CN113344523A

CN113344523A - Data processing method and device, electronic equipment and computer readable storage medium

Info

Publication number: CN113344523A
Application number: CN202110606292.3A
Authority: CN
Inventors: 刘若愚; 宋府昌
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2021-05-27
Filing date: 2021-05-27
Publication date: 2021-09-03

Abstract

The present disclosure provides a data processing method, which can be used in the technical field of big data and also can be used in the technical field of finance. The method comprises the following steps: receiving original request data from a staging service request end; verifying the original request data according to a preset verification rule so as to determine the original request data passing the verification as target basic information data, wherein the target basic information data are data conforming to a preset data format and a preset data type; acquiring target risk screening data; and sending the target risk screening data and the target basic information data to a decision engine so that the decision engine returns original result data related to the decision result to a data processing system after performing data processing according to the target risk screening data and the target basic information data. The present disclosure also provides a data processing apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

Description

Data processing method and device, electronic equipment and computer readable storage medium

Technical Field

The present disclosure relates to the field of big data technologies, and more particularly, to a data processing method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

Background

With the rapid development of the current internet financial industry, more and more staging demands follow, including cash staging, E staging, automobile staging, home decoration staging and the like. After the customer submits the staging application, the financial institution needs to approve the staging application.

In implementing the disclosed concept, the inventors found that there are at least the following problems in the related art: for different staging service lines, the different staging service lines need to be examined and approved separately, and for different staging products, the different staging products need to be interactively executed with requested data separately, so that the maintainability and the expandability are poor.

Disclosure of Invention

In view of the above, the present disclosure provides a data processing method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

One aspect of the present disclosure provides a data processing method, including:

receiving original request data from a staging service request end, wherein the original request data comprises original customer information data and original service information data, and the original service information data is related to the service type of a staging product;

verifying the original request data according to a preset verification rule so as to determine the original request data passing the verification as target basic information data, wherein the target basic information data are data conforming to a preset data format and a preset data type;

acquiring target risk screening data, wherein the target risk screening data are risk screening data matched with the types of the target risk screening data, and the types of the target risk screening data are risk screening data types on which decision-making is executed by a decision-making engine;

and sending the target risk screening data and the target basic information data to a decision engine so that the decision engine returns original result data related to the decision result to a data processing system after performing data processing according to the target risk screening data and the target basic information data.

According to the embodiment of the disclosure, the preset check rule includes a first preset check rule and a second preset check rule, where the first preset check rule is used to determine whether the data type of the original request data conforms to a preset data type, and the second preset check rule is used to determine whether the data format of the original request data conforms to a preset data format, where the preset data type is a request data type according to which the decision engine executes the decision, and the preset data format is a data format that needs to be satisfied when data storage is performed in a database of the data processing system.

According to the embodiment of the disclosure, the first preset check rule includes a general customer information check rule and a plurality of unique service information check rules, wherein the general customer information check rule is used for checking data types of original customer information data under various service types of the products to be classified, and the plurality of unique service information check rules are respectively used for checking data types of the original service information data under respective service types of the products to be classified.

According to an embodiment of the present disclosure, wherein:

the preset data types comprise a first preset data type used for representing target data types of original customer information data under various service types of the products to be classified and a second preset data type respectively used for representing target data types of the original service information data under the respective service types of the products to be classified, wherein the first preset data type is a customer information data type on which a decision engine executes a decision; the second preset data type is a service information data type according to which the decision engine executes the decision.

The verification of the original request data according to the preset verification rule comprises the following steps:

verifying whether the data type of the customer information data under various service types of the staged products conforms to a first preset data type according to a universal customer information verification rule;

respectively verifying whether the data type of the original service information data under the service type of each staged product conforms to a second preset data type according to each unique service information verification rule;

and checking whether the data formats of the client information data and the original service information data accord with the preset data format or not according to a second preset check rule.

According to the embodiment of the present disclosure, verifying the original request data according to the preset verification rule includes:

adding a custom annotation to the original request data;

and respectively verifying each data in the original request data by using the custom annotation and the preset verification rule in a JAVA reflection mode.

According to an embodiment of the present disclosure, obtaining target risk screening data comprises:

acquiring basic risk screening data according to the target basic information data, wherein the basic risk screening data are all types of risk screening data matched with the service types of the staged products;

and screening data matched with the target risk screening data type from the basic risk screening data to obtain target risk screening data.

According to an embodiment of the present disclosure, wherein obtaining the basic risk screening data according to the target basic information data comprises:

analyzing the target basic information data to obtain the service type of the staged product;

acquiring risk screening basic information data related to the service type of the staged product;

and acquiring basic risk screening data according to the risk screening basic information data.

According to an embodiment of the present disclosure, the transmitting and receiving target risk screening data to a decision engine comprises:

and matching each field information of the target risk screening data and the target basic information data with first target field information one by one in a JAVA reflection mode, wherein the first target field information is the field information of data according to which a decision engine executes a decision.

According to an embodiment of the present disclosure, further comprising:

analyzing original result data related to the decision result to obtain decision result data;

and storing the decision result data into a database of the data processing system.

