CN114926260A

CN114926260A - Method and system for processing audit risk of bank outlets

Info

Publication number: CN114926260A
Application number: CN202210444759.3A
Authority: CN
Inventors: 朱江波
Original assignee: Bank of China Ltd
Current assignee: Bank of China Ltd
Priority date: 2022-04-26
Filing date: 2022-04-26
Publication date: 2022-08-19

Abstract

The invention provides a method and a system for processing audit risks of bank outlets, which relate to the technical field of big data processing, and comprise the following steps: for each bank outlet in a predetermined area, determining a risk category vector and a main risk category of the bank outlet; clustering the bank outlets in a preset area to obtain a plurality of bank outlet subsets; for each audit item, determining a probability density function of the sub-set of the bank outlets about the audit duration of the audit item according to the audit duration data; for each bank outlet, determining the auditor representative of each audit item; acquiring the audit data represented by the audit teller in real time; determining the risk of the audit; storing the audit data with risks into a block chain node of a bank outlet, uploading the audit data to a bank server, generating risk prompt information, sending the risk prompt information to an audit teller representative, receiving feedback information with a digital signature of the audit teller representative, and storing the feedback information into a block chain.

Description

Method and system for processing audit risk of bank outlets

Technical Field

The invention relates to the technical field of big data processing, in particular to a method and a system for processing audit risks of bank outlets.

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 the business processing process of a bank outlet, the auditing of bank staff can often avoid many problems of customer transactions, such as false identity, information errors and the like. However, manual operations are problematic and careless, which may cause risks.

In view of the above, a technical solution that can overcome the above-mentioned drawbacks and effectively handle the auditing risks of banking outlets is urgently needed.

Disclosure of Invention

In order to solve the problems in the prior art, the invention provides a method and a system for processing the auditing risk of a bank outlet.

In a first aspect of the embodiments of the present invention, a method for processing an audit risk of a banking outlet is provided, including:

for each banking outlet in a predetermined area, determining a risk category vector and a main risk category of the banking outlet;

clustering the banking outlets in the preset area according to the risk category vector and the main risk category of each banking outlet to obtain a plurality of banking outlet subsets;

for each audit item, acquiring audit data of the audit item in a subset of the bank outlets, extracting audit duration data of the audit item from the audit data, and determining a probability density function of the subset of the bank outlets about the audit duration of the audit item according to the audit duration data;

for each bank outlet, determining the auditor representative of each audit item according to the audit data of the subset of the bank outlet to which the bank outlet belongs about each audit item;

acquiring the audit data represented by the audit teller in real time; determining the risk of the audit at this time according to the audit data represented by the audit teller and the probability density function of the audit duration of the audit item of the subset of the bank outlets to which the bank outlets belong; storing the audit data with risks into a block chain node of a bank outlet, uploading the audit data to a bank server, generating risk prompt information, sending the risk prompt information to the auditor representative, receiving feedback information with a digital signature of the auditor representative, and storing the feedback information into a block chain.

In a second aspect of the embodiments of the present invention, a system for processing risk audit of banking outlets is provided, including:

the data processing module is used for determining a risk category vector and a main risk category of each banking outlet in a predetermined area;

the clustering module is used for clustering the bank outlets in the preset area according to the risk category vector and the main risk category of each bank outlet to obtain a plurality of bank outlet subsets;

the probability density function determining module is used for acquiring the auditing data of the auditing item in the bank branch subset for each auditing item, extracting auditing time length data for auditing the auditing item from the auditing data, and determining the probability density function of the bank branch subset about the auditing time length of the auditing item according to the auditing time length data;

the audit teller representative determining module is used for determining audit teller representatives of all audit items according to audit data of a subset of the bank outlets to which the bank outlets belong about all audit items for each bank outlet;

the audit risk processing module is used for acquiring audit data represented by the audit teller in real time; determining the risk of the audit at this time according to the audit data represented by the audit teller and the probability density function of the audit duration of the audit item of the subset of the bank outlets to which the bank outlets belong; storing the audit data with risks into a block chain node of a bank outlet, uploading the audit data to a bank server, generating risk prompt information, sending the risk prompt information to the auditor representative, receiving feedback information with a digital signature of the auditor representative, and storing the feedback information into a block chain.

