CN117078388A - Financial user risk degree determining method, device, equipment and medium - Google Patents

Financial user risk degree determining method, device, equipment and medium Download PDF

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CN117078388A
CN117078388A CN202311034963.9A CN202311034963A CN117078388A CN 117078388 A CN117078388 A CN 117078388A CN 202311034963 A CN202311034963 A CN 202311034963A CN 117078388 A CN117078388 A CN 117078388A
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risk
financial
financial data
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data
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刘祖泽
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Ping An Bank Co Ltd
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Ping An Bank Co Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/06—Asset management; Financial planning or analysis
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The application provides a method, a device, equipment and a medium for determining risk degree of a financial user, wherein the method comprises the following steps: acquiring financial data of a financial user to be determined and financial data risk types of the financial data; inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type; and determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types. According to the risk assessment method and the risk assessment system, the financial data are input into the risk assessment model corresponding to the financial data risk types of the financial data, the risk assessment scores corresponding to the financial data risk types are obtained, the risk degree of the financial user to be determined is determined, and the accuracy and the efficiency of determining the risk degree of the financial user are improved.

Description

Financial user risk degree determining method, device, equipment and medium
Technical Field
The application relates to the technical field of financial management, in particular to a method, a device, equipment and a medium for determining risk degree of a financial user.
Background
As financial services management becomes more and more standard, risk assessment for financial users becomes more and more important as they transact financial services. Currently, risk level assessment is generally performed on a financial user by a professional of a financial transaction by means of working experience, and then it is determined whether the financial user can transact a corresponding financial transaction based on the assessed risk level of the financial user.
However, the risk degree evaluation method for the financial users by professional staff of the financial business through working experience has subjectivity, so that the risk degree evaluation result for the financial users has lower accuracy and low efficiency.
Disclosure of Invention
Accordingly, the present application is directed to a method, apparatus, device and medium for determining risk level of financial user, which can determine risk level of financial user, and improve accuracy and efficiency of determining risk level of financial user.
In a first aspect, an embodiment of the present application provides a method for determining a risk level of a financial user, where the method for determining a risk level of a financial user includes:
acquiring financial data of a financial user to be determined and financial data risk types of the financial data;
inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type;
the risk assessment model is obtained by training financial sample data corresponding to the financial data risk type and risk assessment scores corresponding to the financial sample data;
and determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types.
In one possible implementation, the financial data risk types include a financial risk type, a public opinion risk type, and an industry index risk type;
the financial data includes financial data of at least one financial data risk type of the financial risk type, public opinion risk type, and industry index risk type.
In one possible implementation manner, if the financial data includes a total positive public opinion number corresponding to a public opinion risk type, a total negative public opinion number, a total positive public opinion number corresponding to each public opinion source, and a total negative public opinion number corresponding to each public opinion source, the financial data is input into a risk assessment model corresponding to a financial data risk type of the financial data, to obtain a risk assessment score corresponding to the financial data risk type, including:
and inputting the total positive public opinion number, the total negative public opinion number, the total positive public opinion number and the total negative public opinion number into a public opinion risk assessment model corresponding to the public opinion risk type to obtain a risk assessment score corresponding to the public opinion risk type.
In one possible implementation manner, determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types includes:
determining a target risk assessment score of the financial user according to the risk assessment scores corresponding to all the financial data risk types;
judging whether the target risk assessment score is within a preset threshold range of the risk degree or not according to each risk degree; no overlap exists between preset threshold ranges of the risk degrees;
and if the target risk assessment score is within the preset threshold range of the risk degree, taking the risk degree as the risk degree of the financial user to be determined.
In one possible implementation, determining the target risk assessment score of the financial user according to the risk assessment scores corresponding to all the financial data risk types includes:
calculating the sum of risk assessment scores corresponding to all financial data risk types to obtain an initial risk assessment score;
if the financial user to be determined exists in the transaction blacklist, determining a target risk assessment score of the financial user to be determined according to the initial risk assessment score and the preset transaction risk score; the transaction blacklist contains financial users with abnormal transaction;
and if the financial user to be determined does not exist in the transaction blacklist, determining the initial risk assessment score as the target risk assessment score of the financial user to be determined.