According to an embodiment of the present disclosure, storing the decision result data in a database of the data processing system includes:

and matching each field information of the decision result data with second target field information one by one in a JAVA reflection mode, wherein the second target field information is the field information adopted when the decision result data are stored in the database.

According to an embodiment of the present disclosure, further comprising:

and reading the decision result from the database according to a preset time interval so as to return the decision result to the staging service request end.

Another aspect of the present disclosure provides a data processing apparatus including a receiving module, a verifying module, an obtaining module, and a sending module.

The receiving module is used for receiving original request data from an staging service request end, wherein the original request data comprises original customer information data and original service information data, and the original service information data is related to the service type of the staging product.

The verification module is used for verifying the original request data according to a preset verification rule so as to determine the original request data passing the verification as target basic information data, wherein the target basic information data is data conforming to a preset data format and a preset data type,

the acquisition module is used for acquiring target risk screening data, wherein the target risk screening data are risk screening data matched with the types of the target risk screening data, and the types of the target risk screening data are risk screening data types according to which the decision engine executes decisions.

And the sending module is used for sending the target risk screening data and the target basic information data to the decision engine so that the decision engine returns original result data related to the decision result to the data processing system after performing data processing according to the target risk screening data and the target basic information data.

According to an embodiment of the present disclosure, wherein: the preset data types comprise a first preset data type used for representing target data types of original customer information data under various service types of the products to be classified and a second preset data type respectively used for representing target data types of the original service information data under the respective service types of the products to be classified, wherein the first preset data type is a customer information data type on which a decision engine executes a decision; the second preset data type is a service information data type on which the decision engine executes the decision;

the checking module comprises a first checking unit, a second checking unit and a third checking unit.

The first checking unit is used for checking whether the data type of the customer information data under various service types of the staged products conforms to a first preset data type according to a universal customer information checking rule; the second checking unit is used for checking whether the data type of the original service information data under the service type of each staged product conforms to a second preset data type according to each unique service information checking rule; and the third checking unit is used for checking whether the data formats of the client information data and the original service information data accord with the preset data format or not according to a second preset checking rule.

According to the embodiment of the disclosure, the verification module comprises an adding unit and a fourth verification unit.

The adding unit is used for adding custom notes to the original request data; and the fourth verification unit is used for verifying each data in the original request data respectively by using the custom annotation and the preset verification rule in a JAVA reflection mode.

According to an embodiment of the present disclosure, the obtaining module includes a obtaining unit and a screening unit.

The system comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is used for acquiring basic risk screening data according to target basic information data, wherein the basic risk screening data are all types of risk screening data matched with the service types of the staged products; and the screening unit is used for screening the data matched with the type of the target risk screening data from the basic risk screening data to obtain the target risk screening data.

According to an embodiment of the present disclosure, the obtaining unit includes a parsing subunit, a first obtaining subunit, and a second obtaining subunit.

The analysis subunit is used for analyzing the target basic information data to obtain the service type of the staged product; the first acquisition subunit acquires risk screening basic information data related to the service type of the staged product; and the second acquisition subunit is used for acquiring the basic risk screening data according to the risk screening basic information data.

According to an embodiment of the present disclosure, in the sending module, sending the target risk screening data and the target basic information data to the decision engine includes: and matching each field information of the target risk screening data and the target basic information data with first target field information one by one in a JAVA reflection mode, wherein the first target field information is the field information of data according to which a decision engine executes a decision.

According to the embodiment of the disclosure, the data processing device further comprises an analysis module and a storage module.

The analysis module is used for analyzing original result data related to the decision result to obtain decision result data; and the storage module is used for storing the decision result data into a database of the data processing system.

According to an embodiment of the present disclosure, in the above storage module, storing the decision result data in a database of the data processing system includes: and matching each field information of the decision result data with second target field information one by one in a JAVA reflection mode, wherein the second target field information is the field information adopted when the decision result data are stored in the database.

According to an embodiment of the present disclosure, the data processing apparatus further includes: and the reading module is used for reading the decision result from the database according to the preset time interval so as to return the decision result to the staging service request end.

Another aspect of the present disclosure provides an electronic device including: one or more processors, and a memory; wherein the memory is for storing one or more programs; wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data processing method as described above.

Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions for implementing the data processing method as described above when executed.

Another aspect of the present disclosure provides a computer program product comprising computer executable instructions for implementing the data processing method as described above when executed.

According to the embodiment of the disclosure, a set of dynamically configurable and self-adaptively supported general data processing flows for different staging products is established through the data processing method, the method is used for establishing a common approval stage of each staging service line, including checking of basic information data and risk screening of customers to obtain risk screening data, the common approval stage is integrated in the same data processing flow, different staging service lines can share the same data processing method, the approval process can be executed only by inputting different customer information data into a product end, a pluggable processing mode is supported, and for newly added/deleted staging service lines, switching of service scenes can be completed only by configuring the basic information data, so that the flexibility is high, the expansibility is strong, the service rule change can be dynamically adapted, the development efficiency is improved, and the service management efficiency is improved, And the development risk is reduced.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:

FIG. 1 schematically illustrates an exemplary system architecture to which the data processing methods and apparatus of the present disclosure may be applied;

FIG. 2 schematically shows a flow chart of a data processing method according to an embodiment of the present disclosure;

FIG. 3 schematically illustrates a flow chart of verifying original request data according to a preset verification rule according to an embodiment of the present disclosure;

FIG. 4 is a schematic diagram illustrating verification of original request data according to a preset verification rule according to an embodiment of the present disclosure;

FIG. 5 schematically illustrates a flow chart for obtaining targeted risk screening data according to an embodiment of the present disclosure;

FIG. 6 schematically illustrates a schematic diagram of obtaining targeted risk screening data according to an embodiment of the present disclosure;

FIG. 7 schematically illustrates a schematic diagram of sending and receiving target risk screening data and target base information data to and from a decision engine, according to an embodiment of the disclosure;

FIG. 8 schematically shows a schematic diagram of a data processing method according to an embodiment of the present disclosure;

fig. 9 schematically shows a schematic diagram of reading a decision result from a database according to a preset time interval and pushing the decision result to an staging service request end at regular time according to an embodiment of the present disclosure;

FIG. 10 schematically shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure; and

fig. 11 schematically shows a block diagram of an electronic device for implementing a data processing method according to an embodiment of the present disclosure.

Detailed Description

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.

Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).

Before the embodiments of the present disclosure are explained in detail, the system structure and the application scenario related to the method provided by the embodiments of the present disclosure are described as follows.

Fig. 1 schematically illustrates an exemplary system architecture 100 to which the data processing methods and apparatus of the present disclosure may be applied. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.

As shown in fig. 1, the system architecture 100 according to this embodiment may include

terminal devices

101, 102, 103, a network 104 and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired and/or wireless communication links, and so forth.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The

terminal devices

101, 102, 103 may have installed thereon various communication client applications, such as a shopping-like application, a web browser application, a search-like application, an instant messaging tool, a mailbox client, and/or social platform software, etc. (by way of example only).

The

terminal devices

101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The server 105 may be a server that provides various services, such as a background management server that provides support for websites browsed by users using the

terminal devices

101, 102, 103. (the server 105 may be a server providing various services, including but not limited to service one, service two, service three, service four, and so on, and service one, service two, service three, and service four may be, for example, services providing support for websites browsed by users using the

terminal devices

101, 102, and 103.) the background management server may analyze and process data such as received user requests, and feed back processing results (e.g., web pages, information, or data obtained or generated according to the user requests) to the terminal devices.

The special staging business refers to the personal mortgage credit loan business provided by the financial institution according to the specific consumption requirements of the customers and integrating the qualification of the customers. Under the system architecture, a user can use the

terminal devices

101, 102, 103 to send raw request data to the server 105 through the network 104, where the raw request data may include various customer information data, business information data, and the like, and the server 105 may be configured to perform data processing on the raw request data and then send the processed data to a service downstream of the system, such as a decision engine, so that the decision engine performs decision tasks according to the data, performs risk screening on the customer, and generates a decision result.

According to the embodiment of the present disclosure, the server 105 performs data processing on the original request data, which may be performing data verification on the original request data to obtain data conforming to a specific data type; it is also possible to perform data interaction with an external componentized service based on the original request data to obtain some intermediate result data, such as risk screening data, etc.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

It should be noted that the data processing method and apparatus of the present disclosure may be used in the field of big data technology, the field of financial technology, or any field other than the field of big data technology and the field of financial technology, and the application field of the data processing method and apparatus is not limited by the present disclosure.

With the rapid development of the current internet financial industry, more and more staging demands follow, including cash staging, E staging, automobile staging, home decoration staging and the like. The special staging business refers to the personal mortgage credit loan business provided by the financial institution according to the specific consumption requirements of the customers and integrating the qualification of the customers. After the client submits the staging application, the financial institution needs to approve the staging application, and a big data rule engine system, such as a Blaze decision engine, is used for screening and deciding the risk of the client according to various related information sent in the approval process.

In the related art, different staging service lines are required to be examined and approved independently, and different staging products are required to be interactively executed independently to request data, so that the maintainability and the expandability are poor.

In the process of implementing the disclosure, different approval processes of each staged product are found to be similar in general, and almost all staged business lines need to perform verification of basic information data, risk screening of customers and the like in the approval process, and the differences mainly lie in that the customer information input from a product end is different and the individual information is sent to a Blaze decision engine. Therefore, by establishing a set of general data processing system, different staging service lines can share the same set of data processing method, so that the approval process is accelerated, and the maintainability and the expandability of the approval system are improved.

Fig. 2 schematically shows a flow chart of a data processing method according to an embodiment of the present disclosure.

As shown in fig. 2, the method includes operations S201 to S204.

In operation S201, original request data from an installment service request terminal is received, the original request data including original customer information data and original service information data, wherein the original service information data is related to the installment product service type. The original customer information data, mainly some personal basic information data of the customer, such as name, age, identification number, monthly income and the like, and the original business information data are related to different service types of the products in installments, for example, for the products in installments, the original business information data can comprise mortgage information and the like, and for the products in installments, the original business information data can comprise property information of the property of the house and the like.

