CN113626526A - Block chain-based cross-bank illegal fund transfer monitoring method and node - Google Patents
Block chain-based cross-bank illegal fund transfer monitoring method and node Download PDFInfo
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Abstract
The embodiment of the application provides a block chain-based cross-bank illegal fund transfer monitoring method and a node, which relate to the field of block chains, and the method comprises the following steps: acquiring a fund transfer risk list broadcasted on a block chain; decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business; and if the identity information is in the fund transfer risk list, generating monitoring early warning information. The method solves the problems of illegal fund transfer among the cross-banks and small-amount high-frequency fund transfer, and provides a more efficient monitoring method for the illegal fund transfer work of modern banks.
Description
Technical Field
The application relates to the field of block chains, in particular to a method and a node for monitoring illegal fund transfer across banks based on the block chains.
Background
Along with the rapid development of science and technology, the fund transfer means also presents the characteristics of specialization, diversification and the like, the illegal fund transfer situation becomes severe day by day, the supervision is tightened continuously, and the current illegal fund transfer method mainly based on over-the-counter transaction in the aspect of banks cannot meet the requirement of the illegal fund transfer work at present. The existing illegal fund transfer working mode mainly depends on the identification of client identity and transaction operation and the screening and analysis of post-affair data by front-line staff, needs to invest a large amount of labor cost and time cost, has poor timeliness and cannot meet the timeliness requirement of modern illegal fund transfer work; because of the information barriers between banks, aiming at the weak link, the fund transfer operation with small amount and high frequency is carried out in batches, different banks, different accounts and different channels, and the similar fund transfer mode is difficult to judge through single or several transactions.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a monitoring method and a node for cross-bank illegal fund transfer based on a block chain, and a fund transfer risk list broadcasted on the block chain is obtained; decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business; and if the identity information is in the fund transfer risk list, generating monitoring early warning information. The invention solves the problems of illegal fund transfer among the cross banks and small-amount high-frequency fund transfer, and provides a more efficient monitoring method for the illegal fund transfer work of modern banks.
In one aspect of the present invention, a method for monitoring illegal fund transfer across banks based on a blockchain is provided, where the blockchain includes at least one bank node, and the method is applied to any bank node on the blockchain, and includes:
acquiring a fund transfer risk list broadcasted on a block chain;
decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business;
and if the identity information is in the fund transfer risk list, generating monitoring early warning information.
In a preferred embodiment, further comprising:
and acquiring the identity information.
In a preferred embodiment, the acquiring the identity information includes:
collecting characteristic information generated in the business handling process of the client;
and determining the identity information of the client according to the characteristic information.
In a preferred embodiment, further comprising: and if the identity information is not in the fund transfer risk list, determining the risk level of the current operation corresponding to the business handling of the client.
In a preferred embodiment, further comprising:
and if the risk level exceeds a set level, updating the fund transfer risk list.
In a preferred embodiment, further comprising:
broadcasting the updated fund transfer risk list to the blockchain so as to perform consensus on the fund transfer risk list together with other bank nodes in the blockchain, and if the consensus passes, updating and storing the fund transfer risk list by the blockchain.
In a preferred embodiment, the determining the risk level of the client currently performing the operation corresponding to the business transaction includes:
matching the identity information of the current customer with the account information operated by the current customer;
if the matching fails, adding one to the matching failure times corresponding to the current client;
and if the matching failure times are larger than a first preset threshold, determining the risk level of the client as a high risk level.
In a preferred embodiment, the determining a risk level of a client currently performing a business transaction corresponding operation further includes:
acquiring transaction frequency information of an IP address of a client currently conducting service handling;
and if the transaction frequency is greater than a second preset threshold, determining the risk level of the customer as a high risk level.
In a preferred embodiment, the determining a risk level of a client currently performing a business transaction corresponding operation further includes:
determining a corresponding identity category according to identity information of a current client, wherein the identity category comprises: a company category and a natural people category;
and if the transaction frequency between the company category and the natural person category is greater than a third preset threshold value and the transaction amount is greater than a fourth preset threshold value, determining the risk level of the customer as a high risk level.
In a preferred embodiment, comparing the fund transfer risk list with the identity information corresponding to the client currently performing the business transaction comprises:
and determining whether the client is in the fund transfer risk list or not by verifying the zero knowledge certificate corresponding to the client currently transacting business.
In a preferred embodiment, further comprising:
and updating the zero knowledge proof every other preset time length.
In another aspect of the present invention, a monitoring node for illegal fund transfer across banks based on a block chain is provided, including:
the risk list acquisition module is used for acquiring a fund transfer risk list broadcasted on the block chain;
the comparison module is used for decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business;
and the early warning monitoring module generates monitoring early warning information if the identity information is in the fund transfer risk list.
In a preferred embodiment, further comprising:
and the identity information acquisition module acquires the identity information.