In one possible embodiment, the method further comprises:
acquiring historical transaction data of a financial user to be determined; the historical transaction data comprises transaction users, transaction amounts and transaction time of the financial users to be determined;
dividing a time period between the earliest transaction time and the latest transaction time in the transaction time into a plurality of sub-time periods;
counting the transfer-out amount and the transfer-in amount between the financial user and the transaction user in each sub-time period;
and if the difference value of the transfer-out amount and the transfer-in amount in the same sub-time period is smaller than a first preset threshold value and the transfer-in amount or the transfer-out amount is larger than a second preset threshold value, adding the financial user to be determined into the transaction blacklist.
In one possible implementation, acquiring financial data of a financial user to be determined, and a financial data risk type of the financial data, includes:
and acquiring financial data of the financial user to be determined and financial data risk types of the financial data from the iceberg database.
In a second aspect, an embodiment of the present application further provides a risk level determining apparatus for a financial user, where the risk level determining apparatus for a financial user includes:
the acquisition module is used for acquiring financial data of a financial user to be determined and financial data risk types of the financial data;
the input module is used for inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type;
the risk assessment model is obtained by training financial sample data corresponding to the financial data risk type and risk assessment scores corresponding to the financial sample data;
and the determining module is used for determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types.
In one possible implementation manner, the input module is specifically configured to input the total positive public opinion number, the total negative public opinion number, the total positive public opinion number and the total negative public opinion number into a public opinion risk assessment model corresponding to a public opinion risk type, so as to obtain a risk assessment score corresponding to the public opinion risk type.
In one possible implementation manner, the determining module is specifically configured to determine a target risk assessment score of the financial user according to risk assessment scores corresponding to all risk types of the financial data; judging whether the target risk assessment score is within a preset threshold range of the risk degree or not according to each risk degree; no overlap exists between preset threshold ranges of the risk degrees; and if the target risk assessment score is within the preset threshold range of the risk degree, taking the risk degree as the risk degree of the financial user to be determined.
In a possible implementation manner, the determining module is further configured to:
calculating the sum of risk assessment scores corresponding to all financial data risk types to obtain an initial risk assessment score;
if the financial user to be determined exists in the transaction blacklist, determining a target risk assessment score of the financial user to be determined according to the initial risk assessment score and the preset transaction risk score; the transaction blacklist contains financial users with abnormal transaction;
and if the financial user to be determined does not exist in the transaction blacklist, determining the initial risk assessment score as the target risk assessment score of the financial user to be determined.
In one possible embodiment, the apparatus further comprises: the system comprises a dividing module, a counting module and an adding module;
the acquisition module is also used for acquiring historical transaction data of the financial user to be determined; the historical transaction data comprises transaction users, transaction amounts and transaction time of the financial users to be determined;
the dividing module is used for dividing the time period between the earliest transaction time and the latest transaction time in the transaction time into a plurality of sub-time periods;
the counting module is used for counting the transfer-out amount and the transfer-in amount between the financial user and the transaction user in each sub-time period;
and the adding module is used for adding the financial user to be determined to the transaction blacklist if the difference value of the transfer-out amount and the transfer-in amount in the same sub-time period is smaller than a first preset threshold value and the transfer-in amount or the transfer-out amount is larger than a second preset threshold value.
In one possible implementation, the acquiring module is specifically configured to acquire financial data of the financial user to be determined and a financial data risk type of the financial data from the iceberg database.
In a third aspect, an embodiment of the present application further provides an electronic device, including: a processor, a storage medium, and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium in communication over the bus when the electronic device is operating, the processor executing the machine-readable instructions to perform the steps of the method of determining the risk level of a financial user as in any one of the first aspects.
In a fourth aspect, embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the risk level determination method of any one of the financial users of the first aspect.
