A bond portfolio management method for corporate financing

Abstract

The present invention relates to the technical field of enterprise financing control, and discloses a bond portfolio control method for enterprise financing, comprising the following steps: step one: obtaining management data of all financing projects, issuance data of all bonds and financial data of all investors, and classifying and forming a data set; step two: analyzing the approval status of each financing project, and generating an efficiency data group; step three: binding the bond portfolio according to the approval document number, and then counting the sales of bonds according to the bond underwriters, and generating a sales data group; step four: analyzing the financial status of each investor, and generating a risk coefficient, accurately screening investors, and achieving high multi-dimensional control efficiency; step five: setting a fixed range of internal thresholds, external thresholds and risk thresholds, evaluating the internal approval progress of the enterprise, the approval progress of the external regulatory agency, the sales speed ranking of the underwriter, and the credit risk of the investor, and generating corresponding early warning signals and ranking forms, with strong risk early warning capabilities.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise financing management and control, and in particular to a bond portfolio management and control method for enterprise financing. Background Art

[0002] In the actual operation of corporate bond issuance and bond management by large comprehensive groups, the entire life cycle of a bond involves "collection of corporate financing needs, formulation of corporate financing plans, preparation of corporate bond issuance materials, project reporting to regulatory agencies, and the need to issue bonds to the outside world at the same time, tracking of the duration of bonds after issuance and tracking of investors' holdings, and formulation and implementation of redemption plans." During the entire issuance process, business personnel need to query through regulatory disclosure systems such as the China Securities Regulatory Commission, and positions must be tracked through various external third-party data statistics providers; in the process of business personnel managing the entire life cycle of bonds, a large number of registration documents and related attachments are usually involved. The registration rules and logic of each document are not unified, and there may be ambiguous registrations in the documents. At present, business personnel need to manually identify and verify a large number of bond management documents, which will lead to the following problems and risks:

[0003] (1) There are a large number of documents and a huge amount of text information. In addition, in the business process, it is necessary to check and verify the bond approval documents and bond issuance registration information many times and repeatedly, which brings heavy workload to business personnel;

[0004] (2) Different business personnel have different evaluation criteria, and it is impossible to achieve unified bond management standards. Everyone has different emotional perceptions of language and text. Different people may have different risk judgments when facing the same document, which in turn causes greater risk hazards. In the business process, there may also be inconsistencies in risk assessment.

[0005] (3) Different business personnel track different bonds, but two different bonds may belong to the same bond approval document. In the process of tracking existing bonds, necessary information is not exchanged, which can easily cause management risks.

[0006] (4) Due to the limitations of manual operation, it is impossible to guarantee the comprehensiveness of the identification of relevant content. During the operation, it is easy for people to miss or misread the content, which may bring potential risks.

[0007] (5) The scale of bond stock of large groups is in the tens or hundreds of billions, and the bond prices are greatly affected by fluctuations in the capital market. Business personnel need to collect, count and analyze data on bond stock from multiple channels, and the delay leads to the inability to identify, resolve and identify risks in a timely manner. Summary of the invention

[0008] 1. Technical issues to be resolved

[0009] In view of the shortcomings of the prior art, the present invention provides a bond portfolio management method for corporate financing, which has the advantages of high multi-dimensional management efficiency and strong risk warning capability, and solves the problems of traditional bond portfolio management methods such as many management loopholes, low financing efficiency and poor risk warning capability.

[0010] (II) Technical solution

[0011] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a bond portfolio management method for corporate financing, comprising the following steps:

[0012] Step 1: Connect to the bond management platform through the network to obtain the management data of all financing projects, the issuance data of all bonds and the financial data of all investors, and classify them into project data sets, issuance data sets and investment data sets;

[0013] Step 2: Analyze the approval status of each financing project based on the project data set and generate the corresponding efficiency data set ;

[0014] Step 3: Bind the bond portfolio according to the issuance data set and approval document number , and then generate the corresponding sales data set according to the bond underwriters' statistics on bond sales ;

[0015] Step 4: Analyze each investor’s financial status based on the investment data set and generate the corresponding risk factor ;

[0016] Step 5: Set the internal threshold of the fixed range , External Threshold and risk thresholds , combined with the efficiency data set , Sales Data Group and risk factor , evaluate the internal approval progress of the enterprise, the approval progress of the external regulatory agency, the underwriter sales speed ranking, and the credit risk of investors, and generate corresponding early warning signals and ranking forms.

