CN114757675A - Credit customer abnormity identification method and device, storage medium and electronic equipment - Google Patents
Credit customer abnormity identification method and device, storage medium and electronic equipment Download PDFInfo
- Publication number
- CN114757675A CN114757675A CN202210295126.0A CN202210295126A CN114757675A CN 114757675 A CN114757675 A CN 114757675A CN 202210295126 A CN202210295126 A CN 202210295126A CN 114757675 A CN114757675 A CN 114757675A
- Authority
- CN
- China
- Prior art keywords
- credit
- customer
- capital
- proportion
- total
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/03—Credit; Loans; Processing thereof
Landscapes
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Engineering & Computer Science (AREA)
- Finance (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Economics (AREA)
- Marketing (AREA)
- Technology Law (AREA)
- Development Economics (AREA)
- Computer Security & Cryptography (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The application provides a credit customer abnormity identification method and device, a storage medium and electronic equipment, wherein the method comprises the following steps: the method comprises the steps of obtaining the deduction preparation promotion amount, the economic capital occupation amount and the risk adjustment capital return rate corresponding to each credit business of a credit customer, calculating the deduction preparation promotion proportion, the economic capital occupation proportion and the total risk adjustment capital return rate corresponding to the credit customer, judging whether the credit customer is an abnormal customer or not based on the deduction preparation promotion proportion, the economic capital occupation proportion and the total risk adjustment capital return rate corresponding to the credit customer, achieving abnormal identification of the credit customer, and generating abnormal prompt information under the condition that the credit customer is determined to be the abnormal customer so that credit business personnel can conduct risk investigation, reducing bank risks, improving efficiency of risk investigation and further improving the profitability of a bank.
Description
Technical Field
The application relates to the technical field of computer application, in particular to a credit customer abnormity identification method and device, a storage medium and electronic equipment.
Background
Commercial banks, as financial enterprises aiming at profit, raise funds through liabilities and convert the liabilities into assets to obtain profits through functions of loan issuance and the like. After the loan is issued, if the credit customer is abnormal, namely the key indexes of the profitability (the reduction preparation calculation amount, the economic capital occupation amount and the risk adjustment capital return rate) of the credit customer are abnormal, the bank is caused to have a large risk.
Therefore, how to provide a technical scheme capable of identifying an abnormal credit customer to reduce bank risks is a problem that needs to be solved urgently by those skilled in the art at present.
Disclosure of Invention
The application provides a credit customer abnormity identification method and device, a storage medium and electronic equipment, and aims to realize identification of an abnormal credit customer so as to reduce bank risks.
In order to achieve the above object, the present application provides the following technical solutions:
a credit customer anomaly identification method, comprising:
acquiring a deduction value preparation advance amount, an economic capital occupation amount and an insurance adjustment capital return rate corresponding to each credit business of a credit customer;
calculating the proportion of the credit customer corresponding to the reduced value preparation accounting improvement based on the reduced value preparation accounting improvement amount corresponding to each credit business of the credit customer;
calculating the economic capital occupation proportion corresponding to the credit customer based on the economic capital occupation amount corresponding to each credit business of the credit customer;
calculating the risk adjustment capital total rate of return corresponding to the credit client based on the risk adjustment capital rate of return corresponding to each credit business of the credit client;
judging whether the credit client is an abnormal client or not based on the deduction preparation calculation and promotion proportion, the economic capital occupation proportion and the total risk-adjusted capital return rate corresponding to the credit client;
and in the case that the credit client is determined to be an abnormal client, generating abnormal prompt information.
The method optionally, wherein the calculating the percentage of the credit customer to be credited for the deduction based on the amount of the credit customer to be credited for each credit transaction includes:
summing the deduction preparation accounting and fund-drawing amount corresponding to each credit business of the credit customer to obtain the deduction preparation accounting and total fund-drawing amount corresponding to the credit customer;
calculating the total loan balance based on the loan balance of each credit business of the credit customer;
calculating a deduction value preparation accounting and offering proportion corresponding to the credit customer based on the total loan balance and the deduction value preparation accounting and offering total amount;
the calculating the economic capital occupation proportion corresponding to the credit customer based on the economic capital occupation amount corresponding to each credit business of the credit customer comprises the following steps:
summing the economic capital occupation amount corresponding to each credit business of the credit customer to obtain the economic capital occupation total amount corresponding to the credit customer;
calculating the economic capital occupation proportion corresponding to the credit customer based on the loan balance and the economic capital occupation total amount;
the calculating the total risk adjusted capital return rate corresponding to the credit client based on the risk adjusted capital return rate corresponding to each credit business of the credit client comprises the following steps:
and calculating the risk adjustment capital return rate corresponding to each credit business of the credit client according to the preset weight corresponding to each credit business to obtain the total risk adjustment capital return rate corresponding to the credit client.
