CN115238289A - Method and device for controlling internal risks of bank - Google Patents
Method and device for controlling internal risks of bank Download PDFInfo
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- CN115238289A CN115238289A CN202210890826.4A CN202210890826A CN115238289A CN 115238289 A CN115238289 A CN 115238289A CN 202210890826 A CN202210890826 A CN 202210890826A CN 115238289 A CN115238289 A CN 115238289A
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Abstract
The invention provides a method and a device for controlling internal risks of a bank, which relate to the technical field of computer data processing, and comprise the following steps: when a client transacts business at a network point and needs a staff to check and authorize, determining relevant indexes of the client and the staff; and correcting the biometric threshold value of the staff according to the relevant indexes of the client and the staff, the first corresponding relation between the biometric threshold value and the risk coefficient under the condition of each pre-stored relevant index and the second corresponding relation between the biometric threshold value and the risk coefficient, wherein the biometric threshold value is used for controlling the internal risk of business handling.
Description
Technical Field
The invention relates to the technical field of computer data processing, in particular to a method and a device for controlling internal risks of a bank.
Background
This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
In a banking scene, sometimes, a bank worker needs to perform audit authorization to advance a process of handling customer business, but the audit authorization of the worker may introduce internal risks, which may cause property loss to customers, so that the bank needs to control the internal risks when the worker audits authorization.
Therefore, a technical solution that can overcome the above-mentioned drawbacks and effectively control the internal risks of the bank is needed.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a method and a device for controlling risks in a bank.
In a first aspect of an embodiment of the present invention, a method for controlling risks inside a bank is provided, where the method includes:
when a client transacts business at a website and staff verification and authorization are required, determining relevant indexes of the client and the staff;
and correcting the biometric threshold value of the staff according to the relevant indexes of the client and the staff, the first corresponding relation between the biometric threshold value and the risk coefficient under the condition of each pre-stored relevant index and the second corresponding relation between the biometric threshold value and the risk coefficient, wherein the biometric threshold value is used for controlling the internal risk of business handling.
In a second aspect of the embodiments of the present invention, a device for controlling risks inside a bank is provided, including:
when a client transacts business at a website and staff verification and authorization are required, determining relevant indexes of the client and the staff;
and correcting the biometric threshold value of the staff according to the relevant indexes of the client and the staff, the first corresponding relation between the biometric threshold value and the risk coefficient under the condition of each pre-stored relevant index and the second corresponding relation between the biometric threshold value and the risk coefficient, wherein the biometric threshold value is used for controlling the internal risk of business handling.
In a third aspect of the embodiments of the present invention, a computer device is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the computer device implements a method for controlling risks inside a bank.
In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, in which a computer program is stored, and the computer program, when executed by a processor, implements a method for controlling risk inside a bank.
In a fifth aspect of embodiments of the present invention, a computer program product is presented, the computer program product comprising a computer program, which when executed by a processor implements a method of controlling risk inside a bank.
The method and the device for controlling the internal risk of the bank determine the relevant indexes of a client and a worker; according to the relevant indexes of the client and the staff, the first corresponding relation between the biological recognition threshold and the risk coefficient and the second corresponding relation between the biological recognition threshold and the risk coefficient under the condition of each pre-stored relevant index, the biological recognition threshold of the staff is corrected, so that when the client transacts business at a website and requires the authorization of the staff, the internal risk of the bank is effectively controlled, the business transaction of the client is ensured to be smoothly carried out, the property safety of the client is protected, and powerful technical support is provided for the digital risk control of the bank.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are 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 schematic flow chart of a method for controlling internal risks of a bank according to an embodiment of the present invention.
FIG. 2 is a flowchart illustrating a process of determining related indexes of a client and a worker according to an embodiment of the present invention.
Fig. 3 is a flowchart illustrating a process of determining a first corresponding relationship and a second corresponding relationship according to an embodiment of the invention.
FIG. 4 is a flowchart illustrating a process of correcting a biometric threshold of a worker according to an embodiment of the invention.
Fig. 5 is a schematic diagram of the architecture of a risk control device inside a bank according to an embodiment of the present invention.
Fig. 6 is a schematic structural diagram of a bank internal risk control device according to another embodiment of the present invention.
Fig. 7 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The principles and spirit of the present invention will be described with reference to several exemplary embodiments. It is understood that these embodiments are given solely for the purpose of enabling those skilled in the art to better understand and to practice the invention, and are not intended to limit the scope of the invention in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
According to the embodiment of the invention, a method and a device for controlling risks in a bank are provided, and the technical field of computer data processing is involved.
The principles and spirit of the present invention are explained in detail below with reference to several exemplary embodiments of the present invention.
Fig. 1 is a schematic flow chart of a method for controlling internal risks of a bank according to an embodiment of the present invention. As shown in fig. 1, the method includes:
s1, when a client transacts business at a website and staff check authorization is needed, relevant indexes of the client and the staff are determined;
and S2, correcting the biological recognition threshold value of the worker according to the relevant indexes of the client and the worker, the first corresponding relation between the biological recognition threshold value and the risk coefficient under the condition of each pre-stored relevant index and the second corresponding relation between the biological recognition threshold value and the risk coefficient, wherein the biological recognition threshold value is used for controlling the internal risk of business handling.