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 in the memory and executable on the processor, where the processor implements a method for processing audit risks at a banking outlet when executing the computer program.

In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements a method for processing an audit risk of a banking outlet.

In a fifth aspect of the embodiments of the present invention, a computer program product is provided, where the computer program product includes a computer program, and when the computer program is executed by a processor, the computer program implements an audit risk processing method of a banking outlet.

The method and the system for processing the auditing risk of the bank outlets determine the risk category vectors and the main risk categories of the bank outlets by analyzing the bank outlets; further clustering the bank outlets in the preset area to obtain a plurality of bank outlet subsets; for each audit item, analyzing audit data, extracting audit duration data of the audit item from the audit data, and determining a probability density function of the sub-set of the bank outlets about the audit duration of the audit item according to the audit duration data; according to the audit data of the subset of the bank outlets about each audit item, determining an audit teller representative of each audit item; and finally, determining the risk represented by the teller to be audited based on the probability density function, and processing the audit risk.

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 an audit risk processing method of a banking outlet according to an embodiment of the present invention.

Fig. 2 is a schematic diagram illustrating a specific process for determining a risk category vector and a main risk category of a banking outlet according to an embodiment of the present invention.

Fig. 3 is a schematic flow chart of clustering the banking outlets in the predetermined area according to an embodiment of the present invention.

Fig. 4 is a detailed flowchart illustrating clustering of banking outlets in a predetermined area according to an embodiment of the present invention.

FIG. 5 is a schematic diagram illustrating a detailed flow of the exemplary auditor representative for determining each audit item, according to one embodiment of the invention.

Fig. 6 is a schematic diagram of a specific process of determining a very large auditor among all auditors of a banking outlet according to an embodiment of the present invention.

Fig. 7 is a schematic view of an audit risk processing system of a banking outlet according to an embodiment of the present invention.

Fig. 8 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 a number of 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 system for processing the auditing risk of a bank outlet are provided, and the method and the system relate to the technical field of big data processing.

In a business processing scenario of a bank outlet, a bank auditor usually conforms to a certain probability distribution when auditing various business data. This risk is often implied when the length of the audit operation is too long or too short. According to the invention, the abnormal handling behavior of the auditor is found through data analysis, so that the risk is reduced to a certain extent.

The auditing item comprises auditing face identification information, identity card information, filled transaction information and the like. The auditing duration is influenced by many factors, such as specific auditing items, and risk auditing skills of bank auditors, and risks possibly involved. Under normal conditions, each type of auditing time of a bank outlet accords with certain distribution, the auditing time can be regarded as a sample of the distribution in practice, correspondingly, when the number of the samples is enough, the distribution can be accurately estimated, then auditing risks are processed, the effect of manual auditing is effectively ensured, business risks are reduced, and digital risk control of the bank is realized.

In the technical scheme of the application, the acquisition, storage, use, processing and the like of the face recognition information, the identity card information and the filled transaction information meet the relevant regulations of national laws and regulations.

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 an audit risk processing method of a banking outlet according to an embodiment of the present invention. As shown in fig. 1, the method includes:

s1, determining the risk category vector and the main risk category of each banking outlet in the preset area;

s2, clustering the bank outlets in the preset area according to the risk category vector and the main risk category of each bank outlet to obtain a plurality of bank outlet subsets;

s3, for each audit item, acquiring audit data of the audit item in the subset of the bank outlets, extracting audit duration data of the audit item from the audit data, and determining a probability density function of the subset of the bank outlets about the audit duration of the audit item according to the audit duration data;

s4, for each bank outlet, determining the auditor representative of each audit item according to the audit data of the subset of the bank outlet to which the bank outlet belongs about each audit item;

s5, acquiring the audit data represented by the auditor in real time; determining the risk of the audit at this time according to the audit data represented by the audit teller and the probability density function of the audit duration of the audit item of the subset of the bank outlets to which the bank outlets belong; storing the audit data with risks into a block chain node of a bank outlet, uploading the audit data to a bank server, generating risk prompt information, sending the risk prompt information to an audit teller representative, receiving feedback information with a digital signature of the audit teller representative, and storing the feedback information into a block chain.

In order to explain the above-mentioned auditing risk processing method of banking outlets more clearly, each step is described in detail below.