The embodiment of the application provides a method, a device, equipment and a medium for determining the risk degree of a financial user, wherein the method comprises the following steps: acquiring financial data of a financial user to be determined and financial data risk types of the financial data; inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type; the risk assessment model is obtained by training financial sample data corresponding to the financial data risk type and risk assessment scores corresponding to the financial sample data; and determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types. According to the risk assessment method and the risk assessment system, the financial data are input into the risk assessment model corresponding to the financial data risk types of the financial data, the risk assessment scores corresponding to the financial data risk types are obtained, the risk degree of the financial user to be determined is determined, and the accuracy and the efficiency of determining the risk degree of the financial user are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a risk level determination method for a financial user according to an embodiment of the present application;
FIG. 2 is a flow chart of another method for determining risk level of a financial user according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a risk level determining apparatus for a financial user according to an embodiment of the present application;
fig. 4 shows a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for the purpose of illustration and description only and are not intended to limit the scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. A flowchart, as used in this disclosure, illustrates operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be implemented out of order and that steps without logical context may be performed in reverse order or concurrently. Moreover, one or more other operations may be added to or removed from the flow diagrams by those skilled in the art under the direction of the present disclosure.
In addition, the described embodiments are only some, but not all, embodiments of the application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
In order to enable those skilled in the art to make and use the present disclosure, the following embodiments are presented in connection with a specific application scenario "financial management technical field". It will be apparent to those having ordinary skill in the art that the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the application. Although the application is described primarily in the context of "financial management technology," it should be understood that this is but one exemplary embodiment.
It should be noted that the term "comprising" will be used in embodiments of the application to indicate the presence of the features stated hereafter, but not to exclude the addition of other features.
The following describes a method for determining risk degree of a financial user according to an embodiment of the present application in detail.
Referring to fig. 1, a flow chart of a method for determining risk level of a financial user according to an embodiment of the present application is shown, where a specific implementation process of the method for determining risk level of a financial user is as follows:
s101, acquiring financial data of a financial user to be determined and financial data risk types of the financial data.
S102, inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type.
S103, determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types.
The embodiment of the application provides a risk degree determining method for a financial user, which comprises the following steps: acquiring financial data of a financial user to be determined and financial data risk types of the financial data; inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type; the risk assessment model is obtained by training financial sample data corresponding to the financial data risk type and risk assessment scores corresponding to the financial sample data; and determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types. According to the risk assessment method and the risk assessment system, the financial data are input into the risk assessment model corresponding to the financial data risk types of the financial data, the risk assessment scores corresponding to the financial data risk types are obtained, the risk degree of the financial user to be determined is determined, and the accuracy and the efficiency of determining the risk degree of the financial user are improved.
Exemplary steps of embodiments of the present application are described below:
s101, acquiring financial data of a financial user to be determined and financial data risk types of the financial data.
In an embodiment of the application, financial data of a financial user to be determined and financial data risk types of the financial data are acquired from an ADS layer of an iceberg database. The financial data risk types comprise a financial risk type, a public opinion risk type and an industry index risk type; the financial data includes financial data of at least one financial data risk type of the financial risk type, public opinion risk type, and industry index risk type.
Wherein the financial data of the financial risk type includes total assets, total liabilities, net assets, intangible assets, incomes, operating profits, net profits, and the like of the financial user; the financial data of the public opinion risk type comprises total positive public opinion numbers, total negative public opinion numbers, total positive public opinion numbers corresponding to each public opinion source respectively, total negative public opinion numbers corresponding to each public opinion source respectively and the like; industry index risk types include industry competition index, etc.
Here, the financial data may be data in a relational database, a non-relational database, a file, an excel table file, and stored in a specified directory, and the financial data is extracted from the specified directory by the Filechannel timing of the flume system. In consideration of reality, the non-relational database needs to be extracted again, and the file in the non-relational database is obtained by calling the packaged Java program before the extraction is performed, and is stored under a specified directory. The method can also collect log data and financial data of public opinion data types in real time by adopting a flink program based on kafka, wherein the log data comprises log-in logs and operation logs of database operators; the log is mainly used for acquiring log information by capturing personal identities, wherein the log information comprises log date, identity information and the like; the operation log is generated by setting a buried point in each interface method and triggering the operation log when clicking each time; financial data of the public opinion data type comes from web crawlers. All collected data is hierarchically stored into the iceberg database. In addition, the embodiment of the application can also judge whether the database operator has illegal operation or not through the log data, and if so, the method sends early warning to the management user.
