Dynamic financing management system and method for electric power receivable

Abstract

The invention discloses a dynamic financing management system and method for electric power receivable, and the method comprises the steps: building an electric power supply chain receivable data pool: carrying out the butt joint with an electric power transaction platform through a block chain technology, obtaining the contract, invoice and receivable right confirmation information of a core enterprise and a supplier in real time, and forming a non-tampering electronic certificate. According to the method, a hyperdger Fabric alliance chain is utilized to construct a cross-institution data pool, and automatic verification and synchronization of contracts, invoices and payment records are achieved. For example, the state grid'electricity e service 'platform confirms the right through the block chain, the time from financing application to loan is shortened to be within 24 hours, and the efficiency is improved by 90%; the electronic certificate which cannot be tampered eliminates the risk of manual intervention, and financing disputes caused by receipt errors are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power financing, and in particular to a dynamic financing management system and method for electric power accounts receivable. Background Art

[0002] As my country's economic system reform continues to deepen, power companies are increasingly facing problems in their accounts receivable management as they move towards the market. This article analyzes the problems power companies face in accounts receivable management and proposes that they should establish a "win-win" accounts receivable management model and further strengthen management in terms of both pre-control and daily management of accounts receivable.

[0003] Currently, accounts receivable financing management in the power industry primarily relies on traditional financial instruments, which present several technical bottlenecks: Accounts receivable confirmation requires manual review by core enterprises, paper contracts and invoices require a long circulation cycle (averaging 3-5 business days), and cross-institutional data cannot be synchronized in real time. For example, State Grid suppliers must submit contracts and invoices offline to the finance department, resulting in redundant processes and delayed financing responses. Therefore, there is an urgent need to design a dynamic financing management system and method for power accounts receivable to address these issues. Summary of the Invention

[0004] The purpose of the present invention is to provide a dynamic financing management system and method for electricity accounts receivable to solve the above-mentioned deficiencies in the prior art.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A dynamic financing management method for power accounts receivable includes the following steps:

[0007] S1 establishes a data pool for accounts receivable in the power supply chain: by connecting to the power trading platform through blockchain technology, it obtains real-time information on contracts, invoices, and accounts receivable confirmation between core enterprises (State Grid, China Southern Power Grid, and its subsidiaries) and suppliers, forming an unalterable electronic certificate;

[0008] S2 dynamic credit assessment: Using a machine learning model, based on supplier historical transaction data, core enterprise credit ratings, and industry risk coefficient (R = a·Ccore+β·Vhistory+γ·Isector, where α+β+γ=1);

[0009] S3 financing quota dynamic matching: based on the age and amount of accounts receivable and the payment cycle of core enterprises:

[0010] Q=0.7A·e -λt Calculate real-time credit limit;

[0011] S4 interest rate dynamic adjustment: based on LPR benchmark interest rate and supplier credit score

[0012] S5 automated repayment settlement: triggers the transfer of principal and interest on the core enterprise’s payment date through smart contracts, and returns the remaining amount to the supplier’s account.

[0013] Preferably, the blockchain nodes in step S1 include power trading platforms, financial institutions, and third-party credit reporting agencies, and Hyperledger Fabric consortium chain is used to achieve cross-institutional data synchronization.

[0014] Preferably, the credit assessment model of step S2 integrates enterprise electricity consumption data, tax payment records and industry prosperity index, and the input layer uses an LSTM neural network to process time series data.

[0015] Preferably, the risk attenuation coefficient λ in step S3 is dynamically adjusted according to the historical payment delay rate of the core enterprise, and λ increases by 0.05 for every 1% increase in the delay rate.

[0016] Preferably, in step S4, an interest rate floating upper limit mechanism is set: when Scredit≤60, rmax≤9%; when Scredit>80, rmin≥5%.

[0017] Preferably, it also includes an accounts receivable securitization module, which will reorganize asset packages that meet the conditions (account period > 6 months, amount > 5 million yuan) in a hierarchical manner to generate tradable ABS products.

[0018] Preferably, the smart contract in step S5 sets dual trigger conditions: the core enterprise pays or the factoring company initiates the compensation procedure 30 days before the expiration of the account period.

[0019] Preferably, a risk hedging mechanism is introduced: when the industry risk coefficient R>0.6, the purchase of credit insurance and the reduction of financing amount by 20% are automatically triggered.

[0020] Preferably, a supplier profiling system should be established, incorporating indicators such as accounts receivable turnover rate and bad debt rate into the blockchain credit score, and updating financing permissions every quarter.