[0017] Preferably, in step 1, the expression of the project data set is , to The first to the Management data of each financing project, including the start time, application time and approval time. Indicates the declared amount of each financing project.

[0018] Preferably, in step 1, the expression of the issued data set is , to The first to the The issuance data of bonds includes the face value, bond type, underwriter and sales record of bonds. The bond types include special bonds and market-based financing bonds. Indicates the approval document number corresponding to each bond.

[0019] Preferably, in step 1, the expression of the investment data set is , to The first to the Financial data of each investor, including purchase size, cash flow and historical default times, Indicates the amount of debt each investor has.

[0020] Preferably, in step 2, the efficiency data set The calculation process is as follows:

[0021] According to the project data set, extract the management data of each financing project and The start time of each financing project is marked as , will The application time point of each financing project is marked as , will The approval time point of each financing project is marked as , will The declared amount of each financing project is marked as ; In the formula, It indicates the time difference between project application and start-up, which is the internal approval time of the enterprise. It represents the ratio of the declared amount to the internal approval time of the enterprise, that is, the internal approval time of the enterprise. The processing efficiency of each financing project, It indicates the time difference between project approval and application, that is, the time required for external regulatory agencies to review and approve the project. It represents the ratio of the declared amount to the time taken for external regulatory authorities to review and approve the application. The efficiency of handling financing projects.

[0022] Preferably, in step 3, the bond portfolio The binding process is as follows:

[0023] Based on the issuance data set, screen bonds by approval number. If the approval numbers of any two bonds are the same, bind the two bonds into one bond portfolio. If the approval numbers of any two bonds are inconsistent, the two bonds will be bound into two bond combinations. , a single bond portfolio Approval documents for a single financing project, a single bond portfolio The total face value of all bonds should be less than or equal to the approved amount in the approval document.

[0024] Preferably, in step 3, the sales data group The calculation process is as follows:

[0025] S11. Based on the issuance dataset, the bond underwriters are marked as , to Indicates the first to underwriters, among which the Underwriters marked , ;

[0026] S12. According to the issued data set, count the Underwriters sales records and Underwriters The total sales amount is marked as , will Underwriters The sales duration is marked as ; In the formula,, It represents the ratio of total sales to sales time, which is Underwriters Sales speed, It means calculating the sales speed of all underwriters at the same time, which is the sales data group.

[0027] Preferably, in step 4, the risk factor The calculation process is as follows:

[0028] Extract the investment data set The financial data of each investor and The purchase size of each investor is marked as , will The cash flows of each investor are denoted by , will The historical default times of an investor are marked as , will The debt amount of each investor is marked as ; In the formula, Represents the evaluation weight for the purchase size and cash flow ratio, represents the assessment weight for the number of historical defaults, represents the assessment weight for the debt amount, , Indicates according to , and Weight, get Risk factor for each investor .

[0029] Preferably, in step 5, the efficiency data set The efficiency of internal approval in the enterprise is lower than the internal threshold When the internal approval process of the enterprise is slow, a corresponding follow-up warning signal is generated, and the processing efficiency of the external regulatory agency during approval is lower than the external threshold When the external regulatory agency's approval progress is slow, a corresponding follow-up warning signal is generated.

[0030] Preferably, in step 5, according to the sales data group , rank underwriters from high to low according to sales speed, generate corresponding underwriter ranking table, and the risk coefficient of a single investor Exceeding risk threshold , it indicates that the credit risk of the investor is high and a corresponding risk warning signal is generated.

[0031] Compared with the prior art, the present invention provides a bond portfolio management method for corporate financing, which has the following beneficial effects:

[0032] 1. The present invention connects to the bond management platform through the network to obtain the management data of all financing projects, the issuance data of all bonds and the financial data of all investors, and classifies them into project data sets, issuance data sets and investment data sets. According to the project data sets, the approval status of each financing project is analyzed, and the corresponding efficiency data sets are generated. Internal approval is done by building a form in the enterprise management system and is managed synchronously with the OA process. For the external regulatory approval process, the enterprise management system sets a scheduled task to remind business personnel to track and update the status regularly. The bond portfolio is bound according to the issuance data set and the approval document number. , and then generate the corresponding sales data set according to the bond underwriters' statistics on bond sales , bond management from the underwriter dimension helps bond managers to conduct overall control at the macro level, analyze the financial status of each investor based on the investment data set, and generate corresponding risk coefficients , accurately screen out investors with higher risks, and achieve high efficiency in multi-dimensional management and control.