The method optionally includes the step of determining whether the credit client is an abnormal client based on the reduced value preparation promotion proportion, the economic capital occupation proportion and the risk adjustment total capital return rate corresponding to the credit client, including:
determining whether the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derating readiness contribution proportion is greater than a second proportional threshold;
determining the credit customer as an anomalous customer if the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derated readiness quote proportion is greater than a second proportional threshold.
Optionally, the above method, wherein the generating the abnormal prompt information includes:
and calling a preset abnormal prompt template to generate abnormal prompt information based on the deduction preparation plan-to-mention proportion, the economic capital occupation proportion, the risk adjustment total return rate and the business data of each credit business of the credit customer corresponding to the credit customer.
Optionally, the above method, after generating the abnormal prompt information, further includes:
sending the abnormal prompt information to a credit service personnel terminal to prompt credit service personnel to check in time;
and obtaining the checking result fed back by the credit service personnel.
A credit customer anomaly identification apparatus, comprising:
the first acquisition unit is used for acquiring the deduction preparation calculation amount, the economic capital occupation amount and the risk adjustment capital return rate corresponding to each credit business of the credit customer;
the first calculation unit is used for calculating the reduction preparation accounting and raising proportion corresponding to the credit customer based on the reduction preparation accounting and raising amount corresponding to each credit business of the credit customer;
the second calculation unit is used for calculating the economic capital occupation proportion corresponding to the credit client based on the economic capital occupation amount corresponding to each credit business of the credit client;
the third calculation unit is used for calculating the risk adjustment capital total rate of return corresponding to the credit client based on the risk adjustment capital rate of return corresponding to each credit business of the credit client;
the judging unit is used for judging whether the credit client is an abnormal client or not based on the deduction preparation calculation and improvement proportion, the economic capital occupation proportion and the risk adjustment total capital return rate corresponding to the credit client;
and the generating unit is used for generating abnormal prompt information under the condition that the credit client is determined to be an abnormal client.
Optionally, the above apparatus, wherein the first calculating unit is specifically configured to:
summing the deduction preparation accounting and fund-drawing amount corresponding to each credit business of the credit customer to obtain the deduction preparation accounting and total fund-drawing amount corresponding to the credit customer;
calculating the total loan balance based on the loan balance of each credit business of the credit customer;
calculating a deduction value preparation accounting and offering proportion corresponding to the credit customer based on the total loan balance and the deduction value preparation accounting and offering total amount;
the second computing unit is specifically configured to:
summing the economic capital occupation amount corresponding to each credit business of the credit customer to obtain the economic capital occupation total amount corresponding to the credit customer;
calculating the economic capital occupation proportion corresponding to the credit customer based on the loan balance and the economic capital occupation total amount;
the third computing unit is specifically configured to:
and calculating the risk adjustment capital return rate corresponding to each credit business of the credit client according to the preset weight corresponding to each credit business to obtain the total risk adjustment capital return rate corresponding to the credit client.
Optionally, the determining unit is specifically configured to:
determining whether the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derating readiness contribution proportion is greater than a second proportional threshold;
determining the credit customer as an abnormal customer if the total risk adjusted capital return rate is less than a return rate threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derating readiness to credit proportion is greater than a second proportional threshold.
A storage medium storing a set of instructions, wherein the set of instructions, when executed by a processor, implement a credit customer anomaly identification method as described above.
An electronic device, comprising:
a memory for storing at least one set of instructions;
a processor for executing a set of instructions stored in said memory, said set of instructions being executable to implement a credit customer exception identification method as described above.
Compared with the prior art, the method has the following advantages:
the application provides a credit customer abnormity identification method and device, a storage medium and electronic equipment, wherein the method comprises the following steps: the method comprises the steps of calculating the reduction preparation plan-raising amount, the economic capital occupation amount and the risk adjustment capital return rate corresponding to each credit business of a credit customer by obtaining the reduction preparation plan-raising amount, the economic capital occupation amount and the risk adjustment capital return rate corresponding to each credit business of the credit customer, judging whether the credit customer is an abnormal customer or not based on the reduction preparation plan-raising amount, the economic capital occupation amount and the risk adjustment capital total return rate corresponding to the credit customer, realizing abnormal identification of the credit customer, and generating abnormal prompt information under the condition that the credit customer is determined to be the abnormal customer so as to facilitate risk investigation of credit business personnel, thereby reducing bank risks, improving the efficiency of the risk investigation and further improving the profit capacity of the bank.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a method for identifying credit customer anomalies according to the present application;
FIG. 2 is a flow chart of another method of identifying credit customer anomalies according to the present application;
FIG. 3 is a flow chart of another method of identifying credit customer anomalies according to the present application;
FIG. 4 is a schematic diagram of the structure of a credit customer abnormality recognition device provided by the present application;
fig. 5 is a schematic structural diagram of an electronic device provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the disclosure of the present application are only used for distinguishing different systems, modules or units, and are not used for limiting the order or interdependence relationship of the functions executed by the systems, modules or units.
It is noted that references to "a", "an", and "the" modifications in the disclosure herein are exemplary rather than limiting, and those skilled in the art will understand that "one or more" will be understood unless the context clearly dictates otherwise.