[0021] In addition, a dynamic financing management system for electricity accounts receivable is provided, which is implemented using the dynamic financing management method for electricity accounts receivable.

[0022] In the aforementioned technical solution, the present invention provides a dynamic financing management system and method for electricity accounts receivable. This system utilizes the Hyperledger Fabric consortium blockchain to build a cross-institutional (grid companies, suppliers, and financial institutions) data pool, enabling automated verification and synchronization of contracts, invoices, and payment records. For example, the State Grid Corporation of China's "Electricity e-Financial Services" platform uses blockchain-based title verification to shorten the time from financing application to loan disbursement to within 24 hours, improving efficiency by 90%. Tamper-proof electronic certificates eliminate the risk of manual intervention and reduce financing disputes caused by document errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0024] Figure 1 A schematic diagram of the steps of an embodiment of a dynamic financing management system and method for electricity accounts receivable provided by the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0026] like Figure 1 As shown, an embodiment of the present invention provides a dynamic financing management method for power accounts receivable, comprising the following steps:

[0027] S1 establishes a data pool for accounts receivable in the power supply chain: by connecting to the power trading platform through blockchain technology, it obtains real-time information on contracts, invoices, and accounts receivable confirmation between core enterprises (State Grid, China Southern Power Grid, and its subsidiaries) and suppliers, forming an unalterable electronic certificate;

[0028] S2 dynamic credit assessment: Using a machine learning model, based on supplier historical transaction data, core enterprise credit ratings, and industry risk coefficient (R = α·Ccore+β·Vhistory+γ·Isector, where α+β+γ=1);

[0029] S3 financing quota dynamic matching: based on the age and amount of accounts receivable and the payment cycle of core enterprises:

[0030] Q=0.7A·e -λt Calculate real-time credit limit;

[0031] S4 interest rate dynamic adjustment: based on LPR benchmark interest rate and supplier credit score

[0032] S5 automated repayment settlement: triggers the transfer of principal and interest on the core enterprise’s payment date through smart contracts, and returns the remaining amount to the supplier’s account.

[0033] In step S1, the blockchain nodes include the power trading platform, financial institutions, and third-party credit reporting agencies, and the Hyperledger Fabric consortium chain is used to achieve cross-institutional data synchronization.

[0034] The credit assessment model in step S2 integrates corporate electricity consumption data, tax payment records, and industry prosperity index. The input layer uses an LSTM neural network to process time series data.

[0035] The risk attenuation coefficient λ in step S3 is dynamically adjusted according to the historical payment delay rate of the core enterprise. For every 1% increase in the delay rate, λ increases by 0.05.

[0036] In step S4, an interest rate floating upper limit mechanism is set: when Scredit≤60, rmax≤9%; when Scredit>80, rmin≥5%.

[0037] It also includes an accounts receivable securitization module, which will restructure asset packages that meet the requirements (account period > 6 months, amount > 5 million yuan) in a hierarchical manner to generate tradable ABS products.

[0038] The smart contract in step S5 sets dual trigger conditions: the core enterprise pays or the factoring company initiates the compensation procedure 30 days before the expiration of the account.

[0039] Introduce a risk hedging mechanism: When the industry risk coefficient R>0.6, it will automatically trigger the purchase of credit insurance and reduce the financing limit by 20%.

[0040] Establish a supplier profiling system, incorporate indicators such as accounts receivable turnover rate and bad debt rate into blockchain credit scoring, and update financing permissions every quarter.

[0041] Example 1

[0042] A dynamic financing management method for power accounts receivable includes the following steps:

[0043] S1 establishes a data pool for accounts receivable in the power supply chain: by connecting to the power trading platform through blockchain technology, it obtains real-time information on contracts, invoices, and accounts receivable confirmation between core enterprises (State Grid, China Southern Power Grid, and its subsidiaries) and suppliers, forming an unalterable electronic certificate;

[0044] S2 dynamic credit assessment: Using a machine learning model, based on supplier historical transaction data, core enterprise credit ratings, and industry risk coefficient (R = α·Ccore+β·Vhistory+γ·Isector, where α+β+γ=1);

[0045] S3 financing quota dynamic matching: based on the age and amount of accounts receivable and the payment cycle of core enterprises:

[0046] Q=0.7A·e -λt Calculate real-time credit limit;

[0047] S4 interest rate dynamic adjustment: based on LPR benchmark interest rate and supplier credit score

[0048] S5 automated repayment settlement: triggers the transfer of principal and interest on the core enterprise’s payment date through smart contracts, and returns the remaining amount to the supplier’s account.

