TWM604457U - Loan approval level classification system - Google Patents

Abstract

This case provides a loan approval hierarchical classification system, which includes a plurality of electronic devices on the loan verification side and a bank server that is communicatively connected to the electronic devices on the verification side. Each electronic device at the end of verification and loan corresponds to a level of verification and loan respectively, and each end of verification and credit electronic device is used to receive the requirements of verification and loan that meet the level of verification and loan respectively. The bank-side server includes a loan acceptance module, a risk assessment module, a first-level loan-level assessment module, and a loan-approval request module. The loan acceptance module is used to receive loan requests, and the loan request contains the loan amount value. The risk assessment module is used to generate an assessment risk value based on the credit rating comparison risk comparison table. The first nuclear loan level evaluation module is used to generate the nuclear loan level according to the evaluation risk value and the loan amount value comparison table by comparing the nuclear loan level. The loan approval request module is used to send the loan approval request.

Description

Loan approval level classification system

This case is related to the credit collection management system, especially a tiered classification system for loan approval.

Loan refers to an economic behavior in which a bank lends funds to those who need funds at a certain interest rate in accordance with national policies and agrees to return it within a time limit. Loans are a type of credit, which is a business in which banks grant credit to customers and assume risks.

In the internal operating procedures of traditional banks, the bank's corporate finance or personal finance and other related credit business, from application to completion of loan applications, almost all rely on manual procedures. In recent years, electronic systems in various fields have gradually become popular. As a result, electronic credit investigation systems (eLoan) are widely used in various banks. The electronic credit investigation systems integrate various databases required for credit business to improve the efficiency of credit investigation services. .

The current electronic credit collection system determines the level of credit approval supervisors assigned based on the loan application amount. Specifically, the higher the loan amount, the higher the level of credit review supervisor assigned. However, the loan application amount of the loan application cannot fully correspond to the risk level of the loan application case, resulting in the loan application case being unable to be correctly assigned to the approval supervisor level with equivalent authority.

In this way, it may happen that loan applications with low loan amount but high risk have not been reviewed by senior supervisors; or loan applications with high loan amount but low risk waste the review time of senior supervisors. Therefore, there is a need for improvement.

This case provides a loan approval hierarchical classification system, which includes a plurality of electronic devices on the loan verification side and a bank server that is communicatively connected to the electronic devices on the verification side. Each electronic device at the end of verification and loan corresponds to a level of verification and loan respectively, and each end of verification and credit electronic device is used to receive the requirements of verification and loan that meet the level of verification and loan respectively. The bank-side server includes a loan acceptance module, a risk assessment module, a first-level loan-level assessment module, and a loan-approval request module. The loan acceptance module is used to receive loan requests, and the loan request contains the loan amount value. The risk assessment module is used to generate an assessment risk value based on the credit rating comparison risk comparison table. The first nuclear loan level evaluation module is used to generate the nuclear loan level according to the evaluation risk value and the loan amount value comparison table by comparing the nuclear loan level. The loan approval request module is used to send the loan approval request corresponding to the loan approval level.

Please refer to Figure 1, which is a system schematic diagram of an embodiment of the loan approval hierarchical classification system of this case. The loan approval hierarchical classification system of this case includes a plurality of credit-verifying electronic devices 10 and a bank server 20 coupled to each of the credit-verifying electronic devices 10. The bank server 20 can generate a loan approval request corresponding to the loan approval level according to the loan amount and credit rating of the loan application case of the bank to which the appropriate loan approval electronic device 10 performs the loan approval.

In this case, the electronic devices 10 at the end of verification and loan respectively correspond to a level of verification, and the electronic devices 10 at the end of verification and approval are respectively used to receive the verification requirements of the verification level. The bank-side server 20 includes a loan acceptance module 21, a risk assessment module 22, a first verification loan level assessment module 23, and a loan verification request module 24. The loan acceptance module 21 is used to receive a loan request, and the loan request includes the loan amount. The risk assessment module 22 is used for generating an assessment risk value based on the credit rating comparison risk comparison table. The first nuclear loan level evaluation module 23 is used to generate the nuclear loan level according to the evaluation risk value and the loan amount value comparison table by comparing the nuclear loan level. The loan approval request module 24 is used to send the loan approval request corresponding to the loan approval level.