In order to explain the control method of the internal risk of the bank more clearly, the following detailed description is made in conjunction with each step.
In S1, referring to fig. 2, determining the relevant index of the customer and the staff includes:
s11, obtaining an internal correlation diagram, wherein each node of the internal correlation diagram is a customer or a staff of a bank, each edge of the internal correlation diagram corresponds to a correlation index, the correlation index represents the correlation degree of two nodes corresponding to the edge, and the value of the correlation index is between 0 and 1;
wherein the internal correlation diagram is constructed by the bank server.
And S12, determining the relevant indexes of the client and the staff according to the internal correlation diagram.
In one embodiment, (S12) determining the related indexes of the customer and the staff according to the internal correlation diagram includes:
s121, according to the internal correlation diagram, initializing the potential correlation indexes corresponding to the nodes which have edges and are directly connected with the client into the correlation indexes corresponding to the edges which are corresponding to the nodes in the internal correlation diagram of the client, and initializing the potential correlation indexes corresponding to the nodes which do not have edges and are directly connected with the client into 0;
s122, taking a set formed by all other nodes except the client in the internal correlation diagram as a node set to be determined;
s123, circularly executing the following steps (S123-1 to S123-5) until the correlation index of the client and the staff is determined:
s123-1, taking out the node S with the maximum corresponding potential correlation index from the node set to be determined;
s123-2, determining whether the node S is the staff or not;
s123-3, if the node S is the worker, determining the relevant indexes of the client and the worker as potential relevant indexes corresponding to the node S, and stopping executing the cycle;
s123-4, for each node T with an edge directly connected with the node S, updating the potential correlation index corresponding to the node T to be the maximum value of f (S) x r (S, T) and f (T), wherein f (T) is the potential correlation index corresponding to the node T before updating, f (S) is the potential correlation index corresponding to the node S, and r (S, T) is the correlation index corresponding to the corresponding edge in the internal correlation diagram of the node S and the node T;
and S123-5, deleting the node S from the node set to be determined.
Specifically, (S12) determining the relevant index of the customer and the staff according to the internal correlation diagram, including:
determining a correlation distance value corresponding to each edge of the internal correlation graph according to the following formula:
d = -lg (r), wherein d is a correlation distance value corresponding to the edge, and r is a correlation index corresponding to the edge;
determining the minimum related distance d between the client and the staff according to the internal related graph and the related distance value m ；
According to the minimum related distance d between the client and the staff m And determining a correlation index s between the client and the staff, wherein,
in one embodiment, referring to fig. 3, the method further includes determining a first corresponding relationship between the biometric threshold and the risk factor and a second corresponding relationship between the biometric threshold and the risk factor under the conditions of the relevant indexes as follows:
s301, acquiring historical audit data of a bank;
s302, regarding each piece of historical audit data, taking relevant indexes of a client and a corresponding worker corresponding to the historical audit data as relevant indexes corresponding to the historical audit data;
s303, regarding each relevant index, taking the historical audit data of which the corresponding relevant index is equal to the relevant index as the historical audit data of the relevant index;
s304, for each banking outlet, selecting the historical audit data of the banking outlet corresponding to the relevant indexes from the historical audit data of the relevant indexes;
s305, according to historical audit data of the relevant indexes corresponding to each bank website, determining a first bank website and a second bank website corresponding to the relevant indexes;
s306, according to the historical audit data of the first banking outlet corresponding to the relevant index, determining a first corresponding relation between the biological identification threshold and the risk coefficient under the relevant index condition, and according to the historical audit data of the second banking outlet corresponding to the relevant index, determining a second corresponding relation between the biological identification threshold and the risk coefficient under the relevant index condition.
It should be noted that, with reference to the method for determining the relevant indexes of the client and the staff in S1, the relevant indexes of the client and the corresponding staff corresponding to each piece of historical review data in S302 may be determined.
Specifically, (S305) determining a first banking outlet and a second banking outlet corresponding to the relevant index according to the historical audit data of the relevant index corresponding to each banking outlet, where the method includes at least the following two methods.
The first method comprises the following steps:
s305-11, determining the auditing risk coefficient of each bank network point corresponding to the relevant indexes according to the historical auditing data of the relevant indexes of each bank network point;
for example, the ratio of the audit data related to the risk in the historical audit data of the banking outlet corresponding to the relevant index is used as the audit risk coefficient of the banking outlet corresponding to the relevant index.
S305-12, determining a transaction risk coefficient of each banking outlet according to the transaction data of each banking outlet;
the transaction data of each banking outlet refers to the transaction data of each banking outlet related to the audited transaction.
S305-13, determining a partial order of the banking outlets, wherein the partial order is used for determining whether a first banking outlet in any two banking outlets is superior to a second banking outlet; if the auditing risk coefficient of the first bank outlet corresponding to the relevant index is less than or equal to the auditing risk coefficient of the second bank outlet corresponding to the relevant index, and the transaction risk coefficient of the first bank outlet is less than or equal to the transaction risk coefficient of the second bank outlet, determining that the first bank outlet is superior to the second bank outlet in the partial sequence;
s305-14, determining a first banking outlet and a second banking outlet corresponding to the relevant indexes according to the partial order of the banking outlets.