The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, distributed computing environments that include any of the above systems or devices, and the like.
In the present embodiment, for convenience of understanding, the terms related to the present application are described as follows:
RAROC (RiskAdjusted Return On Capital) is a comprehensive index that considers revenue, risk and Capital, and the result can be regarded as the expected profit obtained by consuming unit Capital.
The credit customer preparation for calculating the reduction value is that a bank really accounts the operation result, keeps steady operation and continuous development and meets the information disclosure requirement in order to resist risks, and the bank calculates the amount of the expected loss according to certain standards, methods and programs aiming at the credit customer calculation result based on the reduction loss on the basis of reasonable estimation and judgment.
The financial capital record of a credit customer is the capital required by a bank to resist future unexpected losses and maintain normal operations during normal operations management.
The application is operational with numerous general purpose or special purpose computing device environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multi-processor apparatus, distributed computing environments that include any of the above devices or equipment, and the like.
The embodiment of the application provides a credit customer exception identification method, which can be applied to various system platforms, wherein an execution subject of the method can be a computer terminal or a processor of various mobile devices, and a flow chart of the method is shown in fig. 1, and specifically comprises the following steps:
s101, obtaining a deduction value preparation advance amount, an economic capital occupation amount and an insurance adjustment capital return rate corresponding to each credit business of a credit customer.
In this embodiment, the banking system stores in advance the customer information and credit transaction issuance data of each credit customer. In this embodiment, the customer information includes, but is not limited to, a customer identification, which may be, for example, an organization code.
The credit service issuance data includes, but is not limited to, the credit service issuance deadline, the issuance amount, and the issuance credit item.
In the embodiment, each credit business corresponding to the credit customer is determined based on the customer information and the credit business issuing data of the credit customer, so that the deduction preparation increase amount, the economic capital occupation amount and the risk adjustment capital return rate corresponding to each credit business of the credit customer are obtained based on the business identification of each credit business.
It should be noted that the service identifier is used to uniquely identify a credit service.
In the embodiment, within the monitoring interval, the deduction value corresponding to each credit business of the credit customer is acquired according to the preset period to prepare the credit amount, the economic capital occupation amount and the risk adjustment capital return rate. Wherein the preset period is determined based on the issuance time and the recovery time of each credit service. For example, a month end time point of each month after the credit service is issued is determined as the preset period. The monitoring interval is determined based on the credit service issuance time and the credit service reclaim interval.
It should be noted that the reduction preparation calculation amount, the economic capital occupation amount and the risk adjustment return rate corresponding to each credit business are stored in different banking systems in advance, and the banking systems periodically calculate the reduction preparation calculation amount, the economic capital occupation amount and the risk adjustment return rate of each credit business.
In the method provided by the embodiment of the application, the economic capital occupation amount, the reduced value preparation calculation and improvement amount and the RAROC (Risk adjusted capital return rate) of each credit customer are calculated and generated by different bank systems, and the same customer only has a unique identifier, so that the data calculated by the same customer in different bank systems are compared and screened through the unique identifier (such as an organization code and the like) of the customer, and the reduced value preparation calculation and improvement amount, the economic capital occupation amount and the risk adjusted capital return rate of the credit customer at a certain statistical time point can be obtained simultaneously.
In this embodiment, an association relationship network may also be constructed for the deduction preparation increase amount, capital occupation amount and risk adjustment return rate corresponding to each credit operation of the credit customer.
S102, calculating the deduction preparation credit-earning proportion corresponding to the credit customer based on the deduction preparation credit-earning amount corresponding to each credit business of the credit customer.
In this embodiment, the deduction preparation accounting and loan proportion corresponding to the credit customer is calculated based on the deduction preparation accounting amount and the loan balance corresponding to each credit transaction of the credit customer.
Specifically, the method comprises the following steps:
summing the deduction preparation accounting and withdrawal amount corresponding to each credit business of the credit customer to obtain the deduction preparation accounting and withdrawal total amount corresponding to the credit customer;
calculating the total loan balance based on the loan balance of each credit business of the credit customer;
and calculating the corresponding deduction preparation accounting and offering proportion of the credit customer based on the total balance of the loan and the deduction preparation accounting and offering total amount.
In this embodiment, the deduction preparation credit sum corresponding to each credit operation of the credit customer is accumulated to obtain a deduction preparation credit sum, the loan balance of each credit operation of the credit customer is accumulated to obtain a total loan balance, the deduction preparation credit sum corresponding to the credit customer is calculated based on the total loan balance and the deduction preparation credit sum, and specifically, the deduction preparation credit sum corresponding to the credit customer is obtained by dividing the deduction preparation credit sum by the total loan balance.
S103, calculating the economic capital occupation proportion corresponding to the credit customer based on the economic capital occupation amount corresponding to each credit business of the credit customer.
In the embodiment, the economic capital occupation proportion corresponding to the credit customer is calculated based on the economic capital occupation amount and the loan balance corresponding to each credit business of the credit customer.
