CN112801800A - Behavior fund analysis system, behavior fund analysis method, computer equipment and storage medium - Google Patents
Behavior fund analysis system, behavior fund analysis method, computer equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention relates to the technical field of fund analysis, and particularly discloses a behavior fund analysis system, a behavior fund analysis method, computer equipment and a storage medium, wherein account data of a target account is obtained in real time, and the account data comprises account information and transaction data; obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data, and identifying current abnormal data existing in the account data of the target accounts; and inputting the current abnormal data into the risk evaluation model to obtain the risk probability corresponding to the account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value, so that the risk evaluation can be performed on the fund status of the target account of the target person, and when the target account and a large number of other accounts have transaction relations, the early warning can be sent to the abnormal transaction information to remind the target person of the risk state of the account.
Description
Technical Field
The embodiment of the invention relates to the technical field of fund analysis, in particular to a behavior fund analysis system, a behavior fund analysis method, computer equipment and a storage medium.
Background
When risk assessment is carried out on the fund condition of a target person of a specific group, an analyst usually firstly calls fund transaction data of the target person, and then analyzes the fund transaction data through SQL (structured query language) or Excel and other tools.
Disclosure of Invention
An object of an embodiment of the present invention is to provide a behavior fund analysis system, method, computer device, and storage medium, so as to solve the problems set forth in the foregoing background art.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a behavioural funds analysis system comprising a processing device and at least one transaction terminal, each transaction terminal being in communication with the processing device, wherein:
the transaction terminal is used for binding a target account and generating account data corresponding to the target account, wherein the account data comprises account information and transaction data; sending the account data to a processing device, receiving early warning information returned by the processing device and expressing the early warning information;
the processing device is used for receiving the account data from the transaction terminal and obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data; calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account; and calling a trained risk evaluation model, inputting the current abnormal data into the risk evaluation model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value.
As a further limitation of the technical solution of the embodiment of the present invention, the transaction terminal specifically includes:
the account binding module is used for binding the target account;
the data generation module is used for generating account data corresponding to the target account;
the sending module is used for sending the account data to the processing equipment;
and the early warning module is used for receiving the early warning information returned by the processing equipment and expressing the early warning information.
As a further limitation of the technical solution of the embodiment of the present invention, the processing apparatus specifically includes:
the data receiving module is used for receiving account data from the transaction terminal;
the vector acquisition module is used for obtaining transaction characteristic vectors of the target accounts arranged according to the time sequence in the target time period according to the account information and the transaction data;
the first calling module is used for calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model and identifying current abnormal data existing in the account data of the target account;
the second calling module is used for calling the trained risk assessment model and inputting the current abnormal data into the risk assessment model to obtain the risk probability corresponding to the account data of the target account;
and the judgment execution module is used for sending early warning information to the target account when the risk probability is higher than a threshold value.
As a further limitation of the technical solution of the embodiment of the present invention, the vector acquisition module specifically includes:
the characteristic extraction unit is used for extracting the characteristics of the transaction data to obtain transaction attributes;
the attribute processing unit is used for preprocessing the transaction attribute;
and the vector construction unit is used for constructing transaction characteristic vectors of the target accounts arranged according to the time sequence in the target time period according to the preprocessed transaction attributes.
As a further limitation of the technical solution of the embodiment of the present invention, the judgment execution module specifically includes:
the threshold determining unit is used for calculating the threshold of the item data corresponding to each current abnormal data according to the sample data of the normal record and the sample data of the abnormal record corresponding to the same current abnormal data;
a risk probability obtaining unit, configured to obtain the risk probability obtained by the second invoking module;
the judging unit is used for comparing the risk probability with the threshold value and judging whether the risk probability is larger than the threshold value or not;
and the execution unit is used for sending early warning information to the target account when the risk probability is higher than a threshold value.
The embodiment of the invention also provides a behavior fund analysis method, which comprises the following steps:
acquiring account data of a target account in real time, wherein the account data comprises account information and transaction data;
obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data;
calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account;
and calling a trained risk evaluation model, inputting the current abnormal data into the risk evaluation model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value.
As a further limitation of the technical solution of the embodiment of the present invention, the step of obtaining the transaction feature vectors of the target accounts arranged in time sequence in the target time period according to the account information and the transaction data specifically includes:
performing feature extraction on the transaction data to obtain transaction attributes;
preprocessing the transaction attribute;
and constructing a transaction characteristic vector of the target account arranged in time sequence in the target time period according to the preprocessed transaction attributes.