Specifically, (S305-14) determining, according to the partial order of the banking outlets, a first banking outlet and a second banking outlet corresponding to the relevant index, including:
taking the maximum elements of the partial orders of the bank outlets as maximum outlets corresponding to the relevant indexes, and taking the minimum elements of the partial orders of the bank outlets as minimum outlets corresponding to the relevant indexes;
when the maximum value of the auditing risk coefficient of the maximum network point corresponding to the relevant index corresponds to the relevant index is used as a maximum auditing coefficient threshold value, and the maximum value of the transaction risk coefficient of the maximum network point corresponding to the relevant index is used as a maximum transaction coefficient threshold value; taking the minimum value of the audit risk coefficient of the minimum network point corresponding to the relevant index as a minimum audit coefficient threshold value, and taking the minimum value of the transaction risk coefficient of the minimum network point corresponding to the relevant index as a minimum transaction coefficient threshold value;
when the historical audit data of the maximum network point corresponding to the relevant index is larger than or equal to the data volume threshold value, taking the maximum network point corresponding to the relevant index as a first bank network point corresponding to the relevant index; when the historical audit data of the maximum network point corresponding to the relevant index is smaller than the data path threshold, taking the bank network point of which the corresponding audit risk coefficient is smaller than or equal to the maximum audit coefficient threshold and the corresponding transaction risk coefficient is smaller than or equal to the maximum transaction coefficient threshold as a first bank network point corresponding to the relevant index;
when the historical audit data of the minimum website corresponding to the relevant index is larger than or equal to the data volume threshold value, the minimum website corresponding to the relevant index is taken as a second bank website corresponding to the relevant index; and when the historical audit data of the minimum network point corresponding to the relevant index is smaller than the data path threshold, taking the bank network point of which the corresponding audit risk coefficient is greater than or equal to the minimum audit coefficient threshold and the corresponding transaction risk coefficient is greater than or equal to the minimum transaction coefficient threshold as a second bank network point corresponding to the relevant index.
The second method comprises the following steps:
s305-21, determining the auditing risk coefficient of the relevant indexes of each bank network point according to the historical auditing data of the relevant indexes of the bank network point;
for example, the ratio of the audit data related to the risk in the historical audit data of the banking outlet corresponding to the relevant index is used as the audit risk coefficient of the banking outlet corresponding to the relevant index.
S305-22, taking the bank outlets corresponding to the relevant indexes and having the auditing risk coefficients smaller than the coefficient threshold value as the first bank outlets corresponding to the relevant indexes, and taking the bank outlets corresponding to the relevant indexes and having the auditing risk coefficients larger than or equal to the coefficient threshold value as the second bank outlets corresponding to the relevant indexes.
Specifically, (S306) determining a first corresponding relationship between the biometric threshold and the risk factor under the condition of the relevant indicator according to the historical audit data of the relevant indicator corresponding to the first banking outlet corresponding to the relevant indicator, and determining a second corresponding relationship between the biometric threshold and the risk factor under the condition of the relevant indicator according to the historical audit data of the relevant indicator corresponding to the second banking outlet corresponding to the relevant indicator, including:
s306-1, setting a plurality of biological identification discrete values;
s306-2, for each biometric discrete value, determining the proportion of audit data related to risks in the historical audit data of the relevant index corresponding to the first bank outlet corresponding to the relevant index when the biometric threshold value is set as the biometric discrete value, and taking the proportion as a first risk coefficient corresponding to the biometric discrete value; determining the occupation ratio of audit data related to risks in the historical audit data of the relevant indexes corresponding to the second bank outlets corresponding to the relevant indexes when the biometric threshold value is set as the biometric discrete value, and taking the occupation ratio as a second risk coefficient corresponding to the biometric discrete value;
s306-3, constructing a first risk coefficient function and a second risk coefficient function, wherein the independent variables of the first risk coefficient function and the second risk coefficient function are a plurality of set biological identification discrete values, the function value of each biological identification discrete value corresponding to the first risk coefficient function is equal to the first risk coefficient corresponding to the biological identification discrete value, and the function value of each biological identification discrete value corresponding to the second risk coefficient function is equal to the second risk coefficient corresponding to the biological identification discrete value;
s306-4, the first risk coefficient function and the second risk coefficient function are serialized, the continuous function corresponding to the first risk coefficient function is used as the first corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition, and the continuous function corresponding to the second risk coefficient function is used as the second corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition.
In an embodiment, the method further comprises:
s0110, for each first banking outlet corresponding to the relevant index, determining a priority coefficient corresponding to the first banking outlet according to an audit risk coefficient (and a transaction risk coefficient of the first banking outlet) of the first banking outlet corresponding to the relevant index;
s0120, according to the priority coefficient corresponding to the first bank branch corresponding to the relevant index, carrying out risk control on the real-time audit data of the bank branch.