In S1, referring to fig. 2, for each banking site in the predetermined area, the specific method for determining the risk category vector and the main risk category of the banking site is as follows:

s101, determining risk coefficients of the bank outlets corresponding to various risk categories according to historical transaction data of the bank outlets;

s102, taking the risk category with the maximum difference between the corresponding risk coefficient and the corresponding set threshold value as the main risk category of the bank outlet;

s103, setting a risk category vector of the banking website, wherein components of the risk category vector correspond to risk categories of the banking website one by one, and the value of each component is equal to a risk coefficient of the banking website corresponding to the risk category corresponding to the component.

In an embodiment, S101 determines, according to the historical transaction data of each banking outlet, a risk coefficient of each risk category corresponding to the banking outlet, specifically:

acquiring transaction data of the banking outlet in a first time period; determining the proportion of the transaction data related to each risk category in the transaction data of each day in the first period as the risk coefficient of the bank website corresponding to each risk category on each day;

for each risk category, determining the variance of the risk coefficients of the banking outlet corresponding to the risk category based on the risk coefficients of the banking outlet corresponding to the risk category on all days in the first period;

selecting an acceptable risk coefficient error threshold value epsilon and a probability P that the acceptable risk coefficient error is larger than epsilon, and determining the number-of-days threshold value of the bank website corresponding to each risk category, wherein the number-of-days threshold value of the bank website corresponding to the ith risk category is

Wherein sigma _i Is the variance of the risk coefficient of the ith risk category corresponding to the banking outlet;

for each risk category, selecting a second period with the number of days greater than the threshold of the number of days of the banking website corresponding to the risk category, and taking the average value of the risk coefficients of the banking website corresponding to the risk category on all days in the second period as the risk coefficient of the banking website corresponding to the risk category, wherein for each day in the second period, the proportion of the transaction data related to the risk category in the transaction data of the day is taken as the risk coefficient of the banking website corresponding to the risk category on the day.

In S2, referring to fig. 3, the specific method for clustering the banking outlets in the predetermined area according to the risk category vector and the main risk category of each banking outlet to obtain a plurality of banking outlet subsets includes:

s201, determining a distance function of the banking outlets, wherein the independent variable of the distance function is any two banking outlets, and the corresponding function value is the distance between two risk category vectors corresponding to the two banking outlets;

s202, according to the distance function and the main risk category of the bank outlets, clustering the bank outlets in the preset area to obtain a plurality of bank outlet subsets.

In an embodiment, referring to fig. 4, (S202) according to the distance function and the main risk category of the banking outlets, clustering the banking outlets in the predetermined area to obtain a plurality of banking outlet subsets, specifically:

s2021, selecting a clustering algorithm to cluster the bank outlets in the preset area according to the distance function of the bank outlets to obtain a plurality of bank outlet subsets;

s2022, for each obtained bank outlet subset, selecting the main risk category with the largest number of the bank outlets corresponding to the bank outlet subset from all the main risk categories, and determining the number of the bank outlets of the bank outlet subset corresponding to the selected main risk category as a centralized index of the bank outlet subset;

s2023, for each obtained banking outlet subset, determining whether the following condition t is satisfied: and if the ratio of the centralized index of the bank outlet subset to the number of the bank outlets of the bank outlet subset is not met, continuing to cluster the bank outlet subset by using a clustering algorithm until each newly generated bank outlet subset meets the condition t.

In S3, for each audit item, acquiring audit data of the audit item in the subset of banking outlets, extracting audit duration data of the audit item from the audit data, and determining a probability density function of the subset of banking outlets about the audit duration of the audit item according to the audit duration data.

In one embodiment, for each audit item, a confidence interval is set according to a probability density function of the sub-set of the bank outlets about the audit duration of the audit item and a preset probability value A; the specific method comprises the following steps:

calculating the mean value of the audit duration of the audit item according to the probability density function of the audit duration of the audit item;

acquiring a minimum value n of values satisfying the following conditions: 1/2, the integral of the probability density function from the mean value to the value is greater than or equal to the preset probability value A;

obtaining a maximum value m among values satisfying the following conditions: 1/2, where the integral of the probability density function of the item from the value to the mean value is greater than or equal to the preset probability value A;

setting a confidence interval as [ m, n ];

and when the transaction amount processed by the bank server is greater than the transaction amount threshold value, issuing the confidence interval corresponding to the audit item to the banking outlets of the banking outlet subset.

In one embodiment, a function may be established according to the confidence interval, where the input of the function includes the service class and the corresponding service transaction duration, and the function determines whether the service transaction duration is within the confidence interval corresponding to the service class, and if not, the function outputs a risk, otherwise, the function is risk-free.

In an actual application scenario, the function can be compiled into an executable program and issued to a bank outlet, and the bank outlet determines whether business handling is risky or not based on the function, so that the probability density function can be ensured not to be acquired by other people.

Furthermore, the probability density function of the auditing duration of each auditing item of the banking outlet subset can be directly used as the probability density function of the auditing duration of each auditing item of each banking outlet of the banking outlet subset. And correcting the probability density function of the banking outlets about the auditing duration of each auditing item based on the business handling data of each banking outlet. For each audit item, for example, a mean value a and a variance b are determined according to sample data of the audit duration of the bank website about the audit item, then a probability density function (the mean value of the probability density function is c, and the variance is d) of the audit duration of the bank website about the audit item is corrected, that is, the abscissa of the probability density function is deformed into b/d, and the ordinate of the probability density function is deformed into the original d/b, and then the deformed probability density function is translated by a-c b/d.

In a practical application scenario, the above-mentioned S1-S3 are completed by the bank server.

In S4, referring to fig. 5, for each banking node, according to the audit data of the banking node subset to which the banking node belongs about each audit item, a specific method for determining that the audit teller of each audit item represents is as follows:

s401, for each audit item, determining a risk coefficient of the bank outlet about the audit item and each risk category according to audit data about the audit item of a bank outlet subset to which the bank outlet belongs; setting a risk category vector corresponding to the audit item, wherein each component of the risk category vector corresponds to each risk category one by one, and the value of each component is equal to the risk coefficient of the bank outlet about the audit item and the risk category corresponding to the component;

s402, for each auditor of the bank outlet, obtaining audit data of the auditor; determining the risk coefficient of the auditor about each risk category according to the audit data of the auditor; setting a risk category vector corresponding to the auditor; each component of the risk category vector corresponds to each risk category one by one, and the value of each component is equal to the risk coefficient of the auditor about the risk category corresponding to the component;

s403, for each audit item, determining the partial order of the audit teller about the audit item according to the risk category vector corresponding to the audit item and the risk category vector corresponding to each audit teller of the bank website, wherein the partial order is used for determining whether a first audit teller is superior to a second audit teller in any two audit tellers;

s404, determining a maximum audit teller in all audit tellers of the bank outlet according to the partial order of the audit teller about the audit item, wherein the maximum audit teller is a maximum element of the partial order;

s405, taking the maximum audit teller in all the audit tellers of the bank network as the audit teller representative of the audit item.

In an embodiment, the method for determining the risk coefficients of the banking outlets about the audit item and the risk categories, and the method for determining the risk coefficients of the auditors about the risk categories may refer to the method for determining the risk coefficients of the banking outlets corresponding to the risk categories.

In an embodiment, (S403) for each audit item, according to the risk category vector corresponding to the audit item and the risk category vector corresponding to each audit teller at the banking site, a detailed method for determining the partial order of the audit teller with respect to the audit item includes:

when the partial order of the auditor about the audit item is determined, for any two auditors of the bank outlet, calculating a first difference value between a risk category vector of a first auditor of the two auditors and a risk category vector of a second auditor of the two auditors, and calculating a second difference value between the risk category vector of the first auditor and the risk category vector corresponding to the audit item, and if each component of the first difference value is less than or equal to 0 and a component of the second difference value is less than 0, determining that the first auditor is better than the second auditor.

It should be noted that the partial order maximum element is in the set corresponding to the partial order, and there is no other element close to the maximum element.

In an embodiment, referring to fig. 6, (S404) according to the partial order of the auditor about the audit item, a maximum auditor among all the auditors of the bank site is determined, which is as follows:

s4041, initializing the maximum identification corresponding to each auditor of all auditors to be possible;

s4042, sequentially setting the maximum identifier corresponding to the audit teller as possible for each audit teller of all audit tellers, and initializing the audit teller to be compared corresponding to the audit teller as all other audit tellers except the audit teller in all audit tellers;

s4043, selecting each to-be-compared audit teller corresponding to the audit teller in sequence, and confirming whether the to-be-compared audit teller is superior to the audit teller; if the auditor to be compared is superior to the auditor, setting the corresponding maximum identification of the auditor as no; if the audit teller is superior to the audit teller to be compared, setting the corresponding maximum identification of the audit teller to be compared as no; otherwise, the corresponding maximum identification of the audit teller and the corresponding maximum identification of the audit teller to be compared are kept unchanged;

s4044, if all the auditors to be compared of the auditors are confirmed not to be superior to the auditors, the auditors are determined as the maximum auditors in all the auditors.

In S5, acquiring audit data of the auditor representative in real time; determining the risk of the audit at this time according to the audit data represented by the audit teller and the probability density function of the audit duration of the audit item of the subset of the bank outlets to which the bank outlets belong; the specific method for storing the audit data with risks in the block chain node of the bank outlet, uploading the audit data to the bank server, generating risk prompt information, sending the risk prompt information to the auditor representative, receiving feedback information with a digital signature of the auditor representative, and storing the feedback information in the block chain comprises the following steps:

if the current bank outlets store the confidence interval of the audit item, determining whether the audit has risks based on the confidence interval, if the audit duration of the audit item is not in the confidence interval, determining that the audit is risky, otherwise, determining that the audit has no risks;

if the current bank website does not store the confidence interval of the audit item, the bank website sends the audit data to a bank server, the bank server determines the probability corresponding to the audit data according to the corresponding probability density function, and if the probability is smaller than a preset probability threshold value, the bank server considers that the bank server is risky; otherwise, it is risk-free.

Further, after daily closing of the bank outlets, the bank server determines the risk of each teller and each type of business based on all the audit data of all the audit tellers of all the bank outlets audited in the day. Storing the at-risk audit data into a block link point of the bank server. And the risk prompt message is sent to the teller, the feedback message of the digital signature of the teller is received, and the feedback message is stored in the block chain.

For each teller, audit data for various audit items of the teller is obtained. And for various audit items, determining the probability corresponding to the audit duration data of the audit item of the teller according to the audit duration data of the teller about the audit item and the probability distribution function of the audit time of the audit item. And for the teller, uploading a plurality of pieces of audit data with the probability smaller than the threshold value in the corresponding audit data to a block chain, sending risk prompt information to the teller, and receiving feedback information of the digital signature of the teller.

For each type of audit item, screening multiple audits with the minimum probability of audit duration data from the audit data of the audit item, and determining the multiple audits as risky. And sending the risk prompt information to the corresponding teller and receiving the feedback information of the digital signature of the teller.

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, an audit risk processing system for a banking outlet of an exemplary embodiment of the present invention is next described with reference to fig. 7.

The implementation of the risk auditing and processing system of a bank outlet can refer to the implementation of the method, and repeated parts are not described again. 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 an audit risk processing system of a bank outlet, as shown in fig. 7, the system comprises:

a data processing module 710, configured to determine, for each banking outlet in a predetermined area, a risk category vector and a main risk category of the banking outlet;

a clustering module 720, configured to cluster the banking outlets in the predetermined area according to the risk category vector and the main risk category of each banking outlet to obtain a plurality of banking outlet subsets;

a probability density function determining module 730, configured to obtain, for each audit item, audit data of the audit item in the subset of the bank outlets, extract audit duration data of the audit item from the audit data, and determine, according to the audit duration data, a probability density function of the subset of the bank outlets with respect to the audit duration of the audit item;

the audit teller representative determining module 740 is configured to determine, for each banking outlet, an audit teller representative of each audit item according to audit data about each audit item of a banking outlet subset to which the banking outlet belongs;

the audit risk processing module 750 is used for acquiring audit data represented by the auditor in real time; determining the risk of the audit at this time according to the audit data represented by the audit teller and the probability density function of the audit duration of the audit item of the subset of the bank outlets to which the bank outlets belong; storing the audit data with risks into a block chain node of a bank outlet, uploading the audit data to a bank server, generating risk prompt information, sending the risk prompt information to an audit teller representative, receiving feedback information with a digital signature of the audit teller representative, and storing the feedback information into a block chain.