[0033] 2. The present invention sets a fixed range of internal thresholds , External Threshold and risk thresholds , combined with the efficiency data set , Sales Data Group and risk factor , evaluate the internal approval progress of enterprises, the approval progress of external regulatory agencies, the sales speed ranking of underwriters, and the credit risk of investors, efficiency data group The efficiency of internal approval in the enterprise is lower than the internal threshold When the internal approval process of the enterprise is slow, a corresponding follow-up warning signal is generated, and the processing efficiency of the external regulatory agency during approval is lower than the external threshold When the external regulatory agency is slow in approving, a corresponding follow-up warning signal is generated. , rank underwriters from high to low according to sales speed, generate corresponding underwriter ranking table, and the risk coefficient of a single investor Exceeding risk threshold When , it indicates that the credit risk of the investor is high, and a corresponding risk warning signal is generated, indicating a strong risk warning capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a step diagram of the method of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Due to the problems of many management loopholes, low financing efficiency and poor risk early warning ability of traditional bond portfolio management methods, a bond portfolio management method for corporate financing is provided. Figure 1 , a bond portfolio management method for corporate financing, comprising the following steps:

[0037] Step 1: Connect to the bond management platform through the network to obtain the management data of all financing projects, the issuance data of all bonds and the financial data of all investors, and classify them into project data sets, issuance data sets and investment data sets;

[0038] The expression for the project data set is , to The first to the Management data of each financing project, including the start time, application time and approval time. Indicates the application amount of each financing project. Specifically, a project progress database can be established based on the project data set. Business personnel can track each stage according to internal financing needs in the enterprise management system;

[0039] The expression of the release data set is , to The first to the The issuance data of the bonds include the face value, type of bonds, underwriters and sales records. The types of bonds include special bonds and market-based financing bonds. The project income is managed in separate accounts and independently accounted for. Financing platforms that have not completed the market-oriented transformation and have not yet resolved their existing hidden debts cannot participate in bond market-based financing as project units. Indicates the approval document number corresponding to each bond. Specifically, the issuance data set corresponds to the preparation stage of the enterprise financing project. Through the bond approval quota usage report, multiple data of all bonds during the planned issuance are collected, and OCR technology is used to parse offline issuance documents to identify the quota approved by the regulator in the bond approval document, the type of bonds reported, and the corresponding underwriter information;

[0040] The expression of the investment data set is , to The first to the Financial data of each investor, including purchase size, cash flow and historical default times, Indicates the liability amount of each investor. Specifically, the investment data set comes from the position report. RPA technology is used to collect information about each investor, position data, and transaction price and volume of bonds from third-party public data every day.

[0041] Step 2: Analyze the approval status of each financing project based on the project data set and generate the corresponding efficiency data set , the calculation process is as follows:

[0042] According to the project data set, extract the management data of each financing project and The start time of each financing project is marked as , will The application time point of each financing project is marked as , will The approval time point of each financing project is marked as , will The declared amount of each financing project is marked as ; In the formula, It indicates the time difference between project application and start-up, which is the internal approval time of the enterprise. It represents the ratio of the declared amount to the internal approval time of the enterprise, that is, the internal approval time of the enterprise. The processing efficiency of each financing project, It indicates the time difference between project approval and application, that is, the time required for external regulatory agencies to review and approve the project. It represents the ratio of the declared amount to the time taken for external regulatory authorities to review and approve the application. In order to improve the processing efficiency of individual financing projects, the internal approval is done by the self-built form of the enterprise management system, and is managed synchronously with the OA process. For the external supervision and approval process, the enterprise management system sets up scheduled tasks to regularly remind business personnel to track and update the status.