Specifically, the method comprises the following steps:
summing the economic capital occupation amount corresponding to each credit business of the credit customer to obtain the economic capital occupation total amount corresponding to the credit customer;
and calculating the corresponding economic capital occupation proportion of the credit customer based on the loan balance and the total economic capital occupation amount.
In this embodiment, the economic basic occupation amount corresponding to each credit service of the credit customer is accumulated to obtain the total economic capital occupation amount, the economic capital occupation proportion corresponding to the credit customer is calculated based on the loan balance and the total economic capital occupation amount, and specifically, the economic capital occupation proportion corresponding to the credit customer is obtained by dividing the total economic capital occupation amount by the loan balance.
And S104, calculating the risk adjustment capital total return rate corresponding to the credit customer based on the risk adjustment capital return rate corresponding to each credit business of the credit customer.
In the implementation, the total risk adjusted capital return rate corresponding to the credit customer is calculated based on the risk adjusted capital return rate corresponding to each credit business of the credit customer, and specifically, the total risk adjusted capital return rate corresponding to each credit business of the credit customer is calculated according to the preset weight corresponding to each credit business of the credit customer, so as to obtain the total risk adjusted capital return rate corresponding to the credit customer.
The preset weight corresponding to each credit service is an artificially set numerical value and can be adjusted according to requirements.
And S105, judging whether the credit client is an abnormal client or not based on the deduction preparation calculation and improvement proportion, the economic capital occupation proportion and the total risk adjustment capital return rate corresponding to the credit client.
In this embodiment, whether the credit customer is an abnormal customer is determined based on the reduction preparation plan extension proportion, the economic capital occupation proportion, and the total risk-adjusted capital return rate corresponding to the credit customer.
Referring to fig. 2, the process of determining whether a credit client is an abnormal client based on the credit client's corresponding reduction preparation plan extension ratio, economic capital occupation ratio and risk adjustment total return rate includes the following steps:
s201, judging whether the total risk adjustment capital return rate is smaller than a return rate threshold, whether the economic capital occupation ratio is larger than a first proportion threshold and whether the reduction preparation cost ratio is larger than a second proportion threshold, if so, executing S202, and if not, executing S203.
In this embodiment, it is determined whether the total risk adjusted capital return rate is smaller than a return rate threshold, whether the economic capital occupation ratio is larger than a first ratio threshold, and whether a reduction preparation cost ratio is larger than a second ratio threshold, where the return rate threshold, the first ratio threshold, and the second ratio threshold are artificially set values and may be adjusted according to requirements.
Illustratively, the threshold rate of return may be 10%, the economic capital occupancy rate is 10%, and the reduction ready to be accounted for rate is 5%.
S202, determining the credit customer as an abnormal customer.
And if the risk adjusted capital return rate is less than the return rate threshold, the economic capital occupation proportion is greater than the first proportional threshold and the reduction preparation plan improvement proportion is greater than the second proportional threshold, determining the credit customer as the abnormal customer.
And S203, determining that the credit client is not an abnormal client.
And if the risk adjusted capital return rate is not less than the return rate threshold, the economic capital occupation proportion is greater than the first proportion threshold or the reduction preparation credit rate is not greater than the second proportion threshold, determining that the credit client is not the abnormal client.
And S106, generating abnormal prompt information under the condition that the credit client is determined to be an abnormal client.
In this embodiment, an exception prompt template is preset.
In the present embodiment, in the case where it is determined that the credit customer is an abnormal customer, the abnormality prompt information is generated. Specifically, a preset exception prompting template is called to generate exception prompting information based on a deduction preparation promotion proportion, an economic capital occupation proportion, a risk adjustment capital total return rate and business data of each credit business of the credit customer corresponding to the credit customer.
In this embodiment, the deduction preparation plan-to-plan proportion, the economic capital occupation proportion, the risk adjustment total return rate and the business data of each credit business of the credit customer corresponding to the credit customer are determined, a writing position in the exception prompting template is determined, and the deduction preparation plan-to-plan proportion, the economic capital occupation proportion, the risk adjustment total return rate and the business data of each credit business of the credit customer corresponding to the credit customer are written into the corresponding writing position, so that the exception prompting information is generated.
It should be noted that, in the exception prompting message, the deduction preparation promotion proportion, the economic capital occupation proportion, the total risk adjustment capital return rate, and the business data of each credit business of the credit customer are arranged according to the preset rules, for example, the arrangement result is: reporting period-credit customer name-credit business issuing time-issuing amount-credit business product information-credit customer at bank rating information-credit customer at bank debt item rating information-credit customer at bank rating information-credit customer five-level risk classification result-credit business cost-credit business income-quality mortgage guarantee information (if any) -risk adjustment capital total return rate-economic capital occupation ratio-reduction ready-to-add ratio-economic capital occupation amount-reduction ready-to-add amount-credit customer loan balance.
