CN110648239B - Monitoring index generation method and device, data monitoring system - Google Patents

Abstract

The application discloses a method and device for generating monitoring indexes and a data monitoring system. Wherein the method comprises the following steps: acquiring the type of a monitoring index to be generated, wherein the monitoring index is used for monitoring investment data of financial products; the method comprises the steps that a configuration unit required by generating a type of monitoring index is obtained from a plurality of configuration units, wherein the configuration unit is a minimum component unit of a numerator and a denominator of a calculation formula corresponding to the monitoring index; and generating a monitoring index to be generated according to the acquired configuration unit. The method and the device solve the technical problems that the existing financial product is long in investment monitoring index development period, serious in index redundancy and lack of expansibility.

Description

Monitoring index generation method and device, data monitoring system

Technical Field

The present application relates to the field of financial product investment monitoring, and more specifically, to a method and device for generating monitoring indicators, and a data monitoring system.

Background technique

The existing investment monitoring indicator development process for financial products includes the following steps: business personnel submitting requirements, technical personnel reviewing requirements, technical personnel developing, technical personnel testing, business personnel testing, and the system being officially put into production and launched. It takes a long time and is slow to respond to business needs. At the same time, each development requires a lot of energy from business personnel, technical developers, technical testers, and related code reviewers, and the cost is high, especially for the development of a series of new indicators of the same type, there is a lot of duplicate code and low efficiency.

Currently, no effective solution has been proposed to address the problems of long development cycle, serious indicator redundancy and lack of scalability of investment monitoring indicators of existing financial products.

Summary of the invention

The embodiments of the present application provide a monitoring indicator generation method and device, and a data monitoring system, so as to at least solve the technical problems of long development cycle of investment monitoring indicators of existing financial products, serious indicator redundancy problem, and lack of scalability.

According to one aspect of an embodiment of the present application, a method for generating a monitoring indicator is provided, comprising: obtaining the type of the monitoring indicator to be generated, the monitoring indicator being used to monitor the investment data of a financial product; obtaining a configuration unit required for generating the type of monitoring indicator from a plurality of configuration units, the configuration unit being the smallest component unit of the numerator and denominator of a calculation formula corresponding to the monitoring indicator; and generating the monitoring indicator to be generated based on the obtained configuration unit.

Optionally, financial products include: bond products, stock products, fund products, non-standard asset products, derivative products and pension products.

Optionally, before obtaining the configuration units required for generating the monitoring indicators of the type from multiple configuration units, the above method also includes: determining multiple configuration units in the following manner: determining multiple configuration units based on common attributes and individual attributes, wherein the common attributes include: the name of the configuration unit, the type of the configuration unit, and the value of the configuration unit; the individual attributes include at least one of the following: basic information, detailed subject information, credit rating information, and flow transaction information.

Optionally, after generating the monitoring indicator to be generated according to the acquired configuration unit, the method further includes: acquiring information corresponding to the personality attribute at a preset time interval.

Optionally, before generating the monitoring indicator to be generated according to the acquired configuration unit, the method further includes:

The data acquisition logic of the configuration unit is obtained, and the data acquisition logic is used to characterize the data acquisition rule of the configuration unit; whether the data acquisition logic is consistent with the preset data acquisition logic is determined; if it is determined that the data acquisition logic is consistent with the preset data acquisition logic, the configuration unit is determined to be the target configuration unit.

Optionally, after generating the monitoring indicator to be generated according to the acquired configuration unit, the method further includes:

The investment data of the financial product corresponding to the monitoring indicator to be generated is calculated based on the monitoring indicator to be generated to obtain the monitoring indicator value of the financial product; the monitoring indicator value is compared with the preset threshold, and whether the investment data of the financial product meets the standard is determined based on the comparison result; an alarm is issued for the investment data that does not meet the standard, and a prompt is given to process the investment data that does not meet the standard.

Optionally, after prompting to process the investment data that does not meet the standards, the method further includes: detecting whether the processing of the investment data that does not meet the standards is completed; if the processing is not completed, prompting to continue processing the investment data that does not meet the standards.

According to another aspect of an embodiment of the present application, a data monitoring system is also provided, including: a monitoring module for executing the method for generating monitoring indicators of any one of claims 1 to 7; a database for acquiring and storing information corresponding to the individual attributes of multiple configuration units; and a risk management module for monitoring the method for generating monitoring indicators of any one of claims 1 to 7.

