is monitored.
10. The micro-service architecture based collection and case distribution system of claim 8, wherein the collection and case distribution system further comprises a multi-channel collection and case distribution sub-module for integrating the short message platform, the outbound call center, the AI intelligent outbound call, the intelligent short message sending, the one-touch mass texting, the one-touch outbound call, and the AI intelligent dialing.
11. The microservice-based architecture catalyst staging system according to any one of claims 7 to 10, wherein the means for optimizing catalyst processes for different catalyst regimes comprises:
a submodule for coordinating the collection process through real-time voice quality inspection;
a submodule for counting the multi-dimensional data to generate a statistical result;
and the submodule is used for carrying out security reinforcement on the system data.
12. The microservice-based framework-based catalytic delivery system of claim 11, wherein the sub-module for compliance with the catalytic delivery process via real-time voice quality inspection comprises:
the intelligent voice recognition unit is used for carrying out intelligent voice recognition on the record of the call-up, and the front end displays the content of the converted voice into the text;
the voice quality inspection prompting unit is used for customizing keywords such as required terms, illegal terms and the like and scoring the call according to quality inspection rules;
and the risk early warning unit is used for presetting an early warning scheme by the system and automatically executing early warning operation.
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