Further, (S0120) performing risk control on the real-time audit data of the banking outlets according to the priority coefficient corresponding to the first banking outlet corresponding to the relevant index, including:
s0121, sorting the first bank outlets corresponding to the relevant indexes;
s0122, determining, according to the priority coefficient corresponding to the first banking outlet corresponding to the relevant index, the priority lower bound value corresponding to each first banking outlet according to the following formula:
w k is the preferential lower bound value, x, corresponding to the kth first banking outlet i And x j The priority coefficients corresponding to the ith and jth first banking outlets corresponding to the relevant index are respectively, and g is a real function with a value range larger than 0 and a partial derivative smaller than 0;
s0123, selecting a random number generator which accords with uniform distribution and has a value range of [0,1 ];
s0124, for each real-time auditing data of the bank outlets, generating a random number according to the selected random number generator, and taking the random number as the random number corresponding to the real-time auditing data;
s0125, selecting the maximum priority lower bound value less than the random number corresponding to the real-time audit data from the priority lower bound values corresponding to the first bank outlets;
s0126, according to the corresponding checking risk control method of the first bank outlet with the priority lower limit value equal to the maximum priority lower limit value, carrying out risk control on the real-time checking data of the bank outlet.
In an embodiment, the method further comprises:
s0210, training a prediction model by taking a risk as a prediction identifier according to historical audit data of a second bank outlet corresponding to the relevant index, wherein the historical audit data of the relevant index corresponds to the relevant index, and taking the obtained prediction model as an audit prediction model corresponding to the bank outlet;
s0220, according to the corresponding auditing and predicting model of the bank outlets, risk prediction is carried out on real-time auditing data of the bank outlets.
In S2, referring to fig. 4, the modifying the biometric threshold of the staff according to the relevant index of the client and the staff, the first corresponding relationship between the biometric threshold and the risk coefficient under the condition of each pre-stored relevant index, and the second corresponding relationship between the biometric threshold and the risk coefficient includes:
s21, acquiring a biometric threshold value of the worker stored by the bank server;
s22, determining a potential risk coefficient of the staff according to the biometric threshold of the staff, the related indexes of the client and the staff and the first corresponding relation between the biometric threshold and the risk coefficient under the condition of the related indexes;
s23, determining the potential biological identification threshold value of the worker according to the potential risk coefficient of the worker and the second corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition;
and S24, correcting the biometric threshold of the worker according to the potential biometric threshold of the worker.
It should be noted that although the operations of the method of the present invention have been described in the above embodiments and the accompanying drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the operations shown must be performed, to achieve the desired results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
Having described the method of an exemplary embodiment of the present invention, next, a bank internal risk control apparatus of an exemplary embodiment of the present invention will be described with reference to fig. 5.
The implementation of the control device for the internal risk of the bank can refer to the implementation of the method, and repeated details are omitted. The term "module" or "unit" used hereinafter may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Based on the same inventive concept, the invention also provides a device for controlling risks in a bank, as shown in fig. 5, the device comprises:
a relevant index determining module 510, configured to determine relevant indexes of a client and a worker when the client transacts a service at a website and the worker needs to check and authorize;
and a biometric threshold modification module 520, configured to modify the biometric threshold of the worker according to the relevant indexes of the client and the worker, the first corresponding relationship between the biometric threshold and the risk coefficient under the pre-stored relevant indexes, and the second corresponding relationship between the biometric threshold and the risk coefficient, where the biometric threshold is used to control internal risks of business handling.
In an embodiment, the correlation index determining module is specifically configured to:
acquiring an internal correlation diagram, wherein each node of the internal correlation diagram is a customer or a staff of a bank, each edge of the internal correlation diagram corresponds to a correlation index, the correlation index represents the correlation degree of two nodes corresponding to the edge, and the value of the correlation index is between 0 and 1;
and determining the related indexes of the client and the staff according to the internal correlation diagram.
In an embodiment, the correlation index determining module is specifically configured to:
according to the internal correlation diagram, initializing the potential correlation indexes corresponding to each node which has the direct connection with the client into the correlation indexes corresponding to the client and the corresponding edges of the nodes in the internal correlation diagram, and initializing the potential correlation indexes corresponding to each node which has no direct connection with the client into 0;
taking a set formed by all other nodes except the client in the internal correlation diagram as a node set to be determined;
and circularly executing the following steps until the relevant indexes of the client and the staff are determined:
taking out the node S with the maximum corresponding potential correlation index from the node set to be determined;
determining whether the node S is the worker;
if the node S is the worker, determining the relevant indexes of the client and the worker as potential relevant indexes corresponding to the node S, and stopping executing the cycle;
for each node T with an edge directly connected with the node S, updating the potential correlation index corresponding to the node T to be the maximum value of f (S) x r (S, T) and f (T), wherein f (T) is the potential correlation index corresponding to the node T before updating, f (S) is the potential correlation index corresponding to the node S, and r (S, T) is the correlation index corresponding to the corresponding edge in the internal correlation diagram of the node S and the node T;
and deleting the node S from the node set to be determined.