[0049] Example 2

[0050] This embodiment is further limited based on the embodiment 1. In step S1, the blockchain nodes include the power trading platform, financial institutions, and third-party credit agencies, using Hyperledger The Fabric consortium chain enables cross-institutional data synchronization. The credit assessment model in step S2 integrates corporate electricity consumption data, tax payment records, and industry prosperity indexes, and the input layer uses an LSTM neural network to process time-series data. The risk attenuation coefficient λ in step S3 is dynamically adjusted based on the core enterprise's historical payment delay rate, with λ increasing by 0.05 for every 1% increase in the delay rate. Step S4 establishes a floating interest rate cap: when Scredit ≤ 60, rmax ≤ 9%; when Scredit > 80, rmin ≥ 5%. It also includes an accounts receivable securitization module that tiers and restructures asset packages that meet the requirements (account period > 6 months, amount > 5 million yuan) to generate tradable ABS products. The smart contract in step S5 sets dual trigger conditions: the factoring company's compensation process is initiated 30 days before the core enterprise pays or the account expires. A risk hedging mechanism is introduced: when the industry risk coefficient R > 0.6, it automatically triggers the purchase of credit insurance and reduces the financing limit by 20%. A supplier profiling system is established, incorporating indicators such as accounts receivable turnover rate and bad debt rate into blockchain credit scoring, and financing permissions are updated quarterly.

[0051] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

Claims

1. A dynamic financing management method for power accounts receivable, characterized in that: The following steps are involved: S1 establishes a data pool for accounts receivable in the power supply chain: by connecting to the power trading platform through blockchain technology, it obtains real-time information on contracts, invoices, and accounts receivable confirmation between core enterprises (State Grid, China Southern Power Grid, and its subsidiaries) and suppliers, forming an unalterable electronic certificate; S2 dynamic credit assessment: Using a machine learning model, based on supplier historical transaction data, core enterprise credit ratings, and industry risk coefficient (R = α·Ccore+β·Vhistory+γ·Isector, where α+β+γ=1); S3 financing quota dynamic matching: based on the age and amount of accounts receivable and the payment cycle of core enterprises: Q = 0.7A·e -λt Calculate real-time credit limit; S4 interest rate dynamic adjustment: based on LPR benchmark interest rate and supplier credit score S5 automated repayment settlement: triggers the transfer of principal and interest on the core enterprise’s payment date through smart contracts, and returns the remaining amount to the supplier’s account.

2. The dynamic financing management method for power accounts receivable according to claim 1, characterized in that: In step S1, the blockchain nodes include the power trading platform, financial institutions, and third-party credit reporting agencies, and the Hyperledger Fabric consortium chain is used to achieve cross-institutional data synchronization.

3. The dynamic financing management method for power accounts receivable according to claim 1, characterized in that: The credit assessment model in step S2 integrates corporate electricity consumption data, tax payment records, and industry prosperity index. The input layer uses an LSTM neural network to process time series data.

4. The method for dynamic financing management of power accounts receivable according to claim 1, characterized in that: The risk attenuation coefficient λ in step S3 is dynamically adjusted according to the historical payment delay rate of the core enterprise. For every 1% increase in the delay rate, λ increases by 0.

05.

5. The method for dynamic financing management of power accounts receivable according to claim 1, characterized in that: In step S4, an interest rate floating upper limit mechanism is set: when Scredit≤60, rmax≤9%; when Scredit>80, rmin≥5%.

6. The method for dynamic financing management of power accounts receivable according to claim 1, characterized in that: It also includes an accounts receivable securitization module, which will restructure asset packages that meet the requirements (account period > 6 months, amount > 5 million yuan) in a hierarchical manner to generate tradable ABS products.

7. The method for dynamic financing management of power accounts receivable according to claim 1, characterized in that: The smart contract in step S5 sets dual trigger conditions: the core enterprise pays or the factoring company initiates the compensation procedure 30 days before the expiration of the account.

8. The method for dynamic financing management of power accounts receivable according to claim 1, characterized in that: Introduce a risk hedging mechanism: When the industry risk coefficient R>0.6, it will automatically trigger the purchase of credit insurance and reduce the financing limit by 20%.

9. The method for dynamic financing management of power accounts receivable according to claim 1, characterized in that: Establish a supplier profiling system, incorporate indicators such as accounts receivable turnover rate and bad debt rate into blockchain credit scoring, and update financing permissions every quarter.

10. A dynamic financing management system for electricity accounts receivable, characterized in that: This is achieved by using the dynamic financing management method for electricity accounts receivable as described in any one of claims 1-9.

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