In one embodiment, the electronic device 10 at the end of the verification terminal may be, but not limited to, a handheld computer, a tablet computer, or a desktop computer.

In one embodiment, the electronic device 10 at the end of the verification and loan may be connected to the server 20 at the bank end via a physical line communication. It may also be connected to the bank server 20 via wireless communication. Here, the physical line communication connection can be, but is not limited to, physical connection through a coaxial cable or a data network line. The wireless communication connection can be, but is not limited to, Bluetooth, WiFi, or Near Field Communication (NFC).

In one embodiment, the electronic device 10 at the end of credit and loan communication connected to the server 20 at the bank may be an electronic device used by the supervisor responsible for credit approval. Here, the supervisor in charge of nuclear loans can include low-level supervisors, middle-level supervisors, and high-level supervisors. Therefore, the level of nuclear loan is low-level, mid-level, and high-level, but this case is not limited to this. In other embodiments , The level of nuclear loan can also be a job title or rank.

In one embodiment, the electronic device 10 of the verification terminal may include a display and an input device. The display is used to display the loan approval requirements, and the input device is used to input the approval instructions. Here, the loan approval request can be an electronic form, an electronic official document or a reminder message. The loan approval instruction can be text, number or tick. In some embodiments, the input device may be a mouse, a keyboard, or a touchpad, but this case is not limited to this.

In one embodiment, the bank server 20 belongs to the bank. Here, the server can be, but is not limited to, a computer system or other electronic devices with computing and processing capabilities. And the bank is a bank that can provide loan demand. In this embodiment, the loan acceptance module 21, the risk assessment module 22, the first loan approval level assessment module 23 and the loan approval request module 24 are installed on the bank server 20.

In one embodiment, the loan acceptance module 21 may include a user interface, and the user interface may be displayed on a display of an electronic device that is communicatively connected to the bank server 20. In one embodiment, the loan application is sent from the loan applicant to the bank to which the bank server 20 belongs, and the loan request is issued by the clerk of the bank to which the bank server 20 belongs. After the bank applies for the loan, the clerk of the bank belonging to the bank server 20 communicates with the bank server 20 through its electronic device, and the loan acceptance module 21 displays the user interface on the display of the clerk’s electronic device for the bank clerk to make loans However, this case is not limited to this.

In other embodiments, the bank accepting the loan may also provide the loan applicant to apply for the loan online, and the loan request in this embodiment is issued by the loan applicant. In this embodiment, the user-side electronic device 30 is further included. The loan applicant can be communicatively connected to the bank-side server 20 by the user-side electronic device 30, and then the user of the loan acceptance module 21 of the bank-side server 20 The interface makes a loan request. Here, it can be connected to the bank-side server 20 through webpage or application type communication.

1 and 2, in one embodiment, the bank server 20 further includes a storage module 25. The storage module 25 can be, but is not limited to, a hard disk, a hard disk array, non-volatile memory or other electronic storage media . Here, the storage module 25 can store various bank internal forms, customer data, and loan application case data.

In one embodiment, the storage module 25 stores relevant application forms and data of the loan application. Here, the relevant data of the loan application stored in the storage module 25 at least includes loan amount, loan period and guarantee information.

In one embodiment, the storage module 25 stores a risk comparison table, which is a comparison table of credit rating and assessed risk value. The purpose of Credit Rating is to show the size of the default risk of the subject's loan. The credit rating can show its credit rating through numbers.

In an embodiment, the credit rating may be one of the bank's internal credit rating and external rating, or both.

In one embodiment, the risk assessment module 22 compares the risk comparison table such as <Table 1> according to the internal credit rating to generate an estimated risk value. In this embodiment, the internal credit rating is 1-13. In Table 1, the internal credit rating of 1~4 corresponds to the assessed risk value of low risk. The internal credit rating of 5~10 corresponds to the assessed risk value of medium risk. The internal credit rating of 11~13 corresponds to the assessed risk value of high risk.