Optionally, before acquiring the financial data of the financial user to be determined and the financial data risk type of the financial data, whether the financial user to be determined is penalized or not may also be determined by acquiring judicial data of the financial user to be determined, and if not, continuing to acquire the financial data of the financial user to be determined and the financial data risk type of the financial data.
S102, inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type.
In the embodiment of the application, the larger the risk assessment value is, the larger the risk of the financial user to be determined is. Each financial data risk type corresponds to a risk assessment model.
The risk assessment model is obtained through training of financial sample data corresponding to the financial data risk type and risk assessment scores corresponding to the financial sample data.
Specifically, if the financial data includes a total positive public opinion number, a total negative public opinion number, a total positive public opinion number corresponding to each public opinion source, and a total negative public opinion number corresponding to each public opinion source, the financial data is input into a risk assessment model corresponding to a financial data risk type of the financial data, to obtain a risk assessment score corresponding to the financial data risk type, including: and inputting the total positive public opinion number, the total negative public opinion number, the total positive public opinion number and the total negative public opinion number into a public opinion risk assessment model corresponding to the public opinion risk type to obtain a risk assessment score corresponding to the public opinion risk type.
Specifically, if the financial data includes total assets, total liabilities, net assets, intangible assets, business incomes, business profits and net profits corresponding to the financial risk types, the financial data is input into a risk assessment model corresponding to the financial data risk types of the financial data to obtain a risk assessment score corresponding to the financial data risk types, including: and inputting the total assets, the total liabilities, the net assets, the intangible assets, the business incomes, the business profits and the net profits into a financial risk assessment model corresponding to the financial risk types to obtain risk assessment scores corresponding to the financial risk types.
Specifically, if the financial data includes financial data corresponding to an industry index risk type, inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type, including: and inputting the financial data corresponding to the industry index risk type into an industry index risk assessment model corresponding to the industry index risk type to obtain a risk assessment score corresponding to the industry index risk type.
S103, determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types.
In the embodiment of the application, the risk degree comprises three risk degrees of no risk, low risk, medium risk and high risk; and if the risk degree of the financial user to be determined is no risk or low risk, determining the financial user to be determined as a high-quality financial user, and pushing financial products which are not processed by the high-quality financial user to the high-quality financial user.
Determining the risk level of the financial user to be determined by:
I. and determining target risk assessment scores of the financial users according to the risk assessment scores corresponding to all the financial data risk types.
Specifically, calculating the sum of risk assessment scores corresponding to all financial data risk types to obtain an initial risk assessment score; if the financial user to be determined exists in the transaction blacklist, determining the sum of the initial risk assessment score and the preset transaction risk score as a target risk assessment score of the financial user to be determined; the transaction blacklist contains financial users with abnormal transaction; and if the financial user to be determined does not exist in the transaction blacklist, determining the initial risk assessment score as the target risk assessment score of the financial user to be determined.
II. And judging whether the target risk assessment score is within a preset threshold range of the risk degree or not according to each risk degree. There is no overlap between the preset threshold ranges of the risk levels.
In the embodiment of the application, each risk degree corresponds to a preset threshold range.
And III, if the target risk assessment score is within a preset threshold range of the risk degree, taking the risk degree as the risk degree of the financial user to be determined.
Referring to fig. 2, a flowchart of another risk determining method for a financial user according to an embodiment of the present application is shown, and the following description describes exemplary steps of the embodiment of the present application:
s201, determining a target risk assessment score of the financial user according to the risk assessment scores corresponding to all financial data risk types.
