CN112184238A - Anti-money laundering monitoring method and device for financial leasing industry, electronic equipment and medium - Google Patents
Anti-money laundering monitoring method and device for financial leasing industry, electronic equipment and medium Download PDFInfo
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Abstract
The embodiment of the invention discloses an anti-money laundering monitoring method, an anti-money laundering monitoring device, electronic equipment and a medium in the financial leasing industry. The method comprises the following steps: responding to an anti-money laundering monitoring instruction of a target client, and identifying identity information of the target client; determining the money laundering risk level of the target client according to the identity information, and determining whether the subsequent transaction of the target client meets the monitoring condition according to the money laundering risk level; and if the subsequent transaction of the target client meets the monitoring condition, intercepting the target subsequent transaction when the target subsequent transaction performed by the target client meets the intercepting condition. The scheme of the embodiment of the invention solves the problems that the anti-money laundering monitoring efficiency is lower and a large amount of human resources are wasted due to the fact that the information of the risk customers is checked manually and the transactions of the risk customers are monitored, and can realize automatic monitoring of the anti-money laundering behavior in the financial leasing industry.
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to an anti-money laundering monitoring method, an anti-money laundering monitoring device, electronic equipment and a medium in the financial leasing industry.
Background
With the rapid development of the financial leasing industry, how to monitor the anti-money laundering in the financial leasing industry is widely researched by the industry people; the anti-money laundering in the financial leasing industry refers to identifying possible money laundering activities by a financial leasing institution and intercepting the ongoing money laundering activities in real time so as to prevent criminal activities.
At present, the information of the risk customers is mainly checked manually, and the transactions of the risk customers are monitored, so that the anti-money laundering monitoring efficiency is low, and a large amount of human resources are wasted.
Disclosure of Invention
The embodiment of the invention provides an anti-money laundering monitoring method, an anti-money laundering monitoring device, electronic equipment and a medium in a financial leasing industry, and aims to realize anti-money laundering monitoring of the financial leasing industry.
In a first aspect, an embodiment of the present invention provides an anti-money laundering monitoring method in a financial leasing industry, including:
responding to an anti-money laundering monitoring instruction of a target client, and identifying identity information of the target client;
determining the money laundering risk level of the target customer according to the identity information, and determining whether the subsequent transaction of the target customer meets the monitoring condition according to the money laundering risk level;
and if the subsequent transaction of the target customer meets the monitoring condition, intercepting the target subsequent transaction when the target subsequent transaction performed by the target customer meets the intercepting condition.
In a second aspect, an embodiment of the present invention further provides an anti-money laundering monitoring apparatus in a financial leasing industry, including:
the identity information identification module is used for responding to an anti-money laundering monitoring instruction of a target client and identifying the identity information of the target client;
the money laundering risk grade determining module is used for determining the money laundering risk grade of the target customer according to the identity information and determining whether the subsequent transaction of the target customer meets the monitoring condition or not according to the money laundering risk grade;
and the target subsequent transaction intercepting module is used for intercepting the target subsequent transaction when the target subsequent transaction performed by the target client meets the intercepting condition if the subsequent transaction of the target client meets the monitoring condition.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, the one or more programs cause the one or more processors to implement the method for anti-money laundering monitoring in the financial leasing industry according to any embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a storage medium containing computer-executable instructions, where the computer-executable instructions, when executed by a computer processor, are configured to perform a method for monitoring anti-money laundering in a financial leasing industry according to any one of the embodiments of the present invention.
The embodiment of the invention responds to the anti-money laundering monitoring instruction of the target client to identify the identity information of the target client; determining the money laundering risk level of the target client according to the identity information, and determining whether the subsequent transaction of the target client meets the monitoring condition according to the money laundering risk level; if the subsequent transaction of the target customer meets the monitoring condition, the target subsequent transaction is intercepted when the target subsequent transaction performed by the target customer meets the intercepting condition, so that the problems that the efficiency of money laundering monitoring is low and a large amount of human resources are wasted due to the fact that the information of the risk customer is manually checked and the transaction of the risk customer is monitored are solved, and the money laundering behavior of the financial leasing industry can be automatically monitored.