<Table 1> Risk comparison table Evaluate the value of risk Internal credit rating External credit rating low risk 1 AAA~A 2 3 4 Medium risk 5 BBB~B 6 7 8 9 10 high risk 11 CCC~C 12 13

1 and 2, in one embodiment, the internal credit rating may be manually rated and stored in the storage module 25 by the bank clerk after the loan application case is applied. The internal credit rating can also be calculated by the internal credit rating module 26 of the bank server 20 extracting the loan application data of the loan application in the storage module 25.

In one embodiment, the internal credit rating module 26 includes multiple customer category rating models, and each customer category rating model includes multiple rating sub-models. In one embodiment, the rating model for multiple customer categories includes publicly issued companies, non-publicly issued companies, individuals, and overseas companies. In this embodiment, when the internal credit rating is calculated by the internal credit rating module 26, the internal credit rating module 26 will, after the loan acceptance module 21 receives the loan request, follow the application of the loan request The information of the lender selects the customer category rating model that matches the qualification of the loan applicant for internal credit rating.

In one embodiment, the rating model of each customer category of the internal credit rating module 26 may be a risk prediction model established by logistic regression analysis based on customer information, but this case is not limit. The risk prediction model established by Logis regression analysis is an internal credit rating model that corresponds to the relationship between independent variables and strains. In one embodiment, the independent variable is a risk factor, and the strain factor is a credit value.

In other embodiments, the customer category rating model may also be built in the form of an expert score card.

In one embodiment, the rating sub-models included in each customer category rating model are respectively a financial sub-model, a joint enterprise sub-model, a joint enterprise owner sub-model, and a protonation model.

In an embodiment in which the internal credit rating is calculated by the internal credit rating module 26, the internal credit rating module 26 may retrieve the storage module after the loan acceptance module 21 receives the loan request. The loan application data within 25 are rated and the internal credit rating is produced.

In an embodiment, the risk assessment module 22 may also compare the risk comparison table such as <Table 1> according to the external credit rating to generate an estimated risk value.

In this embodiment, the external credit rating is rated by the external credit rating agency 40 of the bank to which the non-bank server 20 belongs. The external credit rating agency 40 may include credit rating agencies in the capital market, credit rating agencies in the commercial market, and consumer credit rating agencies based on different data collection objects.

In one embodiment, a credit rating agency in the capital market is an institution that can conduct credit ratings on countries, banks, securities companies, funds, bonds, and listed companies, and is recognized by the my country Financial Supervision and Administration Commission (hereinafter referred to as the Financial Regulatory Commission) The following external credit rating agencies 40 belong to. Well-known credit rating agencies include Taiwan Rattings Company (TRC), Standard & Poor's (S&P), and Moody's Investors Service Corporation (Moody's). ) Or Fitch Ratings (Fitch Ratings, referred to as Fitch).

In one embodiment, credit rating agencies in the commercial market can conduct credit investigations and evaluations on commercial enterprises, such as Dun & Bradstreet Corporation.

In one embodiment, the consumer credit rating agency may provide the consumer's personal credit investigation status, such as Equifax, Trans Union, or Experian.

For example, the external credit rating values listed in <Table 1> are explained by taking the S&P and Moody’s external rating values with the same rating definition as examples. If the external credit rating listed in <Table 1> is AAA~A, the corresponding assessed risk value is low risk. The internal credit rating value of BBB~B corresponds to the assessed risk value of medium risk. Those whose internal credit rating is CCC~C correspond to high risk.

Among them, those with an external rating of AAA are considered to have the highest credit quality, which means the lowest expected credit risk. This rating represents that the rated candidate has the strongest financial commitment solvency. This ability is extremely unlikely to be negatively affected by predictable events.

Those with an external rating of AA are considered to have extremely high credit quality, which means extremely low expected credit risk. This rating represents that the rated person has a strong financial commitment solvency. It is unlikely that this capability will be negatively affected by foreseeable events.

Those with an external rating of A are considered to have high credit quality, which means low expected credit risk. This rating represents that the rated person has strong financial commitment solvency. However, this ability may be more likely to be affected due to changes in environmental or economic conditions than those with higher ratings.

Those with an external rating of BBB are considered to have good credit quality, which represents the current low expected credit risk. Respondents have reasonable financial commitment solvency, but this ability is more likely to be affected by negative changes in environmental and economic conditions. This rating is the lowest rating in the investment grade rating.