Determining a target risk assessment score for a financial user by:
I. and calculating the sum of risk assessment scores corresponding to all financial data risk types to obtain an initial risk assessment score.
II. If the financial user to be determined exists in the transaction blacklist, determining a target risk assessment score of the financial user to be determined according to the initial risk assessment score and the preset transaction risk score; the transaction blacklist contains financial users with transaction anomalies.
Optionally, determining the target risk assessment score of the financial user to be determined according to the initial risk assessment score and the preset transaction risk score includes: and determining the sum of the initial risk assessment score and the preset transaction risk score as a target risk assessment score of the financial user to be determined.
Optionally, determining the target risk assessment score of the financial user to be determined according to the initial risk assessment score and the preset transaction risk score includes: determining the sum of the initial risk assessment score and the preset transaction risk score as an intermediate risk assessment score of the financial user to be determined; judging whether the financial user to be determined meets a preset risk reduction standard or not; if yes, determining the difference between the intermediate risk assessment score and the reduction score corresponding to the preset risk reduction standard with the determined result being met as a target risk assessment score.
The preset risk reduction standards comprise enterprise marks with high and new technologies of financial users, special and new enterprise marks and the like.
And III, if the financial user to be determined does not exist in the transaction blacklist, determining the initial risk assessment score as the target risk assessment score of the financial user to be determined.
Further, the establishment process of the transaction blacklist comprises the following steps: acquiring historical transaction data of a financial user to be determined; the historical transaction data comprises transaction users, transaction amounts and transaction time of the financial users to be determined; dividing a time period between the earliest transaction time and the latest transaction time in the transaction time into a plurality of sub-time periods; counting the transfer-out amount and the transfer-in amount between the financial user and the transaction user in each sub-time period; and if the difference value of the transfer-out amount and the transfer-in amount in the same sub-time period is smaller than a first preset threshold value and the transfer-in amount or the transfer-out amount is larger than a second preset threshold value, adding the financial user to be determined into the transaction blacklist.
Here, the time period between the earliest transaction time and the latest transaction time in the transaction time is divided into a plurality of sub-time periods according to a preset duration; the duration of each sub-time period is a preset duration. If the difference value of the transfer-out amount and the transfer-in amount in the same sub-time period is smaller than a first preset threshold value, the transfer-out amount and the transfer-in amount of the financial user to be determined in a short time are basically consistent, the transfer-in amount or the transfer-out amount is larger than a second preset threshold value, the account is excessively large, and the transaction risk of back money laundering of the financial user to be determined is indicated.
S202, judging whether the target risk assessment score is within a preset threshold range of the risk degree or not according to each risk degree.
Wherein, there is no overlap between the preset threshold ranges of each risk degree.
And S203, if the target risk assessment value is within a preset threshold range of the risk degree, taking the risk degree as the risk degree of the financial user to be determined.
The embodiment of the application provides another method for determining the risk degree of the financial user, which can determine the risk degree of the financial user to be determined.
Based on the same inventive concept, the embodiment of the application further provides a risk degree determining device of the financial user corresponding to the risk degree determining method of the financial user, and since the principle of solving the problem by the device in the embodiment of the application is similar to that of the risk degree determining method of the financial user in the embodiment of the application, the implementation of the device can refer to the implementation of the method, and the repetition is omitted.
Referring to fig. 3, a schematic diagram of a risk level determining apparatus for a financial user according to an embodiment of the present application is shown, where the risk level determining apparatus for a financial user includes:
an acquiring module 301, configured to acquire financial data of a financial user to be determined, and a financial data risk type of the financial data;
the input module 302 is configured to input financial data into a risk assessment model corresponding to a financial data risk type of the financial data, to obtain a risk assessment score corresponding to the financial data risk type;
the risk assessment model is obtained by training financial sample data corresponding to the financial data risk type and risk assessment scores corresponding to the financial sample data;
the determining module 303 is configured to determine a risk degree of the financial user to be determined according to risk assessment scores corresponding to all risk types of the financial data.
In one possible implementation manner, the input module 302 is specifically configured to input the total positive public opinion number, the total negative public opinion number, the total positive public opinion number and the negative public opinion number into a public opinion risk assessment model corresponding to a public opinion risk type, so as to obtain a risk assessment score corresponding to the public opinion risk type.
In one possible implementation manner, the determining module 303 is specifically configured to determine a target risk assessment score of the financial user according to the risk assessment scores corresponding to all risk types of the financial data; judging whether the target risk assessment score is within a preset threshold range of the risk degree or not according to each risk degree; no overlap exists between preset threshold ranges of the risk degrees; and if the target risk assessment score is within the preset threshold range of the risk degree, taking the risk degree as the risk degree of the financial user to be determined.
In a possible implementation manner, the determining module 303 is further configured to:
calculating the sum of risk assessment scores corresponding to all financial data risk types to obtain an initial risk assessment score;
if the financial user to be determined exists in the transaction blacklist, determining a target risk assessment score of the financial user to be determined according to the initial risk assessment score and the preset transaction risk score; the transaction blacklist contains financial users with abnormal transaction;
and if the financial user to be determined does not exist in the transaction blacklist, determining the initial risk assessment score as the target risk assessment score of the financial user to be determined.
In one possible embodiment, the apparatus further comprises: the dividing module 304, the counting module 305 and the adding module 306;
the acquiring module 301 is further configured to acquire historical transaction data of a financial user to be determined; the historical transaction data comprises transaction users, transaction amounts and transaction time of the financial users to be determined;
a dividing module 304, configured to divide a time period between an earliest transaction time and a latest transaction time in the transaction times into a plurality of sub-time periods;
the statistics module 305 is configured to count the amount of transfer and the amount of transfer between the financial user and the transaction user in each sub-time period;
and the adding module 306 is configured to add the financial user to be determined to the transaction blacklist if the difference between the transfer-out amount and the transfer-in amount in the same sub-period is smaller than the first preset threshold and the transfer-in amount or the transfer-out amount is larger than the second preset threshold.
In one possible implementation, the obtaining module 301 is specifically configured to obtain, from the iceberg database, financial data of the financial user to be determined, and a financial data risk type of the financial data.
The application provides a risk degree determining device for a financial user, which is used for determining the risk degree of the financial user to be determined by inputting financial data into a risk assessment model corresponding to the financial data risk types of the financial data and obtaining risk assessment scores corresponding to the financial data risk types, so that the accuracy and the efficiency of determining the risk degree of the financial user are improved.
As shown in fig. 4, an electronic device 400 provided in an embodiment of the present application includes: the system comprises a processor 401, a memory 402 and a bus, the memory 402 storing machine-readable instructions executable by the processor 401, the processor 401 and the memory 402 communicating over the bus when the electronic device is running, the processor 401 executing the machine-readable instructions to perform the steps of the risk level determination method of a financial user as described above.
Specifically, the above-mentioned memory 402 and the processor 401 can be general-purpose memories and processors, and are not particularly limited herein, and the above-mentioned risk level determination method of the financial user can be performed when the processor 401 runs a computer program stored in the memory 402.
Corresponding to the above method for determining risk level of financial users, the embodiment of the application also provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and the computer program executes the steps of the above method for determining risk level of financial users when being executed by a processor.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the method embodiments, and are not repeated in the present disclosure. In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, and the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, and for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, indirect coupling or communication connection of devices or modules, electrical, mechanical, or other form.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the information processing method according to the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily appreciate variations or alternatives within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims (10)

1. A risk level determination method for a financial user, the risk level determination method for a financial user comprising:
acquiring financial data of a financial user to be determined and a financial data risk type of the financial data for evaluating risk;
inputting the financial data into a risk assessment model corresponding to a financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type;
the risk assessment model is obtained by training financial sample data corresponding to financial data risk types and risk assessment scores corresponding to the financial sample data;
and determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types.
2. The method of claim 1, wherein the financial data risk types include a financial risk type, a public opinion risk type, and an industry index risk type;
the financial data includes financial data of at least one financial data risk type of the financial risk type, public opinion risk type, and industry index risk type.