Drawings
FIG. 1 is a flow chart of an anti-money laundering monitoring method in the financial leasing industry according to one embodiment of the invention;
FIG. 2 is a flow chart of an anti-money laundering monitoring method in the financial leasing industry according to a second embodiment of the invention;
FIG. 3 is a flow chart of an anti-money laundering monitoring method in the financial leasing industry according to a third embodiment of the invention;
FIG. 4 is a schematic structural diagram of an anti-money laundering monitoring device in the financial leasing industry according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device in a fifth embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described in further detail with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad invention. It should be further noted that, for convenience of description, only some structures, not all structures, relating to the embodiments of the present invention are shown in the drawings.
Example one
Fig. 1 is a flowchart of an anti-money laundering monitoring method in a financial rental industry in an embodiment of the present invention, where the embodiment is applicable to a situation in the financial rental industry, the method may be executed by an anti-money laundering monitoring apparatus in the financial rental industry, the apparatus may be implemented by software and/or hardware, and is integrated in an electronic device executing the method, and in the embodiment, the electronic device executing the method may be an intelligent terminal such as a computer, a tablet computer, and/or a mobile phone. Specifically, referring to fig. 1, the method specifically includes the following steps:
The target customer may be any customer of the financial leasing institution, the customer may be a new customer, or a stock customer (a customer who has performed a transaction and stored identity information), which is not limited in this embodiment.
In an optional implementation manner of this embodiment, when an anti-money laundering monitoring instruction for a target client is received, identity information of the target client may be further identified; the identity information of the target client may include: basic information (for example, a customer name, a telephone call, an office location, and the like), historical transaction information (historical transaction time, transaction amount, transaction location, and the like), contract information (signing time, contract details, a person signing a contract, and the like), insurance information (amount of purchasing insurance, type of purchasing insurance, and the like), and the like, which are not limited in the present embodiment.
And step 120, determining the money laundering risk level of the target customer according to the identity information, and determining whether the subsequent transaction of the target customer meets the monitoring condition according to the money laundering risk level.
Wherein the money laundering risk level may be: low, medium high or high grade, etc.; the number of the stages may be one, two, three, or four, and the present embodiment is not limited thereto.
In an optional implementation manner of this embodiment, after the identification of the identity information of the target customer, the money laundering risk level of the target customer may be further determined according to the identity information, and whether the subsequent transaction of the target customer meets the monitoring condition, that is, whether the subsequent transaction of the target customer needs to be monitored is determined according to the money laundering risk level.
For example, if the money laundering risk level of the target client is determined to be high according to the identity information of the target client, the money laundering risk of the target client can be determined to be high, and then the subsequent transaction of the target client can be monitored in real time; the subsequent transaction of the target customer may be an online transfer transaction or an online transfer transaction, which is not limited in this embodiment.
And step 130, if the subsequent transaction of the target client meets the monitoring condition, intercepting the target subsequent transaction when the target subsequent transaction performed by the target client meets the intercepting condition.
The target subsequent transaction may be a large amount transaction or a suspicious transaction, which is not limited in this embodiment. The large amount transaction can be a transaction with a transaction amount larger than a certain amount, for example, larger than 5 million or 1 hundred million RMB; the suspicious transaction may be a location exception of the payee account, a high money laundering risk level, or the like, which is not limited in this embodiment.
In an optional implementation manner of this embodiment, if it is determined that the subsequent transaction of the target customer satisfies the monitoring condition, that is, in the process of monitoring the subsequent transaction of the target customer in real time, when the target subsequent transaction performed by the target customer is a large-volume transaction or a suspicious transaction, the target subsequent transaction is intercepted.
According to the scheme of the embodiment, the identity information of the target client is identified by responding to the anti-money laundering monitoring instruction of the target client; determining the money laundering risk level of the target client according to the identity information, and determining whether the subsequent transaction of the target client meets the monitoring condition according to the money laundering risk level; if the subsequent transaction of the target customer meets the monitoring condition, the target subsequent transaction is intercepted when the target subsequent transaction performed by the target customer meets the intercepting condition, so that the problems that the efficiency of money laundering monitoring is low and a large amount of human resources are wasted due to the fact that the information of the risk customer is manually checked and the transaction of the risk customer is monitored are solved, and the money laundering behavior of the financial leasing industry can be automatically monitored.
Example two
Fig. 2 is a flowchart of an anti-money laundering monitoring method in the financial leasing industry in the second embodiment of the present invention, which is a further refinement of the above technical solutions, and the technical solutions in this embodiment may be combined with various alternatives in one or more of the above embodiments. As shown in fig. 2, the anti-money laundering monitoring method of the financial leasing industry may include the steps of:
and step 210, determining the identity information integrity condition.