According to the credit customer abnormity identification method provided by the embodiment of the application, the deduction preparation promotion amount, the economic capital occupation amount and the risk adjustment capital return rate corresponding to each credit business of a credit customer are obtained, the deduction preparation promotion proportion, the economic capital occupation proportion and the risk adjustment capital return rate corresponding to the credit customer are calculated, and therefore whether the credit customer is an abnormal customer or not is judged based on the deduction preparation promotion proportion, the economic capital occupation proportion and the risk adjustment capital return rate corresponding to the credit customer, abnormity identification of the credit customer is achieved, and abnormity prompt information is generated under the condition that the credit customer is determined to be the abnormal customer, so that risk investigation is conveniently conducted by credit business personnel, bank risks are reduced, the risk investigation efficiency is improved, and the bank profitability is improved.
According to the credit customer abnormity identification method provided by the embodiment of the application, implementation, operation and maintenance risks are reduced and the business purchasing workload is reduced through standardized operation and implementation.
Referring to fig. 3, in this embodiment, after step S106, the method for identifying an exception of a credit customer according to the embodiment of the present application may further include the following steps:
s301, sending the abnormal prompt information to a credit business personnel terminal to prompt credit business personnel to check in time.
In this embodiment, after the exception prompting information is generated, the exception prompting information may be sent to a terminal of a credit service staff to prompt the credit service staff to check in time.
In this embodiment, the credit service personnel performs a verification process on the content in the exception prompting information, where the verification process includes, but is not limited to: prompting a bank customer manager to do daily regulation actions of management after loan, updating a financial statement after customer audit in time, and doing customer rating continuity management; contacting the customer, renegotiating product pricing, and increasing the fund transaction amount in the bank settlement account; adding a guarantor; adding a pledge of quality control, and adding a deposit and payment guarantee fund; recovering the enterprise loan, adjusting the credit customer risk classification result and the like.
S302, obtaining the checking result fed back by the credit service personnel.
In this embodiment, the credit service staff feeds back the checking result after finishing checking the abnormal prompt information.
In this embodiment, the checking result fed back by the credit service staff is obtained.
Optionally, the checking result may be stored.
According to the credit customer abnormity identification method provided by the embodiment of the application, abnormity prompt information can be sent to the credit business personnel terminal to prompt the credit business personnel to check in time, so that bank risks are reduced.
The method for identifying an exception of a credit client provided in the embodiment of the present application is exemplified as follows:
a. and identifying and acquiring the issuing data of the credit customer in the bank credit business from the bank system according to the corresponding organization code of the credit customer, and obtaining the issuing deadline and the issuing amount of the credit customer credit business and the issuing credit variety of the credit customer in the fixed monitoring interval.
b. According to the debt item number identification corresponding to each credit business in the banking business data, abstracting and identifying the corresponding relation of each credit client and each credit business, and forming a credit fund issuing-economic capital occupation-deduction value preparation plan-basic mapping path.
c. Based on profit assessment indexes RAROC formed by credit customers after bank credit funds are issued based on consideration of risk management requirements such as income, expense, cost and the like, the profit assessment indexes RAROC of the credit customers are matched with economic preparation occupation and reduction preparation accounting at the monitoring time point of the associated credit business, and are combined to form an association relationship network of the core indexes of the profit value creation process of the credit customers in an integral linkage mode. For example: the company A is used as a monitored credit enterprise, information such as guarantee information, offset pledge information, cost, income and expense of credit business within the stage time of a credit client and the like is used as profit creation value process data of the company A and displayed in parallel according to a unique organization code of the company A, and the information is brought into a monitoring range together to form profit creation value basic data of the monitoring credit client, wherein the profit creation value basic data comprises basic information, internal rating information, debt item rating information, asset risk classification results, RAROC, reduction value preparation and investment and economic capital occupation of the company A.
d. And determining a related profit creation value monitoring interval according to the credit service issuing time of the credit customer, setting an initial value as the month end point of each month after the credit service is issued, wherein the corresponding monitoring interval is the month end point of 1 month before the credit service is withdrawn after the loan is issued.
e. Based on the unique organization code and the unique debt number of the credit client, each debt item of the credit client is determined to be included in the monitoring list.
f. And extracting basic information, internal rating information, debt rating information, asset risk classification results, RAROC, reduction preparation calculation and economic capital occupation data corresponding to the credit customers according to the monitoring account list, and carrying out centralized monitoring on the account running water in the monitoring range and the monitoring interval.
g. According to system rules, the deduction preparation calculation and improvement amount and the economic capital occupation amount in the profit creation value indexes corresponding to each credit business of the credit customer are identified, the economic capital occupation proportion and the deduction preparation calculation and improvement proportion are formed through processing, and whether the profit creation value key indexes RAROC, the economic capital occupation proportion and the deduction preparation calculation and improvement proportion of the credit customer are abnormal or not is judged, and the situation that related requirements in bank management cannot be met is achieved. The specific identification rule is as follows: the credit customer related index simultaneously satisfies the following conditions: RAROC index is less than 10%; economic capital occupancy is higher than 10%; the reduction preparation is higher than 5 percent; .