In a preferred embodiment, the identity information obtaining module includes:
the characteristic acquisition unit is used for acquiring characteristic information generated in the business handling process of the client;
and the identity information determining unit is used for determining the identity information of the client according to the characteristic information.
In a preferred embodiment, further comprising: and the risk grade determining module is used for determining the risk grade of the current operation corresponding to the business handling of the client if the identity information is not in the fund transfer risk list.
In a preferred embodiment, further comprising:
and updating the risk list module, and updating the fund transfer risk list if the risk level exceeds a set level.
In a preferred embodiment, further comprising:
and the consensus risk list module broadcasts the updated fund transfer risk list to the block chain so as to perform consensus on the fund transfer risk list together with other bank nodes in the block chain, and if the consensus passes, the block chain updates and stores the fund transfer risk list.
In a preferred embodiment, the risk level determination module includes:
the information matching unit is used for matching the identity information of the current client with the operation account information of the current client;
the unit for counting the matching failure times adds one to the matching failure times corresponding to the current client if the matching fails;
and the risk grade determining unit is used for determining the risk grade of the client as a high risk grade if the matching failure times are larger than a first preset threshold value.
In a preferred embodiment, the risk level determination module further includes:
the transaction frequency acquisition unit is used for acquiring the transaction frequency information of the IP address of the client currently transacting the business;
and the risk grade determining unit is used for determining the risk grade of the customer as a high risk grade if the transaction frequency is greater than a second preset threshold.
In a preferred embodiment, the risk level determination module further includes:
the identity type determining unit determines a corresponding identity type according to the identity information of the current client, wherein the identity type comprises: a company category and a natural people category;
and the risk grade determining unit is used for determining the risk grade of the customer as a high risk grade if the transaction frequency between the company type and the natural person type is greater than a third preset threshold and the transaction amount is greater than a fourth preset threshold.
In a preferred embodiment, the alignment module includes:
and the zero knowledge certificate verifying unit is used for determining whether the client currently transacting business is in the fund transfer risk list or not by verifying the zero knowledge certificate corresponding to the client currently transacting business.
In a preferred embodiment, further comprising:
and the zero knowledge proof updating unit updates the zero knowledge proof every other preset time length.
In another aspect of the present invention, the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the block chain-based method for monitoring illegal fund transfer across banks when executing the program.
In still another aspect of the present invention, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the blockchain-based cross-bank illegal funds transfer monitoring method.
According to the technical scheme, the method for monitoring the illegal fund transfer across banks based on the block chain comprises the following steps: acquiring a fund transfer risk list broadcasted on a block chain; decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business; and if the identity information is in the fund transfer risk list, generating monitoring early warning information. The invention solves the problems of illegal fund transfer among the cross banks and small-amount high-frequency fund transfer, and provides a more efficient monitoring method for the illegal fund transfer work of modern banks.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a block chain-based flow diagram of a cross-bank illegal fund transfer monitoring method.
Fig. 2 is a schematic diagram of a client identity information acquisition process.
Fig. 3 is a schematic view of a risk level determination process.
Fig. 4 is a schematic view of a risk level determination process flow chart ii.
Fig. 5 is a third flowchart of risk level determination.
Fig. 6 is a block chain-based cross-bank illegal fund transfer monitoring node structure diagram.
Fig. 7 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the block chain-based cross-bank illegal fund transfer monitoring method and the node disclosed by the application can be used in the block chain field and can also be used in any field except the block chain field, and the application field of the block chain-based cross-bank illegal fund transfer monitoring method and the node disclosed by the application is not limited.
Along with the rapid development of science and technology, the fund transfer means also presents the characteristics of specialization, diversification and the like, the illegal fund transfer situation becomes severe day by day, the supervision is tightened continuously, and the current illegal fund transfer method mainly based on over-the-counter transaction in the aspect of banks cannot meet the requirement of the illegal fund transfer work at present. The existing illegal fund transfer working mode mainly depends on the identification of client identity and transaction operation and the screening and analysis of post-affair data by front-line staff, needs to invest a large amount of labor cost and time cost, has poor timeliness and cannot meet the timeliness requirement of modern illegal fund transfer work; because of the information barriers between banks, aiming at the weak link, the fund transfer operation with small amount and high frequency is carried out in batches, different banks, different accounts and different channels, and the similar fund transfer mode is difficult to judge through single or several transactions.
Aiming at the problems in the prior art, the application provides a monitoring method and a node for cross-bank illegal fund transfer based on a block chain, and a fund transfer risk list broadcasted on the block chain is obtained; decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business; if the identity information is in the fund transfer risk list, monitoring and early warning information is generated, so that the problems of illegal fund transfer among the cross-banks and small-amount high-frequency fund transfer are solved, and a more efficient monitoring method is provided for the illegal fund transfer work of modern banks.
The following describes the block chain-based cross-bank illegal fund transfer monitoring method and node in detail with reference to the attached drawings.