In an optional implementation manner of this embodiment, before the identification of the identity information of the target client, an identity information integrity condition of the target client may also be determined to determine whether the identity information of the target client needs to be supplemented.
In an optional implementation manner of this embodiment, determining that the identity information satisfies the integrity condition may include: and if the total quantity of the identity information is matched with the quantity of the set standard information, determining that the identity information meets the integrity condition.
For example, if the number of the set standard information is 20 and the total number of the identity information of the target client is 21, it may be determined that the identity information of the target client meets the integrity condition; if the number of the set standard information is 20 and the total number of the identity information of the target client is 15, determining that the identity information of the target client does not meet the integrity condition; it is understood that, in this embodiment, if the total number of the identity information is equal to or slightly different from the number of the set standard information, it may be determined that the identity information of the target client satisfies the integrity condition.
In an optional implementation manner of this embodiment, if it is determined that the identity information does not satisfy the integrity condition, a supplementary instruction of the identity information may be returned to the user side until the identity information satisfies the integrity condition.
In an optional implementation manner of this embodiment, the identification information identification may be divided into primary identification, persistent identification, and re-identification; the primary identification refers to identification, checking, registration, retention of basic information of client identity and the like in the due diligence stage for a newly added client; the continuous identification refers to the situation that for a stock customer, the basic information of the identity of the customer is continuously concerned during the service life; the re-identification means that, for the stock customer, when a specific condition occurs in the customer during the service lifetime (for example, a legal person is replaced or a stockholder is added, which is not limited in this embodiment), the basic identity information of the customer should be re-identified.
And 240, if the subsequent transaction of the target client meets the monitoring condition, intercepting the target subsequent transaction when the target subsequent transaction performed by the target client meets the intercepting condition.
In the scheme of this embodiment, before identifying the identity information of the target client, the method further includes: determining the integrity condition of the identity information; if the identity information is determined not to meet the integrity condition, a supplementary instruction of the identity information is returned to the user side until the identity information meets the integrity condition, so that the validity of the identity information of the client can be ensured, and a basis is provided for monitoring money laundering behaviors of the client.
EXAMPLE III
Fig. 3 is a flowchart of an anti-money laundering monitoring method in the financial leasing industry in a third embodiment of the present invention, which is a further refinement of the above technical solutions, and the technical solutions in this embodiment may be combined with various alternatives in one or more embodiments. As shown in fig. 3, the anti-money laundering monitoring method of the financial leasing industry may include the steps of:
The data types may include: basic information, historical transaction information, contract information, or insurance information; the money laundering risk level may include low, medium, or high.
The standard blacklist data table may be a list of individuals or businesses with all distrust behaviors provided by relevant departments. Optionally, after the standard blacklist data table is obtained, the standard blacklist data table may be screened to filter out unreasonable or wrong blacklist data in the standard blacklist data table.
In an optional implementation manner of this embodiment, after identifying the identity information of the target client, the standard blacklist data table may be further obtained, and the identity information of the target client is queried in the standard blacklist data table; and if the reference data matched with the identity information of the target client is inquired in the standard blacklist data table, determining the target client as the risk client.
Specifically, it may be determined whether reference data related to the identity information of the target client may be queried in the standard blacklist data table; for example, if reference data related to historical transaction information of the target user is queried in the standard blacklist data table, the target customer may be determined to be a risk customer.
Further, determining the data type of the reference data related to the identity information of the target client, and determining the money laundering risk level of the target client according to the data type; for example, if the data type of the reference data related to the identity information of the target customer is insurance information, it may be determined that the money laundering risk level of the target customer is low; if the data type of the reference data related to the identity information of the target customer is the historical transaction information as well as the basic information, it can be determined that the money laundering risk level of the target customer is high.
And step 330, if the money laundering risk level is greater than or equal to the first set threshold, determining that the subsequent transaction of the target customer meets the monitoring condition, and monitoring the subsequent transaction of the target customer in real time.
Wherein the first set threshold is a money laundering risk level, e.g., medium or medium high; it can be two-stage or three-stage, and is not limited in this embodiment.
In an alternative implementation of the embodiment, if the money laundering risk level of the target customer is determined to be high (the first set threshold is medium), then real-time monitoring of subsequent transactions of the target customer may be started.