According to another aspect of an embodiment of the present application, a device for generating monitoring indicators is also provided, including: a first acquisition module, used to obtain the type of monitoring indicators to be generated, the monitoring indicators are used to monitor the investment data of financial products; a second acquisition module, used to obtain the configuration units required for generating the type of monitoring indicators from multiple configuration units, the configuration units being the smallest component units of the numerator and denominator of the configuration formula corresponding to the monitoring indicator; and a generation module, used to generate the monitoring indicators to be generated based on the acquired configuration units.

Optionally, the above-mentioned device also includes: a determination module, which is used to determine multiple configuration units in the following manner: determine multiple configuration units based on common attributes and individual attributes, wherein the common attributes include: the name of the configuration unit, the type of the configuration unit, and the value of the configuration unit; the individual attributes include at least one of the following: basic information, detailed subject information, credit rating information, and flow transaction information.

According to another aspect of the embodiments of the present application, a storage medium is further provided, the storage medium including a stored program, wherein when the program is run, the device where the storage medium is located is controlled to execute the above monitoring indicator generation method.

According to another aspect of the embodiments of the present application, a processor is further provided, and the processor is used to run a program, wherein the above monitoring indicator generation method is executed when the program is running.

In an embodiment of the present application, the type of monitoring indicator to be generated is obtained, and the monitoring indicator is used to monitor the investment data of a financial product; the configuration unit required for the generation type of monitoring indicator is obtained from multiple configuration units, and the configuration unit is the smallest component unit of the numerator and denominator of the calculation formula corresponding to the monitoring indicator; the method of generating the monitoring indicator to be generated is based on the obtained configuration unit, and by adopting a cluster analysis method, the numerator and denominator of the investment monitoring indicator of the financial product are decomposed to the lowest level and the smallest indivisible granular unit (meta-factor), and then the meta-factor is built in a building block manner to generate a new monitoring indicator for the financial product, so that the purpose of being able to operate on the front page of the system and being able to generate the monitoring indicators required for the business in real time is achieved, thereby realizing the technical effect of simplifying the setting process of the investment monitoring indicator of the financial product, effectively improving the business efficiency, and enhancing the user experience, thereby solving the technical problems of the long development cycle of the investment monitoring indicators of the existing financial products, the serious indicator redundancy problem, and the lack of scalability.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

FIG1 is a flow chart of a method for generating a monitoring indicator according to an embodiment of the present application;

FIG2 is a structural diagram of a data monitoring system according to an embodiment of the present application;

FIG3 is a structural diagram of a device for generating monitoring indicators according to an embodiment of the present application.

Detailed ways

In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

According to an embodiment of the present application, an embodiment of a method for generating a monitoring indicator is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

FIG. 1 is a flow chart of a method for generating a monitoring indicator according to an embodiment of the present application. As shown in FIG. 1 , the method includes the following steps:

Step S102, obtaining the type of monitoring indicator to be generated, where the monitoring indicator is used to monitor the investment data of the financial product.

The above-mentioned monitoring indicators to be generated refer to investment monitoring indicators of financial products that need to be newly set.

Step S104, obtaining a configuration unit required for generating a monitoring indicator of a type from a plurality of configuration units, where a configuration unit is a minimum component unit of a numerator and a denominator of a calculation formula corresponding to the monitoring indicator.

The above-mentioned configuration unit refers to decomposing the numerator or denominator of the investment supervision index of the financial product to the lowest level and the smallest indivisible execution unit, which is referred to as a "meta-factor" in the embodiment of the present application.

The "meta-factor" function in the embodiment of the present application adopts the idea of cluster analysis. By systematically studying the attributes of the financial product investment monitoring indicators in the market, the elements of the financial product investment indicators are first split into the smallest indivisible execution units. These smallest units are the basis for the numerator or denominator of the investment monitoring indicators - "meta-factors".

Step S106: Generate a monitoring indicator to be generated according to the acquired configuration unit.

According to the characteristics of meta-factors and combined with the product types involved in the monitoring indicators, the meta-factors are reclassified, and six meta-factor templates for stocks, bonds, funds, pensions, non-standard products, and derivatives are constructed in a parametric way, thereby supporting the rapid generation of investment monitoring indicators required by business personnel, fully simplifying the setting process of investment monitoring indicators, and effectively improving business efficiency.

Specifically, firstly, the existing financial products on the market are standardized, granulated and templated according to their attributes and characteristics. On the one hand, the existing financial products on the market can be classified, and when new financial products appear, the system can respond quickly and classify them into existing categories or create a new category; on the other hand, the existing financial products are granulated, and then the upper-level indicators are built based on these granulated elements. This "bottom-up" indicator creation method has greater freedom, and the indicator creation process does not require the intervention of developers. It is less time-consuming and more efficient than the previous process of "proposing requirements-technician development-production and launch". The building block-like construction of meta-factors provides endless possibilities for the setting of investment monitoring indicators for financial products.

According to an optional embodiment of the present application, when executing step S106, the required meta-factor attributes are checked through the system foreground, and with the assistance of corresponding logical judgment, the monitoring indicators required for the business can be generated in real time, which greatly improves the business efficiency.

Investment monitoring indicators are formed by the association and combination of two or more factors. The indicator table only stores the factor codes to reduce data redundancy. Compared with previous indicator calculations, the existing indicator results can display the calculation results of each factor involved in the indicator according to the calculation formula of the current indicator, providing a clear calculation process for business personnel to check problems, reducing system operation and maintenance costs, and displaying the detailed results of monitoring indicators in a more timely and accurate manner.

Through the above steps, by adopting the cluster analysis method, the numerator and denominator of the investment monitoring indicators of financial products are decomposed into the lowest level indivisible smallest granular unit (meta-factor), and then the meta-factor is built in a building block manner to generate new monitoring indicators for financial products. The purpose of being able to operate on the front page of the system and to generate the monitoring indicators required for the business in real time is achieved, thereby achieving the technical effect of simplifying the setting process of investment monitoring indicators for financial products, effectively improving business efficiency, and enhancing user experience.

In some optional embodiments of the present application, the financial products in step S102 cover six major investment types: bond products, stock products, fund products, non-standard asset products, derivative products and pension products.

According to an optional embodiment of the present application, before executing step S104, it is necessary to determine multiple configuration units in the following manner: determine multiple configuration units based on common attributes and individual attributes, wherein the common attributes include: the name of the configuration unit, the type of the configuration unit, and the value of the configuration unit; the individual attributes include at least one of the following: basic information, detailed subject information, credit rating information, and flow transaction information.

The implementation principle of meta-factors is achieved through initialization templates and parameters. The templates are divided into: bonds, stocks, funds, non-standard assets, derivatives, and pensions. When configuring indicators, configure them in the corresponding templates and quickly configure new investment supervision indicators by selecting the corresponding elements.

In terms of system design, by adopting the logic of the lowest-level factor data, each factor is marked with a numerator or denominator, so that various factors can be flexibly combined, and each indicator is associated and configured through the associated factor code to reduce redundant data. It can also support business personnel to configure the required monitoring meta-factors in real time through template configuration, which greatly reduces the code development work of new factors and improves the overall development efficiency of the system.

The above templates all have some common attributes, including: factor name, factor type, factor value field; except for the common attributes, the rest are individual attributes, which are divided into basic information (from Caihui Information data), detailed accounts (the basis for accounting) and daily transaction information according to the data source.

Taking the template of the bond meta-factor as an example, its basic information includes bond type, financing subject, whether it is a private bond, whether it is a municipal bond, trading market, lock-up period, monitoring reason, issuance scale, remaining term, etc. The detailed account part includes the trading market, issuance method, and whether it includes interest receivable. The transaction flow information includes the trading market, on-site securities flow, offline new bonds, over-the-counter bonds and other daily transaction flow information.

The basic information of the template of stock-related meta-factors includes stock sector, special treatment category (S, ST, etc.), Hong Kong stocks, monitoring reasons, index, non-public index, stock classification, A-share capital, total capital, remaining lock-up period, total market value, CSRC industry category, etc. The detailed account part includes the issuance method and trading market. The transaction flow information includes the on-site securities trading flow and the offline new shares.

The basic information of the template of fund-type meta-factors includes fund type, CSRC classification, operation mode, fund attributes, etc. Transaction information includes on-site securities transaction and open-end fund transactions.

