CN111459961A - Method, device and equipment for updating service data and storage medium - Google Patents
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Abstract
The invention discloses a method, a device, equipment and a storage medium for updating business data, wherein the method for updating the business data determines the target updating frequency corresponding to a target data source according to the target data identification of the target data source, the data source acquisition type and/or the enterprise risk level to which the data source acquisition type belongs; and updating data of the target data source according to the target updating frequency corresponding to the target data source. Through the mode, the data updating frequency corresponding to different data sources is determined according to the data type of the data source, the data source acquisition type and/or the enterprise risk level, so that the updating frequency of different data sources of different enterprises is flexibly set, the waste of updating resources caused by uniformly updating all data is avoided, the data updating efficiency is improved, and the technical problem of low data updating efficiency caused by inquiring or updating data according to the same set frequency in the prior art is solved.
Description
Technical Field
The present invention relates to the field of financial technology (Fintech), and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for updating business data.
Background
With the development of computer technology, more and more technologies are applied in the financial field, the traditional financial industry is gradually changing to financial technology (finth), and the database synchronization technology is no exception, but due to the requirements of security and real-time performance of the financial industry, higher requirements are also put forward on the data updating technology. For an enterprise financial post-loan management system, data query needs to be carried out on the information of a client after loan. For example, the information of tax payment, invoicing, customs, complaints, industry and commerce, water and electricity fee payment and the like of the enterprise end; the statutory represents information of social contact, loan, credit investigation, legal complaint, shopping, telephone fee payment and the like of the personal side of the person. The purpose of querying the customer information data is: and providing a data basis for subsequent risk rule formulation and risk scoring. The current customer information query mode is as follows: all client information and data sources are queried or updated uniformly according to the same set frequency, so that the data updating efficiency is low.
Disclosure of Invention
The invention mainly aims to provide a method, a device and equipment for updating service data and a computer readable storage medium, and aims to solve the technical problem of low data updating efficiency caused by inquiring or updating data according to the same set frequency.
In order to achieve the above object, the present invention provides a method for updating service data, where the method for updating service data includes the following steps:
determining a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs;
and updating data of the target data source according to the target updating frequency corresponding to the target data source.
Optionally, the step of determining the target update frequency corresponding to the target data according to the target data identifier of the target data, the data source acquisition type, and/or the enterprise risk level to which the target data belongs specifically includes:
acquiring a target data identifier of the target data source, and determining the data main degree of the target data source according to a preset data priority list and the target data identifier;
determining a data source acquisition type of a target data source according to a preset data source acquisition channel list and the target data identifier;
determining an enterprise to which the target data source belongs, and determining an enterprise risk level corresponding to the target data source according to a preset enterprise risk level list;
and determining the target updating frequency according to a preset updating frequency list, the data main degree, the data source acquisition type and/or the enterprise risk level.
Optionally, the step of determining the target update frequency according to a preset update frequency list, the data dominance, the data source acquisition type, and/or the enterprise risk level to which the data source acquisition type belongs specifically includes:
and when the data main degree is important data, the data source acquisition type is a free data source, and the enterprise risk is high risk, determining the target update frequency as the highest update frequency.
Optionally, the step of determining the target update frequency according to a preset update frequency list, the data dominance, the data source acquisition type, and/or the enterprise risk level to which the data source acquisition type belongs specifically further includes:
and when the data main degree is non-important data, the data source acquisition type is a pay-per-item data source and the risk of the enterprise is normal, determining the target updating frequency as the lowest updating frequency.
Optionally, before the step of determining the target update frequency corresponding to the target data source according to the target data identifier of the target data source, the data source acquisition type, and/or the enterprise risk level to which the target data source belongs, the method further includes:
acquiring enterprise related information of an enterprise to which the target data source belongs, and determining a risk level of the enterprise to which the target data source belongs according to a preset risk assessment rule and the enterprise related information;
and storing the enterprise identification of the enterprise to which the target data source belongs and the risk level association of the enterprise to which the target data source belongs to the enterprise risk level list.