In an embodiment, referring to fig. 6, the apparatus further comprises: a correspondence determination module 530;
the corresponding relation determining module determines a first corresponding relation between the biological identification threshold and the risk coefficient and a second corresponding relation between the biological identification threshold and the risk coefficient under the condition of each relevant index according to the following method:
acquiring historical audit data of a bank;
regarding each piece of historical audit data, taking relevant indexes of a client and a corresponding worker corresponding to the historical audit data as relevant indexes corresponding to the historical audit data;
for each relevant index, taking the historical audit data of which the corresponding relevant index is equal to the relevant index as the historical audit data of the relevant index;
for each bank outlet, selecting the historical audit data of the bank outlet corresponding to the relevant indexes from the historical audit data of the relevant indexes;
according to historical audit data of the relevant indexes corresponding to each banking site, a first banking site and a second banking site corresponding to the relevant indexes are determined;
according to the historical audit data of the first bank branch corresponding to the relevant index, determining a first corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition, and according to the historical audit data of the second bank branch corresponding to the relevant index, determining a second corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition.
In an embodiment, the correspondence determining module is specifically configured to:
according to the historical audit data of the relevant indexes of each bank network point, determining the audit risk coefficient of the relevant indexes of the bank network point;
determining a transaction risk coefficient of each bank outlet according to the transaction data of each bank outlet;
determining a partial order of banking outlets, wherein the partial order is used for determining whether a first banking outlet of any two banking outlets is superior to a second banking outlet; if the auditing risk coefficient of the first banking outlet corresponding to the relevant index is less than or equal to the auditing risk coefficient of the second banking outlet corresponding to the relevant index, and the transaction risk coefficient of the first banking outlet is less than or equal to the transaction risk coefficient of the second banking outlet, determining that the first banking outlet is superior to the second banking outlet in the partial order;
and determining a first banking outlet and a second banking outlet corresponding to the relevant indexes according to the partial order of the banking outlets.
In an embodiment, the correspondence determining module is specifically configured to:
according to the historical audit data of the relevant indexes corresponding to each bank network point, determining the audit risk coefficient of the relevant indexes corresponding to the bank network point;
and taking the bank outlets with the auditing risk coefficients corresponding to the relevant indexes smaller than the coefficient threshold value as first bank outlets corresponding to the relevant indexes, and taking the bank outlets with the auditing risk coefficients corresponding to the relevant indexes larger than or equal to the coefficient threshold value as second bank outlets corresponding to the relevant indexes.
In an embodiment, the correspondence determining module is specifically configured to:
setting a plurality of biometric discrete values;
for each biometric discrete value, determining the proportion of audit data related to risks in the historical audit data of the relevant index corresponding to the first bank outlet corresponding to the relevant index when the biometric threshold value is set as the biometric discrete value, and taking the proportion as a first risk coefficient corresponding to the biometric discrete value; determining the occupation ratio of audit data related to risks in the historical audit data of the relevant indexes corresponding to the second bank outlets corresponding to the relevant indexes when the biometric threshold value is set as the biometric discrete value, and taking the occupation ratio as a second risk coefficient corresponding to the biometric discrete value;
constructing a first risk coefficient function and a second risk coefficient function, wherein the independent variables of the first risk coefficient function and the second risk coefficient function are a plurality of set biological identification discrete values, the function value of each biological identification discrete value corresponding to the first risk coefficient function is equal to the first risk coefficient corresponding to the biological identification discrete value, and the function value of each biological identification discrete value corresponding to the second risk coefficient function is equal to the second risk coefficient corresponding to the biological identification discrete value;
and the continuous function corresponding to the first risk coefficient function is used as a first corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition, and the continuous function corresponding to the second risk coefficient function is used as a second corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition.
In an embodiment, the biometric threshold modification module is specifically configured to:
acquiring a biometric threshold value of the staff stored by a bank server;
determining a potential risk coefficient of the worker according to the biometric threshold of the worker, the related indexes of the client and the worker and the first corresponding relation between the biometric threshold and the risk coefficient under the condition of the related indexes;
determining the potential biological recognition threshold value of the worker according to the potential risk coefficient of the worker and the second corresponding relation between the biological recognition threshold value and the risk coefficient under the relevant index condition;
and correcting the biometric threshold of the worker according to the potential biometric threshold of the worker.
It should be noted that although in the above detailed description several modules of the control means of the risks inside the bank are mentioned, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the modules described above may be embodied in one module according to embodiments of the invention. Conversely, the features and functions of one module described above may be further divided into embodiments by a plurality of modules.
Based on the aforementioned inventive concept, as shown in fig. 7, the present invention further provides a computer device 700, which includes a memory 710, a processor 720 and a computer program 730 stored in the memory 710 and capable of running on the processor 720, wherein the processor 720 executes the computer program 730 to implement the aforementioned method for controlling risks inside a bank.
Based on the foregoing inventive concept, the present invention proposes a computer-readable storage medium storing a computer program which, when executed by a processor, implements the aforementioned method of controlling risk inside a bank.
