CN114399388A - Risk identification method, device, equipment and storage medium - Google Patents

Risk identification method, device, equipment and storage medium Download PDF

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CN114399388A
CN114399388A CN202210074210.XA CN202210074210A CN114399388A CN 114399388 A CN114399388 A CN 114399388A CN 202210074210 A CN202210074210 A CN 202210074210A CN 114399388 A CN114399388 A CN 114399388A
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transaction
preset
index
transaction data
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林凡
陈桂花
张傲
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China Construction Bank Corp
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China Construction Bank Corp
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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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    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis

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Abstract

The embodiment of the application discloses a risk identification method, a risk identification device, risk identification equipment and a storage medium. The method comprises the following steps: acquiring transaction data to be identified of a target user in the transaction and target transaction data of the target user within preset time; according to a preset index, counting the target transaction data within the preset time to obtain a transaction index; determining a risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score; determining decision information for the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information; and identifying the risk score and the decision information according to preset identification logic to obtain a risk identification result of the transaction.

Description

Risk identification method, device, equipment and storage medium
Technical Field
The present application belongs to the field of data processing technologies, and in particular, to a risk identification method, apparatus, device, and storage medium.
Background
With the development of the internet, some lawbreakers perform illegal activities, such as cross-border gambling, telecommunication network fraud and other illegal activities, by using financial institutions such as banks and third-party payment companies, which causes user fund loss, reputation damage or external supervision and punishment, and brings huge risk prevention and control challenges to the financial institutions.
In order to reduce risks, a financial institution generally uses a risk control system to identify transaction information, but for transactions with large client size, more contract information or high concurrent transactions, the existing risk control system cannot accurately identify risks existing in the transactions.
Disclosure of Invention
The embodiment of the application provides a risk identification method, a risk identification device, risk identification equipment and a storage medium, and transaction risks can be accurately identified.
In a first aspect, an embodiment of the present application provides a risk identification method, where the method includes:
acquiring transaction data to be identified of a target user in the transaction and target transaction data of the target user within preset time;
according to a preset index, counting target transaction data within a preset time to obtain a transaction index;
determining a risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score;
determining decision information for the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information;
and identifying the risk score and the decision information according to the preset identification logic to obtain a risk identification result of the transaction.
In a possible implementation manner, before obtaining the target transaction data within a preset time of the target user to which the transaction data to be identified belongs, the method further includes:
and receiving the preset time input by the user.
In one possible implementation, the transaction data to be identified includes a transaction type; before counting target transaction data within a preset time according to a preset index to obtain a transaction index, the method further comprises the following steps:
and determining a preset index corresponding to the transaction type according to the third corresponding relation between the transaction type and the preset index.
In a possible implementation manner, before determining the preset index corresponding to the transaction type according to the third corresponding relationship between the transaction type and the preset index, the method further includes:
and receiving a preset index input by the user and a third corresponding relation between the transaction type input by the user and the preset index.
In a possible implementation manner, before determining a risk score of the transaction according to a preset condition that the transaction index and the transaction data to be identified satisfy and a first corresponding relationship between the preset condition and the score, the method further includes:
and receiving a first corresponding relation between a preset condition input by a user and the score.
In a possible implementation manner, before determining the decision information for the current transaction according to a preset rule that the transaction index and the transaction data to be identified satisfy and a second corresponding relationship between the preset rule and the decision information, the method further includes:
and receiving a second corresponding relation between the preset rule input by the user and the decision information.
In one possible implementation, the transaction data to be identified and the target transaction data each include account information, and the account information includes at least one of account contract information or channel contract information.
In a second aspect, an embodiment of the present application provides a risk identification apparatus, including:
the acquisition module is used for acquiring the transaction data to be identified of the target user in the transaction and the target transaction data of the target user within the preset time;
the statistical module is used for counting target transaction data within preset time according to preset indexes to obtain transaction indexes;
the determining module is used for determining a risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score; the system is also used for determining decision information of the transaction according to a preset rule which is met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information;
and the identification module is used for identifying the risk score and the decision information according to the preset identification logic to obtain a risk identification result of the transaction.
In one possible implementation, the apparatus further includes:
and the receiving module is used for receiving the preset time input by the user.
In one possible implementation, the transaction data to be identified includes a transaction type;
and the determining module is further used for determining the preset index corresponding to the transaction type according to the third corresponding relation between the transaction type and the preset index.
In one possible implementation, the apparatus further includes:
and the receiving module is used for receiving the preset index input by the user and the third corresponding relation between the transaction type input by the user and the preset index.
