CN113393315A - Loan customer recommendation method and system based on power supply chain data - Google Patents
Loan customer recommendation method and system based on power supply chain data Download PDFInfo
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Abstract
The invention belongs to the technical field of power markets, and particularly relates to a loan customer recommendation method and system based on power supply chain data. The system comprises a power data acquisition module, a potential customer recommending module, a bank pre-approval management module, a loan application module, a loan approval management module, a money-returning account changing module, a payment certificate management module, an approval and payment management module, a payment certificate management module and a financial statistics management module. The method is based on the power supply chain, is oriented to cooperative banks, develops potential loan customer recommendation service, takes power data as a core, analyzes normal and abnormal variation factors of electric charge and electricity quantity, constructs a user credit model, carries out user credit rating on users, assists banks in accurately expanding loan service, opens up a new space for financing of small and medium-sized enterprises, and improves the operator environment. The production and operation conditions of enterprises are objectively and accurately reflected, and the problem of asymmetric information between financial institutions such as government supervision departments, banks and the like and loan objects is solved.
Description
Technical Field
The invention belongs to the technical field of power markets, and particularly relates to a loan customer recommendation method and system based on power supply chain data.
Background
The electric power data has the values of finance, marketing, management, energy efficiency and the like, can be widely applied to power customers such as governments, banks, telecommunication and socialization enterprises and the like, and gradually realize productization and commercialization in the form of algorithms, data models, applications and platforms.
At present, some enterprises in the civil and private enterprises lack credit history, assets for guarantee and standard financial information, and the self-certified production and operation conditions required by enterprise loan generally have the problems of difficult loan and expensive loan. The commercial bank has the problems of difficult loan reservation and difficult inventory loan client management. The bank administration encourages and requires commercial banks to credit the civil enterprises, but the effect is not obvious. Under the background, the service requirements of intelligent power big data and finance are particularly urgent, the power data can objectively and accurately reflect the production and operation conditions of enterprises, and further the problem of information asymmetry between financial institutions such as government supervision departments and banks and loan objects is solved. This not only reduces the risk faced in the transaction, but also makes the medium and small businesses no longer desirable and unreachable in the credit market.
Therefore, it is necessary to develop a method and a system for controlling and monitoring the power data usage status of the existing small and medium-sized enterprises, which is a new subject continuously developed by those skilled in the art.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a loan customer recommendation method and system based on power supply chain data. The loan transaction assisting system aims to solve the problem that information of financial institutions such as government regulatory departments, banks and the like and loan objects is not symmetrical, can assist banks in accurately expanding loan services, opens up a new space for financing of small and medium-sized enterprises, and improves the environment of operators.
The technical scheme adopted by the invention for realizing the purpose is as follows:
a loan customer recommendation system based on power supply chain data, comprising: the system comprises an electric power data acquisition module, a potential customer recommending module, a bank pre-approval management module, a loan application module, a loan approval management module, a money-returning account changing module, a payment certificate management module, an approval and payment management module, a payment certificate management module and a financial statistics management module; the power data acquisition module is connected with an external service basic information database; one end of the recommending potential client module is connected with the electric power data acquisition module, and the other end of the recommending potential client module is connected with the bank preliminary examination management module; the loan application module and the repayment change account module are respectively connected with the system database, and the payment voucher management module is connected with the repayment change account module; the approval and payment management module is simultaneously connected with the change refund account module and the payment certificate management module respectively; the financial statistics management module is connected with the payment voucher management module, and the other end of the payment voucher management module is connected with the approval payment management module.
Further, the electric power data acquisition module is connected to an external service basic information database in a local area network mode, and acquires key indexes formed by supplier bid-winning information, supplier contract information and supplier payment information data distributed in the database;
one end of the potential customer recommending module is connected with the electric power data collecting module, and the other end of the potential customer recommending module is connected with the bank pre-audit management module; key data are acquired from the power data acquisition module, then screened according to bank requirement conditions, organized into high-quality white list customers, and pushed to the bank preliminary examination management module;
the bank preliminary examination management module receives the information recommended by the potential client recommending module, performs preliminary examination according to the credit granting conditions of bank financing loan products, and returns a credit granting result through an information system connected by a bottom private network;
the loan application module is connected with the system database, identifies the initial examination result identification, allows the bank initial examination user to open the loan application operation authority, dynamically verifies and controls the application amount to be less than the credit line, and transmits the financing intention of applying for loan and the loan data list to the loan approval management module through the system;
the loan approval management module receives the financing intention and loan data list information of the loan application module, performs approval operation by combining loan approval conditions, and transmits approval results back to the system;
the system comprises a system database, an examination and approval result identification module, a change fund account identification module and a system, wherein the examination and approval result identification module is connected with the system database, identifies the examination and approval result identification, completes the change of a fund account by an examined and approved user, uploads a change evidence material and returns the change fund account result identification to the system;
the payment voucher management module is connected with the change refund account module, uploads the evidence data of the user who has successfully changed the refund account, and transmits the result identification back to the system;
the approval loan management module is simultaneously connected with the change refund account module and the payment certificate management module, receives the result identification, and marks the allowable loan identification on the user who has successfully completed the necessary operations before two loans are paid;
the money depositing voucher management module uploads a money depositing voucher to the system by a bank according to the actual money depositing condition, and the information is filed and then used by the financial statistics management module;
the financial statistics management module is connected with the money depositing voucher management module, processes money depositing data, collects and counts data such as total number of deposited suppliers, total amount of deposited money, interest distribution and the like, and outputs the data to key authority users such as banks and the like through the system.
A loan customer recommendation method based on power supply chain data comprises the following steps:
step 1, building a potential loan customer recommendation system of electric power data to realize an integrated management platform of electric power service;
step 2, collecting power data, and dynamically acquiring power consumption behavior data of a supplier;
step 3, a platform manager of the potential loan client recommendation system of the electric power data screens potential clients meeting the conditions according to the requirements and recommends the potential clients to a target cooperative bank;
step 4, the recommended potential client carries out authority login and real-name authentication through a potential loan client recommending system of the electric power data, submits a loan application and completes the repayment account number change operation;
step 5, after the bank acquires the potential customer information through a potential loan customer recommending system of the electric power data, carrying out intention cooperation negotiation and completing approval operation;
and 6, the potential loan customer recommendation system of the electric power data monitors the refund transaction condition of a supplier in the loan in real time through a background automatic operation program, gives an early warning in time and assists in bank risk prevention and control.
Further, the power data includes: the method comprises the steps that bid winning information, supplier contract information and supplier payment information of a supplier are obtained, electric power operation data of a user are accessed to a potential loan customer recommendation system of electric power data, and potential customers to be recommended are screened out through a system recommendation model;
the supplier bid-winning information refers to supplier information of each batch of material or non-material bid-winning projects of the winning-winning power company;
the supplier contract information refers to information of a supplier having a direct contract relation with an electric company, and comprises contract amount, payment proportion and pre-payment amount, the system takes the total contract of the supplier as support data and recommends the total contract to a bank, and the bank effectively evaluates whether the supplier meets the condition that the order amount under the business contract is more than or equal to the bank financing amount through the data in a mode of constructing an order pool.
Furthermore, the change of the refund account number refers to a cash collection card account number in a contract between a supplier and an electric power company, and the refund account number needs to be changed into a specified bank account number required by a bank.
Furthermore, the refund transaction condition refers to the abnormal change of the refund account number of the supplier or the abnormal change of the refund amount, the system converts the applicable loan amount of the supplier according to the unpaid amount of the supplier as a key index, the system dynamically checks the filling amount and meets the requirement that the application amount is not more than the value obtained by the system calculation rule.
Further, the method comprises the following steps:
the method comprises the following steps that (1) the cooperation intention of 'potential financing client recommendation' products is achieved with multiple banks, business plates and operation processes are cleared, enterprise qualification, winning bid information, historical performance and electricity utilization conditions are comprehensively analyzed, and important recommendation is conducted on the products to the banks;
step (2) collecting power data, dynamically acquiring power consumption behavior data of a supplier, analyzing normal and abnormal variation factors of power charge and electricity quantity by taking the power data as a core, extracting, processing and converting data from mass data, carrying out user analysis on multi-dimensional index data of power marketing data, constructing a user credit model, and carrying out user credit rating on a user; accessing the power operation data of the user into a potential loan customer recommendation system of the power data, and labeling potential customers to be recommended through a recommendation model;
step (3) the platform manager of the potential loan customer recommendation system of the electric power data combines the bid winning information of the supplier, the contract information of the supplier and the payment information of the supplier, screens potential customers meeting the conditions according to the requirements and recommends the potential customers to a target cooperative bank;
step (4), the recommended potential client performs authority login and real-name authentication through a potential loan client recommendation system of the electric power data, submits a loan application and completes a repayment account number change operation;
step 5, after acquiring potential customer information through a potential loan customer recommendation system of the electric power data, carrying out intention cooperation negotiation and completing approval operation by the bank;
and (6) the potential loan customer recommendation system of the electric power data monitors the refund transaction condition of a supplier in the loan in real time through a background automatic operation program, gives an early warning in time, and assists in bank risk prevention and control.
Further, the completion approval operation satisfies the following conditions:
the bank financing open is less than or equal to (all business contract amount-paid amount under the business contract item-no financing part under the business contract item) multiplied by the financing proportion;
bank financing open = bank financing amount (including loan, bank acceptance draft) -deposit amount-pledge amount of the pledge;
the amount paid under the business contract = prepaid + normal performance payment under the contract;
the part of non-financing under the business contract item is the sum of the quality insurance sum and the sum of other performance guarantee items with longer time limit;
the financing proportion is the financing proportion which is approved by the bank according to the credit and credit conditions of the supplier and is 100 percent at most.
Further, the refund transaction situation of the supplier comprises:
after the bank provides financing, if the system monitors the payment of the core enterprise (party A), the 'control formula' is automatically monitored:
if the control formula is not established, the following measures are taken for the refund of the 'deficit part' (all business contract amount-paid amount under the item of the business contract-non-financing part under the item of the business contract) x financing proportion-bank financing exposure):
paying back bank financing/refund into a deposit account/bank acceptance draft for pledge;
if the control formula is established, the refund fund or the bill is automatically used by the supplier.
A computer storage medium having a computer program stored thereon, the computer program when executed by a processor implementing the steps of a loan client recommendation method based on power supply chain data.
The invention has the following beneficial effects and advantages:
the electric power data can objectively and accurately reflect the production and operation conditions of enterprises, and solve the problem of asymmetric information between financial institutions such as government supervision departments, banks and the like and loan objects.
The invention relies on the power supply chain, faces cooperative banks, develops the recommendation service of potential loan customers, takes power data as the core, analyzes the normal and abnormal variation factors of the electric charge and the electric quantity, extracts, processes and converts the data from mass data, carries out user analysis on the multi-dimensional index data of the electric marketing data, namely basic attribute, electric quantity attribute, electric charge attribute, prepayment attribute, arrearage attribute, metallic property, payment timeliness attribute, acceptance bill attribute, capacity increase and decrease attribute and default electric property, adopts scientific analysis methods such as factor analysis, cluster analysis, normal distribution, weight analysis and the like, constructs a user credit model containing key indexes of arrearage, payment and user electric behavior through complex calculation, carries out user credit rating and accurate recommendation on users, assists banks to accurately extend loan service, and opens up a new space for medium and small enterprises for financing, improving the environment of the operator.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is an overall architectural diagram of the present invention;
fig. 2 is a simplified business process diagram of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
The solution of some embodiments of the invention is described below with reference to fig. 1 and 2.
Example 1
The invention relates to a loan customer recommendation method based on power supply chain data, which comprises the following steps:
step 1, a potential loan customer recommendation system of the electric power data is built, and an integrated management platform of the electric power service is realized.
Specifically, a potential loan customer recommendation system of electric power data is built, and an integrated management platform for carrying services such as target customer pushing, bank loan approval, supplier loan tracking, system transaction monitoring and the like of multi-party user service interaction of an electric power supplier, a power supply enterprise, a credit power utilization enterprise, a bank and the like is realized.
And 2, acquiring power data and dynamically acquiring power consumption behavior data of a supplier.
The power data includes: the method comprises the steps of bidding information of a supplier, contract information of the supplier and payment information of the supplier, accessing electric power operation data of a user into a potential loan customer recommendation system of electric power data, and screening potential customers to be recommended through a system recommendation model.
Preferably, the supplier bid information refers to supplier information of each batch of goods or non-goods bidding items of the winning electric power company.
Preferably, the supplier contract information refers to information of a supplier having a direct contract relationship with the power company, and includes key information such as contract amount, payment proportion, pre-payment amount and the like, the system can recommend the system to a bank by taking the total contract of the supplier as support data, the bank can establish an order pool mode, and whether the supplier meets the condition that the order amount under the business contract is more than or equal to the bank financing amount can be effectively evaluated through the data.
And 3, screening potential customers with good faith levels and contract limit meeting conditions according to the requirements by a platform manager of the potential loan customer recommendation system of the electric power data, and recommending the potential customers to a target cooperative bank.
The platform administrator is a data company.
The meeting condition means that: the historical electricity utilization behavior of the supplier enterprise is good and above, the historical payment performance is good and above, the cooperation is 2 years and above, and the trading contract limit is over 100 ten thousand.
And 4, the recommended potential client performs authority login and real-name authentication through a potential loan client recommendation system of the electric power data, and then submits a loan application to complete the repayment account number change operation.
Preferably, the refund account change refers to a cash collection card account in a contract between a supplier and an electric power company, and needs to be changed into a specified bank account required by a bank.
And 5, after the bank acquires the information of the potential customers through the potential loan customer recommendation system of the electric power data, carrying out intention cooperation negotiation and completing the examination and approval operation.
The approval operation comprises the operations of initial loan examination, re-examination and loan payment.
And 6, the potential loan customer recommendation system of the electric power data monitors the refund transaction condition of a supplier in the loan in real time through a background automatic operation program, gives an early warning in time and assists in bank risk prevention and control.
Preferably, the refund transaction condition refers to the abnormal change of the refund account number of the supplier or the abnormal change of the refund amount, the system needs to convert the applicable loan amount of the supplier according to the unpaid amount of the supplier as a key index, the system dynamically checks the filling amount, and the required application amount is less than or equal to the value obtained by the system calculation rule.
Example 2
The invention also provides a loan customer recommendation system based on the power supply chain data, as shown in fig. 1, and fig. 1 is an overall architecture diagram of the invention.
The system of the invention comprises:
the system comprises a power data acquisition module, a potential customer recommending module, a bank pre-approval management module, a loan application module, a loan approval management module, a money-returning account changing module, a payment certificate management module, an approval payment management module, a payment certificate management module and a financial statistics management module.
The power data acquisition module is connected with an external service basic information database; one end of the recommending potential client module is connected with the electric power data acquisition module, and the other end of the recommending potential client module is connected with the bank preliminary examination management module; the loan application module and the repayment change account module are respectively connected with the system database, and the payment voucher management module is connected with the repayment change account module; the approval and payment management module is simultaneously connected with the change refund account module and the payment certificate management module respectively; the financial statistics management module is connected with the payment voucher management module, and the other end of the payment voucher management module is connected with the approval payment management module.
The electric power data acquisition module is connected to an external service basic information database in a local area network mode, and acquires data such as supplier bid-winning information, supplier contract information and supplier payment information distributed in the database to form key indexes.
One end of the potential customer recommending module is connected with the electric power data acquisition module, the other end of the potential customer recommending module is connected with the bank pre-audit management module, key data are acquired from the electric power data acquisition module, the key data are screened according to bank requirement conditions again, high-quality white list customers are sorted out and pushed to the bank pre-audit management module;
the bank preliminary examination management module receives the information recommended by the potential client recommending module, performs preliminary examination according to the credit granting conditions of bank financing loan products, and returns a credit granting result through an information system connected by a bottom private network;
the loan application module is connected with the system database, identifies the initial examination result identification, allows the bank initial examination user to open the loan application operation authority, dynamically verifies and controls the application amount to be less than the credit line, and transmits the financing intention of applying for loan and the loan data list to the loan approval management module through the system;
the loan approval management module receives the financing intention and loan data list information of the loan application module, performs approval operation by combining loan approval conditions, and transmits approval results back to the system;
the system comprises a system database, an examination and approval result identification module, a change fund account identification module and a system, wherein the examination and approval result identification module is connected with the system database, identifies the examination and approval result identification, completes the change of a fund account by an examined and approved user, uploads a change evidence material and returns the change fund account result identification to the system;
the payment voucher management module is connected with the change refund account module, uploads the evidence data of the user who has successfully changed the refund account, and transmits the result identification back to the system;
the approval loan management module is simultaneously connected with the change refund account module and the payment certificate management module, receives the result identification, and marks the allowable loan identification on the user who has successfully completed the necessary operations before two loans are paid;
and the money depositing voucher management module uploads the money depositing voucher to the system by the bank according to the actual money depositing condition. The information is archived and then used by a financial statistics management module;
the financial statistics management module is connected with the money depositing voucher management module, processes money depositing data, collects and counts data such as total number of deposited suppliers, total amount of deposited money, interest balance and the like, and outputs the data to key authority users such as banks and the like through the system;
the potential loan customer recommendation system for the electric power data provides systematic service, can assist banks to accurately extend loan services, solves the problems of difficult loan and expensive loan of small and medium-sized enterprises, and optimizes the electric power operator environment.
Example 3
The invention also provides a loan customer recommendation method based on the power supply chain data, as shown in fig. 2, and fig. 2 is a business flow diagram of the invention.
The method specifically comprises the following steps:
the method comprises the following steps of (1) achieving the intention of 'potential financing client recommendation' of a product with a plurality of banks, clearing business plates, working processes, comprehensively analyzing conditions of enterprise qualification, winning bid information, historical performance, electricity consumption and the like, intensively recommending to the banks, and assisting the banks in accurately expanding loan services. The electric potential loan customer recommendation system is designed, and an integrated management platform for carrying services such as target customer pushing, bank loan approval, supplier loan tracking, system transaction monitoring and the like of multi-party user service interaction of an electric power supplier, a power supply enterprise, an honest electricity utilization enterprise, a bank and the like is realized.
The method comprises the following steps of (2) acquiring power data, dynamically acquiring power consumption behavior data of a supplier, analyzing normal and abnormal variation factors of power consumption and electric quantity by taking the power data as a core, extracting, processing and converting data from mass data, carrying out user analysis on multi-dimensional index data of power marketing data, namely basic attributes, electric quantity attributes, power consumption attributes, prepayment attributes, arrearage attributes, metallic property, payment timeliness attributes, acceptance bill attributes, increase and decrease capacity attributes and default power consumption attributes, adopting scientific analysis methods such as factor analysis, cluster analysis, normal distribution, weight analysis and the like, constructing a user credit model containing key indexes of arrearage, payment and user power consumption behaviors through complex calculation, and carrying out user credit rating on a user. And accessing the power operation data of the user into a potential loan customer recommendation system of the power data, and labeling potential customers to be recommended through a recommendation model.
And (3) a platform manager of the potential loan customer recommendation system of the electric power data, namely a data company, combines bid winning information, contract information and payment information of a supplier, screens potential customers meeting conditions such as integrity level and contract amount according to needs, and recommends the potential customers to a target cooperative bank.
And (4) recommending potential customers, performing authority login and real-name authentication through the potential loan customer recommending system of the electric power data, and then submitting loan applications to complete the repayment account number changing operation. And searching and tracking the loan state through conditions such as the process state, the number, the supplier name and the like, and inquiring result list display subject information including the number, the process name, the supplier name and the current state.
And (5) after the bank acquires the potential customer information through a potential loan customer recommendation system of the electric power data, carrying out intention cooperative negotiation, and completing approval operations such as initial loan examination, review, loan payment and the like. Filling out intention financing amount and expected fund in-place time aiming at the passing suppliers; and filling out reason feedback for the abandoned enterprises.
The banking rules are as follows:
the bank financing open is less than or equal to (all business contract amount-paid amount under the business contract item-no financing part under the business contract item) multiplied by the financing proportion;
bank financing open = bank financing amount (including loan, bank acceptance draft) -deposit amount-pledge amount of the pledge;
the amount paid under the business contract = prepaid + normal performance payment under the contract;
the part of non-financing under the business contract item is the sum of the quality insurance sum and the sum of other performance guarantee items with longer time limit;
the financing proportion is the financing proportion which is approved by the bank according to the credit and credit conditions of the supplier and is 100 percent at most.
And (6) the potential loan customer recommendation system of the electric power data monitors the refund transaction condition of a supplier in the loan in real time through a background automatic operation program, gives an early warning in time, and assists in bank risk prevention and control. After the bank provides financing, if the system monitors the payment of the core enterprise (party A), the 'control formula' is automatically monitored:
if the control formula is not established, the following measures are required for the refund of the 'deficit part' (all business contract amount-paid amount under the business contract item-non-financing part under the business contract item) x financing proportion-bank financing exposure): paying back bank financing/refund into a deposit account/bank acceptance draft for pledge; if the control formula is established, the refund fund or the bill is independently used by the supplier without any operation.
The refund funds or tickets are made available to the supplier on their own, not including for purchasing property, entering stock market, etc.
Example 4
Based on the same inventive concept, embodiments of the present invention further provide a computer storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps of the loan client recommendation method and system based on power supply chain data described in embodiments 1, 2, or 3.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A loan customer recommendation system based on power supply chain data is characterized in that: the method comprises the following steps: the system comprises an electric power data acquisition module, a potential customer recommending module, a bank pre-approval management module, a loan application module, a loan approval management module, a money-returning account changing module, a payment certificate management module, an approval and payment management module, a payment certificate management module and a financial statistics management module; the power data acquisition module is connected with an external service basic information database; one end of the recommending potential client module is connected with the electric power data acquisition module, and the other end of the recommending potential client module is connected with the bank preliminary examination management module; the loan application module and the repayment change account module are respectively connected with the system database, and the payment voucher management module is connected with the repayment change account module; the approval and payment management module is simultaneously connected with the change refund account module and the payment certificate management module respectively; the financial statistics management module is connected with the payment voucher management module, and the other end of the payment voucher management module is connected with the approval payment management module.
2. The loan customer recommendation system based on the power supply chain data as claimed in claim 1, wherein: the electric power data acquisition module is connected to an external service basic information database in a local area network mode, and acquires key indexes formed by supplier bid-winning information, supplier contract information and supplier payment information data distributed in the database;
one end of the potential customer recommending module is connected with the electric power data collecting module, and the other end of the potential customer recommending module is connected with the bank pre-audit management module; key data are acquired from the power data acquisition module, then screened according to bank requirement conditions, organized into high-quality white list customers, and pushed to the bank preliminary examination management module;
the bank preliminary examination management module receives the information recommended by the potential client recommending module, performs preliminary examination according to the credit granting conditions of bank financing loan products, and returns a credit granting result through an information system connected by a bottom private network;
the loan application module is connected with the system database, identifies the initial examination result identification, allows the bank initial examination user to open the loan application operation authority, dynamically verifies and controls the application amount to be less than the credit line, and transmits the financing intention of applying for loan and the loan data list to the loan approval management module through the system;
the loan approval management module receives the financing intention and loan data list information of the loan application module, performs approval operation by combining loan approval conditions, and transmits approval results back to the system;
the system comprises a system database, an examination and approval result identification module, a change fund account identification module and a system, wherein the examination and approval result identification module is connected with the system database, identifies the examination and approval result identification, completes the change of a fund account by an examined and approved user, uploads a change evidence material and returns the change fund account result identification to the system;
the payment voucher management module is connected with the change refund account module, uploads the evidence data of the user who has successfully changed the refund account, and transmits the result identification back to the system;
the approval loan management module is simultaneously connected with the change refund account module and the payment certificate management module, receives the result identification, and marks the allowable loan identification on the user who has successfully completed the necessary operations before two loans are paid;
the money depositing voucher management module uploads a money depositing voucher to the system by a bank according to the actual money depositing condition, and the information is filed and then used by the financial statistics management module;
the financial statistics management module is connected with the money depositing voucher management module, processes money depositing data, collects and counts data such as total number of deposited suppliers, total amount of deposited money, interest distribution and the like, and outputs the data to key authority users such as banks and the like through the system.
3. A loan customer recommendation method based on power supply chain data is characterized by comprising the following steps: the method comprises the following steps:
step 1, building a potential loan customer recommendation system of electric power data to realize an integrated management platform of electric power service;
step 2, collecting power data, and dynamically acquiring power consumption behavior data of a supplier;
step 3, a platform manager of the potential loan client recommendation system of the electric power data screens potential clients meeting the conditions according to the requirements and recommends the potential clients to a target cooperative bank;
step 4, the recommended potential client carries out authority login and real-name authentication through a potential loan client recommending system of the electric power data, submits a loan application and completes the repayment account number change operation;
step 5, after the bank acquires the potential customer information through a potential loan customer recommending system of the electric power data, carrying out intention cooperation negotiation and completing approval operation;
and 6, the potential loan customer recommendation system of the electric power data monitors the refund transaction condition of a supplier in the loan in real time through a background automatic operation program, gives an early warning in time and assists in bank risk prevention and control.
4. The loan customer recommendation method based on the power supply chain data as claimed in claim 3, wherein: the power data includes: the method comprises the steps that bid winning information, supplier contract information and supplier payment information of a supplier are obtained, electric power operation data of a user are accessed to a potential loan customer recommendation system of electric power data, and potential customers to be recommended are screened out through a system recommendation model;
the supplier bid-winning information refers to supplier information of each batch of material or non-material bid-winning projects of the winning-winning power company;
the supplier contract information refers to information of a supplier having a direct contract relation with an electric company, and comprises contract amount, payment proportion and pre-payment amount, the system takes the total contract of the supplier as support data and recommends the total contract to a bank, and the bank effectively evaluates whether the supplier meets the condition that the order amount under the business contract is more than or equal to the bank financing amount through the data in a mode of constructing an order pool.
5. The loan customer recommendation method based on the power supply chain data as claimed in claim 3, wherein: the change of the refund account number refers to a cash collection and banking card account number in a contract between a supplier and an electric company, and the refund account number needs to be changed into a specified bank account number required by a bank.
6. The loan customer recommendation method based on the power supply chain data as claimed in claim 3, wherein: the refund transaction condition refers to the abnormal change of the refund account number of the supplier or the abnormal change of the refund amount, the system converts the applicable loan amount of the supplier according to the unpaid amount of the supplier as a key index, the system dynamically checks the filling amount and meets the requirement that the application amount is not more than the value obtained by the system calculation rule.
7. The loan customer recommendation method based on the power supply chain data as claimed in claim 3, wherein: the method comprises the following steps:
the method comprises the following steps that (1) the cooperation intention of 'potential financing client recommendation' products is achieved with multiple banks, business plates and operation processes are cleared, enterprise qualification, winning bid information, historical performance and electricity utilization conditions are comprehensively analyzed, and important recommendation is conducted on the products to the banks;
step (2) collecting power data, dynamically acquiring power consumption behavior data of a supplier, analyzing normal and abnormal variation factors of power charge and electricity quantity by taking the power data as a core, extracting, processing and converting data from mass data, carrying out user analysis on multi-dimensional index data of power marketing data, constructing a user credit model, and carrying out user credit rating on a user; accessing the power operation data of the user into a potential loan customer recommendation system of the power data, and labeling potential customers to be recommended through a recommendation model;
step (3) the platform manager of the potential loan customer recommendation system of the electric power data combines the bid winning information of the supplier, the contract information of the supplier and the payment information of the supplier, screens potential customers meeting the conditions according to the requirements and recommends the potential customers to a target cooperative bank;
step (4), the recommended potential client performs authority login and real-name authentication through a potential loan client recommendation system of the electric power data, submits a loan application and completes a repayment account number change operation;
step 5, after acquiring potential customer information through a potential loan customer recommendation system of the electric power data, carrying out intention cooperation negotiation and completing approval operation by the bank;
and (6) the potential loan customer recommendation system of the electric power data monitors the refund transaction condition of a supplier in the loan in real time through a background automatic operation program, gives an early warning in time, and assists in bank risk prevention and control.
8. The loan customer recommendation method based on the power supply chain data as claimed in claim 7, wherein: the completion approval operation meets the following conditions:
the bank financing open is less than or equal to (all business contract amount-paid amount under the business contract item-no financing part under the business contract item) multiplied by the financing proportion;
bank financing open = bank financing amount (including loan, bank acceptance draft) -deposit amount-pledge amount of the pledge;
the amount paid under the business contract = prepaid + normal performance payment under the contract;
the part of non-financing under the business contract item is the sum of the quality insurance sum and the sum of other performance guarantee items with longer time limit;
the financing proportion is the financing proportion which is approved by the bank according to the credit and credit conditions of the supplier and is 100 percent at most.
9. The loan customer recommendation method based on the power supply chain data as claimed in claim 7, wherein: the refund transaction situation of the supplier comprises the following steps:
after the bank provides financing, if the system monitors the payment of the core enterprise (party A), the 'control formula' is automatically monitored:
if the control formula is not established, the following measures are taken for the refund of the 'deficit part' (all business contract amount-paid amount under the item of the business contract-non-financing part under the item of the business contract) x financing proportion-bank financing exposure):
paying back bank financing/refund into a deposit account/bank acceptance draft for pledge;
if the control formula is established, the refund fund or the bill is automatically used by the supplier.
10. A computer storage medium, characterized by: the computer storage medium has stored thereon a computer program that, when executed by a processor, performs the steps of a loan client recommendation method based on power supply chain data as claimed in claims 3-9.
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