In operation S202, the original request data is verified according to a preset verification rule, so that the original request data passing the verification is determined to be target basic information data, where the target basic information data is data conforming to a preset data format and a preset data type.

In operation S203, target risk screening data is acquired, where the target risk screening data is risk screening data matched with a type of the target risk screening data, and the type of the target risk screening data is a type of risk screening data according to which a decision engine performs a decision.

In operation S204, the target risk screening data and the target basic information data are sent to the decision engine, so that the decision engine returns the original result data related to the decision result to the data processing system after performing data processing according to the target risk screening data and the target basic information data. The decision engine is a downstream service system of the data processing system, and is used for risk screening and decision making for the client according to various related information sent in the approval process, for example, a Blaze decision engine may be used.

In the data processing system, the original request data of the request end is mainly preprocessed, some intermediate result data are obtained, and then the obtained data are sent to a service downstream of the system, such as a decision engine, so that the decision engine executes a decision task according to the data, screens risks of customers and generates decision results. In the process of data interaction with the decision engine, the data uploaded to the decision engine needs to meet the data type standard provided by the decision engine, so that the preset data type of the target basic information data is the request data type according to which the decision engine executes the decision; the target risk screening data type of the target risk screening data is a risk screening data type on which a decision engine executes a decision, and may include, for example, blacklist risk screening result data, anti-fraud risk screening result data, cross default risk screening result data, and the like.

In addition, after the target basic information data is generated, the data needs to be persisted and stored in a local database so as to be called by a subsequent processing flow. Therefore, the preset data format of the target basic information data is a data format which needs to be satisfied when data is stored in a database of the data processing system, such as the length of the data, the format of a data dictionary, the format of a date, and the like.

The preset check rule is set by a user, and after the original request data is checked by the check rule, the purpose is to judge and screen the data sent by the staging service request end so as to obtain the target basic information data meeting the preset data standard.

It should be noted that, the acquisition, storage, application, and the like of the personal information of the user involved in the embodiments of the present disclosure all comply with the regulations of the relevant laws and regulations, and do not violate the good customs of the public order.

According to the embodiment of the present disclosure, further, the first preset check rule includes a general customer information check rule and a plurality of unique service information check rules, where the general customer information check rule is used for data type check of the original customer information data under various service types of the products to be staged, and the plurality of unique service information check rules are respectively used for data type check of the original service information data under respective service types of the products to be staged.

According to the embodiment of the present disclosure, further, the preset data types include a first preset data type for representing a target data type of the original customer information data in each of the staged product service types, and a second preset data type for representing a target data type of the original service information data in each of the staged product service types, respectively, where the first preset data type is a customer information data type on which the decision engine performs the decision; the second preset data type is a service information data type according to which the decision engine executes the decision.

FIG. 3 schematically illustrates a flow chart of verifying original request data according to a preset verification rule according to an embodiment of the present disclosure; fig. 4 schematically illustrates a schematic diagram of verifying original request data according to a preset verification rule according to an embodiment of the present disclosure. With reference to fig. 3 and fig. 4, based on the foregoing verification rule, a method for verifying original request data according to a preset verification rule according to the embodiment of the present disclosure is described as follows:

as shown in fig. 3, the method includes operations S301 to S303.

After receiving the original request data from the staging service request end, firstly, judging whether the staging product is an effective staging product according to the original request data, such as customer information and basic information of product service, such as whether the staging product is online, if the staging product is invalid, ending the processing flow, and avoiding unnecessary time waste caused by the fact that a subsequent approval flow is carried out under the condition that the staging product is off shelf.

In the case that the staged product is valid, in operation S301, it is checked whether the data type of the customer information data under various service types of the staged product conforms to a first preset data type according to a general customer information check rule. According to the embodiment of the disclosure, the types of the client information data on which the decision engine executes the decision are basically the same for different stage products, so that in order to accelerate the data processing process, the operation of checking the client information can be extracted to form a general processing flow. The first predetermined data type is determined according to the data interface standard provided by the decision engine, and may include, for example, name, age, identification number, monthly income, and the like. The purpose of this operation is to verify whether the data type of the customer information data is complete, so as to be the basis for decision engine to execute decision.

In operation S302, it is checked whether the data type of the original service information data under the service type of the respective staged product conforms to a second preset data type according to each unique service information check rule, respectively. For each of the products, the data type of the original service information data is related to the service type of the respective product, for example, for the car products, the original service information data should include collateral information, and for the home products, the original service information data should include property information. For the verification of the part of data, respective unique service information verification rules need to be executed for verification.

In operation S303, it is checked whether the data formats of the customer information data and the original service information data conform to the preset data format according to a second preset check rule.

According to the embodiment of the disclosure, after the data verification process is executed, the original request data which conforms to the preset data type and the preset data format is determined as the target basic information data, and after the target basic information data is generated, the data needs to be persisted and stored in the local database so as to be called by the subsequent processing process. Therefore, the preset data format of the target basic information data needs to meet the standard of the data format stored in the database, such as whether the length of the data conforms to the set length standard, whether the format of the data dictionary conforms to the preset dictionary format, whether the format of the date is the preset date format, and the like. After the data verification process is executed, storing the target basic information data into a basic information data table of a local database, and executing a subsequent process after the verification is successful; otherwise, prompting error information and returning.