In one possible implementation, the apparatus further includes:
the receiving module is used for receiving a first corresponding relation between a preset condition input by a user and the score.
In one possible implementation, the apparatus further includes:
and the receiving module is used for receiving a second corresponding relation between the preset rule input by the user and the decision information.
In one possible implementation, the transaction data and the target transaction data each include account information, and the account information includes at least one of account contract information or channel contract information.
In a third aspect, an embodiment of the present application provides an electronic device, including: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, performs the method as in the first aspect or any possible implementation of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon computer program instructions, which, when executed by a processor, implement a method as in the first aspect or any possible implementation manner of the first aspect.
In a fifth aspect, the present application provides a computer program product, and instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the method as in the first aspect or any possible implementation manner of the first aspect.
According to the risk identification method, the risk identification device, the risk identification equipment and the risk identification storage medium, when a target user initiates a transaction, transaction data to be identified of the target user in the transaction and target transaction data of the target user within preset time are obtained firstly; secondly, according to a preset index, counting target transaction data within a preset time to obtain a transaction index; thirdly, determining a risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score; thirdly, determining decision information for the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information; and thirdly, identifying the risk score and the decision information according to the preset identification logic to obtain a risk identification result of the transaction. The transaction data of the target user in the preset time are fully utilized, the data in the preset time are counted to obtain transaction indexes, whether the transaction has risks or not is identified according to the transaction indexes, and the transaction risks can be accurately identified.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a risk identification method according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a risk identification device according to an embodiment of the present application;
fig. 3 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by illustrating examples thereof.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
With the development of the internet, some lawbreakers perform illegal activities, such as cross-border gambling, telecommunication network fraud and other illegal activities, by using financial institutions such as banks and third-party payment companies, which causes user fund loss, reputation damage or external supervision and punishment, and brings huge risk prevention and control challenges to the financial institutions.
In order to reduce risks, a financial institution generally uses a risk control system to identify transaction information, but for transactions with large client size, more contract information or high concurrent transactions, the existing risk control system cannot accurately identify risks existing in the transactions.
In order to solve the above problems, embodiments of the present application provide a risk identification method, apparatus, device, and storage medium, where when a target user initiates a transaction, to-be-identified transaction data of the target user in the current transaction and target transaction data of the target user within a preset time are obtained first; secondly, according to a preset index, counting target transaction data within a preset time to obtain a transaction index; thirdly, determining a risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score; thirdly, determining decision information for the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information; and thirdly, identifying the risk score and the decision information according to the preset identification logic to obtain a risk identification result of the transaction. The transaction data of the target user in the preset time are fully utilized, the data in the preset time are counted to obtain transaction indexes, whether the transaction has risks or not is identified according to the transaction indexes, and the transaction risks can be accurately identified.
According to the technical scheme, the data acquisition, storage, use, processing and the like meet relevant regulations of national laws and regulations.
The execution main body of the embodiment of the application is a terminal which is provided with data storage, data transmission and processing and can display a human-computer interaction interface.
A risk identification method provided by the embodiment of the present application will be described in detail below with reference to fig. 1.
As shown in fig. 1, the method may include the steps of:
s110, acquiring transaction data to be identified of the target user in the transaction and target transaction data of the target user within preset time.
When a target user initiates a transaction, the terminal identifies the risk of the transaction. The terminal obtains the transaction data of the current transaction of the target user as the transaction data to be identified, and obtains the transaction data of each transaction of the target user in the preset time as the target transaction data.
In some embodiments, the terminal further obtains transaction data of the customers other than the target customer when performing transactions within a preset time, and takes the transaction data of the target customer and the customers other than the target customer when performing transactions within the preset time as the target transaction data.
The terminal obtains transaction data of a target user and clients except the target client during transaction within preset time, and the transaction data are used as target transaction data, so that risks of the transaction can be identified according to the dimensionality of the user, and accuracy of risk identification is improved.
And S120, counting target transaction data within a preset time according to a preset index to obtain a transaction index.
And the terminal counts target transaction data related to the preset index within preset time according to the preset index to obtain a transaction index.
In some embodiments, the terminal may include a plurality of preset indexes, and count target transaction data associated with each preset index within a preset time to obtain a plurality of transaction indexes.
In one example, the preset index is an average transaction amount of the target user in the past 30 days, and then the preset time is 30 days, the target transaction data related to the preset index is an amount value of each transaction of each account owned by the target user, and an average value of the amount values of each transaction of each account owned by the target user in the past 30 days is calculated, that is, the transaction index is obtained: the average transaction amount of the target user over the past 30 days is a.
In some embodiments, each preset index corresponds to a time window algorithm, a window period of the time window algorithm is equal to preset time, the time window algorithm takes target transaction data within the preset time as stream data, and statistics is performed on the target transaction data related to the preset index within each window period to obtain the transaction index.
In one example, the preset index is an average transaction amount of the target user in the last 30 days, then the time window of the time window algorithm corresponding to the preset index is 30 days, the target transaction data related to the preset index is the amount of each transaction of each account owned by the target user, the average value of the amount of each transaction of each account owned by the target user in the last 30 days is calculated by using the time window algorithm, and the obtained transaction index is that the average transaction amount of the target user in the last 30 days is equal to a.
In one example, the time window algorithm corresponding to the preset index is a data merging algorithm and/or a data incorporation algorithm, and the time window algorithm merges and calculates the target transaction data in the window period and/or does not merge and calculate the target transaction data in the window period to obtain the transaction index. For example, the preset index is the accumulated transaction amount of the target user within 24 hours, the target transaction data is the amount of each transaction within the previous 24 hours, the amount of each transaction within 24 hours is combined and calculated, and the transaction index is obtained, wherein the accumulated transaction amount of the target user within 24 hours is X. And if the preset index is the sum of each transaction of the target user in 24 hours, the target transaction data is the sum of each transaction in the previous 24 hours, the sum of each transaction in 24 hours is not calculated in a combined manner, and the transaction index is obtained, wherein the sum of each transaction of the target user in 24 hours is P and Q.
And S130, determining the risk score of the transaction according to the preset condition met by the transaction index and the transaction data to be identified and the first corresponding relation between the preset condition and the score.
The terminal judges a preset condition met by the transaction index and the transaction data to be identified, and then determines a risk score of the transaction according to the preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score.
In some embodiments, S120 obtains a plurality of transaction indexes, for each transaction index, the terminal determines a plurality of scores according to a preset condition that the transaction index and the transaction data to be identified satisfy, and a first corresponding relationship between the preset condition and the score, and calculates a risk score of the transaction according to the plurality of scores.
In one example, the transaction index is that an average transaction amount of the target user in the past 30 days is equal to a, a transaction amount of the target user in the transaction data to be identified in the current transaction is equal to b, the preset condition may include a preset condition (1) and a preset condition (2), and the preset condition (1): the difference between the average transaction amount of the target user in the past 30 days and the transaction amount of the transaction is less than or equal to c; preset condition (2): the difference between the average transaction amount of the target user in the past 30 days and the transaction amount of the transaction is larger than c. In the first correspondence relationship, the score corresponding to the preset condition (1) is 0, and the score corresponding to the preset condition (2) is 1. If the difference between a and b is less than or equal to c, the risk score is 0; if the difference between a and b is greater than c, the risk score is 1.
And S140, determining decision information for the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information.
The terminal judges a preset rule which is met by the transaction index and the transaction data to be identified, and then determines decision information for the transaction according to the preset rule which is met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information.
The decision information includes information indicating that the present transaction is allowed or not allowed.
In one example, the transaction index includes a maximum transaction amount allowed for the target user as a, a transaction amount of the target user in the transaction to be identified in the current transaction is equal to B, the preset rule may include a preset rule (1) and a preset rule (2), where the preset rule (1): the transaction amount of the target user is less than or equal to the maximum transaction amount; preset rule (2): the transaction amount of the target user is greater than the maximum transaction amount. The decision information 'yes' corresponding to the preset rule (1) in the second corresponding relation indicates that the transaction is allowed to be carried out, and the decision information 'no' corresponding to the preset rule (2) indicates that the transaction is not allowed to be carried out. If B is less than or equal to A, the decision information is 'Yes'; if B is greater than A, the decision information is NO.
In some embodiments, S120 obtains a plurality of transaction indexes, and for each transaction index, the terminal determines the decision information of the transaction according to a preset rule that the transaction index and the transaction data to be identified satisfy, and a second corresponding relationship between the preset rule and the decision information.
In one example, the decision information includes "no" or "yes", S120 obtains a plurality of transaction indexes, for each transaction index, the terminal determines the decision information corresponding to each transaction index according to a preset rule that the transaction index and the transaction data to be identified satisfy, and a second corresponding relationship between the preset rule and the decision information, and when at least one decision information is "no", it indicates that there is a risk in the transaction, and then the decision information of the transaction is "no"; when each piece of decision information is 'yes', the fact that the transaction has no risk is shown, and then the decision information of the transaction is 'yes'.