h. And according to the output result of the previous step, arranging relevant fields of the system for creating key index situations according with abnormal profit values to form a credit customer profit creation value information backtracking track. The track should contain the fields of report period-credit customer name-credit service issuance time-issuance amount-credit service product information-credit customer at bank rating information-credit customer at bank debt item rating information-credit customer at bank-five-level risk classification result-credit service cost-credit service income-proof guarantee information (if any) -credit customer RAROC-credit customer economic capital occupation ratio-credit customer reduced value preparation extension ratio-credit customer economic capital occupation amount-credit customer reduced value preparation extension amount-credit customer loan balance.
i. And creating a key index backtracking track according to the profit value, generating a data processing result and processing a prompt item.
j. And (4) putting the public business process system, automatically pushing the data processing result and the related prompt to a credit business worker, and requiring the credit business worker to perform strong response (checking and disposing within a specified period) according to the existing process system of the bank.
k. And the credit service personnel responds to the flow, and carries out offline check treatment on the data result and the prompt items (prompting a bank client manager to carry out daily regulation action after loan, updating a financial statement after client audit in time, carrying out client rating continuity management, contacting the client, renegotiating product pricing, increasing the fund transaction amount in a bank settlement account, adding a guarantor, adding a quality security material, additionally storing and paying a guarantee fund, recovering an enterprise loan, adjusting a credit client risk classification result and the like), and checking related service risks.
And l, business personnel timely take relevant corresponding measures, and reply to the checking result in the flow after implementing and completing relevant management measures, and finally complete the dynamic monitoring and troubleshooting work of the whole credit customer profit creation value key index (RAROC, economic capital occupation and deduction preparation record).
It should be noted that while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous.
It should be understood that the various steps recited in the method embodiments disclosed herein may be performed in a different order and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the disclosure is not limited in this respect.
Corresponding to the method shown in fig. 1, an embodiment of the present application further provides a credit customer anomaly identification apparatus, where the credit customer anomaly identification system is constructed in advance based on a deployment rule, and is used for specifically implementing the method shown in fig. 1, and a schematic structural diagram of the apparatus is shown in fig. 4, and specifically includes:
a first obtaining unit 401, configured to obtain a reduction preparation advance amount, an economic capital occupation amount, and an risk adjustment capital return rate corresponding to each credit business of a credit customer;
a first calculating unit 402, configured to calculate a reduced value preparation-to-credit ratio corresponding to the credit customer based on the reduced value preparation-to-credit amount corresponding to each credit transaction of the credit customer;
a second calculating unit 403, configured to calculate an economic capital occupation proportion corresponding to the credit customer based on the economic capital occupation amount corresponding to each credit business of the credit customer;
a third calculating unit 404, for calculating the risk adjusted total return of capital corresponding to the credit client based on the risk adjusted total return of capital corresponding to each credit business of the credit client;
a judging unit 405, configured to judge whether the credit client is an abnormal client based on the deduction preparation calculation proportion, the economic capital occupation proportion and the risk adjustment total capital return rate corresponding to the credit client;
and the generating unit 406 is used for generating abnormal prompt information in the case that the credit client is determined to be an abnormal client.
In the credit customer abnormality identification device provided by the embodiment of the application, the credit customer is judged whether the credit customer is an abnormal customer or not by acquiring the reduction preparation calculation amount, the economic capital occupation amount and the risk adjustment capital return rate corresponding to each credit business of the credit customer and calculating the reduction preparation calculation ratio, the economic capital occupation ratio and the risk adjustment capital total return rate corresponding to the credit customer, so that the abnormality identification of the credit customer is realized, and the abnormality prompt information is generated under the condition that the credit customer is determined to be the abnormal customer, so that the risk investigation of credit business personnel is facilitated, the bank risk is reduced, the risk investigation efficiency is improved, and the bank profit capacity is improved.
In an embodiment of the present application, based on the foregoing solution, the first computing unit 402 is specifically configured to:
summing the deduction preparation and deduction sum corresponding to each credit business of the credit customer to obtain the deduction preparation and deduction total sum corresponding to the credit customer;
calculating the total loan balance based on the loan balance of each credit business of the credit customer;
calculating a deduction value preparation accounting and offering proportion corresponding to the credit customer based on the total loan balance and the deduction value preparation accounting and offering total amount;
the second calculating unit 403 is specifically configured to:
summing the economic capital occupation amount corresponding to each credit business of the credit customer to obtain the economic capital occupation total amount corresponding to the credit customer;
calculating the economic capital occupation proportion corresponding to the credit customer based on the loan balance and the economic capital occupation total amount;
the third calculating unit 404 is specifically configured to:
and calculating the risk adjustment capital return rate corresponding to each credit business of the credit client according to the preset weight corresponding to each credit business to obtain the total risk adjustment capital return rate corresponding to the credit client.
In an embodiment of the present application, based on the foregoing solution, the determining unit 405 is specifically configured to:
determining whether the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derating readiness contribution proportion is greater than a second proportional threshold;
determining the credit customer as an anomalous customer if the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derated readiness quote proportion is greater than a second proportional threshold.