Based on the aforementioned inventive concept, the present invention proposes a computer program product comprising a computer program which, when executed by a processor, implements a method of controlling risks inside a bank.
The method and the device for controlling the internal risk of the bank determine the relevant indexes of a client and a worker; according to the relevant indexes of the client and the staff, the first corresponding relation between the biological recognition threshold and the risk coefficient and the second corresponding relation between the biological recognition threshold and the risk coefficient under the condition of each pre-stored relevant index, the biological recognition threshold of the staff is corrected, so that when the client transacts business at a website and requires the authorization of the staff, the internal risk of the bank is effectively controlled, the business transaction of the client is ensured to be smoothly carried out, the property safety of the client is protected, and powerful technical support is provided for the digital risk control of the bank.
According to the technical scheme, the data acquisition, storage, use, processing and the like meet the relevant regulations of national laws and regulations.
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 and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: those skilled in the art can still make modifications or changes to the embodiments described in the foregoing embodiments, or make equivalent substitutions for some features, within the scope of the disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (19)
1. A method for controlling risks in a bank is characterized by comprising the following steps:
when a client transacts business at a website and staff verification and authorization are required, determining relevant indexes of the client and the staff;
and correcting the biometric threshold value of the staff according to the relevant indexes of the client and the staff, the first corresponding relation between the biometric threshold value and the risk coefficient under the condition of each pre-stored relevant index and the second corresponding relation between the biometric threshold value and the risk coefficient, wherein the biometric threshold value is used for controlling the internal risk of business handling.
2. The method of claim 1, wherein determining the metrics related to the customer and the staff comprises:
acquiring an internal correlation diagram, wherein each node of the internal correlation diagram is a customer or a staff of a bank, each edge of the internal correlation diagram corresponds to a correlation index, the correlation index represents the correlation degree of two nodes corresponding to the edge, and the value of the correlation index is between 0 and 1;
and determining the related indexes of the client and the staff according to the internal correlation diagram.
3. The method as claimed in claim 2, wherein determining the correlation index between the client and the staff member according to the internal correlation diagram comprises:
according to the internal correlation diagram, initializing the potential correlation indexes corresponding to each node which has the direct connection with the client into the correlation indexes corresponding to the client and the corresponding edges of the nodes in the internal correlation diagram, and initializing the potential correlation indexes corresponding to each node which has no direct connection with the client into 0;
taking a set formed by all other nodes except the client in the internal correlation diagram as a node set to be determined;
and circularly executing the following steps until the relevant indexes of the client and the staff are determined:
taking out the node S with the maximum corresponding potential correlation index from the node set to be determined;
determining whether the node S is the worker;
if the node S is the worker, determining the relevant indexes of the client and the worker as potential relevant indexes corresponding to the node S, and stopping executing the cycle;
for each node T with an edge directly connected with the node S, updating the potential correlation index corresponding to the node T to be the maximum value of f (S) multiplied by r (S, T) and f (T), wherein f (T) is the potential correlation index corresponding to the node T before updating, f (S) is the potential correlation index corresponding to the node S, and r (S, T) is the correlation index corresponding to the corresponding edge in the internal correlation diagram of the node S and the node T;
and deleting the node S from the node set to be determined.
4. The method of claim 1, further comprising determining a first correspondence of the biometric threshold value to the risk factor and a second correspondence of the biometric threshold value to the risk factor for each of the relevant indicators as follows:
acquiring historical audit data of a bank;
regarding each piece of historical audit data, taking relevant indexes of a client and a corresponding worker corresponding to the historical audit data as relevant indexes corresponding to the historical audit data;
for each relevant index, taking the historical audit data of which the corresponding relevant index is equal to the relevant index as the historical audit data of the relevant index;
for each bank outlet, selecting the historical audit data of the bank outlet corresponding to the relevant index from the historical audit data of the relevant index;
according to the historical audit data of the relevant indexes corresponding to each bank website, determining a first bank website and a second bank website corresponding to the relevant indexes;
according to the historical audit data of the first bank outlet corresponding to the relevant index, the first corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition is determined, and according to the historical audit data of the second bank outlet corresponding to the relevant index, the second corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition is determined.
5. The method as claimed in claim 4, wherein determining the first banking outlet and the second banking outlet corresponding to the relevant index according to the historical audit data of the relevant index corresponding to each banking outlet comprises:
according to the historical audit data of the relevant indexes corresponding to each bank network point, determining the audit risk coefficient of the relevant indexes corresponding to the bank network point;
determining a transaction risk coefficient of each bank branch according to the transaction data of each bank branch;
determining a partial order of banking outlets, wherein the partial order is used for determining whether a first banking outlet of any two banking outlets is superior to a second banking outlet; if the auditing risk coefficient of the first banking outlet corresponding to the relevant index is less than or equal to the auditing risk coefficient of the second banking outlet corresponding to the relevant index, and the transaction risk coefficient of the first banking outlet is less than or equal to the transaction risk coefficient of the second banking outlet, determining that the first banking outlet is superior to the second banking outlet in the partial order;
and determining a first banking outlet and a second banking outlet corresponding to the relevant indexes according to the partial order of the banking outlets.
6. The method as claimed in claim 4, wherein determining the first banking outlet and the second banking outlet corresponding to the relevant index according to the historical audit data of the relevant index corresponding to each banking outlet comprises:
according to the historical audit data of the relevant indexes corresponding to each bank network point, determining the audit risk coefficient of the relevant indexes corresponding to the bank network point;
and taking the bank outlets with the auditing risk coefficients corresponding to the relevant indexes smaller than the coefficient threshold value as first bank outlets corresponding to the relevant indexes, and taking the bank outlets with the auditing risk coefficients corresponding to the relevant indexes larger than or equal to the coefficient threshold value as second bank outlets corresponding to the relevant indexes.
7. The method as claimed in claim 4, wherein determining a first corresponding relationship between the biometric threshold and the risk factor under the condition of the relevant index according to the historical audit data of the relevant index corresponding to the first banking outlet corresponding to the relevant index, and determining a second corresponding relationship between the biometric threshold and the risk factor under the condition of the relevant index according to the historical audit data of the relevant index corresponding to the second banking outlet corresponding to the relevant index comprises:
setting a plurality of biometric discrete values;
for each biometric discrete value, determining the proportion of audit data related to risks in historical audit data of the relevant index corresponding to the first bank outlet corresponding to the relevant index when the biometric threshold value is set as the biometric discrete value, and taking the proportion as a first risk coefficient corresponding to the biometric discrete value; determining the occupation ratio of audit data related to risks in the historical audit data of the relevant indexes corresponding to the second bank outlets corresponding to the relevant indexes when the biometric threshold value is set as the biometric discrete value, and taking the occupation ratio as a second risk coefficient corresponding to the biometric discrete value;
constructing a first risk coefficient function and a second risk coefficient function, wherein the independent variables of the first risk coefficient function and the second risk coefficient function are a plurality of set biological identification discrete values, the function value of each biological identification discrete value corresponding to the first risk coefficient function is equal to the first risk coefficient corresponding to the biological identification discrete value, and the function value of each biological identification discrete value corresponding to the second risk coefficient function is equal to the second risk coefficient corresponding to the biological identification discrete value;
and the continuous function corresponding to the first risk coefficient function is used as a first corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition, and the continuous function corresponding to the second risk coefficient function is used as a second corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition.
8. The method of claim 1, wherein modifying the biometric threshold of the worker according to the correlation index between the customer and the worker, the first correspondence between the biometric threshold and the risk factor under each of the pre-stored correlation indexes, and the second correspondence between the biometric threshold and the risk factor comprises:
acquiring a biometric threshold value of the worker stored by a bank server;
determining a potential risk coefficient of the worker according to the biometric threshold of the worker, the relevant indexes of the customer and the worker and the first corresponding relation between the biometric threshold and the risk coefficient under the condition of the relevant indexes;
determining the potential biological recognition threshold value of the worker according to the potential risk coefficient of the worker and the second corresponding relation between the biological recognition threshold value and the risk coefficient under the relevant index condition;
and correcting the biometric threshold of the worker according to the potential biometric threshold of the worker.
9. An internal risk control device for a bank, comprising:
the system comprises a correlation index determining module, a correlation index determining module and a correlation index determining module, wherein the correlation index determining module is used for determining correlation indexes of a client and a staff when the client transacts business at a website and the staff need to check and authorize;
and the biological recognition threshold value correcting module is used for correcting the biological recognition threshold value of the staff according to the relevant indexes of the client and the staff, the first corresponding relation between the biological recognition threshold value and the risk coefficient under the condition of each pre-stored relevant index and the second corresponding relation between the biological recognition threshold value and the risk coefficient, wherein the biological recognition threshold value is used for controlling the internal risk of business handling.
10. The apparatus of claim 9, wherein the correlation indicator determination module is specifically configured to:
acquiring an internal correlation diagram, wherein each node of the internal correlation diagram is a customer or a staff of a bank, each edge of the internal correlation diagram corresponds to a correlation index, the correlation index represents the correlation degree of two nodes corresponding to the edge, and the value of the correlation index is between 0 and 1;
and determining the related indexes of the client and the staff according to the internal correlation diagram.
11. The apparatus of claim 10, wherein the correlation indicator determination module is specifically configured to:
according to the internal correlation diagram, initializing the potential correlation indexes corresponding to each node which has the direct connection with the client into the correlation indexes corresponding to the client and the corresponding edges of the nodes in the internal correlation diagram, and initializing the potential correlation indexes corresponding to each node which has no direct connection with the client into 0;
taking a set formed by all other nodes except the client in the internal correlation diagram as a node set to be determined;
and circularly executing the following steps until the relevant indexes of the client and the staff are determined:
taking out the node S with the maximum corresponding potential correlation index from the node set to be determined;
determining whether the node S is the worker;
if the node S is the worker, determining the relevant indexes of the client and the worker as potential relevant indexes corresponding to the node S, and stopping executing the cycle;
for each node T with an edge directly connected with the node S, updating the potential correlation index corresponding to the node T to be the maximum value of f (S) multiplied by r (S, T) and f (T), wherein f (T) is the potential correlation index corresponding to the node T before updating, f (S) is the potential correlation index corresponding to the node S, and r (S, T) is the correlation index corresponding to the corresponding edge in the internal correlation diagram of the node S and the node T;
and deleting the node S from the node set to be determined.