[0043] Specifically, bond project applications should generally meet the following conditions:

[0044] (1) The project has obtained approval from relevant competent authorities, such as project establishment, feasibility study, environmental impact assessment, etc.;

[0045] (2) The project is ready for commencement, with priority given to projects under construction and projects that make up for shortcomings;

[0046] (3) The project implementation entity, project establishment procedures, and financing channels should be legal and compliant, and the ownership of the assets involved should be free of dispute, controversy, and risk;

[0047] (4) If there are other outstanding debts such as bank loans, the repayment responsibilities for the original financing and new financing should be clarified and the cash flow of the principal and interest of the bonds should be ensured (separate accounting is required).

[0048] (5) Projects that are handed over to social capital for investment through PPP should be carefully considered when applying for special bond funds (funding direction, debt repayment source, risk sharing, and benefit sharing);

[0049] (6) Prioritize key support projects;

[0050] After determining the demand for special bond projects, the application is mainly submitted through a combination of online and offline methods. Online reporting is done through the Local Government Debt Management System, which means that a medium- and long-term project database and an immediate project database are established. In principle, projects not included in the project database will not be arranged. The main contents to be reported include basic information of the project, annual investment plans, project income, existing debts, project assets, etc. Offline reporting is done in the name of the department with formal documents, and the content is similar to that reported online.

[0051] Step 3: Bind the bond portfolio according to the issuance data set and approval document number , and then generate the corresponding sales data set according to the bond underwriters' statistics on bond sales ;

[0052] Bond portfolio The binding process is as follows:

[0053] Based on the issuance data set, screen bonds by approval number. If the approval numbers of any two bonds are the same, bind the two bonds into one bond portfolio. If the approval numbers of any two bonds are inconsistent, the two bonds will be bound into two bond combinations. , a single bond portfolio For approval documents of a single financing project, a single approval document may correspond to multiple bonds, and a single bond portfolio The total face value of all bonds should be less than or equal to the approved amount in the approval document;

[0054] Sales Data Group The calculation process is as follows:

[0055] S11. Based on the issuance dataset, the bond underwriters are marked as , to Indicates the first to underwriters, among which the Underwriters marked , ;

[0056] S12. According to the issued data set, count the Underwriters sales records and Underwriters The total sales amount is marked as , will Underwriters The sales duration is marked as ; In the formula, It represents the ratio of total sales to sales time, which is Underwriters Sales speed, It means calculating the sales speed of all underwriters at the same time, which is the sales data group;

[0057] Specifically, bond management is carried out from the underwriter dimension, such as statistics on the unsold balance of bonds, the amount sold, the ranking of investors holding bonds, and bond yield analysis and key indicators of outstanding bond analysis, which are all helpful for bond managers to conduct overall control at the macro level;

[0058] Step 4: Analyze each investor’s financial status based on the investment data set and generate the corresponding risk factor , the calculation process is as follows:

[0059] Extract the investment data set The financial data of each investor and The purchase size of each investor is marked as , will The cash flows of each investor are denoted by , will The historical default times of an investor are marked as , will The debt amount of each investor is marked as ; In the formula, Represents the evaluation weight for the purchase size and cash flow ratio, represents the assessment weight for the number of historical defaults, represents the assessment weight for the debt amount, , Indicates according to , and Weight, get Risk factor for each investor , comprehensively considering multi-dimensional parameters, it can accurately screen out investors with higher risks, and the multi-dimensional management and control efficiency is high;

[0060] Step 5: Set the internal threshold of the fixed range , External Threshold and risk thresholds , combined with the efficiency data set , Sales Data Group and risk factor , evaluate the internal approval progress of enterprises, the approval progress of external regulatory agencies, the sales speed ranking of underwriters, and the credit risk of investors, efficiency data group The efficiency of internal approval in the enterprise is lower than the internal threshold When the internal approval process of the enterprise is slow, a corresponding follow-up warning signal is generated, and the processing efficiency of the external regulatory agency during approval is lower than the external threshold When the external regulatory agency is slow in approving, a corresponding follow-up warning signal is generated. , rank underwriters from high to low according to sales speed, generate corresponding underwriter ranking table, and the risk coefficient of a single investor Exceeding risk threshold When , it indicates that the credit risk of the investor is high, and a corresponding risk warning signal is generated, and the risk warning capability is strong;