Optionally, after the step of updating the data of the target data source according to the target update frequency corresponding to the target data source, the method further includes:
and when detecting that the risk level of the enterprise to which the target data source belongs is increased, temporarily updating the target data source.
Optionally, after the step of updating the data of the target data source according to the target update frequency corresponding to the target data source, the method further includes:
if the risk level of the enterprise to which the target data source belongs is not increased, judging whether the current loan overdue of the enterprise to which the target data source belongs exists;
and if the current loan overdue occurs to the enterprise to which the target data source belongs, acquiring the current longest overdue days of the enterprise to which the target data source belongs, and temporarily updating the target data source when the current longest overdue days exceed a preset threshold value.
In addition, to achieve the above object, the present invention further provides a service data updating apparatus, including:
the updating frequency determining module is used for determining a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs;
and the target data updating module is used for updating data of the target data source according to the target updating frequency corresponding to the target data source.
In addition, to achieve the above object, the present invention further provides a service data updating device, where the service data updating device includes: the system comprises a memory, a processor and an updating program of the business data, wherein the updating program of the business data is stored on the memory and can run on the processor, and when being executed by the processor, the updating program of the business data realizes the steps of the updating method of the business data.
In addition, to achieve the above object, the present invention also provides a computer readable storage medium, on which an update program of service data is stored, the update program of service data implementing the steps of the update method of service data as described above when executed by a processor.
The invention provides a business data updating method, which comprises the steps of determining a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs; and updating data of the target data source according to the target updating frequency corresponding to the target data source. Through the mode, the data updating frequency corresponding to different data sources is determined according to the data type of the data source, the data source acquisition type and/or the enterprise risk level, so that the updating frequency of different data sources of different enterprises is flexibly set, the waste of updating resources caused by uniformly updating all data is avoided, the data updating efficiency is improved, and the technical problem of low data updating efficiency caused by inquiring or updating data according to the same set frequency in the prior art is solved.
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FIG. 1 is a schematic diagram of an apparatus architecture of a hardware operating environment according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a first embodiment of a method for updating service data according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention.
The updating device of the service data of the embodiment of the invention can be a PC or a server device, and a Java virtual machine runs on the updating device.
As shown in fig. 1, the service data updating apparatus may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration of the apparatus shown in fig. 1 is not intended to be limiting of the apparatus and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and an update program of service data.
In the device shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to call an update program of the service data stored in the memory 1005 and perform an operation in the service data update method described below.
Based on the hardware structure, the embodiment of the method for updating the service data is provided.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a service data updating method of the present invention, where the service data updating method includes:
step S10, determining a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs;
in the financial automatic post-loan risk management system, various enterprise information required by risk management is automatically inquired, such as: paying information of tax payment, invoicing, customs, complaints, industry and commerce, water and electricity charge and the like of the enterprise end; the law represents the information of social contact, loan, credit, law, shopping, telephone charge and the like of the personal side. The purpose of querying enterprise information is to provide a data basis for the output of subsequent risk rules and risk scores. For example, the risk management after financial loan of the small and micro enterprise is a series of measures that a bank takes the small and micro enterprise as a financial service object, after a loan is issued to the small and micro enterprise, the credit risk of the small and micro enterprise is monitored in the period before the loan is settled by the enterprise, the repayment capacity of the enterprise is evaluated, and the borrowing amount and the repayment mode are adjusted in time according to the credit risk condition of the enterprise. In the small and micro enterprise financial automatic post-loan risk management mode, compared with the manual post-loan risk management mode, the small and micro enterprise financial automatic post-loan risk management mode is characterized in that the system initiates post-loan management, and automatically draws various client information required by the risk management at preset time, and processes the client information into required indexes, risk rules and risk scores, and carries out a series of processes of risk grade division, loan amount adjustment and repayment mode adjustment on the client according to the condition that the client hits the risk rules and scores. The current customer information query mode is as follows: all client information and all data sources are queried or updated uniformly according to the same set frequency, so that the data updating efficiency is low. In order to solve the technical problems, the data updating frequency corresponding to different data sources is determined according to the data type of the data source, the data source acquisition type and/or the enterprise risk level, so that the updating frequency of different data sources of different enterprises is flexibly set, the waste of updating resources caused by uniformly updating all data is avoided, and the data updating efficiency is improved. Specifically, different update frequencies are set in advance according to the data sources of the enterprises, and are stored in an update frequency list. And then sequentially acquiring each data source of each enterprise as a target data source. And then determining the main degree of the data source based on the target data identification of the target data source, determining the data source acquisition type of the target data source, such as free acquisition, step charge acquisition, packed charge acquisition or pay-per-item charge, and determining the enterprise risk level, such as normal risk, medium risk or high risk, of the enterprise to which the target data source belongs. And then determining the target updating frequency corresponding to the target data source in the updating frequency list based on the parameters.