The basic information of the template of the derivatives meta-factor includes futures product, whether it is a single futures product, current date, delivery date, etc. The transaction information includes accounting items, transaction attributes, etc.

The basic information of the template of non-standard asset meta-factors is mainly derived from accounting data, which are divided into trust, real estate, financial management, insurance, infrastructure debt, etc. according to the attributes of the subject.

The basic information of the pension factor template mainly involves the attributes related to asset classification.

According to an optional embodiment of the present application, after executing step S106, it is also necessary to obtain information corresponding to the personality attribute at a preset time interval.

According to an optional embodiment of the present application, the financial product investment monitoring system has a complete database system, which automatically reads the external information data provided by Caihui through task scheduling every morning, that is, automatically obtains the individual attribute information of the configuration unit through the database. By establishing a complete and scalable underlying database structure, it can ensure timely reading and calling of basic data, and add the data required in the market to the system basic data in real time, which is the basis for generating financial product investment monitoring indicators.

In some optional embodiments of the embodiments of the present application, before step S106 is executed, the number acquisition logic of the configuration unit is obtained, and the number acquisition logic is used to characterize the number acquisition rule of the configuration unit; it is determined whether the number acquisition logic is consistent with the preset number acquisition logic; if it is determined that the number acquisition logic is consistent with the preset number acquisition logic, the configuration unit is determined to be the target configuration unit.

According to an optional embodiment of the present application, the above-mentioned data acquisition logic refers to the data acquisition rules of the configuration unit, for example, obtaining the market value of a bond in the asset valuation table, determining the variety information of a bond through external market data, etc.

When adding parameter factors and dynamic factors, the system provides a factor trial calculation function, which can be used to verify the dynamic factors before they are added and saved, and can also be used to verify the factors that already exist in the system. The results are consistent with the actual indicator calculation.

By obtaining the configured factors and parsing the corresponding data acquisition logic, the system can perform data acquisition verification on the logical correctness of the newly added factors or configured factors in real time, display the calculation results in real time, and verify them through the data acquisition logic description of each factor displayed in the system to ensure the accuracy of the factors and reduce the subsequent maintenance costs of the system.

In an optional embodiment of the present application, after step S106 is executed, the investment data of the financial product corresponding to the monitoring indicator to be generated is calculated based on the monitoring indicator to be generated to obtain the monitoring indicator value of the financial product; the monitoring indicator value is compared with the preset threshold, and whether the investment data of the financial product meets the standard is determined based on the comparison result; an alarm is issued for the investment data that does not meet the standard, and a prompt is given to process the investment data that does not meet the standard.

After the monitoring indicators are built, the system will automatically calculate the monitoring indicator values of each financial product asset. The system automatically calculates the monitoring indicators according to the pre-configured monitoring indicators through task scheduling every morning, and automatically runs batches according to the settlement mode of the assets. At the same time, the system automatically generates tasks for each asset every day, and records the current asset reading status, valuation table status, indicator calculation status and time and other information. For daily business, the automatic calculation of monitoring indicators has fully met business needs, but sometimes it is necessary to manually calculate one or more indicators separately.

The system automatically calculates the monitoring indicators of each asset, and issues warnings and violation judgments based on the set thresholds and directions. The system automatically prompts business personnel to conduct follow-up processing for warning and violation indicators.

According to an optional embodiment of the present application, after prompting to process the investment data that does not meet the standards, it is also necessary to detect whether the processing of the investment data that does not meet the standards is completed; if the processing is not completed, prompt to continue processing the investment data that does not meet the standards. For indicators that are automatically judged as violations or warnings, the monitoring personnel should process them, and the system will automatically judge the processing status of the monitoring personnel and remind them of the unprocessed parts.

FIG. 2 is a structural diagram of a data monitoring system according to an embodiment of the present application. As shown in FIG. 2 , the system includes:

The monitoring module 20 is used to execute the above monitoring indicator generation method.