12. The apparatus of claim 9, further comprising: a correspondence determining module;
the corresponding relation determining module determines a first corresponding relation between the biological identification threshold and the risk coefficient and a second corresponding relation between the biological identification threshold and the risk coefficient under the conditions of all relevant indexes according to the following method:
acquiring historical audit data of a bank;
for each piece of historical audit data, taking relevant indexes of a client and a corresponding worker corresponding to the historical audit data as relevant indexes corresponding to the historical audit data;
for each relevant index, taking historical audit data of the relevant index equal to the corresponding relevant index as the historical audit data of the relevant index;
for each bank outlet, selecting the historical audit data of the bank outlet corresponding to the relevant indexes from the historical audit data of the relevant indexes;
according to the historical audit data of the relevant indexes corresponding to each bank website, determining a first bank website and a second bank website corresponding to the relevant indexes;
according to the historical audit data of the first bank branch corresponding to the relevant index, determining a first corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition, and according to the historical audit data of the second bank branch corresponding to the relevant index, determining a second corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition.
13. The apparatus of claim 12, wherein the correspondence determining module is specifically configured to:
according to the historical audit data of the relevant indexes of each bank network point, determining the audit risk coefficient of the relevant indexes of the bank network point;
determining a transaction risk coefficient of each bank outlet according to the transaction data of each bank outlet;
determining a partial order of banking outlets, wherein the partial order is used for determining whether a first banking outlet of any two banking outlets is superior to a second banking outlet; if the auditing risk coefficient of the first bank outlet corresponding to the relevant index is less than or equal to the auditing risk coefficient of the second bank outlet corresponding to the relevant index, and the transaction risk coefficient of the first bank outlet is less than or equal to the transaction risk coefficient of the second bank outlet, determining that the first bank outlet is superior to the second bank outlet in the partial sequence;
and determining a first banking outlet and a second banking outlet corresponding to the relevant indexes according to the partial order of the banking outlets.
14. The apparatus of claim 12, wherein the correspondence determining module is specifically configured to:
according to the historical audit data of the relevant indexes of each bank network point, determining the audit risk coefficient of the relevant indexes of the bank network point;
and taking the bank outlets with the auditing risk coefficients corresponding to the relevant indexes smaller than the coefficient threshold value as first bank outlets corresponding to the relevant indexes, and taking the bank outlets with the auditing risk coefficients corresponding to the relevant indexes larger than or equal to the coefficient threshold value as second bank outlets corresponding to the relevant indexes.
15. The apparatus of claim 12, wherein the correspondence determining module is specifically configured to:
setting a plurality of biometric discrete values;
for each biometric discrete value, determining the proportion of audit data related to risks in historical audit data of the relevant index corresponding to the first bank outlet corresponding to the relevant index when the biometric threshold value is set as the biometric discrete value, and taking the proportion as a first risk coefficient corresponding to the biometric discrete value; determining the occupation ratio of audit data related to risks in the historical audit data of the relevant indexes corresponding to the second bank outlets corresponding to the relevant indexes when the biological identification threshold is set as the biological identification discrete value, and taking the occupation ratio as a second risk coefficient corresponding to the biological identification discrete value;
constructing a first risk coefficient function and a second risk coefficient function, wherein the independent variables of the first risk coefficient function and the second risk coefficient function are a plurality of set biological identification discrete values, the function value of each biological identification discrete value corresponding to the first risk coefficient function is equal to the first risk coefficient corresponding to the biological identification discrete value, and the function value of each biological identification discrete value corresponding to the second risk coefficient function is equal to the second risk coefficient corresponding to the biological identification discrete value;
and the continuous function corresponding to the first risk coefficient function is used as a first corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition, and the continuous function corresponding to the second risk coefficient function is used as a second corresponding relation between the biological identification threshold value and the risk coefficient under the relevant index condition.
16. The apparatus of claim 9, wherein the biometric threshold modification module is specifically configured to:
acquiring a biometric threshold value of the staff stored by a bank server;
determining a potential risk coefficient of the worker according to the biometric threshold of the worker, the related indexes of the client and the worker and the first corresponding relation between the biometric threshold and the risk coefficient under the condition of the related indexes;
determining the potential biological recognition threshold value of the worker according to the potential risk coefficient of the worker and the second corresponding relation between the biological recognition threshold value and the risk coefficient under the relevant index condition;
and correcting the biometric threshold of the worker according to the potential biometric threshold of the worker.
17. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 8 when executing the computer program.
18. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 8.
19. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1 to 8.
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| CN202210890826.4A CN115238289A (en) | 2022-07-27 | 2022-07-27 | Method and device for controlling internal risks of bank |
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| CN202210890826.4A CN115238289A (en) | 2022-07-27 | 2022-07-27 | Method and device for controlling internal risks of bank |
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