Those with an external rating of BB are speculative, which means that credit risk may be emerging, especially due to negative economic changes; however, the assessed may use flexible business or financial methods to fulfill their financial commitments. The securities that have been awarded this rating are not of investment grade.

Those with an external rating of B are highly speculative. For the issuer and the debt in the performance of the contract, the B rating represents that the credit risk level of the rated person is extremely high, but it still has some security. The financial commitments are still being fulfilled, but the ability to continue to repay depends on whether the operating and economic environment is stable and sound.

For those with an external rating of CCC, for the issuer and the debts in compliance, the CCC rating indicates that the rated person is highly likely to default. The ability to continue to perform financial commitments depends entirely on the stability of the operating and economic environment. Good depends.

For those with an external rating of CC, for the issuer and the debt in performance, the CC rating represents the possibility of some form of violation.

Those with an external rating of C are for the issuer and the debt in performance, and the C rating represents imminent default.

1 and 2, in one embodiment, the risk assessment module 22 simultaneously uses the internal credit rating and external credit rating to compare the risk level comparison table to generate the assessed risk value. In this embodiment, the risk assessment module 22 further includes a comparator 221. Here, the risk assessment module 22 compares Table 1 with the aforementioned method to generate an internal risk assessment value and an external risk assessment value. Then the comparator 221 compares the internal risk assessment value and the external risk assessment value. When the internal risk assessment value is the same as the external risk assessment value, the assessed risk value is one of the internal risk assessment value or the external risk assessment value. When the internal risk assessment value is different from the external risk assessment value, the assessed risk value is the higher of the internal risk assessment value and the external risk assessment value. In this way, the risk assessment module 22 uses the internal credit rating and the external credit rating to generate the assessed risk value.

1 and FIG. 2, in one embodiment, in order to improve the smoothness of the loan verification process, the bank-side server 20 further includes an external data request module 27. The external data request module 27 can be communicatively connected to an external credit rating agency 40. In this embodiment, after the loan acceptance module 21 receives the loan request, the external data request module 27 requests the external credit rating agency 40 for the external credit rating of the applicant. It can be seen that when the loan acceptance module 21 receives the loan request, the internal credit rating module 26 calculates the internal credit rating, and the external data request module 27 can also synchronously request to obtain the external credit rating, so as to improve The efficiency of the loan process.

In one embodiment, the storage module 25 stores the first nuclear loan level comparison table <Table 2>. In this embodiment, when the assessed risk value is generated, the first approved loan level assessment module 23 compares the assessed risk value and the loan amount applied by the applicant, as shown in the first approved loan level comparison table in <Table 2> To generate nuclear loan levels.

<Table 2> Comparison table of the first nuclear loan level Loan amount risk level ~XX million XX million~XXX million XXX million or more high risk Mid-level supervisor Senior supervisor Senior supervisor Medium risk Low-level supervisor Mid-level supervisor Senior supervisor low risk Low-level supervisor Low-level supervisor Mid-level supervisor

From this example, it can be seen that as long as the credit risk is a low-risk loan application, the assigned loan level will not be assigned to the senior executives, and the middle and low-level supervisors can quickly approve the loan; and as long as the credit risk is high-risk The loan application will only be assigned to middle and high-level supervisors for more rigorous review to ensure that the risk of default in the loan application can be controlled.

In one embodiment, the bank server 20 further includes a second nuclear loan level evaluation module 231, and the storage module 25 stores the second nuclear loan level comparison table <Table 3>. In this embodiment, in order to more rigorously ensure the possible default risk of the loan application, the internal credit rating and external credit rating are used in the risk assessment module 22 to generate the assessed risk value and the implementation of the comparator 221 In the example. When the internal risk assessment value is different from the external risk assessment value and one of them is high risk, the second nuclear loan level assessment module 231 compares the second nuclear loan level comparison table according to the information-level guarantee information during the loan period to generate a nuclear loan Level.

<Table 3> Comparison table of the second nuclear loan level Guarantee information loan period information Full guarantee Secondary guarantee No guarantee long Senior supervisor Senior supervisor Senior supervisor Mid-term Mid-level supervisor Senior supervisor Senior supervisor short term Mid-level supervisor Mid-level supervisor Senior supervisor

As a result, for loan applications with different internal and external risk assessment values and one of which is high-risk, the loan period information and guarantee information will be further considered and assigned to middle and senior executives for loan approval.