According to the embodiment of the disclosure, the preset check rule is set, and the preset check rule is further set to be a first preset check rule and a second preset check rule which comprise a general customer information check rule and a plurality of unique service information check rules. Through the verification rules, the universal verification processes of different staging service line products can be extracted for unified verification, and for the unique verification process of each staging service line product, the respective unique service information verification rule is executed for verification, and the respective independent and complete verification process does not need to be executed for each staging service product, so that the data processing efficiency can be improved and the approval process is accelerated through the verification method.

According to the embodiment of the present disclosure, verifying the original request data according to the preset verification rule includes: adding a custom annotation to the original request data; and respectively verifying each data in the original request data by using the custom annotation and the preset verification rule in a JAVA reflection mode.

In the related art, when original request data is verified, each request field is processed in a hard coding mode, and due to the fact that the types of staging service line products are various, the number of detection data items is large, a large number of redundant codes can be generated, and maintainability and expandability are poor.

In order to solve the technical problem, according to the embodiment of the disclosure, by adding custom notes to original request data, that is, adding corresponding notes to the field position to be checked of the product side input information, annotating the data format, the data type and the like of the field, and combining with the use of a JAVA reflection mode, according to a preset check rule, universal check of staging business information can be realized, including check of data must be input, check of uploading stage, length, dictionary, date and the like, eliminating a hard coding mode of traditional data check and uploading parameters, having high code reuse rate, reducing redundant codes and reducing manual operation.

FIG. 5 schematically illustrates a flow chart for obtaining targeted risk screening data according to an embodiment of the present disclosure; fig. 6 schematically illustrates a schematic diagram of acquiring targeted risk screening data according to an embodiment of the present disclosure. A method for acquiring target risk screening data according to an embodiment of the present disclosure is described below with reference to fig. 5 and 6.

As shown in fig. 5, the method includes operations S501 to S504.

In operation S501, the target basic information data is analyzed to obtain the service type of the staged product; for example, the type of the business of the installment product may be determined by parsing the business information data related to the type of the installment product business in the target basic information data.

In operation S502, risk screening basic information data related to the staging product business type is acquired.

Before the data processing method of the embodiment of the present disclosure is executed, a parameter configuration table of the staging business process may be configured in advance, where the parameter configuration table mainly records risk screening basic information data required for executing approval processes of different types of staging product businesses, and the risk screening basic information data is used to represent types of some basic information data required for executing various types of risk screening, for example, names, home addresses, telephones, historical credit record information, and the like of clients required for executing blacklist risk screening. The risk screening basic information data can be obtained by reading a parameter configuration table of the staging business process.

According to the embodiment of the disclosure, before the operation is executed, some customer information, basic information of the product service and the like can be acquired by reading the parameter configuration table of the staging service flow, so as to judge whether the staging product service line is valid, and if the staging product service line is invalid, the processing flow is ended.

In operation S503, if the service line of the staged product is valid, basic risk screening data is obtained according to the risk screening basic information data, where the basic risk screening data is all types of risk screening data matched with the service type of the staged product, and both the basic risk screening number and the target risk screening data are risk screening result data, such as result data indicating whether the customer has fraudulent behavior or not, and result data indicating whether the customer has cross default behavior or not. Specifically, the risk screening basic information data related to the service type of the staged product can be transmitted to the external risk screening application by calling an interface interfacing with the external risk screening application, basic risk screening data is acquired by data interaction with the external risk screening application, and the basic risk screening data is stored in a risk screening data table of a local database after the basic risk screening data is acquired.

In operation S504, data matching the target risk screening data type is screened from the basic risk screening data to obtain target risk screening data. According to the embodiment of the disclosure, the data nodes of the target risk screening data types which need to be uploaded can be registered in advance in a user-defined annotation mode, and then the risk screening data which need to be uploaded to the decision engine is configured to the corresponding data nodes of the target risk screening data types, namely the data nodes under different staging business types are injected with the needed risk screening data. When the operation flow is executed, firstly, the type of the target risk screening data under the service type of the staging product is judged according to the determined service type of the staging product, and then, the risk screening data result under the type of the corresponding risk screening data is read from the risk screening data table of the local database according to the type of the target risk screening data. For example, an approval of an automobile staging product is performed, the types of target risk screening data under the staging product business type including anti-fraud risk screening data, and blacklist risk screening data. And then, reading the screening results of the client related to the anti-fraud and blacklist risk screening from the risk screening data table of the local database.

According to an embodiment of the present disclosure, sending and receiving the target risk screening data and the target basic information data to the decision engine comprises: and matching each field information of the target risk screening data and the target basic information data with first target field information one by one in a JAVA reflection mode, wherein the first target field information is the field information of data according to which a decision engine executes a decision.

Fig. 7 schematically illustrates a schematic diagram of sending and receiving target risk screening data and target basic information data to and from a decision engine according to an embodiment of the present disclosure.