In an embodiment of the present application, based on the foregoing scheme, the generating unit 406 is specifically configured to:
and calling a preset abnormal prompt template to generate abnormal prompt information based on the deduction preparation plan-to-mention proportion, the economic capital occupation proportion, the risk adjustment total return rate and the business data of each credit business of the credit customer corresponding to the credit customer.
In an embodiment of the present application, based on the foregoing scheme, the method may further include:
the sending unit is used for sending the abnormal prompt information to a credit business personnel terminal so as to prompt credit business personnel to check in time;
and the second acquisition unit is used for acquiring the checking result fed back by the credit service staff.
The embodiment of the application also provides a storage medium, wherein the storage medium stores an instruction set, and when the instruction set is operated, the credit customer exception identification method disclosed in any embodiment above is executed.
An embodiment of the present application further provides an electronic device, a schematic structural diagram of which is shown in fig. 5, and specifically includes a memory 501, configured to store at least one set of instruction sets; a processor 502 for executing a set of instructions stored in the memory, the set of instructions being executable to implement a credit customer exception identification method as disclosed in any of the above embodiments.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
While several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
The foregoing description is only exemplary of the preferred embodiments disclosed herein and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other combinations of features described above or equivalents thereof without departing from the spirit of the disclosure. For example, the above features and (but not limited to) technical features having similar functions disclosed in the present disclosure are mutually replaced to form the technical solution.
Claims (10)
1. A credit client exception identification method, comprising:
acquiring a deduction preparation improvement amount, an economic capital occupation amount and an insurance adjustment capital return rate corresponding to each credit business of a credit customer;
calculating the deduction preparation credit-calculation proportion corresponding to the credit customer based on the deduction preparation credit-calculation amount corresponding to each credit operation of the credit customer;
calculating the economic capital occupation proportion corresponding to the credit customer based on the economic capital occupation amount corresponding to each credit business of the credit customer;
calculating the risk adjustment capital total rate of return corresponding to the credit client based on the risk adjustment capital rate of return corresponding to each credit business of the credit client;
judging whether the credit client is an abnormal client or not based on the deduction preparation calculation and promotion proportion, the economic capital occupation proportion and the total risk-adjusted capital return rate corresponding to the credit client;
and in the case that the credit client is determined to be an abnormal client, generating abnormal prompt information.
2. The method according to claim 1 wherein said calculating a reduced value readiness extension ratio for said credit customer based on a reduced value readiness extension amount for each credit transaction of said credit customer comprises:
summing the deduction preparation accounting and fund-drawing amount corresponding to each credit business of the credit customer to obtain the deduction preparation accounting and total fund-drawing amount corresponding to the credit customer;
calculating the total loan balance based on the loan balance of each credit business of the credit customer;
calculating a deduction value preparation accounting and offering proportion corresponding to the credit customer based on the total loan balance and the deduction value preparation accounting and offering total amount;
the calculating the economic capital occupation proportion corresponding to the credit customer based on the economic capital occupation amount corresponding to each credit business of the credit customer comprises the following steps:
summing the economic capital occupation amount corresponding to each credit business of the credit customer to obtain the economic capital occupation total amount corresponding to the credit customer;
calculating the economic capital occupation proportion corresponding to the credit customer based on the loan balance and the economic capital occupation total amount;
said calculating a risk adjusted total return of capital for said credit customer based on said risk adjusted total return of capital for each credit transaction of said credit customer comprising:
and calculating the risk adjustment capital return rate corresponding to each credit business of the credit client according to the preset weight corresponding to each credit business to obtain the total risk adjustment capital return rate corresponding to the credit client.
3. The method according to claim 1 or 2, wherein the determining whether the credit patron is an anomalous patron based on the respective derating preparation extension proportion, economic capital occupancy proportion, and total risk adjusted capital return, comprises:
determining whether the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derating readiness contribution proportion is greater than a second proportional threshold;
determining the credit customer as an anomalous customer if the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derated readiness quote proportion is greater than a second proportional threshold.
4. The method of claim 1, wherein generating the exception prompting message comprises:
and calling a preset abnormal prompt template to generate abnormal prompt information based on the deduction preparation plan-to-mention proportion, the economic capital occupation proportion, the risk adjustment total return rate and the business data of each credit business of the credit customer corresponding to the credit customer.
5. The method of claim 4, wherein after generating the exception prompting message, further comprising:
sending the abnormal prompt information to a credit service personnel terminal to prompt credit service personnel to check in time;
and obtaining the checking result fed back by the credit service personnel.