And step S20, updating the data of the target data source according to the target updating frequency corresponding to the target data source.
In this embodiment, data update is performed on the target data source according to the target update frequency corresponding to the target data source. Therefore, the data sources are flexibly updated according to the data updating frequency respectively corresponding to the data sources of each enterprise. For example, the update frequency of important data sources of high-risk enterprises is increased, and the update frequency of non-important data sources of normal enterprises is reduced.
The embodiment provides a method for updating business data, which determines a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs; and updating data of the target data source according to the target updating frequency corresponding to the target data source. Through the mode, the data updating frequency corresponding to different data sources is determined according to the data type of the data source, the data source acquisition type and/or the enterprise risk level, so that the updating frequency of different data sources of different enterprises is flexibly set, the waste of updating resources caused by uniformly updating all data is avoided, the data updating efficiency is improved, and the technical problem of low data updating efficiency caused by inquiring or updating data according to the same set frequency in the prior art is solved.
Further, based on the first embodiment of the method for updating service data of the present invention, a second embodiment of the method for updating service data of the present invention is provided.
In this embodiment, the step S10 specifically includes:
acquiring a target data identifier of the target data source, and determining the data main degree of the target data source according to a preset data priority list and the target data identifier;
determining a data source acquisition type of a target data source according to a preset data source acquisition channel list and the target data identifier;
determining an enterprise to which the target data source belongs, and determining an enterprise risk level corresponding to the target data source according to a preset enterprise risk level list;
and determining the target updating frequency according to a preset updating frequency list, the data main degree, the data source acquisition type and/or the enterprise risk level.
The information acquisition mode of the data source corresponding to the enterprise comprises the following steps: free, pay by a strip, step or pack, etc., so the data acquisition cost increases gradually as the scale of the enterprise increases and the variety of data sources increases. In order to reduce the data acquisition cost, in the embodiment, the importance degree of each data source of the enterprise is recorded through the data priority list, such as unimportant, general or important. And then acquiring a channel list through the data sources, recording the acquisition type of each data source, and recording the risk level of each enterprise through the enterprise risk level list. And then determining the target updating frequency according to a preset updating frequency list, the data main degree, the data source acquisition type and/or the enterprise risk level to which the data source acquisition type belongs. In a specific embodiment, the corresponding update weight can be set according to the data dominance degree of the target source, the data source acquisition type and the risk level of the enterprise to which the data source acquisition type belongs. The higher the data main degree is, the higher the weight is, the lower the price of the data source acquisition type is, the higher the weight is, the higher the risk of the affiliated enterprise is, and the higher the weight is. Thus, a target update frequency for the target data source is determined based on the cumulative weight for the target data source.
Further, the step S10 specifically includes:
and when the data main degree is important data, the data source acquisition type is a free data source, and the enterprise risk is high risk, determining the target update frequency as the highest update frequency.
And when the data main degree is non-important data, the data source acquisition type is a pay-per-item data source and the risk of the enterprise is normal, determining the target updating frequency as the lowest updating frequency.
In this embodiment, the update frequency of the client information is set in units of data sources. The setting principle of the updating frequency is that the updating frequency of the free data source > the updating frequency of the packing price charging data source > the updating frequency of the charging data source by bar; the updating frequency of the data source with the important reference value for classifying the risk of the client > the updating frequency of the data source with the lower reference value for classifying the risk of the client. For example, the data source update frequency may be: 1 day/time, 1 month/time, 3 months/time, 6 months/time or 12 months/time. After the update frequency setting is completed, all data sources correspond to the respective set update frequencies (i.e., "suggested update frequencies"). Therefore, when the data main degree is important data, the data source acquisition type is a free data source, and the enterprise risk is high risk, the target updating frequency is determined to be the highest updating frequency. And when the data main degree is non-important data, the data source acquisition type is a pay-per-item data source and the risk of the enterprise is normal, determining the target updating frequency as the lowest updating frequency. Therefore, according to the main degree of the data sources and the individual risk condition of the client, the updating frequency of each data source of each client is flexibly set, and the effect of thousands of people is achieved.
The embodiment provides a method for updating business data, which determines a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs; and updating data of the target data source according to the target updating frequency corresponding to the target data source. Through the mode, the data updating frequency corresponding to different data sources is determined according to the data type of the data source, the data source acquisition type and/or the enterprise risk level, so that the updating frequency of different data sources of different enterprises is flexibly set, the waste of updating resources caused by uniformly updating all data is avoided, the data updating efficiency is improved, and the technical problem of low data updating efficiency caused by inquiring or updating data according to the same set frequency in the prior art is solved.
Further, based on the second embodiment of the method for updating service data of the present invention, a third embodiment of the method for updating service data of the present invention is provided.
In this embodiment, before the step S10, the method further includes:
acquiring enterprise related information of an enterprise to which the target data source belongs, and determining a risk level of the enterprise to which the target data source belongs according to a preset risk assessment rule and the enterprise related information;
and storing the enterprise identification of the enterprise to which the target data source belongs and the risk level association of the enterprise to which the target data source belongs to the enterprise risk level list.
In this embodiment, risk ranking is performed on enterprise customers according to existing risk assessment rules. For example, the risk grade of the client is divided into three categories of 'normal', 'medium risk' and 'high risk'. Wherein: normal means that the client's repayment ability is normal, medium risk means that the client's credit risk is increased, but normal repayment is still possible in the near future, and high risk means that the client's repayment ability is poor, and loan overdue may or may have occurred. In particular embodiments, the risk assessment rules may also be extended to more categories of assessments.
Further, after the step S20, the method further includes:
and when detecting that the risk level of the enterprise to which the target data source belongs is increased, temporarily updating the target data source.
If the risk level of the enterprise to which the target data source belongs is not increased, judging whether the current loan overdue of the enterprise to which the target data source belongs exists;
and if the current loan overdue occurs to the enterprise to which the target data source belongs, acquiring the current longest overdue days of the enterprise to which the target data source belongs, and temporarily updating the target data source when the current longest overdue days exceed a preset threshold value.
In this embodiment, the current maximum number of overdue days is counted for each loan client, and the current maximum number of overdue days is the maximum value (the number of overdue days of each loan under the client name). Besides correspondingly updating each data source according to the set updating frequency, the target data source also needs to be updated temporarily under specific conditions, namely, on the basis of completing conventional data source updating, the risk level information change of each enterprise is detected, and if the risk level information change meets any one of the following conditions, the temporary data updating is carried out on the client:
(1) in a specific embodiment, the previous update date of the data source is m days before (m is an integer greater than 1, and for different data sources, the value of m may be different), and the client does not enter a loan collection process;
(2) the method comprises the steps that a client currently has a loan balance, the current longest overdue days are equal to n days (n is an integer larger than 0, and n can be adjusted according to actual risk tolerance), the last updating date of a data source is before m days (namely, if the current loan overdue of an enterprise to which the target data source belongs occurs, the current longest overdue days of the enterprise to which the target data source belongs are obtained, and when the current longest overdue days exceed a preset threshold value, the target data source is temporarily updated), and the client does not enter a loan collection process;
(3) the client currently has a loan balance, and the client does not enter the loan hastening process, and the data source last update date is before the corresponding "recommended update frequency" for example: if the "recommended updating frequency" of the data source a is 1 month/time, but the last updating date of a certain client data source a is more than 1 month away from the current date. In further embodiments, other situations may be included in which a human deems that the data source needs to be updated.
(4) Messages that may cause a deterioration in the customer's risk level are known from internal or third party channels, and the customer's corresponding data source has a last update date before the corresponding "recommended update frequency," such as: if the 'recommended updating frequency' of the data source A is 1 month/time, but the last updating date of a certain client data source A is more than 1 month away from the current date;
in an embodiment, the condition may be other update data sources set by a post-loan manager having data update authority.
The embodiment provides a method for updating business data, which determines a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs; and updating data of the target data source according to the target updating frequency corresponding to the target data source. Through the mode, the data updating frequency corresponding to different data sources is determined according to the data type of the data source, the data source acquisition type and/or the enterprise risk level, so that the updating frequency of different data sources of different enterprises is flexibly set, the waste of updating resources caused by uniformly updating all data is avoided, the data updating efficiency is improved, and the technical problem of low data updating efficiency caused by inquiring or updating data according to the same set frequency in the prior art is solved.
The invention also provides a device for updating the service data, which comprises:
the updating frequency determining module is used for determining a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs;
and the target data updating module is used for updating data of the target data source according to the target updating frequency corresponding to the target data source.
Further, the update frequency determining module specifically includes:
the main degree determining unit is used for acquiring a target data identifier of the target data source and determining the main degree of the data of the target data source according to a preset data priority list and the target data identifier;
the acquisition type determining unit is used for determining the data source acquisition type of the target data source according to a preset data source acquisition channel list and the target data identifier;
the risk level determining unit is used for determining the enterprise to which the target data source belongs and determining the enterprise risk level corresponding to the target data source according to a preset enterprise risk level list;
and the updating frequency determining unit is used for determining the target updating frequency according to a preset updating frequency list, the data main degree, the data source acquisition type and/or the enterprise risk level.
Further, the update frequency determination module is specifically further configured to:
and when the data main degree is important data, the data source acquisition type is a free data source, and the enterprise risk is high risk, determining the target update frequency as the highest update frequency.
Further, the update frequency determination module is specifically further configured to:
and when the data main degree is non-important data, the data source acquisition type is a pay-per-item data source and the risk of the enterprise is normal, determining the target updating frequency as the lowest updating frequency.
Further, the service data updating apparatus further includes a risk level obtaining module, where the risk level obtaining module is configured to:
acquiring enterprise related information of an enterprise to which the target data source belongs, and determining a risk level of the enterprise to which the target data source belongs according to a preset risk assessment rule and the enterprise related information;
and storing the enterprise identification of the enterprise to which the target data source belongs and the risk level association of the enterprise to which the target data source belongs to the enterprise risk level list.
Further, the update apparatus of the service data further includes a first temporary update module, where the first temporary update module is configured to:
and when detecting that the risk level of the enterprise to which the target data source belongs is increased, temporarily updating the target data source.
Further, the update apparatus of the service data further includes a second temporary update module, where the second temporary update module is configured to:
if the risk level of the enterprise to which the target data source belongs is not increased, judging whether the current loan overdue of the enterprise to which the target data source belongs exists;
and if the current loan overdue occurs to the enterprise to which the target data source belongs, acquiring the current longest overdue days of the enterprise to which the target data source belongs, and temporarily updating the target data source when the current longest overdue days exceed a preset threshold value.
The method executed by each program module can refer to each embodiment of the service data updating method of the present invention, and is not described herein again.
The invention also provides a computer readable storage medium.
The computer-readable storage medium of the present invention stores thereon an update program of service data, which when executed by a processor implements the steps of the update method of service data as described above.
The method implemented when the update program of the service data running on the processor is executed may refer to each embodiment of the update method of the service data of the present invention, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A method for updating service data is characterized in that the method for updating service data comprises the following steps:
determining a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs;
and updating data of the target data source according to the target updating frequency corresponding to the target data source.
2. The method for updating business data according to claim 1, wherein the step of determining the target update frequency corresponding to the target data according to the target data identifier of the target data, the data source acquisition type, and/or the enterprise risk level to which the target data belongs specifically comprises:
acquiring a target data identifier of the target data source, and determining the data main degree of the target data source according to a preset data priority list and the target data identifier;
determining a data source acquisition type of a target data source according to a preset data source acquisition channel list and the target data identifier;
determining an enterprise to which the target data source belongs, and determining an enterprise risk level corresponding to the target data source according to a preset enterprise risk level list;
and determining the target updating frequency according to a preset updating frequency list, the data main degree, the data source acquisition type and/or the enterprise risk level.
3. The method for updating business data according to claim 2, wherein the step of determining the target update frequency according to a preset update frequency list, the data dominance, the data source acquisition type, and/or the enterprise risk level to which the target update frequency belongs specifically includes:
and when the data main degree is important data, the data source acquisition type is a free data source, and the enterprise risk is high risk, determining the target update frequency as the highest update frequency.
4. The method for updating business data according to claim 3, wherein the step of determining the target update frequency according to a preset update frequency list, the data dominance, the data source acquisition type, and/or the enterprise risk level to which the target update frequency belongs further comprises:
and when the data main degree is non-important data, the data source acquisition type is a pay-per-item data source and the risk of the enterprise is normal, determining the target updating frequency as the lowest updating frequency.
5. The method for updating business data according to any one of claims 1 to 4, wherein before the step of determining the target update frequency corresponding to the target data source according to the target data identifier of the target data source, the data source acquisition type and/or the enterprise risk level to which the target data source belongs, the method further comprises:
acquiring enterprise related information of an enterprise to which the target data source belongs, and determining a risk level of the enterprise to which the target data source belongs according to a preset risk assessment rule and the enterprise related information;
and storing the enterprise identification of the enterprise to which the target data source belongs and the risk level association of the enterprise to which the target data source belongs to the enterprise risk level list.
6. The method for updating service data according to claim 5, wherein after the step of updating the data of the target data source according to the target update frequency corresponding to the target data source, the method further comprises:
and when detecting that the risk level of the enterprise to which the target data source belongs is increased, temporarily updating the target data source.
7. The method for updating service data according to claim 6, wherein after the step of updating the data of the target data source according to the target update frequency corresponding to the target data source, the method further comprises:
if the risk level of the enterprise to which the target data source belongs is not increased, judging whether the current loan overdue of the enterprise to which the target data source belongs exists;
and if the current loan overdue occurs to the enterprise to which the target data source belongs, acquiring the current longest overdue days of the enterprise to which the target data source belongs, and temporarily updating the target data source when the current longest overdue days exceed a preset threshold value.
8. An apparatus for updating service data, the apparatus comprising:
the updating frequency determining module is used for determining a target updating frequency corresponding to a target data source according to a target data identifier of the target data source, a data source acquisition type and/or an enterprise risk level to which the data source acquisition type belongs;
and the target data updating module is used for updating data of the target data source according to the target updating frequency corresponding to the target data source.
9. An updating device of service data, characterized in that the updating device of service data comprises: memory, a processor and an update program of business data stored on the memory and executable on the processor, the update program of business data implementing the steps of the update method of business data according to any one of claims 1 to 7 when executed by the processor.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon an update program of service data, which when executed by a processor implements the steps of the update method of service data according to any one of claims 1 to 7.
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