In a specific embodiment, there is provided a method for monitoring illegal fund transfer across banks based on a blockchain, where the blockchain includes at least one bank node, and the method is applied to any bank node on the blockchain, as shown in fig. 1, and includes:
s1, acquiring a fund transfer risk list broadcasted on the block chain;
specifically, the funds-transfer risk list includes identification information of the customer having the funds-transfer operation, such as identification number, name, age, nationality, etc., which can uniquely identify the customer. It will be appreciated that in addition to the basic identity information, biometric information of the customer may be included, corresponding to the level of risk of the funds transfer.
In particular embodiments, the funds-transfer risk list is updatable. When any node on the blockchain determines a new risk client, new risk client information is added into the fund transfer risk list, the updated fund transfer risk list is broadcasted to the blockchain so as to perform consensus on the fund transfer risk list together with other banking nodes in the blockchain, and if the consensus passes, the blockchain updates and stores the fund transfer risk list. Generally, the consensus on the list of funds-transfer risks may employ a variety of consensus mechanisms, such as a Byzantine fault-tolerant consensus mechanism. It is understood that the update of the funds-transfer risk list may also be considered as a transaction, and is generally realized by the intelligent contract, and when the consensus is passed, the update of the funds-transfer risk list is realized by executing the corresponding intelligent contract and storing the funds-transfer risk list. In a specific embodiment, the fund transfer risk list is processed by a hash algorithm and then stored in the blockchain block.
S2, decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business;
specifically, in order to ensure the security of data transmission, the data information acquired from the blockchain is asymmetrically encrypted, that is, the acquired fund transfer risk list is an encrypted list ciphertext, and a private key corresponding to the encrypted public key is required to be used for decryption. For a block chain of a bank system, a federation chain is generally used for construction, and only bank nodes subjected to identity verification can join the block chain, so that each node on the block chain is allocated with a corresponding private key.
In a specific embodiment, the decrypted fund transfer risk list is compared with the identity information corresponding to the client currently conducting business handling. It is understood that the risk list includes the identity information of the customer who is at risk of transferring funds, but when comparing the identity information, the information capable of uniquely identifying the customer, such as the identification number, is preferably selected. If the information which can uniquely identify the client is missing, comprehensive comparison is carried out according to a plurality of other identity information. For example, if the identity card number information of the current customer is missing for some reason, it can be determined whether the current customer is in the fund transfer risk list by combining the name information, age information, address information, local information and the like of the customer. In a specific embodiment, whether the client currently transacting business is in the fund transfer risk list is determined by verifying zero knowledge proof corresponding to the client currently transacting business. Verification of zero knowledge proof is achieved by corresponding intelligent contracts deployed in blockchains. In a specific embodiment, zksnarks algorithm is adopted for verification, and a fund transfer risk list is obtained first, so that P ═ P1, P2...., pn is obtained; then acquiring a zero-knowledge certificate pi corresponding to a client currently transacting business; finally, using zksnarks algorithm, if there is (p1-pi) (p 2-pi).. times. (pn-pi). times.0, then the customer is determined to be in the blacklist.
It will be appreciated that the zero knowledge proof of the client needs to be updated every predetermined time period to ensure that the zero knowledge proof of the client represents the risk level. The generation and updating of the zero knowledge proof of the client are set according to the subsequent risk level.
In a specific embodiment, obtaining the identity information of the current client, as shown in fig. 2, includes:
s21, collecting the characteristic information generated in the process of business transaction of the client;
specifically, a customer passes through a cash transaction device during service transaction, the cash transaction device commonly used includes a counter host, an ATM cash dispenser, an ITM intelligent teller machine, and the like, and a feature acquisition device in the devices is used for acquiring feature information generated during the service transaction process of the customer, such as account information, face feature information, fingerprint feature information, and the like.
And S22, determining the identity information of the client according to the characteristic information.
Specifically, the characteristic information can uniquely determine the identity of the customer, for example, the identity card number of the card issuer transacting the bank card is determined through the read bank card number, and then the identity of the customer is determined; the identity of a client is determined by comparing the collected face feature information with data in a face library; and comparing the acquired fingerprint information with data in a fingerprint database to determine the identity of the client.
And S3, if the identity information is in the fund transfer risk list, generating monitoring early warning information.
Specifically, if the current customer is in the fund transfer risk list, bank personnel needs to be prompted by generating monitoring and early warning information to intervene in the operation of the customer. In a specific embodiment, if the customer operates at the bank branch at present, the branch receives the monitoring and early warning information and then timely makes relevant inquiries to the customer according to the in-line regulations, determines the legality of the transaction, and makes corresponding processing to complete the business transaction; if the current customer operates in a self-service transaction mode, such as ATM, ITM and online banking, the transaction frequency and amount are limited by the risk level after receiving the monitoring and early warning information.
In a specific embodiment, if the identity information is not in the fund transfer risk list, determining a risk level of a current operation corresponding to business handling of the client. And if the risk level exceeds a set level, updating the fund transfer risk list. It will be appreciated that the risk levels may be in the form of halves, e.g. high risk and low risk, or in the form of steps, e.g. first, second, third, fourth. The bank nodes in all the block chains adopt a uniform grade mode so as to facilitate subsequent comparison.