As a further limitation of the technical solution of the embodiment of the present invention, when the risk probability is higher than the threshold, the step of sending the warning information to the target account specifically includes:
calculating a threshold value of project data corresponding to each current abnormal data according to the sample data of the normal record and the sample data of the abnormal record corresponding to the same current abnormal data;
obtaining the risk probability obtained from the second invoking module;
comparing the risk probability with the threshold value, and judging whether the risk probability is greater than the threshold value;
and when the risk probability is higher than a threshold value, sending early warning information to the target account.
A computer apparatus, comprising:
one or more processing devices;
a memory;
one or more computer programs, wherein the one or more computer programs are stored in the memory and configured to be executed by the one or more processing devices, the one or more computer programs configured to: and executing the behavior fund analysis method.
A computer-readable storage medium having stored thereon a computer program which, when executed by a processing device, implements the behavioral fund analysis method.
Compared with the prior art, in the embodiment of the invention, the account data of the target account is obtained in real time, wherein the account data comprises account information and transaction data; obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data; calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account; calling a trained risk assessment model, inputting the current abnormal data into the risk assessment model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value, so that risk assessment can be performed on the fund status of the target account of a target person, and when transaction relations between the target account and a large number of other accounts are ensured, early warning can be sent to abnormal transaction information to remind the target person of the risk state of the account.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
FIG. 1 is an architecture diagram of a behavioral fund analysis system according to an embodiment of the present invention.
Fig. 2 is a block diagram of a behavior fund analysis system according to a second embodiment of the present invention.
FIG. 3 is a block diagram of a vector acquisition module in a three-row fund analysis system according to an embodiment of the present invention.
FIG. 4 is a block diagram of a determination execution module in a four-row fund analysis system according to an embodiment of the present invention.
FIG. 5 is a block diagram of a five-element fund analysis method according to an embodiment of the present invention.
FIG. 6 is a block diagram of a sub-process flow of a method for fund analysis in a six-action environment according to an embodiment of the present invention.
FIG. 7 is another sub-flow diagram of a method for fund analysis in accordance with the seventh aspect of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that, although the terms first, second, etc. may be used herein to describe various functional blocks in embodiments of the present invention, these functional blocks should not be limited by these terms. These terms are only used to distinguish one type of functional module from another. For example, a first retrieving module may also be referred to as a second retrieving module without necessarily requiring or implying any such actual relationship or order between such entities or operations without departing from the scope of embodiments of the present invention. Similarly, the second retrieval module may also be referred to as the first retrieval module. 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.
It can be understood that, in the prior art, when risk assessment is performed on the fund status of a target person of a specific group, an analyst often first retrieves fund transaction data of the target person, and then analyzes the fund transaction data through SQL or Excel and other tools, the analysis method mainly performs analysis manually, because the fund transaction relationship is complex, each account may have transaction relationships with a large number of other accounts, so that the data volume to be analyzed is very large, the large number of transaction data are processed and analyzed manually, and therefore, not only is the workload huge and the work efficiency low, but also manual operation errors are easy to occur in the analysis process.
In order to solve the above problem, in the embodiment of the present invention, account data of a target account is obtained in real time, where the account data includes account information and transaction data; obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data; calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account; calling a trained risk assessment model, inputting the current abnormal data into the risk assessment model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value, so that risk assessment can be performed on the fund status of the target account of a target person, and when transaction relations between the target account and a large number of other accounts are ensured, early warning can be sent to abnormal transaction information to remind the target person of the risk state of the account.
The first embodiment is as follows:
fig. 1 shows an architecture diagram of a behavior fund analysis system provided by an embodiment of the present invention, which may specifically include a transaction terminal 100, a network and a processing device 200. The network may be the medium used to provide a communication link between transaction terminal 100 and processing device 200.
The network may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may interact with the transaction terminal 100 to effect the transfer of information, etc. Various fund transaction applications may be installed on the transaction terminal 100.
The transaction terminal 100 may be hardware or software. When the transaction terminal 100 is hardware, it may be various electronic devices having functions of communication, voice broadcasting, recording, data processing, and data transmission and reception, including but not limited to a smart phone, a tablet computer, an e-book reader, an MP3 player, an MP4 player, a laptop portable computer, a desktop computer, and the like. When the transaction terminal 100 is software, it can be installed in the electronic devices listed above. It may be implemented as multiple pieces of software or software modules, or as a single piece of software or software module. And is not particularly limited herein.
The processing device 200 may be a background processing device that supports a funds transaction application on the transaction terminal 100. The processing device 200 may receive data such as transaction data information transmitted by the transaction terminal 100. Then, the processing device 200 may process the transaction data information, automatically determine whether the transaction data information contains abnormal data, and send the abnormal data information and the generated warning information to the transaction terminal 100 for display.
It should be understood that the number of transaction terminals 100, networks and processing devices 200 in fig. 1 is merely illustrative. There may be any number of transaction terminals 100, networks, and processing devices 200, as desired for implementation.
Preferably, as shown in fig. 1, in a preferred embodiment provided by the present invention, a behavior fund analysis system is provided, the system comprises a processing device 200 and at least one transaction terminal 100, each transaction terminal 100 can communicate with the processing device 200 through a network, wherein:
specifically, in the transaction terminal 100 provided in the embodiment of the present invention, the transaction terminal 100 is configured to bind a target account and generate account data corresponding to the target account, where the account data includes account information and transaction data; sending the account data to a processing device 200, receiving early warning information returned by the processing device 200 and expressing the early warning information;
it can be understood that, in the embodiment of the present invention, the transaction terminal 100 may include an application of a fund transaction type installed thereon, and the application has a function of binding a target account, and when a user uses the application on the transaction terminal for fund transaction for multiple times, the generated transaction flow data can be stored by the transaction terminal, so as to generate account data corresponding to the target account.
In addition, the transaction terminal 100 provided in the embodiment of the present invention has a communication module, and data transmission and reception are completed through the communication module, so that the account data generated by the transaction terminal 100 is transmitted to the processing device 200 through the data transmission unit of the communication module for further processing, and in addition, it can be understood that the embodiment of the present invention can also receive information data output after processing by the processing device 200 through the data reception unit of the communication module, and generally, the received information data includes abnormal account data and warning information matched with the abnormal account data.
Further, in a specific implementation, the pre-tightening information may be displayed at the transaction terminal through text information, and may be displayed through picture information or voice information.
With reference to fig. 1, in the transaction terminal 100 provided in the embodiment of the present invention, the processing device 200 is configured to receive account data from the transaction terminal 100, and obtain transaction feature vectors of the target accounts arranged in a time sequence in a target time period according to the account information and the transaction data; calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account; and calling a trained risk evaluation model, inputting the current abnormal data into the risk evaluation model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value.
Specifically, in the embodiment of the present invention, the processing device 200 also has a communication module, which can receive the account data sent from the transaction terminal 100, and it is understood that the account data at least includes account information of the user and transaction data associated with the account information;
further, in the embodiment of the present invention, the processing device 200 processes the received account data, specifically, first, feature extraction is performed on the transaction data to obtain a transaction attribute; then preprocessing the transaction attribute; further, transaction characteristic vectors of the target accounts arranged in time sequence in the target time period can be constructed according to the preprocessed transaction attributes; in the process of identifying abnormal data of account data, transaction characteristic vectors are processed in an abnormal data identification model preset in the processing equipment 200, and during specific processing, the transaction characteristic vectors are input into the abnormal data identification model, so that the abnormal data in the account data can be identified;
in addition, in a specific implementation, current abnormal data is input into a preset risk evaluation model in the processing device 200, the risk probability of the abnormal data is estimated through the risk evaluation model, when the estimated risk probability is higher than a threshold value, it can be determined that the risk of the abnormal data in the account data is high, the abnormal data needs to be returned to the transaction terminal 100, meanwhile, the processing device 200 also generates corresponding early warning information based on the risk probability, and then the early warning information is sent to the transaction terminal 100 through a communication module of the processing device 200.
Example two:
FIG. 2 is a block diagram showing the structure of a behavior fund analysis system according to an embodiment of the present invention.
Specifically, in a preferred embodiment provided by the present invention, the transaction terminal 100 specifically includes:
an account binding module 101, configured to bind a target account;
it can be understood that, in the embodiment of the present invention, the transaction terminal 100 may pass through an installed fund transaction type application, and the application has a function of binding a target account, and when a user uses the application on the transaction terminal for fund transaction for multiple times, the generated transaction flow data can be stored by the transaction terminal;
the transaction terminal 100 further includes:
a data generation module 102, configured to generate account data corresponding to the target account;
through the data generation module 102, processing the transaction flow data stored in the transaction terminal 100 and generating account data corresponding to the target account, it can be understood that the account data at least includes account information of the user and transaction data associated with the account information;
a sending module 103, configured to send the account data to a processing device;
the transaction terminal 100 provided by the embodiment of the present invention has a communication module, and data transmission and reception are completed through the communication module, so that the account data generated by the transaction terminal 100 is transmitted to the processing device 200 for further processing through the data transmission unit of the communication module, i.e. the transmission module 103;
in addition, the transaction terminal 100 provided in the embodiment of the present invention further includes:
the early warning module 104 is configured to receive early warning information returned by the processing device and express the early warning information; specifically, the embodiment of the present invention may further receive, by a data receiving unit of the communication module, information data output after being processed by the processing device 200, and generally, the received information data includes abnormal account data and warning information matched with the abnormal account data.
Further, in a specific implementation, the transaction terminal 100 has a display screen, and the display screen also has a function of inputting information, such as a touch display screen, and the expression of the pre-tightening information on the transaction terminal 100 may be displayed on the display screen of the transaction terminal through text information and picture information, and the voice information serving as the early warning information may be played through a sound provided by the transaction terminal 100.
Further, in a preferred embodiment provided by the present invention, the processing device 200 specifically includes:
a data receiving module 201, configured to receive account data from the transaction terminal;
specifically, in the embodiment of the present invention, the processing device 200 also has a communication module, which can receive the account data sent from the transaction terminal 100, and it is understood that the account data at least includes account information of the user and transaction data associated with the account information;
the vector acquisition module 202 is configured to obtain transaction feature vectors arranged in a time sequence of the target account within a target time period according to the account information and the transaction data;
further, in the embodiment of the present invention, the processing device 200 processes the received account data, specifically, first, feature extraction is performed on the transaction data to obtain a transaction attribute; then preprocessing the transaction attribute; further, transaction characteristic vectors of the target accounts arranged in time sequence in the target time period can be constructed according to the preprocessed transaction attributes;
the first invoking module 203 is configured to invoke a trained abnormal data recognition model, input the transaction feature vector into the abnormal data recognition model, and recognize current abnormal data existing in the account data of the target account;
in the process of identifying abnormal data of account data, transaction characteristic vectors are processed in an abnormal data identification model preset in the processing equipment 200, and during specific processing, the transaction characteristic vectors are input into the abnormal data identification model, so that the abnormal data in the account data can be identified;
the second invoking module 204 is configured to invoke the trained risk assessment model, and input the current abnormal data into the risk assessment model to obtain a risk probability corresponding to the account data of the target account;
in addition, in a specific implementation, current abnormal data is input into a risk assessment model preset in the processing device 200, and the risk probability of the abnormal data is estimated through the risk assessment model;
the judgment execution module 205 is configured to send the warning information to the target account when the risk probability is higher than a threshold, specifically, when the estimated risk probability is higher than the threshold, it may be judged that the risk of the abnormal data in the account data is high, and the abnormal data needs to be returned to the transaction terminal 100 at this time, meanwhile, the processing device 200 may also generate corresponding warning information based on the risk probability, and then send the warning information to the transaction terminal 100 through the communication module of the processing device 200.
Example three:
FIG. 3 is a block diagram of a vector acquisition module in a three-behavior fund analysis system according to an embodiment of the present invention.
Further, in a preferred embodiment provided by the present invention, the vector obtaining module 202 specifically includes:
the feature extraction unit 2021 is configured to perform feature extraction on the transaction data to obtain a transaction attribute;
the attribute processing unit 2022 is used for preprocessing the transaction attributes;
the vector construction unit 2023 is configured to construct transaction feature vectors arranged in a chronological order of the target accounts within the target time period according to the preprocessed transaction attributes.
Example four:
FIG. 4 is a block diagram showing the structure of a judgment execution module in a four-element fund analysis system according to an embodiment of the present invention.
Further, in this embodiment of the present invention, the determining and executing module 205 specifically includes:
a threshold determining unit 2051, configured to calculate, according to sample data of a normal record and sample data of an abnormal record corresponding to the same current abnormal data, a threshold of item data corresponding to each current abnormal data;
a risk probability obtaining unit 2052, configured to obtain the risk probability obtained by the second invoking module;
a determining unit 2053, configured to compare the risk probability with the threshold, and determine whether the risk probability is greater than the threshold;
and an executing unit 2054, configured to send early warning information to the target account when the risk probability is higher than a threshold.
Example five:
FIG. 5 shows a block flow diagram of a five-behavior fund analysis method according to an embodiment of the invention.
The embodiment of the invention also provides a behavior fund analysis method, wherein the method 300 comprises the following steps:
step S301: acquiring account data of a target account in real time, wherein the account data comprises account information and transaction data;
step S302: obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data;
step S303: calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account;
step S304: and calling a trained risk evaluation model, inputting the current abnormal data into the risk evaluation model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value.
Example six:
FIG. 6 shows a sub-flow block diagram of a method for fund analysis in a six-action embodiment of the present invention.
Further, in a preferred embodiment provided by the present invention, the step S302 of obtaining the transaction feature vectors arranged in chronological order by the target account within the target time period according to the account information and the transaction data specifically includes:
step S3021: performing feature extraction on the transaction data to obtain transaction attributes;
step S3022: preprocessing the transaction attribute;
step S3023: and constructing a transaction characteristic vector of the target account arranged in time sequence in the target time period according to the preprocessed transaction attributes.
Example seven:
FIG. 7 shows another sub-flow diagram of a method for fund analysis in accordance with the seventh aspect of the present invention.
Further, in a preferred embodiment provided by the present invention, the step S304 of sending the warning information to the target account when the risk probability is higher than a threshold specifically includes:
step S3041: calculating a threshold value of project data corresponding to each current abnormal data according to the sample data of the normal record and the sample data of the abnormal record corresponding to the same current abnormal data;
step S3042: obtaining the risk probability obtained from the second invoking module;
step S3043: comparing the risk probability with the threshold value, and judging whether the risk probability is greater than the threshold value;
step S3044: and when the risk probability is higher than a threshold value, sending early warning information to the target account.
In summary, in the embodiments of the present invention, account data of a target account is obtained in real time, where the account data includes account information and transaction data; obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data; calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account; calling a trained risk assessment model, inputting the current abnormal data into the risk assessment model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value, so that risk assessment can be performed on the fund status of the target account of a target person, and when transaction relations between the target account and a large number of other accounts are ensured, early warning can be sent to abnormal transaction information to remind the target person of the risk state of the account.
In addition, in another embodiment of the present invention, there is provided a computer apparatus including: one or more processing devices; a memory; one or more computer programs, wherein the one or more computer programs are stored in the memory and configured to be executed by the one or more processing devices, the one or more computer programs configured to: and executing the behavior fund analysis method.
Further, in a further preferred embodiment of the present invention, there is also provided a storage medium having a computer program stored thereon, wherein the computer program is executed by a processing device to implement the behavior fund analysis method.
Illustratively, a computer program can be partitioned into one or more modules, which are stored in memory and executed by a processor to implement the present invention. One or more of the modules may be a series of computer program instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the terminal device.
Those skilled in the art will appreciate that the above description of the terminal device is merely exemplary and not limiting, and that more or fewer components than those described above may be included, or certain components may be combined, or different components may be included, such as input output devices, network access devices, buses, etc.
The processor may be a central processing unit, but may also be other general purpose processors, digital signal processors, application specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or the like. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the terminal equipment and connects the various parts of the entire user terminal using various interfaces and lines.
The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the terminal device by operating or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory can mainly comprise a program storage area and a data storage area, wherein the program storage area can store an operating system and an application program required by at least one function; the storage data area may store data created according to the use of the berth-status display system, and the like. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card, a secure digital card, a flash memory card, at least one magnetic disk storage device, a flash memory device, or other volatile solid state storage device.
In summary, the behavior fund analysis system provided by the embodiment of the present invention can perform risk assessment on the fund status of the target account of the target person, and can issue an early warning to abnormal transaction information and remind the target person of the risk state of the target person's account when the target account and a large number of other accounts have transaction relationships.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A behavioural funds analysis system comprising a processing device and at least one transaction terminal, each transaction terminal being in communication with the processing device, wherein:
the transaction terminal is used for binding a target account and generating account data corresponding to the target account, wherein the account data comprises account information and transaction data; sending the account data to a processing device, receiving early warning information returned by the processing device and expressing the early warning information;
the processing device is used for receiving the account data from the transaction terminal and obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data; calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account; and calling a trained risk evaluation model, inputting the current abnormal data into the risk evaluation model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value.
2. The behavioral fund analysis system according to claim 1, wherein the transaction terminal specifically comprises:
the account binding module is used for binding the target account;
the data generation module is used for generating account data corresponding to the target account;
the sending module is used for sending the account data to the processing equipment;
and the early warning module is used for receiving the early warning information returned by the processing equipment and expressing the early warning information.
3. The behavioral fund analysis system according to claim 2, wherein the processing device specifically comprises:
the data receiving module is used for receiving account data from the transaction terminal;
the vector acquisition module is used for obtaining transaction characteristic vectors of the target accounts arranged according to the time sequence in the target time period according to the account information and the transaction data;
the first calling module is used for calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model and identifying current abnormal data existing in the account data of the target account;
the second calling module is used for calling the trained risk assessment model and inputting the current abnormal data into the risk assessment model to obtain the risk probability corresponding to the account data of the target account;
and the judgment execution module is used for sending early warning information to the target account when the risk probability is higher than a threshold value.
4. The behavioral fund analysis system according to claim 3, wherein the vector acquisition module specifically comprises:
the characteristic extraction unit is used for extracting the characteristics of the transaction data to obtain transaction attributes;
the attribute processing unit is used for preprocessing the transaction attribute;
and the vector construction unit is used for constructing transaction characteristic vectors of the target accounts arranged according to the time sequence in the target time period according to the preprocessed transaction attributes.
5. The behavior fund analysis system according to claim 3, wherein the judgment execution module specifically comprises:
the threshold determining unit is used for calculating the threshold of the item data corresponding to each current abnormal data according to the sample data of the normal record and the sample data of the abnormal record corresponding to the same current abnormal data;
a risk probability obtaining unit, configured to obtain the risk probability obtained by the second invoking module;
the judging unit is used for comparing the risk probability with the threshold value and judging whether the risk probability is larger than the threshold value or not;
and the execution unit is used for sending early warning information to the target account when the risk probability is higher than a threshold value.
6. A behavioral fund analysis method, comprising the steps of:
acquiring account data of a target account in real time, wherein the account data comprises account information and transaction data;
obtaining transaction characteristic vectors of the target accounts arranged in time sequence in a target time period according to the account information and the transaction data;
calling a trained abnormal data identification model, inputting the transaction characteristic vector into the abnormal data identification model, and identifying current abnormal data existing in the account data of the target account;
and calling a trained risk evaluation model, inputting the current abnormal data into the risk evaluation model to obtain a risk probability corresponding to account data of the target account, and sending early warning information to the target account when the risk probability is higher than a threshold value.
7. The behavioral fund analysis method according to claim 6, wherein the step of obtaining the chronological transaction feature vector of the target account within the target time period from the account information and the transaction data specifically comprises:
performing feature extraction on the transaction data to obtain transaction attributes;
preprocessing the transaction attribute;
and constructing a transaction characteristic vector of the target account arranged in time sequence in the target time period according to the preprocessed transaction attributes.
8. A behavioral fund analysis method according to claim 7, wherein the step of sending early warning information to the target account when the risk probability is higher than a threshold value specifically comprises:
calculating a threshold value of project data corresponding to each current abnormal data according to the sample data of the normal record and the sample data of the abnormal record corresponding to the same current abnormal data;
acquiring risk probability;
comparing the risk probability with the threshold value, and judging whether the risk probability is greater than the threshold value;
and when the risk probability is higher than a threshold value, sending early warning information to the target account.
9. A computer device, comprising:
one or more processing devices;
a memory;
one or more computer programs, wherein the one or more computer programs are stored in the memory and configured to be executed by the one or more processing devices, the one or more computer programs configured to: performing a behavioral fund analysis method according to any one of claims 6 to 8.
10. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when executed by a processing device, implements the behavioural fund analysis method according to any one of claims 6 to 8.
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