It can be seen from the above that the bank-side server 20 in this case classified the loan application cases to the nuclear loan supervisors who meet the nuclear loan level through credit rating and loan amount, so that the nuclear loan cases can quickly and correctly enter the nuclear loan process. Improve the processing efficiency of credit cases.

Although this disclosure has been disclosed in some embodiments as described above, it is not intended to limit the disclosure. Anyone with ordinary knowledge in the technical field can make some changes and modifications without departing from the spirit and scope of the disclosure. Therefore, the scope of patent protection in this case shall be determined by the scope of the patent application attached to this specification.

10: Nuclear loan electronic device 20: Bank-side server 21: Loan acceptance module 22: Risk Assessment Module 221: Comparator 23: The first nuclear loan level evaluation module 231: The second nuclear loan level evaluation module 24: Nuclear loan request module 25: storage module 26: Internal credit rating module 27: External data request module 30: User-side electronic devices 40: External credit rating agencies

[Figure 1] System diagram of one embodiment of the loan approval hierarchical classification system of this case. [Figure 2] System diagram of another embodiment of the loan approval hierarchical classification system of this case.

10: Nuclear loan electronic device

20: Bank-side server

21: Loan acceptance module

22: Risk Assessment Module

23: The first nuclear loan level evaluation module

24: Nuclear loan request module

30: User-side electronic devices

Claims (8)

A hierarchical classification system for loan approval, including: A plurality of electronic devices at the verification and credit end respectively correspond to a credit verification level, and each of the verification and credit end electronic devices is respectively used to receive a credit verification requirement that meets the verification and credit level; and A bank-side server, which is communicatively connected to the electronic device at the multiple-check and credit-side, includes: A loan acceptance module for receiving a loan request, the loan request including a loan amount value; A risk assessment module for generating an assessed risk value based on a credit rating comparison against a risk comparison table; A first approved loan level evaluation module for generating the approved loan level based on the evaluation risk value and the loan amount value comparison with a check list of approved loan levels; and A loan approval request module for sending the loan approval request corresponding to the loan approval level. The loan approval hierarchical classification system described in claim 1, further includes an internal credit rating module, which is used to calculate an internal credit rating based on the loan request, and the bank-side server The device can be communicatively connected to an external credit rating agency and request the external credit rating agency to provide an external credit rating according to the loan request, the credit rating including the internal credit rating and the external credit rating value. The loan approval level classification system according to claim 2, wherein the risk assessment module further includes a comparator, and the risk assessment module generates an internal risk assessment value based on the internal credit rating comparison against a risk level comparison table , And generate an external risk assessment value based on the external credit rating ratio to the risk level comparison table. The comparator compares the internal risk assessment value and the external risk assessment value. When the internal risk assessment value and the external risk assessment When the value is the same, the internal risk assessment value or the external risk assessment value is used as the assessment risk value. When the internal risk assessment value is different from the external risk assessment value, the internal risk assessment value and the external risk assessment value are both The higher is the risk value of the assessment. For example, in the loan approval level classification system described in claim 3, the bank-side server further includes a storage module for storing plural loan application data, and the plural loan application data respectively include a loan period information and a loan request corresponding to the loan request. Guarantee information. The loan approval level classification system according to claim 4, wherein the bank-side server further includes a second approval level evaluation module for when the internal risk evaluation value and the external risk evaluation value are different and one of them When the first is high risk, the approved loan level is generated based on the loan period information and the guarantee information compared with a second approved loan level comparison table. For the loan approval hierarchical classification system described in claim 2, wherein the internal credit rating module includes multiple customer category rating models, and the multiple customer category rating models correspond to different loan applicant qualifications, and the internal credit rating The module is used to select the corresponding customer category rating model according to the loan request to calculate the internal credit rating. For the loan approval hierarchical classification system described in claim 6, the plural customer category rating models respectively include plural sub-models, and the plural sub-models include a financial sub-model, a joint enterprise sub-model, and a joint enterprise owner sub-model And the protonation model. The loan approval hierarchical classification system described in claim 1 further includes a user-side electronic device for sending the loan request.

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