6. A credit client anomaly identification apparatus, comprising:
the first acquisition unit is used for acquiring the deduction preparation calculation amount, the economic capital occupation amount and the risk adjustment capital return rate corresponding to each credit business of the credit customer;
the first calculation unit is used for calculating the reduction preparation accounting and raising proportion corresponding to the credit customer based on the reduction preparation accounting and raising amount corresponding to each credit business of the credit customer;
the second calculation unit is used for calculating the economic capital occupation proportion corresponding to the credit client based on the economic capital occupation amount corresponding to each credit business of the credit client;
the third calculation unit is used for calculating the risk adjustment capital total rate of return corresponding to the credit client based on the risk adjustment capital rate of return corresponding to each credit business of the credit client;
the judging unit is used for judging whether the credit client is an abnormal client or not based on the deduction preparation calculation and improvement proportion, the economic capital occupation proportion and the risk adjustment total capital return rate corresponding to the credit client;
and the generating unit is used for generating abnormal prompt information under the condition that the credit client is determined to be an abnormal client.
7. The apparatus according to claim 6, wherein the first computing unit is specifically configured to:
summing the deduction preparation accounting and fund-drawing amount corresponding to each credit business of the credit customer to obtain the deduction preparation accounting and total fund-drawing amount corresponding to the credit customer;
calculating the total loan balance based on the loan balance of each credit business of the credit customer;
calculating a deduction value preparation accounting and offering proportion corresponding to the credit customer based on the total loan balance and the deduction value preparation accounting and offering total amount;
the second computing unit is specifically configured to:
summing the economic capital occupation amount corresponding to each credit business of the credit customer to obtain the economic capital occupation total amount corresponding to the credit customer;
calculating an economic capital occupation proportion corresponding to the credit customer based on the loan balance and the total economic capital occupation amount;
the third computing unit is specifically configured to:
and calculating the risk adjustment capital return rate corresponding to each credit business of the credit client according to the preset weight corresponding to each credit business to obtain the total risk adjustment capital return rate corresponding to the credit client.
8. The apparatus according to claim 6 or 7, wherein the determining unit is specifically configured to:
determining whether the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derating readiness contribution proportion is greater than a second proportional threshold;
determining the credit customer as an anomalous customer if the total risk adjusted capital return is less than a return threshold, the economic capital occupancy proportion is greater than a first proportional threshold, and the derated readiness quote proportion is greater than a second proportional threshold.
9. A storage medium storing a set of instructions, wherein the set of instructions, when executed by a processor, implement the credit customer exception identification method of any one of claims 1-5.
10. An electronic device, comprising:
a memory for storing at least one set of instructions;
a processor for executing a set of instructions stored in the memory, the method for credit customer exception identification as claimed in any one of claims 1-5 being implemented by execution of the set of instructions.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210295126.0A CN114757675A (en) | 2022-03-24 | 2022-03-24 | Credit customer abnormity identification method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210295126.0A CN114757675A (en) | 2022-03-24 | 2022-03-24 | Credit customer abnormity identification method and device, storage medium and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114757675A true CN114757675A (en) | 2022-07-15 |
Family
ID=82327722
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210295126.0A Pending CN114757675A (en) | 2022-03-24 | 2022-03-24 | Credit customer abnormity identification method and device, storage medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114757675A (en) |
-
2022
- 2022-03-24 CN CN202210295126.0A patent/CN114757675A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kuhn et al. | Learning from WorldCom: Implications for fraud detection through continuous assurance | |
| US8355974B2 (en) | Account level liquidity charge determination | |
| CN111476660B (en) | Intelligent wind control system and method based on data analysis | |
| US20130036038A1 (en) | Financial activity monitoring system | |
| Abdymomunov et al. | US banking sector operational losses and the macroeconomic environment | |
| US11403645B2 (en) | Systems and methods for cross-border ATM fraud detection | |
| CN112801529B (en) | Financial data analysis method and device, electronic equipment and medium | |
| CN111144697A (en) | Data processing method, data processing device, storage medium and electronic equipment | |
| US20180232813A1 (en) | Business management system and method through generation of accounting and financial information | |
| CN111127197A (en) | Foreign trade supply chain financial risk control method | |
| CN112581283A (en) | Method and device for analyzing and alarming business bank employee transaction behaviors | |
| US20110125623A1 (en) | Account level cost of funds determination | |
| CN113469818B (en) | Investment risk early warning method and device, electronic equipment and computer readable medium | |
| US8078529B1 (en) | Evaluating customers' ability to manage revolving credit | |
| JP2009193449A (en) | Financial transaction monitoring system and method | |
| JP2021140550A (en) | Illegality detector, foreigner working system and program, and method for detection of illicit work of foreign worker | |
| CN114757675A (en) | Credit customer abnormity identification method and device, storage medium and electronic equipment | |
| CN116934131A (en) | Enterprise operation condition assessment method, device and equipment | |
| US8595114B2 (en) | Account level interchange effectiveness determination | |
| CN111652614B (en) | Data processing system, data processing method and device | |
| CN114580898A (en) | Efficient collection system and method, electronic device and readable storage medium | |
| JP2003036343A (en) | Method of operational risk management and its system | |
| CN113034258A (en) | Tax data processing method and device, electronic equipment and storage medium | |
| CN114880369A (en) | Risk credit granting method and system based on weak data technology | |
| JP6766023B2 (en) | Information processing equipment and programs |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |