CN113487400B - Financial credit consensus method based on honesty bidirectional selection - Google Patents
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Abstract
The invention discloses a financial credit granting consensus method based on honesty bidirectional selection, and belongs to the technical field of block chain consensus. Firstly, preprocessing the honesty to eliminate the influence of financial credit-granting times on the honesty, and calculating the leadership by considering the recent profit condition of an enterprise so as to determine an enterprise leader node; secondly, considering the error factors of the enterprises in combination with the leadership, and determining the packaging and chaining sequence of the enterprises; and finally, the honesty is changed according to whether the enterprise repayment condition is on time or not so as to urge the enterprise to repay on time. The invention judges the profit stability of the enterprise by introducing error factors, greatly respects the intention of the enterprise by adopting a mode of mutual selection of the enterprise and a financial institution, and writes the credit granting process into an intelligent contract, thereby realizing the automation of financial credit granting, reducing the artificial influence and enabling the credit granting process to be open, transparent and traceable.
Description
Technical Field
The invention belongs to an application in the field of block chains, relates to the technologies of consensus mechanisms, machine learning and the like, and particularly relates to a financial credit consensus method based on honesty bidirectional selection.
Background
The block chain technology is a current emerging technology and has the characteristics of decentralization, no tampering, openness and transparency, traceability, automation and the like.
The traditional financial credit granting process is large in manual intervention, subjective consciousness exists, fair and fair disclosure cannot be achieved, the duration of the credit granting process is long, meanwhile, the possibility that a customer forges information is high, and a financial institution cannot grant credit in a targeted mode.
In order to overcome the defects of traditional financial credit, the invention provides a financial credit consensus method based on honesty bidirectional selection, combines a block chain technology and financial credit, and utilizes the characteristics of the block chain technology, so that the financial credit process is fair and transparent.
Disclosure of Invention
The invention aims to provide a reliable financial credit consensus method based on honesty bidirectional selection aiming at a financial credit block chain. The method measures whether the enterprise is timely credited or not by introducing honesty, and measures the operation stability of the enterprise by introducing error factors. In order to make the credit granting process more stable, the initial credit granting amount of the enterprise is set to be a small amount; the method has the advantages that information such as financial institution sequencing trusted by enterprises, requirements of the financial institutions on the enterprises and the like is utilized to formulate corresponding rules of bidirectional selection of the financial institutions and the enterprises, and the willingness of the enterprises and the financial institutions is greatly respected; monitoring the enterprise repayment process according to a machine learning algorithm in a form of a month period, so as to ensure that the enterprise data is real and reliable; the credit granting process is automatically carried out in an intelligent contract mode, human participation is reduced, the credit granting efficiency is improved, and the credit granting reliability is increased.
In order to achieve the purpose, the invention adopts the following technical scheme: the financial credit-granting consensus method based on two-way selection of honesty degree is characterized by comprising the following steps:
step 1: the financial credit-granting enterprise provides monthly company-year-ahead information import enterprise nodes, and financial institutions capable of granting credit import the information of the institutions into the financial nodes; the enterprise nodes meeting the conditions according to preset rules are taken as enterprise candidate nodes, and all financial nodes are taken as financial candidate nodes;
and 2, step: electing an enterprise leader node by the enterprise candidate nodes in the step 1 according to a preset rule 1, packaging the enterprise candidate nodes by the enterprise leader node according to a sequence to generate a block, and writing the block into the enterprise sub-chain; the financial candidate nodes elect financial leader nodes according to a preset rule 2, pack the financial candidate nodes in sequence to generate blocks by the financial leader nodes, and write the blocks into the financial subchains;
and step 3: selecting a certain number of super nodes by the nodes written into the financial sub-chains in the step 2 according to a preset rule, determining a financial credit-granting relationship by the super nodes, and finally packaging and writing the financial credit-granting relationship into a credit-granting main chain;
and 4, step 4: predicting part of information of the next period of the financial credit enterprise according to a preset rule at the end date of each period;
and 5: on the starting date of each period, an enterprise carrying out financial credit granting elects an information leader node according to a preset rule 1, and the information leader node forms transactions of the enterprise carrying out financial credit granting in the current period and the profit condition, and packages and links; if the period is the last period of the enterprise financial credit, the information leader node increases the enterprise financial credit formation times x of the enterprise once according to a preset rule 2, namely, the transaction of x = x +1 is packed and written into the enterprise sub-chain;
step 6: and updating the error factor of the enterprise according to the information obtained in the step 4 and the step 5 according to a preset rule 1, and updating the honesty of the enterprise according to a preset rule 2.