In an embodiment, the data processing module is specifically configured to:

determining the risk coefficient of each risk category corresponding to each bank outlet according to the historical transaction data of each bank outlet;

taking the risk category with the maximum difference between the corresponding risk coefficient and the corresponding set threshold value as the main risk category of the bank outlet;

and setting a risk category vector of the banking website, wherein components of the risk category vector correspond to risk categories of the banking website one by one, and the value of each component is equal to the risk coefficient of the banking website corresponding to the risk category corresponding to the component.

In an embodiment, the clustering module is specifically configured to:

determining a distance function of the banking outlets, wherein the independent variable of the distance function is any two banking outlets, and the corresponding function value is the distance between two risk category vectors corresponding to the two banking outlets;

and clustering the banking outlets in the preset area according to the distance function and the main risk category of the banking outlets to obtain a plurality of banking outlet subsets.

In an embodiment, the probability density function determination module is further configured to:

for each audit item, setting a confidence interval according to a probability density function of the sub-set of the bank outlets about the audit duration of the audit item and a preset probability value A; wherein, include:

acquiring a minimum value n of values satisfying the following conditions: 1/2, where the integral of the probability density function from the mean value to the value is greater than or equal to the preset probability value A;

obtaining a maximum value m among values satisfying the following conditions: is less than the average value, and the integral of the probability density function of the audit item from the value to the average value is greater than or equal to 1/2 of the preset probability value A;

setting a confidence interval as [ m, n ];

and when the transaction amount processed by the bank server is greater than the transaction amount threshold value, issuing the confidence interval corresponding to the audit item to the bank outlets of the bank outlet subset.

In an embodiment, the auditor representative determination module is specifically configured to:

for each audit item, determining the risk coefficient of the bank outlet about the audit item and each risk category according to the audit data about the audit item of the bank outlet subset to which the bank outlet belongs; setting a risk category vector corresponding to the audit item, wherein each component of the risk category vector corresponds to each risk category one by one, and the value of each component is equal to the risk coefficient of the bank outlet about the audit item and the risk category corresponding to the component;

for each audit teller of the bank outlet, acquiring audit data of the audit teller; determining the risk coefficient of the auditor about each risk category according to the audit data of the auditor; setting a risk category vector corresponding to the auditor; each component of the risk category vector corresponds to each risk category one by one, and the value of each component is equal to the risk coefficient of the auditor about the risk category corresponding to the component;

for each audit item, determining the partial order of the audit teller about the audit item according to the risk category vector corresponding to the audit item and the risk category vector corresponding to each audit teller of the bank website, wherein the partial order is used for determining whether a first audit teller is superior to a second audit teller in any two audit tellers;

determining a maximum audit teller in all audit tellers of the bank outlet according to the partial order of the audit teller about the audit item, wherein the maximum audit teller is a maximum element of the partial order;

and taking the maximum audit teller in all the audit tellers of the bank network as the audit teller representative of the audit item.

In an embodiment, the risk audit processing module is specifically configured to:

if the current bank website does not store the confidence interval of the audit item, the bank website sends the audit data to a bank server, the bank server determines the probability corresponding to the audit data according to the corresponding probability density function, and if the probability is smaller than a preset probability threshold value, the bank website considers that the bank website is at risk; otherwise, it is risk-free.

It should be noted that although several modules of an audit risk processing system for a banking outlet are mentioned in the above detailed description, such partitioning 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. 8, the present invention further provides a computer apparatus 800, which includes a memory 810, a processor 820, and a computer program 830 stored in the memory 810 and operable on the processor 820, wherein the processor 820 implements the aforementioned method for processing the audit risk of the banking outlet when executing the computer program 830.

Based on the above inventive concept, the present invention provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the method for processing the audit risk of the banking outlet.

Based on the foregoing inventive concept, the present invention proposes a computer program product comprising a computer program, which when executed by a processor implements a method for auditing risk handling at a banking outlet.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, 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 is 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 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.

Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the following descriptions are only illustrative and not restrictive, and that the scope of the present invention is not limited to the above embodiments: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present 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

1. An auditing risk processing method for banking outlets is characterized by comprising the following steps:

clustering the bank outlets in the preset area according to the risk category vector and the main risk category of each bank outlet to obtain a plurality of bank outlet subsets;

acquiring auditing data of the teller auditing representative in real time; determining the risk of the audit at this time according to the audit data represented by the audit teller and the probability density function of the audit duration of the audit item of the subset of the bank outlets to which the bank outlets belong; storing the audit data with risks into a block chain node of a bank outlet, uploading the audit data to a bank server, generating risk prompt information, sending the risk prompt information to an audit teller representative, receiving feedback information with a digital signature of the audit teller representative, and storing the feedback information into a block chain.

2. The method of claim 1, wherein determining a risk category vector and a major risk category for each banking site in a predetermined area comprises:

determining the risk coefficient of each risk category corresponding to each banking outlet according to the historical transaction data of each banking outlet;

3. The method as claimed in claim 1, wherein clustering the banking outlets in the predetermined area according to the risk category vector and the major risk category of each banking outlet to obtain a plurality of banking outlet subsets comprises:

4. The method of claim 1, further comprising:

for each audit item, setting a confidence interval according to a probability density function of the subset of the banking outlets about the audit duration of the audit item and a preset probability value A; wherein, include:

setting a confidence interval as [ m, n ];

5. The method as claimed in claim 1, wherein for each banking outlet, determining the auditor representative of each audit item according to the audit data about each audit item of the banking outlet subset to which the banking outlet belongs, comprises:

determining a maximum audit teller in all audit tellers of the bank outlets according to the partial order of the audit teller about the audit item, wherein the maximum audit teller is a maximum element of the partial order;

6. The method of claim 5, wherein for each audit item, determining a partial order of the auditor with respect to the audit item based on the risk category vector corresponding to the audit item and the risk category vector corresponding to each auditor at the banking outlet, comprises:

7. The method of claim 1, wherein the audit data is obtained in real time from the auditor representative; determining the risk of the current audit according to the audit data represented by the audit teller and the probability density function of the audit duration of the audit item of the subset of the bank outlets to which the bank outlets belong; storing audit data with risks into a block chain node of a bank outlet, uploading the audit data to a bank server, generating risk prompt information, sending the risk prompt information to an audit teller representative, receiving feedback information with a digital signature of the audit teller representative, and storing the feedback information into a block chain, wherein the method comprises the following steps:

8. An audit risk processing system for a banking outlet, comprising:

the data processing module is used for determining a risk category vector and a main risk category of each banking outlet in a preset area;

the audit teller representative determining module is used for determining audit teller representatives of all audit items according to audit data of a bank outlet subset to which the bank outlet belongs and about all audit items for each bank outlet;

the audit risk processing module is used for acquiring audit data represented by the audit teller in real time; determining the risk of the current audit according to the audit data represented by the audit teller and the probability density function of the audit duration of the audit item of the subset of the bank outlets to which the bank outlets belong; storing the audit data with risks into a block chain node of a bank outlet, uploading the audit data to a bank server, generating risk prompt information, sending the risk prompt information to an audit teller representative, receiving feedback information with a digital signature of the audit teller representative, and storing the feedback information into a block chain.

9. The system of claim 8, wherein the data processing module is specifically configured to:

10. The system of claim 8, wherein the clustering module is specifically configured to:

and clustering the bank outlets in the preset area according to the distance function and the main risk category of the bank outlets to obtain a plurality of bank outlet subsets.

11. The system of claim 8, wherein the probability density function determination module is further configured to:

setting a confidence interval as [ m, n ];

12. The system of claim 8, wherein the audit teller representation determination module is specifically configured to:

for each auditor of the bank outlets, acquiring audit data of the auditor; determining the risk coefficient of the auditor about each risk category according to the audit data of the auditor; setting a risk category vector corresponding to the auditor; each component of the risk category vector corresponds to each risk category one by one, and the value of each component is equal to the risk coefficient of the auditor about the risk category corresponding to the component;

13. The system of claim 12, wherein the audit teller representative determination module is specifically configured to:

14. The system of claim 8, wherein the audit risk processing module is specifically configured to:

15. 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 of claims 1 to 7 when executing the computer program.

16. 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 of claims 1 to 7.

17. 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 7.