In the related art, when target risk screening data and target basic information data are sent to a decision engine, each uploading field is processed in a hard coding mode, and a large number of redundant codes are generated due to the fact that the types of staging business line products are various and the number of inspection data items is large.

In order to solve the above technical problem, according to the embodiment of the present disclosure, each field information of the target risk screening data and the target basic information data is matched with the first target field information one by one in a JAVA reflection manner, as shown in fig. 7, the implementation manner is to perform traversal matching on the target risk screening data and the target basic information data one by one respectively through a JAVA reflection technique until all the field information is successfully matched. During execution, the processing can be performed according to actual conditions, for example, in the case that the data for performing matching is unnecessary information data when the decision engine performs decision, the matching failure can be ignored, otherwise, the matching failure returns an exception.

According to the embodiment of the disclosure, each field information of the target risk screening data and the target basic information data is matched with the first target field information one by one in a JAVA reflection mode, so that the obtained data can be uniformly and automatically mapped into data needing to be uploaded to a decision engine, a hard coding mode of traditional data verification and uploading parameters is eliminated, the code reuse rate is high, redundant codes are reduced, and manual operation is reduced.

According to the embodiment of the present disclosure, after the target risk screening data and the target basic information data are sent to the decision engine, the request data may be converted into a message format of XML through JAXB Context (API entry of Java architecture for XML Binding) of JDK (Java programming language is used to construct a development environment of applications, applets, and components). And creating a local client, and completing the calling of the decision engine by the generated XML message in a web Service mode. And after the decision engine is called to execute the decision, receiving the original result data which is returned by the decision engine and is related to the decision result.

According to an embodiment of the present disclosure, the data processing method further includes: analyzing original result data related to the decision result to obtain decision result data; and storing the decision result data into a database of the data processing system.

According to an embodiment of the present disclosure, the data processing method further includes: and reading the decision result from the database according to a preset time interval so as to return the decision result to the staging service request end.

Fig. 8 schematically shows a schematic diagram of a data processing method according to an embodiment of the present disclosure. As shown in fig. 8, the processing method may include the following steps:

(1) receiving original request data from a staging service request end; the data sent by the staging service request terminal can be, for example, personal basic information data of the client, such as name, age, identification number, monthly income and the like, and also comprises service information data related to different service types of the staging products, such as collateral information and the like, property information of the real estate and the like.

(2) And carrying out universal verification on the original request data according to a preset verification rule so as to determine the original request data passing the verification as target basic information data. Specifically, whether the data type and the data format of the original request data meet the preset standard or not, and whether the data type standard according to which the decision engine executes the decision is met or not, and whether the standard of the database storage data format is met or not are checked through the preset check rule, for example, whether the length of the data meets the set length standard or not, whether the format of the data dictionary meets the format of the preset dictionary or not, whether the format of the date is the preset date format or not, and the like. In the verification process, the interface processor can execute relevant data reading operation, for example, when the data format is verified to meet the preset format, the interface processor can read dictionary entries in the database, and then the dictionary entries are compared with the data sent by the request end one by one for verification. After the verification is passed, the target basic information data can be stored in a basic information data table in a local database.

(3) Target risk screening data is obtained. The method comprises the steps of firstly, reading a pre-configured parameter configuration table for configuring an staging business process to obtain type risk screening basic information data for representing some basic information data required for executing various types of risk screening, then calling an interface in butt joint with an external risk screening application through an interface processor, transmitting the risk screening basic information data related to the staging product business type to the external risk screening application, acquiring basic risk screening data through data interaction with the external risk screening application, and storing the data into a risk screening data table of a local database after acquiring the data. Finally, data matching the target risk screening data type may be screened from the base risk screening data to obtain target risk screening data.

(4) And sending the target risk screening data and the target basic information data to a Blaze decision engine.

(5) And the Blaze decision engine performs data processing according to the target risk screening data and the target basic information data and returns original result data related to the decision result to the data processing system.

(6) And analyzing the original result data returned by the Blaze decision engine to obtain decision result data.

(7) And storing the decision result data into a database of the data processing system.

(8) And reading the decision result from the database according to a preset time interval, and pushing the decision result to a staging service request end at regular time. Fig. 9 schematically shows a schematic diagram of reading a decision result from a database according to a preset time interval and pushing the decision result to an staging service request end at regular time according to an embodiment of the present disclosure. As shown in fig. 9, the number of push execution threads and the execution time for executing the operation are configured by the customized thread pool, the data stored in the database of the data processing system is scanned at regular time, the decision result is queried, and the returned conclusion is pushed at regular time according to the interface rule and the policy provided by the product end. And if the push fails, retry of the failure times is executed according to the rule agreed by the upstream and the downstream. And (4) successfully pushing, and completing closed loop of all the staging business processes.

According to an embodiment of the present disclosure, storing the decision result data in a database of the data processing system includes: and matching each field information of the decision result data with second target field information one by one in a JAVA reflection mode, wherein the second target field information is the field information adopted when the decision result data are stored in the database.

According to the embodiment of the disclosure, each field information of the decision result data is matched with the second target field information one by one in a JAVA reflection mode, so that the obtained data can be uniformly and automatically mapped into the data needing to be stored in a database, a hard coding mode of traditional data verification and uploading parameters is eliminated, the code reuse rate is high, redundant codes are reduced, and manual operation is reduced.

Fig. 10 schematically shows a block diagram 1000 of a data processing apparatus according to an embodiment of the present disclosure. The apparatus 1000 may be used to implement the method described with reference to fig. 2.

As shown in fig. 10, the load prediction apparatus 1000 includes: the system comprises a receiving module 1001, a checking module 1002, an obtaining module 1003 and a sending module 1004.

The receiving module 1001 is configured to receive original request data from an installment service request end, where the original request data includes original customer information data and original service information data, and the original service information data is related to a service type of an installment product.

A checking module 1002, configured to check the original request data according to a preset checking rule, so as to determine the original request data passing the checking as target basic information data, where the target basic information data is data conforming to a preset data format and a preset data type,

an obtaining module 1003, configured to obtain target risk screening data, where the target risk screening data is risk screening data matched with a type of the target risk screening data, and the type of the target risk screening data is a type of risk screening data according to which a decision engine performs a decision.

The sending module 1004 is configured to send the target risk screening data and the target basic information data to the decision engine, so that the decision engine returns original result data related to the decision result to the data processing system after performing data processing according to the target risk screening data and the target basic information data.

According to the embodiment of the disclosure, a set of general data processing flows which can be dynamically configured and adaptively supported can be established through the checking module 1002 and the obtaining module 1003 of the data processing device, the device can be used for establishing a common approval stage of each staging business line, including checking of basic information data and risk screening of customers to obtain risk screening data, the general data processing flows are integrated in the same data processing flow, different staging business lines can share the same data processing flow, the approval flow can be executed only by inputting different customer information data into a product end, a pluggable processing mode is supported, and for newly added/deleted staging business lines, switching of business scenes can be completed only by configuring the basic information data, the flexibility is high, the expansibility is strong, and the device can dynamically adapt to business rule change, The development efficiency is improved, and the development risk is reduced.

the verification module 1002 includes a first verification unit, a second verification unit, and a third verification unit.

According to an embodiment of the present disclosure, the verification module 1002 includes an adding unit and a fourth verification unit.

According to an embodiment of the present disclosure, the obtaining module 1003 includes an obtaining unit and a screening unit.

According to an embodiment of the present disclosure, the sending module 1004 sending the target risk screening data and the target basic information data to the decision engine includes: and matching each field information of the target risk screening data and the target basic information data with first target field information one by one in a JAVA reflection mode, wherein the first target field information is the field information of data according to which a decision engine executes a decision.

Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in any other reasonable manner of hardware or firmware by integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware implementations. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.

For example, any plurality of the receiving module 1001, the verifying module 1002, the obtaining module 1003 and the sending module 1004 may be combined into one module/unit/sub-unit to be implemented, or any one of the modules/units/sub-units may be split into a plurality of modules/units/sub-units. Alternatively, at least part of the functionality of one or more of these modules/units/sub-units may be combined with at least part of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to an embodiment of the present disclosure, at least one of the receiving module 1001, the verifying module 1002, the obtaining module 1003 and the sending module 1004 may be implemented at least partially as a hardware circuit, for example, a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented by any one of three implementations of software, hardware and firmware, or implemented by a suitable combination of any several of them. Alternatively, at least one of the receiving module 1001, the verifying module 1002, the obtaining module 1003 and the sending module 1004 may be at least partly implemented as a computer program module, which when executed may perform a corresponding function.

Fig. 11 schematically shows a block diagram of an electronic device for implementing a data processing method according to an embodiment of the present disclosure. The electronic device shown in fig. 11 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 11, an electronic device 1100 according to an embodiment of the present disclosure includes a processor 1101, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)1102 or a program loaded from a storage section 1108 into a Random Access Memory (RAM) 1103. The processor 1101 may comprise, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 1101 may also include on-board memory for caching purposes. The processor 1101 may comprise a single processing unit or a plurality of processing units for performing the different actions of the method flows according to the embodiments of the present disclosure.

In the RAM 1103, various programs and data necessary for the operation of the electronic device 1100 are stored. The processor 1101, the ROM 1102, and the RAM 1103 are connected to each other by a bus 1104. The processor 1101 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 1102 and/or the RAM 1103. It is noted that the programs may also be stored in one or more memories other than the ROM 1102 and RAM 1103. The processor 1101 may also perform various operations of the method flows according to the embodiments of the present disclosure by executing programs stored in the one or more memories.

Electronic device 1100 may also include input/output (I/O) interface 1105, input/output (I/O) interface 1105 also connected to bus 1104, according to an embodiment of the disclosure. The system 1100 may also include one or more of the following components connected to the I/O interface 1105: an input portion 1106 including a keyboard, mouse, and the like; an output portion 1107 including a signal output unit such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage section 1108 including a hard disk and the like; and a communication section 1109 including a network interface card such as a LAN card, a modem, or the like. The communication section 1109 performs communication processing via a network such as the internet. A driver 1110 is also connected to the I/O interface 1105 as necessary. A removable medium 1111 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1110 as necessary, so that a computer program read out therefrom is mounted into the storage section 1108 as necessary.