In another optional implementation of this embodiment, the target customer is marked as a stable customer if subsequent transactions of the target customer do not satisfy the monitoring condition. For example, if the money laundering risk level of the target customer is less than the first set threshold, it may be determined that the target customer's subsequent transactions do not satisfy the monitoring condition, and the target customer may be marked as a stable customer.
And step 340, intercepting the target subsequent transaction when the target subsequent transaction performed by the target client meets the interception condition.
In an optional implementation manner of this embodiment, when the target subsequent transaction performed by the target client meets the interception condition, intercepting the target subsequent transaction may include: and intercepting the target subsequent transaction when the transaction amount of the target subsequent transaction is larger than a second set threshold value so as to interrupt the target subsequent transaction. The second set threshold may be any amount of money, for example, 500 ten thousand or 5000 ten thousand, and is not limited in this embodiment.
In another optional implementation manner of this embodiment, when the target subsequent transaction performed by the target customer meets the interception condition, intercepting the target subsequent transaction may further include: and intercepting the target subsequent transaction when the location of the payee of the target subsequent transaction is abnormal so as to interrupt the target subsequent transaction. For example, if all payee accounts in all historical transaction records of the target customer are domestic users, when the payee account of the target subsequent transaction is monitored to be in a different place, it can be determined that the payee account of the target subsequent transaction is abnormal, the ongoing target subsequent transaction can be intercepted, and the transaction is terminated.
According to the scheme of the embodiment, the identity information is inquired in the standard blacklist data table by acquiring the standard blacklist data table; if the reference data matched with the identity information is inquired in the standard blacklist data table, determining the target client as a risk client; determining the data type of the reference data, and determining the money laundering risk level of the target client according to the data type; and monitoring the subsequent transaction of the target customer according to the money laundering risk level of the target customer, and providing a basis for automatically monitoring the money laundering behavior of the financial leasing industry.
In order to make those skilled in the art better understand the method for monitoring anti-money laundering in the financial leasing industry of the present embodiment, a specific example is used for description, and the specific process includes:
1. and (5) identifying the identity of the client.
The customer identification comprises primary identification, continuous identification and re-identification, and the system can accurately identify new customers and stock customers. The primary identification means for identifying, checking, registering and keeping basic customer identity information of a new customer in the due diligence stage, the continuous identification means for a stock customer, the re-identification means for the stock customer continuously paying attention to the updating condition of the basic customer identity information in the business existence period, and the re-identification means for the basic identity information of the customer when a specific condition occurs in the customer in the business existence period
In this embodiment, relevant fields for customer identification and matched fields are set according to the supervision requirements of the financial leasing industry, and the fields are used for recording control, recording content and integrity statistics and executing specific system control according to business management requirements.
2. And monitoring and managing the anti-money laundering list.
In this embodiment, an interface for interfacing with an external blacklist data system is developed, information for identifying a client identity is pushed to the external interface, and hit warning information pushed by the external system is received, so that persistence of the warning information is realized.
Screening blacklist data: aiming at the alarm information acquired by the external interface, the system provides a function of screening and managing the alarm information, and system users can further screen the alarm information, reject unreasonable or low-risk alarm information and mark effective alarm information for subsequent use.
After the alarm information acquired by the external interface is manually marked by a person, a blacklist analysis and audit confirmation program is initiated for the client in the system, and finally, whether the client is marked as a blacklist client or not is judged.
3. And (5) carrying out risk classification management on money laundering grades of customers.
In the embodiment, the classification work of the money laundering risk grades of the clients is automatically initiated and developed, the development conditions of the work can be counted and inquired, and the risk grade classification of the clients is carried out according to the classification table of the money laundering risk grades of the clients.
From the customer dimension, the money laundering risk classification is: financial institution customers, non-financial institution customers; from the initiation point, the money laundering risk grades are classified as: primary classification and reclassification; the financial institution client refers to a financial institution which develops fund business and lease asset transfer business with a company; a non-financial institution client refers to a non-financial institution who develops rental business with a company; the primary classification refers to primary money laundering risk grade classification of a new client which is about to establish a business relationship with a company; reclassification refers to reclassifying money laundering risk levels for corporate inventory customers.