The construction of the meta-factor template through the above-mentioned monitoring module 20 fundamentally solves the problems of long investment monitoring indicator setting cycle, slow response to business needs, and poor scalability that have troubled investment monitoring staff. By decomposing the numerator and denominator of the monitoring indicator to the lowest-level factor, namely the meta-factor, and then building the meta-factor in a building block-like manner, the investment monitoring business personnel can operate on the front page of the system without the need for lengthy technical development indicator processes. The indicators required for the business can be generated in real time, making the indicator construction fast and efficient. At the same time, it has good scalability, and can regularly incorporate new financial instruments and products on the market into the "meta-factor" system, reducing the redundant occupation of system investment supervision indicators, and having economies of scale.

The database 22 is used to obtain and store information corresponding to individual attributes of multiple configuration units.

A complete data structure is an important basis for the effective use of the investment monitoring system. The investment monitoring system in the embodiment of the present application establishes complete underlying market basic data, covers all granular market information, and can automatically read market information, effectively improving efficiency.

The risk management module 24 is used to monitor the generation method of the above monitoring indicators.

The risk management module 24 consists of two parts: an investment monitoring workbench and a management cockpit, which monitor the business process and the management process respectively.

The investment supervision workbench takes business flow as the main line, covering the execution of each business process step, including data reading, real-time status of valuation tables, processing of investment supervision indicators, processing of violation results, export and sending of violation data, etc., so that business personnel can perform each step according to system prompts, and business supervisors can monitor business progress in real time, discover potential business risks, and ensure business compliance.

The management cockpit focuses on management, uses the idea of behavioral management, and displays business operations from a full perspective through a visual interface. It supports "drill-down query" and managers can obtain real-time operation status of all employees, all assets, and all processes at any time to improve the efficiency and accuracy of custodial operation management. Through real-time monitoring of the investment supervision operation of the head office and branches, including summary of branch task completion, summary of branch indicator modification, summary of branch violation handling, etc., the head office management personnel can grasp the business operation completion status and business proficiency level of the head office and branch personnel in real time.

Incorporate risk management of the entire business process of investment supervision into the system, and monitor business processes and management processes separately by building an investment supervision workbench and a management cockpit, thereby achieving better full-process risk management of the investment supervision system and reducing business operation risks.

FIG3 is a structural diagram of a device for generating a monitoring indicator according to an embodiment of the present application. As shown in FIG3 , the device includes:

The first acquisition module 30 is used to acquire the type of the monitoring indicator to be generated, where the monitoring indicator is used to monitor the investment data of the financial product. The monitoring indicator to be generated refers to the investment monitoring indicator of the financial product that needs to be newly set.

The second acquisition module 32 is used to acquire the configuration unit required for the monitoring indicator of the generated type from the multiple configuration units, and the configuration unit is the smallest component unit of the numerator and denominator of the configuration formula corresponding to the monitoring indicator. The configuration unit refers to the numerator or denominator of the investment supervision indicator of the financial product decomposed to the lowest level of the smallest execution unit that cannot be further divided, which is called "meta-factor" in the embodiment of the present application.

The "meta-factor" function in the embodiment of the present application adopts the idea of cluster analysis. By systematically studying the attributes of the financial product investment monitoring indicators in the market, the elements of the financial product investment indicators are first split into the smallest indivisible execution units. These smallest units are the basis for the numerator or denominator of the investment monitoring indicator - the "meta-factor".

The generating module 34 is used to generate the monitoring indicator to be generated according to the acquired configuration unit.

According to the characteristics of meta-factors and combined with the product types involved in the monitoring indicators, the meta-factors are reclassified, and six meta-factor templates for stocks, bonds, funds, pensions, non-standard products, and derivatives are constructed in a parametric way, thereby supporting the rapid generation of investment monitoring indicators required by business personnel, fully simplifying the setting process of investment monitoring indicators, and effectively improving business efficiency.

Specifically, firstly, the existing financial products on the market are standardized, granulated and templated according to their attributes and characteristics. On the one hand, the existing financial products on the market can be classified, and when new financial products appear, the system can respond quickly and classify them into existing categories or create a new category; on the other hand, the existing financial products are granulated, and then the upper-level indicators are built based on these granulated elements. This "bottom-up" indicator creation method has greater freedom, and the indicator creation process does not require the intervention of developers. It is less time-consuming and more efficient than the previous process of "proposing requirements-technician development-production and launch". The building block-like construction of meta-factors provides endless possibilities for the setting of investment monitoring indicators for financial products.

By checking the required meta-factor attributes at the system front desk and making corresponding logical judgments, the monitoring indicators required for the business can be generated in real time, greatly improving business efficiency.

Investment monitoring indicators are formed by the association and combination of two or more factors. The indicator table only stores the factor codes to reduce data redundancy. Compared with previous indicator calculations, the existing indicator results can display the calculation results of each factor involved in the indicator according to the calculation formula of the current indicator, providing a clear calculation process for business personnel to check problems, reducing system operation and maintenance costs, and displaying the detailed results of monitoring indicators in a more timely and accurate manner.

In an optional embodiment of the present application, the above-mentioned device also includes: a determination module, which is used to determine multiple configuration units in the following manner: determine multiple configuration units based on common attributes and individual attributes, wherein the common attributes include: the name of the configuration unit, the type of the configuration unit, and the value of the configuration unit; the individual attributes include at least one of the following: basic information, detailed subject information, credit rating information, and flow transaction information.

The implementation principle of meta-factors is achieved through initialization templates and parameters. The templates are divided into: bonds, stocks, funds, non-standard assets, derivatives, and pensions. When configuring indicators, configure them in the corresponding templates and quickly configure new investment supervision indicators by selecting the corresponding elements.

In terms of system design, by adopting the logic of the lowest-level factor data, each factor is marked with a numerator or denominator, so that various factors can be flexibly combined, and each indicator is associated and configured through the associated factor code to reduce redundant data. It can also support business personnel to configure the required monitoring meta-factors in real time through template configuration, which greatly reduces the code development work of new factors and improves the overall development efficiency of the system.

The above templates all have some common attributes, including: factor name, factor type, factor value field; except for the common attributes, the rest are individual attributes, which are divided into basic information (from Caihui Information data), detailed accounts (the basis for accounting) and daily transaction information according to the data source.

It should be noted that the preferred implementation of the embodiment shown in FIG. 3 can refer to the relevant description of the embodiment shown in FIG. 1 , which will not be repeated here.

An embodiment of the present application further provides a storage medium, which includes a stored program, wherein when the program is run, the device where the storage medium is located is controlled to execute the above monitoring indicator generation method.

The storage medium is used to store programs that perform the following functions: obtaining the type of monitoring indicators to be generated, the monitoring indicators are used to monitor the investment data of financial products; obtaining the configuration units required for generating the type of monitoring indicators from multiple configuration units, the configuration units being the smallest components of the numerator and denominator of the calculation formula corresponding to the monitoring indicators; and generating the monitoring indicators to be generated based on the obtained configuration units.

The embodiment of the present application also provides a processor, which is used to run a program, wherein the above monitoring indicator generation method is executed when the program is running.

The processor is used to run a program that performs the following functions: obtaining the type of monitoring indicator to be generated, the monitoring indicator is used to monitor the investment data of financial products; obtaining the configuration unit required for generating the type of monitoring indicator from multiple configuration units, the configuration unit being the smallest component unit of the numerator and denominator of the calculation formula corresponding to the monitoring indicator; and generating the monitoring indicator to be generated based on the obtained configuration unit.

The serial numbers of the embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program code.

The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims (11)