[0061] Specifically, a sound credit rating system is established for corporate financing, and then the following information of investors is evaluated by the evaluation agency:

[0062] Information on the debt structure of investors that determine the liability of the creditor;

[0063] the ability of investors to adhere to prudent budgetary policies and administrative discipline;

[0064] Determine the characteristic amount of indirect income that investors can use;

[0065] An assessment of the investor's overall socio-economic environment;

[0066] Implement risk warnings, promptly handle debt risks, and conduct financial inspections of enterprises to determine whether the enterprise is close to an emergency. If it is close to an emergency, it will be included in the early warning catalog;

[0067] The situations included in the "Early Warning List" include but are not limited to:

[0068] Scenario 1: One of the following two situations occurs:

[0069] (1) At the end of a fiscal year, the general budget and special budget unpaid funds, other than general and special budget surpluses, which are overdue for more than 30 days, exceed 1 / 12 of the available income of the fiscal year;

[0070] (2) At the end of the fiscal year, after deducting the year-end budget savings, the amount of general budget unpaid that is overdue for more than 30 days exceeds 1 / 12 of the budget for that year.

[0071] Scenario 2: The amount of general and special budget funds available to supplement the deficit, deducted from the total deficit of the previous fiscal year, exceeds 1 / 12 of the total general fund budget revenue for the current year.

[0072] Scenario 3: At the end of the fiscal year, the value of cash and marketable securities held by the enterprise, minus the amount of signed checks and guarantee balances, is less than the general budget and special budget balances, and the difference exceeds 1 / 12 of the enterprise's revenue in the previous fiscal year.

[0073] At the same time, the present invention constructs a credit bond precursor default model according to a preset cycle, specifically including:

[0074] Determine each credit bond issuer; obtain a first number of original indicators of each credit bond issuer, generate a second number of dynamic indicators based on the first number of original indicators, and then obtain a third number of variable indicators; wherein the third number is equal to the first number plus the second number;

[0075] Build an integrated learning algorithm model, which includes the XGBoost algorithm model and the random forest algorithm model.

[0076] Using the credit bond precursor default model, the public data database and the internal data database, the credit bond default issuer is predicted, including:

[0077] Using a database of public data and a database of in-line data, respectively running an XGBoost algorithm model and a random forest algorithm model to obtain a first calculation result of the XGBoost model on the public data, a second calculation result of the XGBoost model on the in-line data, a third calculation result of the random forest model on the public data, and a fourth calculation result of the random forest model on the in-line data;

[0078] The defaulting issuer of the credit bond is determined based on the first, second, third and fourth calculation results, and early warning and control are carried out on the credit bond issuer.

[0079] The enterprise management system can formulate core visualization indicators based on the enterprise management characteristics and demands, and display them on a large visualization screen.

[0080] Repayment and interest calculation function: query and filter the bond business ledgers that need to be calculated. If a date selection instruction is received, the bond interest and repayment information for the selected period will be calculated, and interest will be calculated in stages according to interest rate changes. The comprehensive financing cost of the bond business will be calculated based on the bond issuance information consisting of the bond term, underwriting fees, attorney fees, and interest rates.

[0081] Bond interest repayment plan: receiving input bond interest repayment plan information; reviewing the bond interest repayment plan information; after passing the review, executing the bond interest repayment plan.

[0082] Real-time detection of the maturity of bond business: When the maturity of bond business is detected, an advance notice of maturity repayment will be issued, with strong risk warning capabilities.

[0083] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A bond portfolio management and control method for corporate financing, characterized by: The following steps are involved: Step 1: Connect to the bond management platform through the network to obtain the management data of all financing projects, the issuance data of all bonds and the financial data of all investors, and classify them into project data sets, issuance data sets and investment data sets; Step 2: Analyze the approval status of each financing project based on the project data set and generate the corresponding efficiency data set ; Step 3: Bind the bond portfolio according to the issuance data set and approval document number , and then generate the corresponding sales data set according to the bond underwriters' statistics on bond sales ; Step 4: Analyze each investor’s financial status based on the investment data set and generate the corresponding risk factor ; Step 5: Set the internal threshold of the fixed range , External Threshold and risk thresholds , combined with the efficiency data set , Sales Data Group and risk factor , evaluate the internal approval progress of the enterprise, the approval progress of the external regulatory agency, the underwriter sales speed ranking, and the credit risk of investors, and generate corresponding early warning signals and ranking forms.