4. Large transactions and suspicious transaction monitoring.
Customer identity information (specific parameter name), relates to the anti-money laundering black ash suspicious list; for expired customer identity information (specific parameter name), updating is not completed within a regulation period; when repayment is carried out on a company, the actual repayment main body \ account number is more than the contract agreed transaction main body \ account number; the using place of the rental article relates to an anti-money laundering black gray suspicious list.
5. And (5) carrying out real-time monitoring and management on money laundering.
In this embodiment, after the relevant list data is obtained, the customer can be traced back and monitored in the service occurrence process through the set rule. For example, in a financial leasing core business system, in the whole process of leasing business such as customer establishment, project approval, contract making, project loan, risk classification and the like, the system can judge the situation that a customer hits a blacklist in real time, and once the customer with high risk exists, the system can intercept the project in progress in real time. The problems that manual screening efficiency is low, list information is not completely covered and updated timely, the rate of false alarm of suspected hit in manual screening is high, repeated screening and work are tedious, and support audit cannot be effectively stored in the list monitoring process are effectively solved.
The scheme of the embodiment provides a powerful supplement for the comprehensiveness of the core business system of the financial leasing, and has great significance for the financial leasing industry through the active practice of technological means on compliance business in the era of the powerful supervision and normalization of anti-money laundering. The real-time and accurate sanction blacklist monitoring is realized, the client identity is effectively identified, the large amount and suspicious transactions are timely and accurately reported, the method is very important for each financial institution in anti-money laundering compliance business, and the method is also beneficial to the steady development of the financial leasing industry.
Example four
Fig. 4 is a schematic structural diagram of an anti-money laundering monitoring apparatus in the financial rental industry according to a fourth embodiment of the present invention, which can execute the anti-money laundering monitoring method in the financial rental industry according to the foregoing embodiments. Referring to fig. 4, the apparatus includes: an identity information recognition module 410, a money laundering risk level determination module 420, and a target subsequent transaction interception module 430.
The identity information identification module 410 is used for responding to an anti-money laundering monitoring instruction of a target client and identifying the identity information of the target client;
the money laundering risk level determining module 420 is configured to determine a money laundering risk level of the target customer according to the identity information, and determine whether a subsequent transaction of the target customer meets a monitoring condition according to the money laundering risk level;
and the target subsequent transaction intercepting module 430 is configured to intercept the target subsequent transaction when the target subsequent transaction performed by the target customer satisfies the intercepting condition if the subsequent transaction of the target customer satisfies the monitoring condition.
According to the scheme of the embodiment, the identity information of the target client is identified by the identity information identification module in response to the anti-money laundering monitoring instruction of the target client; determining the money laundering risk grade of the target client according to the identity information through a money laundering risk grade determining module, and determining whether the subsequent transaction of the target client meets the monitoring condition according to the money laundering risk grade; the target follow-up transaction is intercepted by the target follow-up transaction intercepting module, so that the problems that the efficiency of anti-money laundering monitoring is low and a large amount of human resources are wasted due to the fact that information of a risk client is manually checked and the transaction of the risk client is monitored are solved, and the anti-money laundering behavior of the financial leasing industry can be automatically monitored.
Optionally, the apparatus further comprises: the integrity condition determining module is used for determining the integrity condition of the identity information; and if the identity information is determined not to meet the integrity condition, returning a supplementary instruction of the identity information to the user side until the identity information meets the integrity condition.
Optionally, the integrity condition determining module is specifically configured to determine that the identity information satisfies the integrity condition if it is determined that the total amount of the identity information matches the number of the set standard information.
Optionally, the money laundering risk level determining module 420 includes: the system comprises a standard blacklist data sheet acquisition module and a money laundering risk grade determination submodule;
the standard blacklist data table acquisition module is used for acquiring a standard blacklist data table and inquiring identity information in the standard blacklist data table;
the money laundering risk level determining submodule is used for determining the target client as a risk client if the reference data matched with the identity information is inquired in the standard blacklist data table;
determining the data type of the reference data, and determining the money laundering risk level of the target client according to the data type;
wherein the data types include: basic information, historical transaction information, contract information, or insurance information; the money laundering risk level includes low, medium, or high.
Optionally, the money laundering risk level determining module 420 further includes: and the screening module is used for screening the standard blacklist data table and filtering unreasonable or wrong blacklist data.