1. A method for generating a monitoring indicator, characterized by comprising: Acquire the type of the monitoring indicator to be generated, where the monitoring indicator to be generated is an investment monitoring indicator of a financial product that needs to be newly set, and the investment monitoring indicator is used to monitor the investment data of the financial product; Acquire the configuration unit required for generating a monitoring indicator of the type from a plurality of configuration units, wherein the configuration unit is the smallest component unit of the numerator and denominator of the calculation formula corresponding to the monitoring indicator; Determine the configuration unit required to generate the monitoring indicator of the type to be generated from the system basic data according to the common attributes and the individual attributes, wherein the common attributes include: the name of the configuration unit, the type of the configuration unit, and the value of the configuration unit, and the individual attributes include at least one of the following: basic information, detailed account information, credit rating information, and transaction flow information; Verifying in real time the correctness of the data acquisition logic of the configuration unit required for determining the generation of the type of monitoring indicator to be generated, and determining the configuration unit that passes the verification as the target configuration unit; Classifying the configuration units according to the product type of the financial product to be newly set; constructing different configuration unit templates in a parameterized manner; The target configuration unit generates the monitoring indicator to be generated according to the configuration unit template; The investment data of the financial product corresponding to the monitoring indicator to be generated is calculated based on the monitoring indicator to be generated to obtain the monitoring indicator value of the financial product, the relationship between the monitoring indicator value and the preset threshold and the investment trend of the obtained investment data are analyzed, and the generated monitoring indicator and investment data are given early warning and violation verification. 2. The method according to claim 1 is characterized in that the financial products include: bond products, stock products, fund products, non-standard asset products, derivative products and pension products. 3. The method according to claim 1, characterized in that after the target configuration unit generates the monitoring indicator to be generated according to the configuration unit template, the method further comprises: The information corresponding to the personality attribute is obtained at a preset time interval. 4. The method according to claim 1, characterized in that before the target configuration unit generates the monitoring indicator to be generated according to the configuration unit template, the method further comprises: Acquire the data acquisition logic of the configuration unit, where the data acquisition logic is used to characterize the data acquisition rule of the configuration unit; Determine whether the data acquisition logic is consistent with the preset data acquisition logic; If it is determined that the data acquisition logic is consistent with the preset data acquisition logic, the configuration unit is determined to be the target configuration unit. 5. The method according to claim 1, characterized in that the method further comprises: Comparing the monitoring indicator value with the preset threshold value, and determining whether the investment data of the financial product meets the standard based on the comparison result; An alarm is issued for the investment data that does not meet the standards, and a prompt is given to process the investment data that does not meet the standards. 6. The method according to claim 5, characterized in that after prompting to process the investment data that does not meet the standards, the method further comprises: Detecting whether the processing of the investment data that does not meet the standards is completed; If the processing is not completed, it is prompted to continue processing the investment data that does not meet the standards. 7. A data monitoring system, comprising: A monitoring module, used to execute the method for generating monitoring indicators according to any one of claims 1 to 6; A database, used to obtain and store information corresponding to individual attributes of multiple configuration units; A risk management module, used to monitor the method for generating the monitoring indicator described in any one of claims 1 to 6. 8. A device for generating monitoring indicators, characterized in that it includes: A first acquisition module is used to acquire the type of the monitoring indicator to be generated, wherein the monitoring indicator to be generated is an investment monitoring indicator of a financial product that needs to be newly set, and the investment monitoring indicator is used to monitor the investment data of the financial product; and to acquire the configuration unit required for generating the type of monitoring indicator from a plurality of configuration units, wherein the configuration unit is the minimum component unit of the numerator and denominator of the calculation formula corresponding to the monitoring indicator; The second acquisition module is used to determine the configuration unit required to generate the monitoring indicator of the type to be generated from the system basic data according to the common attributes and the individual attributes, wherein the common attributes include: the name of the configuration unit, the type of the configuration unit, and the value of the configuration unit, and the individual attributes include at least one of the following: basic information, detailed account information, credit rating information, and flow transaction information; verify the correctness of the data acquisition logic of the configuration unit required to generate the monitoring indicator of the type to be generated in real time, and determine the configuration unit that passes the verification as the target configuration unit; A generation module, used for classifying the configuration units according to the product type of the financial product to be newly set; constructing different configuration unit templates in a parameterized manner; the target configuration unit generates the monitoring indicator to be generated according to the configuration unit template; Other units except the above-mentioned units are used to calculate the investment data of the financial product corresponding to the monitoring indicator to be generated based on the monitoring indicator to be generated, obtain the monitoring indicator value of the financial product, analyze the relationship between the monitoring indicator value and the preset threshold and the investment trend of the obtained investment data, and perform early warning and violation verification on the generated monitoring indicator and the investment data. 9. The device according to claim 8, characterized in that the device also includes: A determination module is used to determine multiple configuration units in the following ways: The multiple configuration units are determined based on common attributes and individual attributes, wherein the common attributes include: the name of the configuration unit, the type of the configuration unit, and the value of the configuration unit; the individual attributes include at least one of the following: basic information, detailed subject information, credit rating information, and flow transaction information. 10. A storage medium, characterized in that the storage medium includes a stored program, wherein when the program is run, the device where the storage medium is located is controlled to execute the monitoring indicator generation method described in any one of claims 1 to 6. 11. A processor, characterized in that the processor is used to run a program, wherein the program executes the method for generating monitoring indicators described in any one of claims 1 to 6 when running.