Further, in step 1, the enterprise information should include basic information of the enterprise, business information in an enterprise period, decision variables related to the system and the enterprise, and the like; the basic information of the enterprise comprises: mortgage value k, credit line w wanted to be obtained, credit return cycle number d and trusted financial institution sequence Y, wherein Y is an array, the head of the array is the most trusted financial institution of the enterprise, and the tail of the array is the most untrusted financial institution of the enterprise; information within the enterprise cycle includes: the purchase generation cost a1, the payroll a2, the tax due a3, the welfare due a4, other expenses a5, the loan amount a6, the total expense a, the normal sale b1, other business income b2, the total income b, the profit c, whether to perform financial credit q, wherein the value of q is 0 or 1,1 represents that the period is within the financial credit validity period, and 0 represents that the period is not within the financial credit validity period; decision variables related to the system and enterprises are information specially needed by the system, are updated in real time in the process of credit granting and comprise: the financial credit granting times x and x are the financial credit granting times of an enterprise on the system and are initially set to be 0, in the final cycle of repayment process after the enterprise obtains credit, the index of whether the enterprise repays on time is measured according to the preset rule 2 in the step 5, the index is initially set to be 0, in the repayment process after the enterprise obtains credit, the index is updated according to the preset rule 2 in the step 6, the error factor eta is an index for measuring the enterprise operation stability degree, the index is initially set to be 0, in the repayment process after the enterprise obtains credit, the index is updated according to the preset rule 1 in the step 6 and is an effective enterprise Vc, the Vc is used for recording whether the enterprise in the enterprise sub-chain participates in the financial credit granting process of the current time, the initial setting is 0 for representing that the enterprise is effective, and in the financial credit granting process, the financial credit granting process is updated in real time according to the preset rules in the steps 1 and 3; the unit of the amount related to the parameters is ten thousand yuan.
Further, in step 1, the financial institution information includes: the method comprises the steps of judging whether the financial institution is an effective financial institution Vb, a tolerable minimum value m of near four quarter profits, an investment return rate n and a credit granting amount calculation formula, wherein the Vb is 0 or 1, the default value is 0, the financial institution is represented to be effective, otherwise, the financial institution is represented to be ineffective, the m unit is ten thousand yuan, and the credit granting amount calculation formula can be provided or not.
Further, in step 1, the preset rule is:
(1) Verifying the enterprise node wanting to obtain the credit:
(1) profit of the enterprise c continues n 1 Quarterly positive, or negative with increasing profitTrend;
(2) p with loan amount lower than mortgage amount 1 ％，
Wherein n is 1 、p 1 Are all a constant, and p 1 Has a value range of (0,100)]；
(2) A Vc =1 transaction is formed for a business node that does not satisfy the above conditions, with the business being invalid.
Further, in step 2, the preset rule 1 is:
(1) Competitive selection of an enterprise leader node:
defining the leadership L, and calculating the formula as follows:
wherein epsilon is the honesty of the enterprise candidate nodes, x is the financial crediting times of the enterprise candidate nodes, and alpha 1 Is a very small positive number, the prevented denominator is 0,C is the sum of the total profits of the enterprise candidate node in nearly four quarters, β =10 N N is the maximum number of total profits of all enterprises in nearly four seasons;
calculating the leadership L of each enterprise candidate node, wherein the enterprise candidate with the largest leadership serves as an enterprise leader node;
(2) The enterprise leader node determines the packing order of the enterprise candidate nodes:
defining a priority value P, and calculating the formula as follows:
wherein L is the leadership of the enterprise candidate node, η is an error factor of the enterprise candidate node, x is the financial crediting times of the enterprise candidate node, and α 2 Is a very small positive number, the prevented denominator is 0;
the enterprise leader node calculates the priority value of each enterprise candidate node, and packages the nodes according to the priority value, wherein the larger the priority value is, the more the packaging sequence is;
(3) The enterprise leader node issues a validation to the network:
the enterprise leader node packs the enterprise candidate nodes which are not packed according to the packing sequence and sends a verification request to the network;
(4) Enterprise candidate node response request:
the enterprise candidate node responds after receiving the verification invitation sent by the enterprise leader node;
(5) The enterprise leader node processes the response result:
if it exceeds p 2 % of the enterprise candidate nodes respond to the verification request sent by the enterprise leader node, if the consensus is passed, the enterprise leader node writes the information of the enterprise candidate nodes into the enterprise sub-chain; wherein p is 2 Is a constant with the value range of (0, 100);
(6) And (3) circularly executing until finishing:
if there are still enterprise candidate nodes that are not packaged, repeating (2) through (6).
Further, in step 2, the preset rule 2 is:
(1) Competing and selecting the financial leader node:
obtaining the probability P that the ith financial candidate node is taken as the financial leader node i And cumulative probability Q i ：
Wherein P is i The calculation method of (2) is as follows:
wherein R is i For the ith financial institution return on investment, Q i The calculation method of (c) is as follows:
selecting financial leaders according to roulette method, specifically in [0,1]Generating a random number over the intervalNumber r, e.g. r<Q 1 Then financial institution B 1 Successfully selecting as a leader; q k-1 ≤r<Q k If yes, the kth financial candidate node is successfully elected as a financial leader;
(2) The financial leader node issues a verification to the network:
the financial leader node selects one of the unpacked financial candidate nodes to pack, and sends a verification request to the network;
(3) The financial candidate node responds to the request:
the financial candidate node responds after receiving the verification invitation sent by the financial leader node;
(4) The financial leader node processes the response results:
if it exceeds p 3 % of the financial candidate nodes respond to the verification request sent by the financial leader node, if the consensus is passed, the financial leader node writes the information of the financial candidate nodes into the financial subchain; wherein p is 3 % is a constant with the value range of (0, 100);
(5) And (3) circularly executing until finishing:
if there are unpacked financial candidate nodes, repeating (2) through (5).
Further, in step 3, the preset rule is:
(1) Competing and electing the super nodes:
determining a super node according to the sequence Y of the financial institutions trusted by each enterprise written into the enterprise sub-chain, and defining the super leadership SL, wherein the calculation formula is as follows:
wherein,
for the currently valid financial institution B t The super leadership degree of (1), sc is the total number of effective enterprise nodes in the enterprise sub-chain at the current time, and Sb is the effective number in the financial sub-chain at the current timeTotal number of financial nodes, G (Y) ck [i]) Whether the ith bit of the financial institution sequence representing the trust of the enterprise is B t The calculation formula is as follows:
wherein, Y ck [i]For enterprise C k Ith trusted financial institution, B t A financial institution for which the super-leadership is currently to be calculated;
therefore, a fixed number of super nodes are elected according to the super leadership, the super leadership is larger, the super nodes are easier to be elected, and if financial institutions with the same super leadership value exist, the investment return rate n is larger, the super nodes are easier to be elected;
(2) Drawing a super-node block-out sequence:
randomly planning the sequence of blocks in the selected super nodes with fixed number;
(3) The super node determines the credit relationship:
determining a super node of a current block according to a randomly drawn block output sequence, taking out the earliest packed and effective enterprise nodes in the sub-chain of the enterprise by the super node, comparing the effective financial nodes in the sub-chain of the enterprise one by one, and recording a financial institution which can give credit to the enterprise, namely the minimum value of the near-four quarter profits of the enterprise is more than or equal to the minimum value m of the near-four quarter profits tolerable by the financial institution; the super node selects a financial institution which trusts the enterprise according to the financial institution sequence Y trusted by the enterprise from the financial institutions which can trust the enterprise; if the enterprise does not meet the conditions in all the financial nodes, the super node writes the Vc =1 transaction formed by the current enterprise into the enterprise sub-chain, and then the operation (3) is carried out again;
(4) The super node calculates the credit amount:
the credit amount may be obtained from a calculation formula provided by the financial institution, and if the financial institution does not provide the calculation formula, the following formula may be referred to:
wherein: w is the credit amount, the min function is the minimum value of the two, W is the credit amount which the enterprise wants to obtain, k is the collateral value of the enterprise, eta is the error factor of the enterprise, x is the financial credit times of the enterprise, and alpha 3 、α 4 Is a very small positive number, the prevented denominator is 0, the AVGc is the average value of profits of enterprises in nearly three quarters, epsilon is the honesty of the enterprises, n 2 、n 3 All the constants are constants, and the value ranges of all the constants are positive integers;
(5) Packaging the credit information by the super node and sending verification:
the super node responsible for the current block packaging the information of the enterprise obtaining the credit, the financial institution giving the credit, the credit amount and the like, and sending verification requests to all the super nodes;
(6) The super node responds to the request:
the super node responds after receiving the verification requirement of the super node responsible for the current block;
(7) The super node processes the response result:
if it exceeds p 4 % of the super nodes respond to the verification request sent by the super node which is currently responsible for the block, if the consensus is passed, the super node which is currently responsible for the block writes the credit information into the credit main chain, and forms a Vc =1 transaction to the enterprise in the current credit information and writes the transaction into an enterprise sub-chain, wherein p is 4 Is a constant with the value range of (0, 100);
(8) And circulating until the round of credit granting is finished:
and (3) when the effective enterprise nodes still exist in the enterprise sub-chain, if all the super nodes in the randomly drawn block output sequence output all the blocks in the round, executing (2) to (8), and otherwise, executing (3) to (8).
Further, in step 4, the preset rule is:
(1) Predicting the enterprise part information of the next period according to the uplink data of the enterprise, wherein the calculation formula is as follows:
Y＝RNN(X) (8)
wherein, X is the enterprise part information and the credit granting condition in all the periods of the enterprise in the chain, and Y is the predicted enterprise part information in the next period.
Further, in step 4, the partial information of the enterprise includes: the purchase generation fee a1, payroll a2, welfare a4, other expenses a5, normal sales b1, other business income b2.
Further, in step 5, the preset rule 1 is:
(1) Competitive election information leader node:
defining the average honesty A epsilon, and calculating according to the following formula:
where ε is the honesty of the enterprise candidate node, x is the financial crediting times of the enterprise candidate node, α 5 Is a very small positive number, the prevented denominator is 0;
calculating the average honesty A epsilon of each enterprise node, and taking the enterprise with the maximum average honesty as an information leader node;
(2) The information leader node issues a verification to the network:
the information leader node selects an enterprise from the enterprise nodes which do not form a transaction, packs the repayment condition and the profit condition of the enterprise into a transaction, and sends a verification request to the network;
(3) The enterprise node responds to the request:
the enterprise node responds after receiving the verification invitation sent by the information leader node;
(4) The information leader node processes the response result:
if it exceeds p 5 % of the enterprise nodes respond to the verification request sent by the information leader node, the consensus is passed, and the information leader node writes the transaction into the credit main chain, wherein p 5 Is a constant with the value range of (0, 100);
(5) And circulating until finishing:
and (5) if the enterprise nodes which do not form the transaction exist in the credit main chain, repeating the steps (2) to (5).
Further, in step 5, the preset rule 2 is:
(1) The information leader node issues a verification to the network:
the information leader node forms a transaction of x = x +1 for the enterprise and sends a verification request to the network;
(2) The enterprise node responds to the request:
the enterprise node responds after receiving the verification invitation sent by the information leader node;
(3) The information leader node processes the response result:
if it exceeds p 6 % of the enterprise nodes respond to the verification request sent by the information leader node, the consensus is passed, and the information leader node writes the transaction into the enterprise sub-chain, wherein p 6 Is a constant with the value range of (0, 100).
Further, in step 6, the preset rule 1 is:
the formula for updating the error factor is:
wherein eta is an error factor, a1 'is used for predicting the expense generated by purchasing the enterprise in the next period, a2' is used for predicting the wage due by the enterprise in the next period, a4 'is used for predicting the benefit fee due by the enterprise in the next period, a5' is used for predicting the other expenses of the enterprise in the next period, b1 'is used for predicting the normal sale of the enterprise in the next period, b2' is used for predicting the income of the other services in the next period, a1 is used for generating the expense generated by purchasing the enterprise in the next period, a2 is used for the wage due by the enterprise in the next period, a4 is used for the benefit fee due by the enterprise in the next period, a5 is used for the other expenses of the enterprise in the next period, b1 is used for the normal sale of the enterprise in the next period, and b2 is used for the income of the other services in the next period.
Further, in step 6, the preset rule 2 is:
if the enterprise repays on time, the honesty is as follows:
wherein epsilon is honesty, d is the cycle number of loan return;
if the enterprise is not credited on time, the honesty is not changed.
Through the design scheme, the invention can bring the following beneficial effects: the invention provides a financial credit consensus method based on honesty bidirectional selection, and firstly, the method urges enterprises to repay on time by introducing honesty; secondly, an error factor is introduced, so that the stability of the profit of the enterprise is concerned, and a reference is provided for the later financial credit granting; moreover, the enterprise selects the financial institution which gives credit to the enterprise within the allowed range of the financial institution in view of the enterprise's will; and finally, the credit granting implementation mechanism is written into the intelligent contract, so that the automation of the financial credit granting process is realized, the manual intervention is reduced, and the financial credit granting time is saved.
Drawings
FIG. 1 is a block diagram of an algorithm according to the present invention; FIG. 2 is a flow chart of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to specific examples.
A financial credit-granting consensus method based on honesty is applied to a financial credit-granting system based on a block chain, and the credit-granting system comprises an enterprise management module, a financial institution management module, a credit-granting request module, a credit-granting module and a loan-repaying module.
The enterprise management module is used for managing account information of an enterprise;
the financial institution management module is used for managing account information of the financial institution;
the credit granting request module is used for managing account information of a financial credit granting enterprise;
the credit granting module is used for recording the credit granting relationship between the enterprise and the corresponding financial institution;
and the loan repaying module is used for recording the information of the returned loan of the enterprise.
In the embodiment, an application of the method is shown in the operation process of the financial credit system based on the block chain.
The financial credit-granting consensus method based on two-way selection of integrity degree comprises the following steps:
1. the financial credit-granting enterprise provides monthly company-year-ahead information import enterprise nodes, and financial institutions capable of granting credit import the information of the institutions into the financial nodes; taking the enterprise nodes meeting the conditions according to preset rules as enterprise candidate nodes, and taking all financial nodes as financial candidate nodes;
in the example of the present invention, h is 2, and there are 5 enterprises, and the information of each enterprise is as follows:
TABLE 1 Enterprise C 1 Information table
TABLE 2 Enterprise C 2 Information table
TABLE 3 Enterprise C 3 Information table
TABLE 4 Enterprise C 4 Information table
TABLE 5 Enterprise C 5 Information table
There are 5 financial institutions, and the information of each financial institution is as follows:
table 6 financial institution information table
1.1 verifying enterprise nodes: in this case, take n 1 Is 3,p 1 Is 70. Obtaining enterprise node C by preset rules 4 Negative values exist in profits in nearly 3 seasons, but the profits do not rise, the profits cannot serve as enterprise candidate nodes, and other enterprise nodes pass verification and become enterprise candidate nodes;
1.2 verifying financial nodes: all financial nodes become financial candidate nodes.
2. The enterprise candidate node elects an enterprise leader node according to a preset rule 1, and the enterprise leader node packs the enterprise candidate nodes in sequence to generate a block, and writes the block into the enterprise sub-chain; the financial candidate nodes elect financial leader nodes according to a preset rule 2, pack the financial candidate nodes in sequence to generate blocks by the financial leader nodes, and write the blocks into the financial subchains;
2.1 election of Enterprise leaders: calculate the leadership of 4 enterprises according to formula 1,
2.2 determining the packing order: the priority values of the 4 enterprises are calculated according to formula 2,
2.3 the Enterprise leader node issues a validation to the network: enterprise leader node C 1 Enterprise candidate node C that is not packaged according to packaging order 1 Packaging and sending a verification request to a network;
2.4 Enterprise candidate node response request: enterprise candidate node C 3 、C 5 Receiving the verification request and responding to the verification request;
2.5 Enterprise leader node processing response results: in this case, take p 2 Is 66.67. 66.67% of the existing enterprise candidate nodes do requestsIn response, the consensus passes, and the enterprise leader node C 1 Node C as a candidate of an enterprise 1 Writing the information into the enterprise sub-chain;
2.6 repeat 2.3 to 2.5 until the packing order queue is empty. At this point, enterprise C 1 、C 3 、C 2 、C 5 All have been written into the enterprise sub-chain;
2.7 election financial leader nodes: obtaining P of 5 financial candidate nodes according to formula 3 i ，
Calculating Q of 5 financial candidate nodes according to equation 4 i ，
Q 1 ＝0.225688073，Q 2 ＝0.423853211，Q 3 ＝0.590835688，Q 4 ＝0.726605505，Q 5 ＝1；
Random number r =0.631, so B 4 Becoming a financial candidate node;
2.8 the financial leader node issues a verification to the network: finance leader node B 4 Selecting B from unpacked financial candidate nodes 1 Packaging and sending a verification request to a network;
2.9 financial candidate node responds to the request: financial candidate node B 3 、B 4 、B 5 Receiving the verification request and responding to the verification request;
2.10 financial leader node processes the response results: in this case, take p 3 It was 66.67. If 66.67% of the financial candidate nodes respond to the request, the consensus passes, and the financial leader nodeB 4 Node B financial candidate 1 Writing the information into the financial subchain;
2.11 repeat 2.8 through 2.10 until all financial candidate nodes are packaged. At this time, financial institution B 1 、B 2 、B 3 、B 4 、B 5 Have all been written into the finance subchain.
3. Selecting a certain number of super nodes by the nodes written in the financial sub-chain according to a preset rule, determining a financial credit-granting relationship by the super nodes, and finally packaging and writing the financial credit-granting relationship into a credit-granting main chain;
3.1 competitive election of super nodes: calculating the super leadership of the currently valid financial institution according to formula 5:
SL B1 ＝5+4+2+4＝15，SL B2 ＝3+5+4+1＝13，SL B3 ＝4+1+5+5＝15，
SL B4 ＝2+2+3+3＝10，SL B5 ＝1+3+1+2＝7，
assuming that the number of the selected super nodes is 4, the selected super nodes are as follows: b is 1 、B 3 、B 2 、B 4 ；
3.2 drawing up a super node block output sequence: randomly drawing the block output sequence of the super nodes as follows: b 2 、B 3 、B 1 、B 4 ；
3.3, the super node determines the credit relationship: the super node responsible for the current block is B 2 Therefore, B 2 Take out enterprise node C that was earliest packed and is valid in enterprise sub-chain 1 Obtaining the minimum value of profit of 50.6 ten thousand yuan of the enterprise nodes in nearly four seasons, and connecting the minimum value with the effective financial node B in the financial sub-chain 1 、B 2 、B 3 、B 4 、B 5 Comparing to obtain: can be to enterprise node C 1 Financial node B for performing financial credit 1 、B 2 、B 3 、B 4 Comparing enterprise node C 1 Trusted financial institution order Y available to Enterprise node C 1 The financial institution which carries out the credit is B 1 ；
3.4 the super node calculates the credit amount: since the financial institution B 1 No credit is providedThe amount is calculated by formula, so formula 7 is used to calculate the amount of credit, in this case, n is taken 2 Is 3, take n 3 Is as follows (6):
3.5, packaging the trust information by the super node and sending verification: super node B responsible for current out-of-block 2 Enterprise C 1 Financial institution B 1 Packaging information such as credit amount and the like, and sending verification requests to all super nodes;
3.6 response request of super node: super node B 1 、B 4 Receiving the verification request and responding to the verification request;
3.7 super node processes response result: in this case, take p 4 Is 66.67. If 66.67% of the super nodes respond to the request, the consensus is passed, and the super node B responsible for the current block is responsible 2 Writing the packaged credit information into a credit main chain and writing the enterprise C related in the current credit information 1 Forming a Vc =1 transaction write enterprise sub-chain;
3.8 according to the proposed super node block-out sequence, the super node responsible for the current block-out is changed into B 3 And repeating the steps 3.3-3.7 until all effective enterprises in the enterprise sub-chain perform the authorization process, and if the block output sequence of the super node is drawn up and is finished, randomly determining the block sequence again.
4. Predicting part of information of the next period of the financial credit enterprise according to a preset rule at the end date of each period; forecasting Enterprise C according to equation 8 1 The partial information results of (a):
the purchase cost a1' is 7.88 ten thousand yuan; payroll a2' is 5.8 ten thousand yuan; the amount of the welfare a4' due to the welfare is 5.2 ten thousand yuan; the other expenditure a5' is 1.64 ten thousand yuan; normal sale b1' is 36.84 ten thousand yuan; the other business revenue b2' is 4.3 ten thousand yuan.
5. On the starting date of each period, an enterprise carrying out financial credit granting elects an information leader node according to a preset rule 1, and the information leader node forms transactions of the enterprise carrying out financial credit granting in the current period and the profit condition, and packages and links; if the period is the last period of the enterprise financial credit, the information leader node increases the enterprise financial credit granting times of the enterprise once according to a preset rule 2, namely, the transaction of x = x +1 is formed, and the transaction is packed and written into the enterprise sub-chain:
5.1 competing election information leader node: the average honesty is calculated according to equation 9,
Aε c1 ＝1.4，Aε c2 ＝0，Aε c3 ＝0，Aε c5 =0, so enterprise C1 is the information leader node;
5.2 the information leader node issues a validation to the network: information leader node C 1 Enterprise C 1 Loan repayment situation in this period: loan-repayment and profit scenario: the purchase generating cost a1 is 8 ten thousand yuan, the payroll a2 is 5.7 ten thousand yuan, the welfare a4 is 5 ten thousand yuan, other expenses a5 is 1.8 ten thousand yuan, the normal sale b1 is 38 ten thousand yuan, other business income b2 is 4 ten thousand yuan to form a transaction, and a verification request is sent to the network;
5.3 Enterprise response request: enterprise candidate node C 2 、C 5 Receiving the verification request and responding to the verification request;
5.4 the information leader node processes the response results: in this case, take p 5 It was 66.67. 66.67% of the enterprise candidate nodes respond to the request, and the consensus passes, the information leader node C 1 Writing the enterprise transaction into a credit main chain;
5.5, repeating the steps from 5.2 to 5.4 until all enterprises which are carrying out financial credit authorization form a transaction writing credit authorization main chain; at this point, enterprise C 1 、C 2 、C 3 、C 5 Both the loan repayment scenario and the profit scenario of (c) have formed a transaction write credit backbone.
6. Updating error factors of the enterprise according to a preset rule 1, and updating the honesty of the enterprise according to a preset rule 2;
6.1 update C according to equation 10 1 Error factor of enterprise
6.2 updating the honesty according to equation 11
In conclusion, the application screens the enterprises needing financial credit authorization to the enterprises which carry out financial credit authorization, and clearly displays the credit authorization process. According to the invention, the honesty is introduced firstly, enterprises are supervised and urged to repay on time, and the burden of financial institutions is reduced; secondly, introducing an error factor, predicting the profit condition of the enterprise in the next period in a machine learning mode, and judging the profit stability condition of the enterprise by combining the data uploaded by the enterprise to make a reference for later financial credit; moreover, the enterprise and the financial institution mutually select, so that the intention of the enterprise is greatly respected; and finally, the credit granting process is written into an intelligent contract in advance, so that the automation of financial credit granting is realized, the artificial influence is reduced, and the credit granting process is open and transparent and traceable.
Claims (7)
1. A financial credit consensus method based on honesty bidirectional selection is characterized by mainly comprising the following steps:
step 1: the financial credit-granting enterprise provides monthly company-year-ahead information import enterprise nodes, and financial institutions capable of granting credit import the information of the institutions into the financial nodes; taking the enterprise nodes meeting the conditions according to preset rules as enterprise candidate nodes, and taking all financial nodes as financial candidate nodes;
step 2: electing an enterprise leader node by the enterprise candidate nodes in the step 1 according to a preset rule 1, packaging the enterprise candidate nodes by the enterprise leader node according to a sequence to generate a block, and writing the block into the enterprise sub-chain; the financial candidate nodes elect financial leader nodes according to a preset rule 2, pack the financial candidate nodes in sequence to generate blocks by the financial leader nodes, and write the blocks into the financial subchains;
and 3, step 3: selecting a certain number of super nodes by the nodes written into the financial sub-chains in the step 2 according to a preset rule, determining a financial credit-granting relationship by the super nodes, and finally packaging and writing the financial credit-granting relationship into a credit-granting main chain;
and 4, step 4: predicting part of information of the next period of the financial credit enterprise according to a preset rule at the end date of each period;
and 5: selecting an information leader node by an enterprise which is carrying out financial credit according to a preset rule 1 at the starting date of each period, forming transactions according to the period loan repaying condition and the profit condition of the enterprise which is carrying out financial credit by the information leader node, and packaging and chaining; if the period is the last period of the enterprise financial credit, the information leader node increases the enterprise financial credit formation times x of the enterprise once according to a preset rule 2, namely, the transaction of x = x +1 is packed and written into the enterprise sub-chain;
and 6: updating error factors of the enterprises according to a preset rule 1 and updating the honesty of the enterprises according to a preset rule 2 by the information obtained in the step 4 and the step 5;
wherein, the rule for calculating the credit amount after the credit relationship is determined in the step 3 is as follows: the credit amount may be obtained from a calculation formula provided by the financial institution, and if the financial institution does not provide the calculation formula, the following formula may be referred to:
w is the credit amount, the min function is the minimum value of the two, W is the credit amount which the enterprise wants to obtain, k is the collateral value of the enterprise, eta is the error factor of the enterprise, x is the financial credit times of the enterprise, and alpha 3 、α 4 Is a very small positive number, the prevented denominator is 0, the AVGc is the average value of profits of enterprises in nearly three quarters, epsilon is the honesty of the enterprises, n 2 、n 3 All the constants are constants, and the value ranges of all the constants are positive integers;
wherein, the rule of competing and electing the information leader node in the step 5 is as follows: defining the average honesty A epsilon, and calculating according to the following formula:
ε is the honesty of the Enterprise candidate node, x is the financial crediting times of the Enterprise candidate node, α 5 The number is very small, the prevented denominator is 0, the average honesty A epsilon of each enterprise node is calculated, and the enterprise with the largest average honesty serves as an information leader node;
wherein, the rule for updating the error factors of the enterprises in the step 6 is as follows: the formula for updating the error factor is:
eta is an error factor, a1 'is used for predicting the cost of purchasing the enterprise in the next period, a2' is used for predicting the salary due for the enterprise in the next period, a4 'is used for predicting the benefit fee due for the enterprise in the next period, a5' is used for predicting the other expenses due for the enterprise in the next period, b1 'is used for predicting the normal sale of the enterprise in the next period, b2' is used for predicting the income of other services in the enterprise in the next period, a1 is used for generating the cost of purchasing the enterprise in the next period, a2 is used for the salary due for the enterprise in the next period, a4 is used for the benefit fee due for the enterprise in the next period, a5 is used for the other expenses due for the enterprise in the next period, b1 is used for the normal sale of the enterprise in the next period, and b2 is used for the income of the other services in the enterprise in the next period;
wherein, the rule for updating the honesty of the enterprise in the step 6 is as follows: if the enterprise repays on time, the honesty is as follows:
epsilon is the honesty degree, d is the loan repayment cycle number, and if the enterprise does not repay on time, the honesty degree is not changed.
2. The financial credit consensus method based on honesty two-way selection as claimed in claim 1, wherein: in step 1, the enterprise information includes basic information of an enterprise, operation information in an enterprise period, and decision variables related to the system and the enterprise; the basic information of the enterprise comprises: mortgage value k, credit line w wanted to be obtained, credit return cycle number d and trusted financial institution sequence Y, wherein Y is an array, the head of the array is the most trusted financial institution of the enterprise, and the tail of the array is the most untrusted financial institution of the enterprise; information within the enterprise cycle includes: the purchase generation cost a1, the payroll a2, the tax due a3, the welfare due a4, other expenses a5, the loan amount a6, the total expense a, the normal sale b1, other business income b2, the total income b, the profit c, whether to perform financial credit q, wherein the value of q is 0 or 1,1 represents that the period is within the financial credit validity period, and 0 represents that the period is not within the financial credit validity period; decision variables related to the system and enterprises are information specially needed by the system, are updated in real time in the process of credit granting and comprise: the financial credit granting times x and x are the financial credit granting times of an enterprise on the system and are initially set to be 0, in the final cycle of repayment process after the enterprise obtains credit, the index of whether the enterprise repays on time is measured according to the preset rule 2 in the step 5, the index is initially set to be 0, in the repayment process after the enterprise obtains credit, the index is updated according to the preset rule 2 in the step 6, the error factor eta is an index for measuring the enterprise operation stability degree, the index is initially set to be 0, in the repayment process after the enterprise obtains credit, the index is updated according to the preset rule 1 in the step 6 and is an effective enterprise Vc, the Vc is used for recording whether the enterprise in the enterprise sub-chain participates in the financial credit granting process of the current time, the initial setting is 0 for representing that the enterprise is effective, and in the financial credit granting process, the financial credit granting process is updated in real time according to the preset rules in the steps 1 and 3; wherein, the units of the amount related to the parameters are ten thousand yuan.
3. The financial credit consensus method based on honesty two-way selection as claimed in claim 1, wherein: step 1The preset rule in (1) is as follows: verifying the enterprise node wanting to obtain the credit: (1) Profit of the enterprise c continues n 1 The quarter is positive, or negative values exist but the profit tends to rise; (2) P with loan amount lower than mortgage amount 1 % wherein n 1 、p 1 Are all a constant, and p 1 Has a value range of (0,100)]。
4. The financial credit consensus method based on honesty two-way selection as claimed in claim 1, wherein: the rule for selecting the enterprise leader node in the step 2 is as follows: defining the leadership L, and calculating the formula as follows:
wherein epsilon is the honesty of the enterprise candidate nodes, x is the financial crediting times of the enterprise candidate nodes, and alpha 1 Is a very small positive number, the prevented denominator is 0,C is the sum of the total profits of the enterprise candidate node in nearly four quarters, β =10 N N is the maximum number of total profits of all enterprises in nearly four seasons; and calculating the leadership L of each enterprise candidate node, wherein the enterprise candidate with the highest leadership serves as the enterprise leader node.
5. The financial credit consensus method based on honesty two-way selection as claimed in claim 1, wherein: in step 2, the packing sequence determination rule is as follows: defining a priority value P, and calculating the formula as follows:
wherein L is the leadership of the enterprise candidate node, η is an error factor of the enterprise candidate node, x is the financial crediting times of the enterprise candidate node, and α 2 Is a very small positive number, the prevented denominator is 0; the Enterprise leader node calculates a priority value, root, for each of the enterprise candidate nodesAnd packing according to the size of the priority value, wherein the packing sequence is earlier the higher the priority value is.
6. The financial credit consensus method based on honesty two-way selection as claimed in claim 1, wherein: the rule for selecting the super node in the step 3 is as follows: determining a super node according to the sequence Y of the financial institutions trusted by each enterprise written into the enterprise sub-chain, and defining the super leadership SL, wherein the calculation formula is as follows:
wherein,
for the currently valid financial institution B t Sc is the total number of effective enterprise nodes in the enterprise sub-chain at the current time, sb is the total number of effective financial nodes in the financial sub-chain at the current time, and G (Y) ck [i]) Whether the ith bit of the financial institution sequence representing the trust of the enterprise is B t The calculation formula is as follows:
wherein, Y ck [i]For enterprise C k Ith trusted financial institution, B t A financial institution for which the super-leadership is currently to be calculated;
therefore, a fixed number of super nodes are elected according to the super leadership, the larger the super leadership is, the easier the super nodes are to be elected, and if financial institutions with the same super leadership value exist, the larger the investment return rate n is, the easier the super nodes are to be elected.
7. The financial credit consensus method based on honesty two-way selection as claimed in claim 1, wherein: in step 3, the rules for determining the financial credit authorization relationship by the super node are as follows: determining a super node of a current block according to a randomly drawn block output sequence, taking out the earliest packed and effective enterprise nodes in the sub-chain of the enterprise by the super node, comparing the effective financial nodes in the sub-chain of the enterprise one by one, and recording a financial institution which can give credit to the enterprise, namely the minimum value of the near-four quarter profits of the enterprise is more than or equal to the minimum value m of the near-four quarter profits tolerable by the financial institution; the super node selects a financial institution which trusts the enterprise according to the financial institution sequence Y trusted by the enterprise from the financial institutions which can trust the enterprise; if the enterprise does not meet the conditions in all the financial nodes, the super node forms a Vc =1 transaction write-in enterprise sub-chain for the current enterprise.
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