According to embodiments of the present disclosure, method flows according to embodiments of the present disclosure may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 1109 and/or installed from the removable medium 1111. The computer program, when executed by the processor 1101, performs the above-described functions defined in the system of the embodiment of the present disclosure. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.

The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.

According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. Examples may include, but are not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

For example, according to embodiments of the present disclosure, a computer-readable storage medium may include the ROM 1102 and/or the RAM 1103 and/or one or more memories other than the ROM 1102 and the RAM 1103 described above.

Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method provided by the embodiments of the present disclosure, when the computer program product is run on an electronic device, the program code being adapted to cause the electronic device to carry out the data processing method provided by the embodiments of the present disclosure.

The computer program, when executed by the processor 1101, performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure. The systems, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.

In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted in the form of a signal on a network medium, distributed, downloaded and installed via the communication part 1109, and/or installed from the removable medium 1111. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.

The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims

1. A method of data processing, comprising:

acquiring target risk screening data, wherein the target risk screening data is risk screening data matched with a target risk screening data type, and the target risk screening data type is a risk screening data type on which a decision engine executes a decision; and

and sending the target risk screening data and the target basic information data to a decision engine so that the decision engine returns original result data related to a decision result to a data processing system after performing data processing according to the target risk screening data and the target basic information data.

2. The method according to claim 1, wherein the preset check rule includes a first preset check rule and a second preset check rule, wherein the first preset check rule is used to determine whether the data type of the original request data conforms to the preset data type, the second preset check rule is used to determine whether the data format of the original request data conforms to the preset data format, wherein the preset data type is the request data type according to which a decision engine executes a decision, and the preset data format is a data format that needs to be satisfied when data storage is performed in a database of the data processing system.

3. The method of claim 2, wherein the first preset check rule includes a general customer information check rule for data type check of the original customer information data in each of the staged product service types and a plurality of unique service information check rules for data type check of the original service information data in each of the staged product service types, respectively.

4. The method of claim 3, wherein:

the preset data types comprise a first preset data type used for representing a target data type of the original customer information data under various staging product service types and a second preset data type respectively used for representing the target data type of the original service information data under the respective staging product service types, wherein the first preset data type is a customer information data type on which a decision engine executes a decision; the second preset data type is a service information data type on which a decision engine executes a decision;

the verifying the original request data according to a preset verification rule comprises:

verifying whether the data type of the customer information data under various service types of the staged products conforms to the first preset data type or not according to the general customer information verification rule;

respectively verifying whether the data type of the original service information data under the service type of each staged product conforms to the second preset data type according to each unique service information verification rule;

and verifying whether the data formats of the client information data and the original service information data conform to the preset data format or not according to the second preset verification rule.

5. The method of claim 1, wherein verifying the original request data according to a preset verification rule comprises:

adding a custom annotation to the original request data;

6. The method of claim 1, acquiring targeted risk screening data comprising:

acquiring basic risk screening data according to the target basic information data, wherein the basic risk screening data are all types of risk screening data matched with the service types of the staging products;

screening data matching the target risk screening data type from the basic risk screening data to obtain the target risk screening data.

7. The method of claim 6, wherein obtaining basic risk screening data from the target base information data comprises:

analyzing the target basic information data to obtain the service type of the staging product;

and acquiring the basic risk screening data according to the risk screening basic information data.

8. The method of claim 1, sending the target risk screening data and the target base information data to a decision engine comprising:

and matching each field information of the target risk screening data and the target basic information data with first target field information one by one in a JAVA reflection mode, wherein the first target field information is the field information of data on which a decision engine executes a decision.

9. The method of claim 1, further comprising:

analyzing the original result data related to the decision result to obtain decision result data;

and storing the decision result data into a database of a data processing system.

10. The method of claim 9, storing the decision result data in a database of a data processing system comprises:

11. The method of claim 9, further comprising:

12. A data processing apparatus comprising:

the system comprises a receiving module, a sending module and a receiving module, wherein the receiving module is used for receiving original request data from a staging service request end, the original request data comprises original customer information data and original service information data, and the original service information data is related to the service type of a staging product;

the verification module is used for verifying the original request data according to a preset verification rule so as to determine the original request data passing the verification as target basic information data, wherein the target basic information data are data conforming to a preset data format and a preset data type;

the system comprises an acquisition module, a decision engine and a processing module, wherein the acquisition module is used for acquiring target risk screening data, the target risk screening data is risk screening data matched with a target risk screening data type, and the target risk screening data type is a risk screening data type according to which the decision engine executes a decision;

and the sending module is used for sending the target risk screening data and the target basic information data to a decision engine so that the decision engine returns original result data related to a decision result to a data processing system after performing data processing according to the target risk screening data and the target basic information data.

13. An electronic device, comprising:

one or more processors;

a memory for storing one or more programs,

wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-11.

14. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to carry out the method of any one of claims 1 to 11.

15. A computer program product comprising computer executable instructions for implementing the method of any one of claims 1 to 11 when executed.