Optionally, the target subsequent transaction intercepting module 430 includes: and the monitoring submodule is used for determining that the subsequent transaction of the target customer meets the monitoring condition and monitoring the subsequent transaction of the target customer in real time if the money laundering risk level is greater than or equal to a first set threshold value.
Optionally, the target subsequent transaction intercepting module 430 further includes: and the first interruption submodule is used for intercepting the target subsequent transaction when the transaction amount of the target subsequent transaction is larger than a second set threshold value so as to interrupt the target subsequent transaction.
Optionally, the target subsequent transaction intercepting module 430 further includes: and the second interruption submodule is used for intercepting the target subsequent transaction when the location of the payee of the target subsequent transaction is abnormal so as to interrupt the target subsequent transaction.
Optionally, the apparatus further comprises: and the stable client determining module is used for marking the target client as the stable client if the subsequent transaction of the target client does not meet the monitoring condition.
The anti-money laundering monitoring device of the financial leasing industry provided by the embodiment of the invention can execute the anti-money laundering monitoring method of the financial leasing industry provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE five
Fig. 5 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention, as shown in fig. 5, the electronic device includes a processor 50, a memory 51, an input device 52, and an output device 53; the number of the processors 50 in the electronic device may be one or more, and one processor 50 is taken as an example in fig. 5; the processor 50, the memory 51, the input device 52 and the output device 53 in the electronic apparatus may be connected by a bus or other means, and the bus connection is exemplified in fig. 5.
The memory 51 is used as a computer-readable storage medium for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the anti-money laundering monitoring method in the financial leasing industry (for example, the identity information identification module 410, the money laundering risk level determination module 420, and the target subsequent transaction interception module 430 in the anti-money laundering monitoring apparatus in the financial leasing industry) in the embodiment of the present invention. The processor 50 executes various functional applications and data processing of the electronic device by executing software programs, instructions and modules stored in the memory 51, so as to implement the anti-money laundering monitoring method in the financial leasing industry.
The memory 51 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 51 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 51 may further include memory located remotely from the processor 50, which may be connected to the electronic device through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 52 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function controls of the electronic apparatus. The output device 53 may include a display device such as a display screen.
EXAMPLE six
An embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a method for anti-money laundering monitoring in a financial leasing industry, the method including:
responding to an anti-money laundering monitoring instruction of a target client, and identifying identity information of the target client;
determining the money laundering risk level of the target customer according to the identity information, and determining whether the subsequent transaction of the target customer meets the monitoring condition according to the money laundering risk level;
and if the subsequent transaction of the target customer meets the monitoring condition, intercepting the target subsequent transaction when the target subsequent transaction performed by the target customer meets the intercepting condition.
Of course, the embodiment of the present invention provides a storage medium containing computer-executable instructions, and the computer-executable instructions are not limited to the method operations described above, and can also perform related operations in the anti-money laundering monitoring method for the financial leasing industry provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the anti-money laundering monitoring apparatus in the financial leasing industry, the included units and modules are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be realized; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (20)
1. An anti-money laundering monitoring method for a financial leasing industry is characterized by comprising the following steps:
responding to an anti-money laundering monitoring instruction of a target client, and identifying identity information of the target client;
determining the money laundering risk level of the target customer according to the identity information, and determining whether the subsequent transaction of the target customer meets the monitoring condition according to the money laundering risk level;
and if the subsequent transaction of the target customer meets the monitoring condition, intercepting the target subsequent transaction when the target subsequent transaction performed by the target customer meets the intercepting condition.
2. The method of claim 1, further comprising, prior to said identifying the identity information of the target customer:
determining the identity information integrity condition;
and if the identity information is determined not to meet the integrity condition, returning a supplementary instruction of the identity information to the user side until the identity information meets the integrity condition.
3. The method of claim 2, wherein the determining that the identity information satisfies a completeness condition comprises:
and if the total quantity of the identity information is determined to be matched with the quantity of the set standard information, determining that the identity information meets the integrity condition.
4. The method of claim 1, wherein determining a money laundering risk level for the target customer based on the identity information comprises:
acquiring a standard blacklist data table, and inquiring the identity information in the standard blacklist data table;
if the reference data matched with the identity information is inquired in the standard blacklist data table, determining the target client as a risk client;
determining the data type of the reference data, and determining the money laundering risk level of the target customer according to the data type;
wherein the data types include: basic information, historical transaction information, contract information, or insurance information; the money laundering risk levels include low, medium, or high.