And S150, identifying the risk score and the decision information according to the preset identification logic to obtain a risk identification result of the transaction.
And the terminal identifies the risk score and the decision information according to the preset identification logic for identifying the risk to obtain a risk identification result of the transaction.
In some embodiments, the preset identification logic includes whether the risk score is higher than the preset score and whether the decision information includes "no", when the risk score is higher than the preset score or the decision information includes "no", it indicates that the transaction has a risk, and the risk identification result includes a result indicating that the transaction is not allowed to be performed; and when the risk score is lower than the preset score and the decision information comprises 'yes', the transaction is free from risk, and the risk identification result comprises a result indicating that the transaction is allowed to be carried out.
In some embodiments, when the risk identification result includes a result indicating that the transaction is not allowed to be performed, the risk identification result may further include warning information indicating a reason why the transaction is not allowed to be performed.
And when the risk score is higher than a preset score and/or the decision information comprises information which does not allow the transaction, the terminal generates early warning information according to a preset condition corresponding to the score and/or a preset rule corresponding to the information which does not allow the transaction.
In one example, the risk score is lower than a preset score, the decision information includes information that the transaction is not allowed to be performed, and a preset rule corresponding to the information that the transaction is not allowed to be performed is as follows: the transaction amount of the target user is larger than the maximum transaction amount, and the terminal: "the transaction amount of the target user is larger than the maximum transaction amount", determining the early warning information: "transaction amount is greater than maximum transaction amount".
When the risk identification result comprises a result indicating that the transaction is not allowed to be carried out, the risk identification result also comprises early warning information, so that a worker or a target user can know the reason why the transaction is not allowed to be carried out, and the worker or the target user can adopt corresponding measures according to the reason.
According to the method provided by the embodiment of the application, when a target user initiates a transaction, transaction data to be identified of the target user in the transaction and target transaction data of the target user within preset time are obtained firstly; secondly, according to a preset index, counting target transaction data within a preset time to obtain a transaction index; thirdly, determining a risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score; thirdly, determining decision information for the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information; and thirdly, identifying the risk score and the decision information according to the preset identification logic to obtain a risk identification result of the transaction. The transaction data of the target user in the preset time are fully utilized, the data in the preset time are counted to obtain transaction indexes, whether the transaction has risks or not is identified according to the transaction indexes, and the transaction risks can be accurately identified.
In some embodiments, after the risk score and the decision information are identified according to the preset identification logic to obtain the risk identification result of the transaction, that is, after S150, the method may further include:
and carrying out corresponding processing on the transaction according to the risk identification result.
When the risk identification result comprises a result indicating that the transaction is allowed to be carried out, the terminal allows the transaction to be carried out; and when the risk identification result comprises a result indicating that the transaction is not allowed, the terminal intercepts the transaction.
In some embodiments, when the risk identification result includes a result indicating that the transaction is not allowed to be performed, the risk identification result may further include warning information indicating a reason why the transaction is not allowed to be performed. And the terminal intercepts the transaction and displays early warning information to a target user.
And when the risk identification result comprises a result indicating that the transaction is not allowed, the terminal intercepts the transaction and displays early warning information to the target user. The property safety of the target user is protected, and meanwhile, the user can conveniently know the risk of the transaction.
According to the method provided by the embodiment of the application, the transaction is allowed to be carried out or intercepted according to the risk identification result, the transaction with the risk is avoided, and the property safety of the target client is protected.
In some embodiments, before obtaining the target transaction data within the preset time of the target user to which the transaction data to be identified belongs, i.e. before S110, the method may further include:
and receiving the preset time input by the user.
The user can enable staff, the user can set the preset time of the target transaction data related to each preset index according to the characteristics of the preset index and/or the precision requirement of each preset index, and the terminal receives the preset time of each target transaction data input by the user.
In one example, the preset index is an average transaction amount of the target user in the past 30 days, the target transaction data related to the preset index is an amount of each transaction of the target user in the past 30 days, the preset time is 30 days, and the terminal receives the preset time of the preset index input by the user: for 30 days.
In one example, the preset index is the accumulated transaction amount of the target user in the past 24 hours, the target transaction data related to the preset index is the amount of each transaction of the target user in the past 24 hours, the preset time is 24 hours, and the terminal receives the preset time of the preset index input by the user: for 24 hours.
In some embodiments, each preset index corresponds to a time window algorithm, a window period of the time window algorithm is equal to a preset time, and the terminal receives a user input of the window period of the time window algorithm corresponding to each preset index.
According to the method provided by the embodiment of the application, the user can set the preset time according to the characteristics of each preset index or the precision requirement of each preset index so as to improve the accuracy of risk identification.
In some embodiments, the transaction data to be identified includes a transaction type; before counting target transaction data within a preset time according to a preset index to obtain a transaction index, that is, before S120, the method may further include:
and determining a preset index corresponding to the transaction type according to the third corresponding relation between the transaction type and the preset index.
When risk identification is carried out on each transaction type, the adopted preset indexes are not completely the same, and the terminal determines the preset index corresponding to the transaction type in the transaction data to be identified according to the third corresponding relation between the transaction type and the preset indexes.
According to the method provided by the embodiment of the application, the preset index corresponding to the transaction type is determined according to the transaction type in the transaction data to be identified and the third corresponding relation between the transaction type and the preset index, and the accuracy of risk identification is improved.
In some embodiments, before determining the preset index corresponding to the transaction type according to the third corresponding relationship between the transaction type and the preset index, the method may further include:
and receiving a preset index input by the user and a third corresponding relation between the transaction type input by the user and the preset index.
The user can comprise a staff, the staff sets the transaction type and the preset index, sets a third corresponding relation between the transaction type and the preset index, inputs the preset index and the third corresponding relation between the transaction type and the preset index into the terminal, and the terminal receives the preset index input by the user and the third corresponding relation between the transaction type and the preset index input by the user.
According to the method provided by the embodiment of the application, the terminal receives the preset index input by the user and the third corresponding relation between the transaction type input by the user and the preset index, when the terminal carries out risk identification on the transaction, the used preset index can be determined according to the transaction type of the transaction, and the accuracy of risk identification is improved.
In some embodiments, before determining the risk score of the transaction according to the preset condition that the transaction index and the transaction data to be identified satisfy, and the first corresponding relationship between the preset condition and the score, that is, before S130, the method may further include:
and receiving a first corresponding relation between a preset condition input by a user and the score.
The user can comprise a worker, the worker inputs the preset conditions and the first corresponding relation between the preset conditions and the scores into the terminal, and the terminal receives the preset conditions input by the user and the first corresponding relation between the preset conditions and the scores.
According to the method provided by the embodiment of the application, the terminal receives the preset condition input by the user and the first corresponding relation between the preset condition and the score, when the terminal carries out risk identification on the transaction, the score can be determined according to the preset condition and the first corresponding relation, and a basis is provided for determining the risk score of the transaction.
In some embodiments, the transaction data to be identified includes a transaction type, and before determining a risk score of the transaction according to a preset condition that the transaction index and the transaction data to be identified satisfy and a first corresponding relationship between the preset condition and the score, that is, before S130, the method may further include:
and determining the preset condition corresponding to the transaction type according to the fourth corresponding relation between the transaction type and the preset condition.
When risk identification is carried out on each transaction type, the adopted preset conditions are not completely the same, and the terminal determines the preset conditions corresponding to the transaction types in the transaction data to be identified according to the fourth corresponding relation between the transaction types and the preset conditions.
The method provided by the embodiment of the application determines the preset condition corresponding to the transaction type according to the transaction type in the transaction data to be identified and the fourth corresponding relation between the transaction type and the preset condition, and the preset condition corresponding to the transaction type is adopted, so that the accuracy of risk identification can be improved when the current transaction is subjected to risk identification.
In some embodiments, before determining the preset condition corresponding to the transaction type according to the fourth corresponding relationship between the transaction type and the preset condition, the method may further include:
and receiving a preset condition input by a user, and a fourth corresponding relation between the transaction type and the preset condition.
The user can comprise a staff, the staff inputs the preset conditions and the corresponding relation between the transaction type and the preset conditions into the terminal, and the terminal receives the preset conditions input by the user and the fourth corresponding relation between the transaction type input by the user and the preset conditions.
According to the method provided by the embodiment of the application, the terminal receives the preset condition input by the user and the fourth corresponding relation between the transaction type input by the user and the preset condition, when the terminal carries out risk identification on the secondary transaction, the used preset condition can be determined according to the transaction type of the secondary transaction and the fourth corresponding relation, and the accuracy of risk identification is improved.
In some embodiments, before determining the decision information for the current transaction according to the preset rule satisfied by the transaction index and the transaction data to be identified and the second corresponding relationship between the preset rule and the decision information, that is, before S140, the method may further include:
and receiving a second corresponding relation between the preset rule input by the user and the decision information.
The user can comprise a worker, the worker inputs the preset rule and the second corresponding relation between the preset rule and the decision information into the terminal, and the terminal receives the preset condition input by the user and the second corresponding relation between the preset rule and the decision information.
According to the method provided by the embodiment of the application, the terminal receives the preset rule input by the user and the second corresponding relation between the preset rule and the decision information, when the terminal identifies the risk of the transaction, the decision information can be determined according to the rule and the second corresponding relation, and a basis is provided for determining the decision information of the transaction.
In some embodiments, the transaction data to be identified includes a transaction type, and before determining the decision information for the current transaction according to the preset rule satisfied by the transaction index and the transaction data to be identified and the second corresponding relationship between the preset rule and the decision information, that is, before S140, the method may further include:
and determining the preset rule corresponding to the transaction type according to the fifth corresponding relation between the transaction type and the preset rule.
When risk identification is carried out on each transaction type, the adopted preset rules are not completely the same, and the terminal determines the preset rule corresponding to the transaction type in the transaction data to be identified according to the fifth corresponding relation between the transaction type and the preset rules.
The method provided by the embodiment of the application determines the preset rule corresponding to the transaction type according to the transaction type in the transaction data to be identified and the fifth corresponding relation between the transaction type and the preset rule, and the preset rule corresponding to the transaction type is adopted, so that the accuracy of risk identification can be improved when the current transaction is subjected to risk identification.
In some embodiments, before determining the preset rule corresponding to the transaction type according to the fifth correspondence between the transaction type and the preset rule, the method may further include:
and receiving a preset rule input by a user and a fifth corresponding relation between the transaction type and the preset rule.
The user can comprise a worker, the worker inputs the preset rule and the fifth corresponding relation between the transaction type and the preset rule into the terminal, and the terminal receives the preset rule input by the user and the fifth corresponding relation between the transaction type input by the user and the preset rule.
According to the method provided by the embodiment of the application, the terminal receives the preset rule input by the user and the corresponding relation between the transaction type input by the user and the preset rule, when the terminal identifies the risk of the secondary transaction, the used preset rule can be determined according to the transaction type of the secondary transaction and the fifth corresponding relation, and the accuracy of risk identification is improved.
In some embodiments, the transaction data and the target transaction data each include account information, the account information including at least one of account contract information or channel subscription information.
The target user may have a plurality of transaction accounts, the terminal determines user identity information of the target user according to the account information of the transaction account used in the transaction, and then searches account contract information of the target user according to the user identity information of the user, so that account information of other transaction accounts of the target user is obtained, and target transaction data of each transaction account in each transaction within preset time is obtained.
According to the method provided by the embodiment of the application, the terminal acquires the account contract information and the channel signing information, so that the transaction indexes can be counted according to dimensions of different products and different channels traded by a target user, and the accuracy of risk identification is improved.
In some embodiments, obtaining target transaction data within a preset time of a target user may include:
the method comprises the steps of firstly obtaining date end data and first transaction data in a first preset time.
The daily end data comprises account information and transaction data, the account information comprises at least one item of account contract information or channel signing information, and the transaction data comprises a transaction amount, transaction time, a transaction place and the like. The end-of-day data represents data of all transactions generated during the previous day, and the first transaction data during the first preset time may include data of transactions other than the previous day during the preset time.
Then, target transaction data is generated according to the day end data and the first transaction data.
And completing the data of each transaction according to the account information and the transaction data of the daily end data, and combining the data with the first transaction data to obtain target transaction data.
According to the method provided by the embodiment of the application, the daily data and the first transaction data are merged. Target transaction data are obtained, and data support is provided for identifying the risk of the transaction.
The embodiment of the present application further provides a risk identification apparatus, as shown in fig. 2, the apparatus 200 may include an obtaining module 210, a counting module 220, a determining module 230, and an identifying module 240.
The obtaining module 210 is configured to obtain transaction data to be identified of the target user in the current transaction and target transaction data of the target user within a preset time.
The counting module 220 is configured to count target transaction data within a preset time according to a preset index to obtain a transaction index.
The determining module 230 is configured to determine a risk score of the transaction according to a preset condition that the transaction index and the transaction data to be identified meet, and a first corresponding relationship between the preset condition and the score; and the decision information of the current transaction is determined according to a preset rule which is met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information.
And the identification module 240 is used for identifying the risk score and the decision information according to the preset identification logic to obtain a risk identification result of the transaction.
According to the device provided by the embodiment of the application, when a target user initiates a transaction, transaction data to be identified of the target user in the transaction and target transaction data of the target user within preset time are obtained firstly; secondly, according to a preset index, counting target transaction data within a preset time to obtain a transaction index; thirdly, determining a risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score; thirdly, determining decision information for the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information; and thirdly, identifying the risk score and the decision information according to the preset identification logic to obtain a risk identification result of the transaction. The transaction data of the target user in the preset time are fully utilized, the data in the preset time are counted to obtain transaction indexes, whether the transaction has risks or not is identified according to the transaction indexes, and the transaction risks can be accurately identified.
In some embodiments, the apparatus 200 may further include a receiving module 250.
The receiving module 250 is configured to receive a preset time input by a user.
According to the device provided by the embodiment of the application, a user can set the preset time according to the characteristics of each preset index or the precision requirement of each preset index so as to improve the accuracy of risk identification.
In some embodiments, the transaction data to be identified may include a transaction type.
The determining module 230 may further be configured to determine the preset index corresponding to the transaction type according to a third corresponding relationship between the transaction type and the preset index.
The device provided by the embodiment of the application determines the preset index corresponding to the transaction type according to the transaction type in the transaction data to be identified and the third corresponding relation between the transaction type and the preset index, so that the accuracy of risk identification is improved.
In some embodiments, the apparatus 200 may further include a receiving module 250.
The receiving module 250 is configured to receive a preset index input by the user, and a third corresponding relationship between the transaction type input by the user and the preset index.
The device provided by the embodiment of the application receives the preset index input by the user and the third corresponding relation between the transaction type input by the user and the preset index, and can determine the used preset index according to the transaction type of the transaction when the risk of the transaction is identified, so that the accuracy of risk identification is improved.
In some embodiments, the apparatus 200 may further include a receiving module 250.
The receiving module 250 is configured to receive a first corresponding relationship between a preset condition input by a user and a score.
The device provided by the embodiment of the application receives the preset condition input by the user and the first corresponding relation between the preset condition and the score, and when the risk identification is carried out on the transaction, the score can be determined according to the preset condition and the first corresponding relation, so that a basis is provided for determining the risk score of the transaction.
In some embodiments, the apparatus 200 may further include a receiving module 250.
The receiving module 250 is configured to receive a second corresponding relationship between the preset rule and the decision information, where the preset rule is input by the user.
The device provided by the embodiment of the application receives the preset rule input by the user and the second corresponding relation between the preset rule and the decision information, and when risk identification is carried out on the transaction, the decision information can be determined according to the rule and the second corresponding relation, so that basis is provided for determining the decision information of the transaction.
In some embodiments, the transaction data and the target transaction data each include account information, the account information including at least one of account contract information or channel subscription information.
The device provided by the embodiment of the application acquires the account contract information and the channel signing information, so that the transaction indexes can be counted according to the dimensions of different products and different channels traded by a target user, and the accuracy of risk identification is improved.
The risk identification device provided in the embodiment of the present application executes each step in the method shown in fig. 1, and can achieve the technical effect of improving accuracy of risk identification, which is not described in detail herein for brevity.
Fig. 3 shows a hardware structure diagram of an electronic device according to an embodiment of the present application.
The electronic device may comprise a processor 301 and a memory 302 in which computer program instructions are stored.
Specifically, the processor 301 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or may be configured to implement one or more Integrated circuits of the embodiments of the present Application.
Memory 302 may include mass storage for data or instructions. By way of example, and not limitation, memory 302 may include a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, tape, or Universal Serial Bus (USB) Drive or a combination of two or more of these. Memory 302 may include removable or non-removable (or fixed) media, where appropriate. The memory 302 may be internal or external to the integrated gateway disaster recovery device, where appropriate. In a particular embodiment, the memory 302 is a non-volatile solid-state memory. In a particular embodiment, the memory 302 includes Read Only Memory (ROM). Where appropriate, the ROM may be mask-programmed ROM, Programmable ROM (PROM), Erasable PROM (EPROM), Electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory or a combination of two or more of these.
Processor 301 implements any of the risk identification methods of the embodiments shown in fig. 1 by reading and executing computer program instructions stored in memory 302.
In one example, the electronic device may also include a communication interface 303 and a bus 310. As shown in fig. 3, the processor 301, the memory 302, and the communication interface 303 are connected via a bus 310 to complete communication therebetween.
The communication interface 303 is mainly used for implementing communication between modules, apparatuses, units and/or devices in the embodiment of the present application.
Bus 310 includes hardware, software, or both to couple the components of the electronic device to each other. By way of example, and not limitation, a bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hypertransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus or a combination of two or more of these. Bus 310 may include one or more buses, where appropriate. Although specific buses are described and shown in the embodiments of the application, any suitable buses or interconnects are contemplated by the application.
The electronic device may execute the risk identification method in the embodiment of the present application, thereby implementing the risk identification method described in conjunction with fig. 1.
In addition, in combination with the risk identification method in the foregoing embodiments, the embodiments of the present application may be implemented by providing a computer-readable storage medium. The computer readable storage medium having stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement any of the risk identification methods of the embodiments described above.
In combination with the risk identification method in the foregoing embodiments, the present application may provide a computer program product, and when executed by a processor of an electronic device, instructions in the computer program product cause the electronic device to perform any one of the risk identification methods in the foregoing embodiments.
It is to be understood that the present application is not limited to the particular arrangements and instrumentality described above and shown in the attached drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions or change the order between the steps after comprehending the spirit of the present application.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
As described above, only the specific embodiments of the present application are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered within the scope of the present application.

Claims (17)

1. A method for risk identification, the method comprising:
acquiring transaction data to be identified of a target user in the transaction and target transaction data of the target user within preset time;
according to a preset index, counting the target transaction data within the preset time to obtain a transaction index;
determining a risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score;
determining decision information for the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information;
and identifying the risk score and the decision information according to preset identification logic to obtain a risk identification result of the transaction.
2. The method according to claim 1, wherein before the obtaining target transaction data within a preset time of a target user to which the transaction data to be identified belongs, the method further comprises:
and receiving the preset time input by the user.
3. The method of claim 1, wherein the transaction data to be identified comprises a transaction type; before the counting the target transaction data within the preset time according to the preset index to obtain a transaction index, the method further includes:
and determining the preset index corresponding to the transaction type according to the third corresponding relation between the transaction type and the preset index.
4. The method according to claim 3, wherein before said determining said preset indicator corresponding to said transaction type according to a third correspondence of said transaction type to said preset indicator, said method further comprises:
receiving the preset index input by the user and the third corresponding relation between the transaction type input by the user and the preset index.
5. The method according to claim 1, wherein before determining the risk score of the transaction according to a preset condition that the transaction index and the transaction data to be identified satisfy and a first corresponding relationship between the preset condition and the score, the method further comprises:
receiving the first corresponding relation between the preset condition input by the user and the score.
6. The method according to claim 1, wherein before determining the decision information for the current transaction according to the preset rule satisfied by the transaction index and the transaction data to be identified and the second corresponding relationship between the preset rule and the decision information, the method further comprises:
and receiving the second corresponding relation between the preset rule and the decision information input by the user.
7. The method of any of claims 1-6, wherein the transaction data to be identified and the target transaction data each include account information, the account information including at least one of account contract information or channel contract information.
8. A risk identification device, the device comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring transaction data to be identified of a target user in the transaction and target transaction data of the target user within preset time;
the statistic module is used for counting the target transaction data in the preset time according to a preset index to obtain a transaction index;
the determining module is used for determining the risk score of the transaction according to a preset condition met by the transaction index and the transaction data to be identified and a first corresponding relation between the preset condition and the score; the system is also used for determining decision information of the transaction according to a preset rule met by the transaction index and the transaction data to be identified and a second corresponding relation between the preset rule and the decision information;
and the identification module is used for identifying the risk score and the decision information according to preset identification logic to obtain a risk identification result of the transaction.
9. The apparatus of claim 8, further comprising:
and the receiving module is used for receiving the preset time input by the user.
10. The apparatus of claim 8, wherein the transaction data to be identified comprises a transaction type;
the determining module is further configured to determine the preset index corresponding to the transaction type according to a third corresponding relationship between the transaction type and the preset index.
11. The apparatus of claim 10, further comprising:
the receiving module is used for receiving the preset index input by the user and the third corresponding relation between the transaction type and the preset index input by the user.
12. The apparatus of claim 8, further comprising:
and the receiving module is used for receiving the first corresponding relation between the preset condition and the score input by the user.
13. The apparatus of claim 8, further comprising:
and the receiving module is used for receiving the second corresponding relation between the preset rule and the decision information input by the user.
14. The apparatus of any of claims 8-13, wherein the transaction data and target transaction data each include account information, the account information including at least one of account contract information or channel contract information.
15. An electronic device, characterized in that the device comprises: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements a risk identification method as claimed in any of claims 1-7.
16. A computer-readable storage medium having computer program instructions stored thereon, which when executed by a processor implement the risk identification method of any one of claims 1-7.
17. A computer program product, wherein instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the risk identification method of any of claims 1-7.
CN202210074210.XA 2022-01-21 2022-01-21 Risk identification method, device, equipment and storage medium Pending CN114399388A (en)

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