2. The bond portfolio management and control method for corporate financing according to claim 1, characterized in that: In step 1, the expression of the project data set is , to The first to the Management data of each financing project, including the start time, application time and approval time. Indicates the declared amount of each financing project.

3. The bond portfolio management and control method for corporate financing according to claim 2, characterized in that: In step 1, the expression of the released data set is: , to The first to the The issuance data of bonds includes the face value, bond type, underwriter and sales record of bonds. The bond types include special bonds and market-based financing bonds. Indicates the approval document number corresponding to each bond.

4. The bond portfolio management and control method for corporate financing according to claim 3, characterized in that: In step 1, the expression of the investment data set is: , to The first to the Financial data of each investor, including purchase size, cash flow and historical default times, Indicates the amount of debt each investor has.

5. The bond portfolio management and control method for corporate financing according to claim 4, characterized in that: In step 2, the efficiency data set The calculation process is as follows: According to the project data set, extract the management data of each financing project and The start time of each financing project is marked as , will The application time point of each financing project is marked as , will The approval time point of each financing project is marked as , will The declared amount of each financing project is marked as ; In the formula, It indicates the time difference between project application and start-up, which is the internal approval time of the enterprise. It represents the ratio of the declared amount to the internal approval time of the enterprise, that is, the internal approval time of the enterprise. The processing efficiency of each financing project, It indicates the time difference between project approval and application, that is, the time required for external regulatory agencies to review and approve the project. It represents the ratio of the declared amount to the time taken for external regulatory authorities to review and approve the application. The efficiency of handling financing projects.

6. The bond portfolio management and control method for corporate financing according to claim 5, characterized in that: In step 3, the bond portfolio The binding process is as follows: Based on the issuance data set, screen bonds by approval number. If the approval numbers of any two bonds are the same, bind the two bonds into a bond portfolio. If the approval numbers of any two bonds are inconsistent, the two bonds will be bound into two bond combinations. , a single bond portfolio Approval documents for a single financing project, a single bond portfolio The total face value of all bonds should be less than or equal to the approved amount in the approval document.

7. A bond portfolio management and control method for corporate financing according to claim 6, characterized in that: In step 3, the sales data group The calculation process is as follows: S11. Based on the issuance dataset, the bond underwriters are marked as , to Indicates the first to underwriters, among which the Underwriters marked , ; S12. According to the issued data set, count the Underwriters sales records and Underwriters The total sales amount is marked as , will Underwriters The sales duration is marked as ; In the formula, It represents the ratio of total sales to sales time, which is Underwriters Sales speed, It means calculating the sales speed of all underwriters at the same time, which is the sales data group.

8. The bond portfolio management and control method for corporate financing according to claim 7, characterized in that: In step 4, the risk factor The calculation process is as follows: Extract the investment data set The financial data of each investor and The purchase size of each investor is marked as , will The cash flows of each investor are denoted by , will The historical default times of an investor are marked as , will The debt amount of each investor is marked as ; In the formula, Represents the evaluation weight for the purchase size and cash flow ratio, represents the assessment weight for the number of historical defaults, represents the assessment weight for the debt amount, , Indicates according to , and Weight, get Risk factor for each investor .

9. A bond portfolio management and control method for corporate financing according to claim 8, characterized in that: Step 5: Efficiency Data Group The efficiency of internal approval in the enterprise is lower than the internal threshold When the internal approval process of the enterprise is slow, a corresponding follow-up warning signal is generated, and the processing efficiency of the external regulatory agency during approval is lower than the external threshold When it is detected, it indicates that the approval progress of the external regulatory agency is slow, and a corresponding follow-up warning signal is generated.

10. A bond portfolio management and control method for corporate financing according to claim 9, characterized in that: Step 5: According to the sales data group , rank underwriters from high to low according to sales speed, generate corresponding underwriter ranking table, and the risk coefficient of a single investor Exceeding risk threshold , it indicates that the credit risk of the investor is high and a corresponding risk warning signal is generated.

Images