5. The method of claim 4, after said obtaining a standard blacklist data table, further comprising:
and screening the standard blacklist data table, and filtering unreasonable or wrong blacklist data.
6. The method of claim 1, wherein said determining whether subsequent transactions of the target customer satisfy a monitoring condition based on the money laundering risk level comprises:
and if the money laundering risk level is greater than or equal to a first set threshold value, determining that the subsequent transaction of the target customer meets the monitoring condition, and monitoring the subsequent transaction of the target customer in real time.
7. The method of claim 1, wherein intercepting the target subsequent transaction by the target customer when the target subsequent transaction satisfies an interception condition comprises:
and intercepting the target subsequent transaction when the transaction amount of the target subsequent transaction is larger than a second set threshold value so as to interrupt the target subsequent transaction.
8. The method of claim 1, wherein intercepting the target subsequent transaction by the target customer when the target subsequent transaction satisfies an interception condition, further comprises:
and intercepting the target subsequent transaction when the location of the payee of the target subsequent transaction is abnormal so as to interrupt the target subsequent transaction.
9. The method of claim 1, further comprising: and if the subsequent transaction of the target customer does not meet the monitoring condition, marking the target customer as a stable customer.
10. An anti-money laundering monitoring device for financial leasing industry, comprising:
the identity information identification module is used for responding to an anti-money laundering monitoring instruction of a target client and identifying the identity information of the target client;
the money laundering risk grade determining module is used for determining the money laundering risk grade of the target customer according to the identity information and determining whether the subsequent transaction of the target customer meets the monitoring condition or not according to the money laundering risk grade;
and the target subsequent transaction intercepting module is used for intercepting the target subsequent transaction when the target subsequent transaction performed by the target client meets the intercepting condition if the subsequent transaction of the target client meets the monitoring condition.
11. The apparatus of claim 10, further comprising:
the integrity condition determining module is used for determining the integrity condition of the identity information;
and if the identity information is determined not to meet the integrity condition, returning a supplementary instruction of the identity information to the user side until the identity information meets the integrity condition.
12. The apparatus of claim 11, wherein the completeness condition determination module is specifically configured to
And if the total quantity of the identity information is determined to be matched with the quantity of the set standard information, determining that the identity information meets the integrity condition.
13. The apparatus of claim 10, wherein the money laundering risk level determination module comprises: the system comprises a standard blacklist data sheet acquisition module and a money laundering risk grade determination submodule;
the standard blacklist data table acquisition module is used for acquiring a standard blacklist data table and inquiring the identity information in the standard blacklist data table;
the money laundering risk level determining submodule is used for determining the target client as a risk client if the reference data matched with the identity information is inquired in the standard blacklist data table;
determining the data type of the reference data, and determining the money laundering risk level of the target customer according to the data type;
wherein the data types include: basic information, historical transaction information, contract information, or insurance information; the money laundering risk levels include low, medium, or high.
14. The apparatus of claim 13, wherein the money laundering risk level determination module further comprises:
and the screening module is used for screening the standard blacklist data table and filtering unreasonable or wrong blacklist data.
15. The apparatus of claim 10, wherein the target subsequent transaction interception module comprises: monitoring submodule for
And if the money laundering risk level is greater than or equal to a first set threshold value, determining that the subsequent transaction of the target customer meets the monitoring condition, and monitoring the subsequent transaction of the target customer in real time.
16. The apparatus of claim 10, wherein the target subsequent transaction interception module further comprises: a first interrupt submodule for
And intercepting the target subsequent transaction when the transaction amount of the target subsequent transaction is larger than a second set threshold value so as to interrupt the target subsequent transaction.
17. The apparatus of claim 10, wherein the target subsequent transaction interception module further comprises: a second interrupt submodule for
And intercepting the target subsequent transaction when the location of the payee of the target subsequent transaction is abnormal so as to interrupt the target subsequent transaction.
18. The apparatus of claim 10, further comprising:
and the stable client determining module is used for marking the target client as a stable client if the subsequent transaction of the target client does not meet the monitoring condition.
19. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the anti-money laundering monitoring method of the financial leasing industry of any of claims 1-9.
20. A storage medium containing computer-executable instructions for performing the method of anti-money laundering monitoring of the financial leasing industry of any one of claims 1-9 when executed by a computer processor.
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