In a specific embodiment, the risk level of the operation currently performed by the client for the business transaction may be determined according to the matching degree between the identity information of the client and the operation account, as shown in fig. 3, including:
s101, matching the identity information of the current customer with the account information operated by the current customer;
s102, if the matching fails, adding one to the matching failure times corresponding to the current client;
and S103, if the matching failure times are larger than a first preset threshold value, determining the risk level of the customer as a high risk level.
Specifically, the identity information of the current customer is matched with the operated account information, so as to determine whether the accounts of a large number of different customers operated by the same person or a small number of persons are in transaction, under normal conditions, the same person cannot operate a large number of different accounts, and the accounts of the large number of different customers operated by the same person or the small number of persons are only operated when the funds are transferred by adopting a plurality of different accounts. The identity information of the customer generally refers to information capable of uniquely identifying the customer, such as an identification number, and the account information includes an account number of a bank card. When the bank card of the customer is opened, the account information of the bank card and the identity card number information of the customer are bound together, so that the identity information of the account owner can be obtained by acquiring the account information, and the identity information of the current customer and the identity information of the account owner can be matched. The selection of the first preset threshold needs to be determined according to actual conditions, and if an overlarge first preset threshold is selected, part of fund transfer behaviors are omitted; if a first predetermined threshold is selected that is too small, then some non-funds-transfer activities may be misjudged as funds-transfer activities.
In a specific embodiment, the determining a risk level of a current operation performed by a client for service handling may further include, according to ip address information of the client, as shown in fig. 4:
s201, acquiring transaction frequency information of an IP address of a client for currently transacting business;
and S202, if the transaction frequency is greater than a second preset threshold, determining the risk level of the customer as a high risk level.
Specifically, the risk level is determined by the IP address, and whether multiple transactions of different accounts are performed by the same IP address in a short time. It can be understood that the transaction frequency information of the ip address refers to the number of accounts transacted in a unit time, for example, if 10 accounts are logged in the ip address for transaction in 1 minute, the transaction frequency is 10. If only one account is logged in the ip address within 1 minute, the corresponding transaction frequency is 1. The setting of said second predetermined threshold value also needs to be combined with the actual situation, for example an ATM in a commercial area, for which the set threshold value should be relatively high, since the normal transaction frequency per unit time is high; and an ATM in a closed cell should have a relatively low corresponding second predetermined threshold because the frequency of normal transactions per unit time is low.
In a specific embodiment, the determining the risk level of the current operation corresponding to the business handling performed by the client may further include, according to the identity category information of the client, as shown in fig. 5:
s301, determining a corresponding identity type according to the identity information of the current client, wherein the identity type comprises: a company category and a natural people category;
and S302, if the transaction frequency between the company category and the natural person category is greater than a third preset threshold and the transaction amount is greater than a fourth preset threshold, determining the risk level of the customer as a high risk level.
Specifically, when the identity information of the customer is of a company type, the transaction frequency and the transaction amount between the customer and the natural human are obtained, and if the transaction frequency is high or the transaction amount is large, the risk level of the customer is a high risk level. It can be understood that, in order to ensure that normal transactions between the company category and the natural people category are not affected, the third preset threshold and the fourth preset threshold also need to be set according to actual conditions. For example, if a company issues wages to employees, and if the amount of normal transactions between the company and natural persons is not particularly large, the company can be determined as high risk by setting a fourth preset threshold. On the other hand, if the company needs to purchase a certain material from a natural person, the transaction amount is large and exceeds the fourth preset threshold, but the company cannot frequently purchase such large amount of material, so that the determination of the company as a high risk can be avoided by setting the transaction frequency.
As can be seen from the above description, the method for monitoring illegal fund transfer across banks based on the block chain obtains the fund transfer risk list broadcasted on the block chain; decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business; if the identity information is in the fund transfer risk list, monitoring and early warning information is generated, so that the method and the system can accurately reflect the execution conditions of the database statements in different time periods in a real operating environment, have good universality and can detect the database statements in different types.
From a software aspect, the present application provides an embodiment of a block chain-based cross-bank illegal fund transfer monitoring node for executing all or part of contents in the block chain-based cross-bank illegal fund transfer monitoring method, and referring to fig. 6, the block chain-based cross-bank illegal fund transfer monitoring node specifically includes the following contents:
the risk list acquisition module 1 is used for acquiring a fund transfer risk list broadcasted on a block chain;
the comparison module 2 is used for decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business;
and the early warning monitoring module 3 generates monitoring early warning information if the identity information is in the fund transfer risk list.
As can be seen from the above description, the node acquires the fund transfer risk list broadcast on the blockchain, and the monitoring node for illegal fund transfer across banks based on the blockchain provided by the present invention; decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business; and if the identity information is in the fund transfer risk list, generating monitoring early warning information. The invention solves the problems of illegal fund transfer among the cross banks and small-amount high-frequency fund transfer, and provides a more efficient monitoring method for the illegal fund transfer work of modern banks.
In a specific embodiment, a block chain-based node for monitoring illegal fund transfer across banks is provided, which specifically includes:
a risk list acquiring module 1, configured to execute acquiring a fund transfer risk list broadcasted on a block chain;
specifically, the funds-transfer risk list includes identification information of the customer having the funds-transfer operation, such as identification number, name, age, nationality, etc., which can uniquely identify the customer. It will be appreciated that in addition to the basic identity information, biometric information of the customer may be included, corresponding to the level of risk of the funds transfer.
In particular embodiments, the funds-transfer risk list is updatable. When any node on the blockchain determines a new risk client, new risk client information is added into the fund transfer risk list, the updated fund transfer risk list is broadcasted to the blockchain so as to perform consensus on the fund transfer risk list together with other banking nodes in the blockchain, and if the consensus passes, the blockchain updates and stores the fund transfer risk list. Generally, the consensus on the list of funds-transfer risks may employ a variety of consensus mechanisms, such as a Byzantine fault-tolerant consensus mechanism. It is understood that the update of the funds-transfer risk list may also be considered as a transaction, and is generally realized by the intelligent contract, and when the consensus is passed, the update of the funds-transfer risk list is realized by executing the corresponding intelligent contract and storing the funds-transfer risk list. In a specific embodiment, the fund transfer risk list is processed by a hash algorithm and then stored in the blockchain block.
The comparison module 2 is used for executing decryption of the fund transfer risk list and comparing the fund transfer risk list with identity information corresponding to the client currently conducting business handling;
specifically, in order to ensure the security of data transmission, the data information acquired from the blockchain is asymmetrically encrypted, that is, the acquired fund transfer risk list is an encrypted list ciphertext, and a private key corresponding to the encrypted public key is required to be used for decryption. For a block chain of a bank system, a federation chain is generally used for construction, and only bank nodes subjected to identity verification can join the block chain, so that each node on the block chain is allocated with a corresponding private key.
In a specific embodiment, the decrypted fund transfer risk list is compared with the identity information corresponding to the client currently conducting business handling. It is understood that the risk list includes the identity information of the customer who is at risk of transferring funds, but when comparing the identity information, the information capable of uniquely identifying the customer, such as the identification number, is preferably selected. If the information which can uniquely identify the client is missing, comprehensive comparison is carried out according to a plurality of other identity information. For example, if the identity card number information of the current customer is missing for some reason, it can be determined whether the current customer is in the fund transfer risk list by combining the name information, age information, address information, local information and the like of the customer. In a specific embodiment, whether the client currently transacting business is in the fund transfer risk list is determined by verifying zero knowledge proof corresponding to the client currently transacting business. Verification of zero knowledge proof is achieved by corresponding intelligent contracts deployed in blockchains. In a specific embodiment, zksnarks algorithm is adopted for verification, and a fund transfer risk list is obtained first, so that P ═ P1, P2...., pn is obtained; then acquiring a zero-knowledge certificate pi corresponding to a client currently transacting business; finally, using zksnarks algorithm, if there is (p1-pi) (p 2-pi).. times. (pn-pi). times.0, then the customer is determined to be in the blacklist.
It will be appreciated that the zero knowledge proof of the client needs to be updated every predetermined time period to ensure that the zero knowledge proof of the client represents the risk level. The generation and updating of the zero knowledge proof of the client are set according to the subsequent risk level.
In a specific embodiment, the identity information obtaining module includes:
the characteristic acquisition unit is used for acquiring characteristic information generated in the business handling process of the client;
specifically, a customer passes through a cash transaction device during service transaction, the cash transaction device commonly used includes a counter host, an ATM cash dispenser, an ITM intelligent teller machine, and the like, and a feature acquisition device in the devices is used for acquiring feature information generated during the service transaction process of the customer, such as account information, face feature information, fingerprint feature information, and the like.
And the identity information determining unit is used for determining the identity information of the client according to the characteristic information.
Specifically, the characteristic information can uniquely determine the identity of the customer, for example, the identity card number of the card issuer transacting the bank card is determined through the read bank card number, and then the identity of the customer is determined; the identity of a client is determined by comparing the collected face feature information with data in a face library; and comparing the acquired fingerprint information with data in a fingerprint database to determine the identity of the client.
And the early warning monitoring module 3 is used for executing the monitoring early warning information if the identity information is in the fund transfer risk list.
Specifically, if the current customer is in the fund transfer risk list, bank personnel needs to be prompted by generating monitoring and early warning information to intervene in the operation of the customer. In a specific embodiment, if the customer operates at the bank branch at present, the branch receives the monitoring and early warning information and then timely makes relevant inquiries to the customer according to the in-line regulations, determines the legality of the transaction, and makes corresponding processing to complete the business transaction; if the current customer operates in a self-service transaction mode, such as ATM, ITM and online banking, the transaction frequency and amount are limited by the risk level after receiving the monitoring and early warning information.
In a specific embodiment, if the identity information is not in the fund transfer risk list, a risk level determination module needs to be executed to determine a risk level of a current operation performed by the client. And if the risk level exceeds a set level, updating the fund transfer risk list. It will be appreciated that the risk levels may be in the form of halves, e.g. high risk and low risk, or in the form of steps, e.g. first, second, third, fourth. The bank nodes in all the block chains adopt a uniform grade mode so as to facilitate subsequent comparison.
In a specific embodiment, the risk level determining module may determine, according to a matching degree between the identity information of the client and the operation account, a risk level of an operation corresponding to a current business transaction of the client, including:
the information matching unit is used for matching the identity information of the current client with the operated account information;
the statistical matching failure times unit is used for executing that if the matching fails, the matching failure times corresponding to the current client are added by one;
and the risk level determining unit is used for determining the risk level of the client as a high risk level if the matching failure times are greater than a first preset threshold.
Specifically, the identity information of the current customer is matched with the operated account information, so as to determine whether the accounts of a large number of different customers operated by the same person or a small number of persons are in transaction, under normal conditions, the same person cannot operate a large number of different accounts, and the accounts of the large number of different customers operated by the same person or the small number of persons are only operated when the funds are transferred by adopting a plurality of different accounts. The identity information of the customer generally refers to information capable of uniquely identifying the customer, such as an identification number, and the account information includes an account number of a bank card. When the bank card of the customer is opened, the account information of the bank card and the identity card number information of the customer are bound together, so that the identity information of the account owner can be obtained by acquiring the account information, and the identity information of the current customer and the identity information of the account owner can be matched. The selection of the first preset threshold needs to be determined according to actual conditions, and if an overlarge first preset threshold is selected, part of fund transfer behaviors are omitted; if a first predetermined threshold is selected that is too small, then some non-funds-transfer activities may be misjudged as funds-transfer activities.
In a specific embodiment, the risk level determining module may further determine a risk level of the current client according to ip address information of the client, and specifically includes:
the transaction frequency acquisition unit is used for executing and acquiring the transaction frequency information of the IP address of the client for currently transacting the business;
and the risk level determining unit is used for determining the risk level of the customer as a high risk level if the transaction frequency is greater than a second preset threshold.
Specifically, the risk level is determined by the IP address, and whether multiple transactions of different accounts are performed by the same IP address in a short time. It can be understood that the transaction frequency information of the ip address refers to the number of accounts transacted in a unit time, for example, if 10 accounts are logged in the ip address for transaction in 1 minute, the transaction frequency is 10. If only one account is logged in the ip address within 1 minute, the corresponding transaction frequency is 1. The setting of said second predetermined threshold value also needs to be combined with the actual situation, for example an ATM in a commercial area, for which the set threshold value should be relatively high, since the normal transaction frequency per unit time is high; and an ATM in a closed cell should have a relatively low corresponding second predetermined threshold because the frequency of normal transactions per unit time is low.
In a specific embodiment, the risk level determining module may further include, according to the identity category information of the client:
the identity category determining unit is used for determining a corresponding identity category according to the identity information of the current client, and the identity category comprises: a company category and a natural people category;
and the risk grade determining unit is used for determining the risk grade of the customer as a high risk grade if the transaction frequency between the company type and the natural person type is greater than a third preset threshold and the transaction amount is greater than a fourth preset threshold.
Specifically, when the identity information of the customer is of a company type, the transaction frequency and the transaction amount between the customer and the natural human are obtained, and if the transaction frequency is high or the transaction amount is large, the risk level of the customer is a high risk level. It can be understood that, in order to ensure that normal transactions between the company category and the natural people category are not affected, the third preset threshold and the fourth preset threshold also need to be set according to actual conditions. For example, if a company issues wages to employees, and if the amount of normal transactions between the company and natural persons is not particularly large, the company can be determined as high risk by setting a fourth preset threshold. On the other hand, if the company needs to purchase a certain material from a natural person, the transaction amount is large and exceeds the fourth preset threshold, but the company cannot frequently purchase such large amount of material, so that the determination of the company as a high risk can be avoided by setting the transaction frequency.
As can be seen from the above description, the monitoring node for illegal fund transfer across banks based on the block chain provided by the present invention includes a dynamic information obtaining module 1, configured to execute and obtain dynamic information of database statements during program execution, where the dynamic information includes call feature data of the database statements during program execution; and the abnormal statement detection module 2 is used for detecting abnormal database statements according to the dynamic information. The invention solves the problems of illegal fund transfer among the cross banks and small-amount high-frequency fund transfer, and provides a more efficient monitoring method for the illegal fund transfer work of modern banks.
From a hardware aspect, the present application provides an embodiment of an electronic device for implementing all or part of contents in a block chain-based method for monitoring illegal fund transfer across banks, where the electronic device specifically includes the following contents:
fig. 7 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 7, the electronic device 9600 can include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 7 is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.
In one embodiment, the blockchain-based cross-bank illegal funds transfer monitoring method function may be integrated into the central processor. Wherein the central processor may be configured to control:
s1, the dynamic information is used for executing and acquiring the dynamic information of the database statement in the program executing process, and the dynamic information comprises the calling characteristic data of the database statement when a plurality of programs are executed;
s2, detecting abnormal database statement according to the dynamic information.
From the above description, the electronic device provided by the embodiment of the application solves the problems of illegal fund transfer between cross-banks and small-amount high-frequency fund transfer, and provides a more efficient monitoring method for the illegal fund transfer work of modern banks.
In another embodiment, the block chain-based cross-bank illegal fund transfer monitoring node may be configured separately from the central processor 9100, for example, the block chain-based cross-bank illegal fund transfer monitoring node may be configured as a chip connected to the central processor 9100, and the function of the block chain-based cross-bank illegal fund transfer monitoring method may be implemented by the control of the central processor.
As shown in fig. 7, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 also does not necessarily include all of the components shown in fig. 7; further, the electronic device 9600 may further include components not shown in fig. 7, which may be referred to in the art.
As shown in fig. 7, a central processor 9100, sometimes referred to as a controller or operational control, can include a microprocessor or other processor device and/or logic device, which central processor 9100 receives input and controls the operation of the various components of the electronic device 9600.
The memory 9140 can be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 9100 can execute the program stored in the memory 9140 to realize information storage or processing, or the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. Power supply 9170 is used to provide power to electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but is not limited thereto.
The memory 9140 can be a solid state memory, e.g., Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 9140 could also be some other type of device. Memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 being used for storing application programs and function programs or for executing a flow of operations of the electronic device 9600 by the central processor 9100.
The memory 9140 can also include a data store 9143, the data store 9143 being used to store data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers for the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, contact book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. The communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing ordinary telecommunications functions. The audio processor 9130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100, thereby enabling recording locally through the microphone 9132 and enabling locally stored sounds to be played through the speaker 9131.
An embodiment of the present application further provides a computer-readable storage medium capable of implementing all steps in the block chain based cross-bank illegal fund transfer monitoring method in the foregoing embodiment, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements all steps of the block chain based cross-bank illegal fund transfer monitoring method, where an execution subject of the computer program is a server or a client, for example, when the processor executes the computer program, the processor implements the following steps:
s1, the dynamic information is used for executing and acquiring the dynamic information of the database statement in the program executing process, and the dynamic information comprises the calling characteristic data of the database statement when a plurality of programs are executed;
s2, detecting abnormal database statement according to the dynamic information.
From the above description, it can be seen that the computer-readable storage medium provided in the embodiments of the present application solves the problem of illegal fund transfer between banks and the problem of small-amount high-frequency fund transfer, and provides a more efficient monitoring method for the illegal fund transfer work of modern banks.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (nodes), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (24)
1. A method for monitoring illegal fund transfer across banks based on a blockchain, wherein the blockchain comprises at least one bank node, and the method is applied to any bank node on the blockchain, and is characterized by comprising the following steps:
acquiring a fund transfer risk list broadcasted on a block chain;
decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business;
and if the identity information is in the fund transfer risk list, generating monitoring early warning information.
2. The method for monitoring illegal fund transfer across banks based on block chain as claimed in claim 1 further comprising:
and acquiring the identity information.
3. The method for monitoring illegal fund transfer across banks based on block chain as claimed in claim 2, wherein the obtaining the identity information comprises:
collecting characteristic information generated in the business handling process of the client;
and determining the identity information of the client according to the characteristic information.
4. The method for monitoring illegal fund transfer across banks based on block chain as claimed in claim 1 further comprising: and if the identity information is not in the fund transfer risk list, determining the risk level of the current operation corresponding to the business handling of the client.
5. The method for monitoring illegal fund transfer across banks based on block chain as claimed in claim 4, further comprising:
and if the risk level exceeds a set level, updating the fund transfer risk list.
6. The method for monitoring illegal fund transfer across banks based on block chain as claimed in claim 5, further comprising:
broadcasting the updated fund transfer risk list to the blockchain so as to perform consensus on the fund transfer risk list together with other bank nodes in the blockchain, and if the consensus passes, updating and storing the fund transfer risk list by the blockchain.
7. The method for monitoring illegal fund transfer across banks based on block chain as claimed in claim 4, wherein the determining the risk level of the client currently performing the corresponding operation of business transaction comprises:
matching the identity information of the current customer with the account information operated by the current customer;
if the matching fails, adding one to the matching failure times corresponding to the current client;
and if the matching failure times are larger than a first preset threshold, determining the risk level of the client as a high risk level.
8. The method as claimed in claim 4, wherein the step of determining the risk level of the client currently performing the operation corresponding to the business transaction further comprises:
acquiring transaction frequency information of an IP address of a client currently conducting service handling;
and if the transaction frequency is greater than a second preset threshold, determining the risk level of the customer as a high risk level.
9. The method as claimed in claim 4, wherein the step of determining the risk level of the client currently performing the operation corresponding to the business transaction further comprises:
determining a corresponding identity category according to identity information of a current client, wherein the identity category comprises: a company category and a natural people category;
and if the transaction frequency between the company category and the natural person category is greater than a third preset threshold value and the transaction amount is greater than a fourth preset threshold value, determining the risk level of the customer as a high risk level.
10. The method for monitoring illegal fund transfer across banks based on the block chain as claimed in claim 1, wherein comparing the risk list of fund transfer with the identity information corresponding to the client currently transacting business comprises:
and determining whether the client is in the fund transfer risk list or not by verifying the zero knowledge certificate corresponding to the client currently transacting business.
11. The method for monitoring illegal fund transfer across banks based on block chain as claimed in claim 10 further comprising:
and updating the zero knowledge proof every other preset time length.
12. A monitoring node for illegal fund transfer across banks based on a block chain is characterized by comprising:
the risk list acquisition module is used for acquiring a fund transfer risk list broadcasted on the block chain;
the comparison module is used for decrypting the fund transfer risk list and comparing the fund transfer risk list with the identity information corresponding to the client currently transacting the business;
and the early warning monitoring module generates monitoring early warning information if the identity information is in the fund transfer risk list.
13. The node for monitoring illegal fund transfer across banks based on block chain as claimed in claim 12 further comprising:
and the identity information acquisition module acquires the identity information.
14. The node for monitoring illegal fund transfer across banks based on block chain according to claim 13, wherein the identity information acquiring module comprises:
the characteristic acquisition unit is used for acquiring characteristic information generated in the business handling process of the client;
and the identity information determining unit is used for determining the identity information of the client according to the characteristic information.
15. The node for monitoring illegal fund transfer across banks based on block chain as claimed in claim 12 further comprising: and the risk grade determining module is used for determining the risk grade of the current operation corresponding to the business handling of the client if the identity information is not in the fund transfer risk list.
16. The node for monitoring illegal fund transfer across banks based on block chain as claimed in claim 15 further comprising:
and updating the risk list module, and updating the fund transfer risk list if the risk level exceeds a set level.
17. The node for monitoring illegal fund transfer across banks based on block chain as claimed in claim 16 further comprising:
and the consensus risk list module broadcasts the updated fund transfer risk list to the block chain so as to perform consensus on the fund transfer risk list together with other bank nodes in the block chain, and if the consensus passes, the block chain updates and stores the fund transfer risk list.
18. The node for monitoring illegal fund transfer across banks based on block chain according to claim 15, wherein the risk level determining module comprises:
the information matching unit is used for matching the identity information of the current client with the operation account information of the current client;
the unit for counting the matching failure times adds one to the matching failure times corresponding to the current client if the matching fails;
and the risk grade determining unit is used for determining the risk grade of the client as a high risk grade if the matching failure times are larger than a first preset threshold value.
19. The node for monitoring illegal fund transfer across banks based on block chain according to claim 15, wherein the risk level determining module further comprises:
the transaction frequency acquisition unit is used for acquiring the transaction frequency information of the IP address of the client currently transacting the business;
and the risk grade determining unit is used for determining the risk grade of the customer as a high risk grade if the transaction frequency is greater than a second preset threshold.
20. The node for monitoring illegal fund transfer across banks based on block chain according to claim 15, wherein the risk level determining module further comprises:
the identity type determining unit determines a corresponding identity type according to the identity information of the current client, wherein the identity type comprises: a company category and a natural people category;
and the risk grade determining unit is used for determining the risk grade of the customer as a high risk grade if the transaction frequency between the company type and the natural person type is greater than a third preset threshold and the transaction amount is greater than a fourth preset threshold.
21. The node for monitoring illegal fund transfer across banks based on block chain as claimed in claim 12, wherein the comparing module comprises:
and the zero knowledge certificate verifying unit is used for determining whether the client currently transacting business is in the fund transfer risk list or not by verifying the zero knowledge certificate corresponding to the client currently transacting business.
22. The node for monitoring illegal fund transfer across banks based on block chain as claimed in claim 21 further comprising:
and the zero knowledge proof updating unit updates the zero knowledge proof every other preset time length.
23. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the block chain based cross-bank illegal funds transfer monitoring method of any of claims 1 to 11 when executing the program.
24. A computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the blockchain-based cross-bank illegal funds transfer monitoring method of any of claims 1 to 11.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115086434A (en) * | 2022-06-14 | 2022-09-20 | 中国银行股份有限公司 | Bank business handling method and device based on block chain |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115086434A (en) * | 2022-06-14 | 2022-09-20 | 中国银行股份有限公司 | Bank business handling method and device based on block chain |
| CN115086434B (en) * | 2022-06-14 | 2024-04-16 | 中国银行股份有限公司 | Bank business handling method and device based on blockchain |
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