3. The method for determining the risk degree of a financial user according to claim 2, wherein if the financial data includes a total positive public opinion number, a total negative public opinion number, a total positive public opinion number corresponding to each public opinion source, and a total negative public opinion number corresponding to each public opinion source, the inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data, obtaining a risk assessment score corresponding to the financial data risk type includes:
and inputting the total positive public opinion number, the total negative public opinion number, the total positive public opinion number and the negative public opinion number into a public opinion risk assessment model corresponding to the public opinion risk type to obtain a risk assessment score corresponding to the public opinion risk type.
4. The method for determining the risk level of a financial user according to claim 3, wherein determining the risk level of the financial user to be determined according to risk assessment values corresponding to all risk types of financial data comprises:
determining a target risk assessment score of the financial user according to the risk assessment scores corresponding to all financial data risk types;
judging whether the target risk assessment score is within a preset threshold range of the risk degree or not according to each risk degree; no overlap exists between preset threshold ranges of the risk degrees;
and if the target risk assessment value is within the preset threshold range of the risk degree, taking the risk degree as the risk degree of the financial user to be determined.
5. The method for determining a risk level of a financial user according to claim 4, wherein determining a target risk assessment score of the financial user according to risk assessment scores corresponding to all risk types of financial data comprises:
calculating the sum of risk assessment scores corresponding to all financial data risk types to obtain an initial risk assessment score;
if the financial user to be determined exists in the transaction blacklist, determining a target risk assessment score of the financial user to be determined according to the initial risk assessment score and a preset transaction risk score; the transaction blacklist comprises financial users with transaction anomalies;
and if the financial user to be determined does not exist in the transaction blacklist, determining the initial risk assessment score as the target risk assessment score of the financial user to be determined.
6. The method of claim 5, further comprising:
acquiring historical transaction data of the financial user to be determined; the historical transaction data comprises transaction users, transaction amounts and transaction time of the financial users to be determined;
dividing a time period between the earliest transaction time and the latest transaction time in the transaction time into a plurality of sub-time periods;
counting the transfer-out amount and the transfer-in amount between the financial user and the transaction user in each sub-time period;
and if the difference value between the transfer-out amount and the transfer-in amount in the same sub-time period is smaller than a first preset threshold value and the transfer-in amount or the transfer-out amount is larger than a second preset threshold value, adding the financial user to be determined into a transaction blacklist.
7. The method for determining risk level of a financial user according to claim 1, wherein the acquiring financial data of the financial user to be determined and a financial data risk type of the financial data includes:
and acquiring financial data of the financial user to be determined and financial data risk types of the financial data from the iceberg database.
8. A risk level determination apparatus for a financial user, the risk level determination apparatus comprising:
the acquisition module is used for acquiring financial data of a financial user to be determined and financial data risk types of the financial data;
the input module is used for inputting the financial data into a risk assessment model corresponding to the financial data risk type of the financial data to obtain a risk assessment score corresponding to the financial data risk type;
the risk assessment model is obtained by training financial sample data corresponding to financial data risk types and risk assessment scores corresponding to the financial sample data;
and the determining module is used for determining the risk degree of the financial user to be determined according to the risk assessment scores corresponding to all the financial data risk types.
9. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over the bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the financial user risk level determination method of any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the risk level determination method of a financial user as claimed in any one of claims 1 to 7.
CN202311034963.9A 2023-08-16 2023-08-16 Financial user risk degree determining method, device, equipment and medium Pending CN117078388A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311034963.9A CN117078388A (en) 2023-08-16 2023-08-16 Financial user risk degree determining method, device, equipment and medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311034963.9A CN117078388A (en) 2023-08-16 2023-08-16 Financial user risk degree determining method, device, equipment and medium

Publications (1)

Publication Number Publication Date
CN117078388A true CN117078388A (en) 2023-11-17

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Application Number Title Priority Date Filing Date
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Country Status (1)

Country Link
CN (1) CN117078388A (en)

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