CN111028068A - Data processing method, electronic equipment and computer readable storage medium - Google Patents
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Abstract
The embodiment of the invention provides a data processing method, electronic equipment and a computer readable storage medium, wherein the level parameters of a first node and a second node are obtained, the weighting parameters of a first data object and a second data object of the first node are determined according to the level parameters, and a pool entry record is generated according to the weighting parameters of the first data object and the second data object, so that the combination of the first data object and the second data object of the first node enters a data pool, therefore, the first data object and the second data object of the first node can be hedged, the first node can be separated from a digital offer chain, and meanwhile, the data object parameters of the first node can be adjusted.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a data processing method, an electronic device, and a computer-readable storage medium.
Background
Under the influence of various factors such as market environment, bank payment mode and industry payment mode, the transfer of the debt right (accounts receivable) and the debt (accounts payable) is slow and settled due to various reasons, the period is prolonged, even bad accounts appear, huge capital pressure is caused to individuals or companies, and normal operation and development of the companies are influenced.
Creditor relationship chains are something that is almost everywhere visible in real economy, e.g., in one creditor relationship chain, company A has accounts payable corresponding to company B, company B has accounts payable corresponding to company C, and company C has accounts payable … … corresponding to company D
At present, when debt settlement is carried out, each debt in the debt right chain needs to be paid by a debtor completely, if one debt has problems such as arrears, the debt parties need to deal with hassle, and at present, processing is only carried out between the debt parties, so that a plurality of linkage problems can be caused. Therefore, the manual settlement of the credit and debt requires a large amount of manpower and material resources, and causes problems such as a long period of the credit and debt in a plurality of credit and debt tethers. Therefore, how to efficiently process data objects such as creditors and debts in the creditor relationship chain by using a computer technology developed at a high speed is a problem to be solved.
Disclosure of Invention
Embodiments of the present invention provide a data processing method, an electronic device, and a computer-readable storage medium, so that a first data object and a second data object of a first node are collided, so that the first node can be disconnected from a digital offer chain, and at the same time, a data object parameter of the first node is adjusted.
In a first aspect, an embodiment of the present invention provides a data processing method, where the method includes:
receiving a request for a combination of a first data object and a second data object of a first node to enter a data pool;
determining a corresponding third data object from the first data object, wherein the third data object is attributed to a second node, the first data object and the third data object corresponding to a same digital offer between the first node and the second node;
determining a level parameter of the first node and the second node in response to the state of the third data object being pooled;
determining weighting parameters of the first data object and the second data object according to the level parameters of the first node and the second node;
and generating a pool entry record according to the weighting parameters of the first data object and the second data object.
Optionally, generating a pool entry record according to the weighting parameters of the first data object and the second data object includes:
determining a first reference value corresponding to the first data object according to the weighting parameter of the first data object;
determining a second reference value corresponding to the second data object according to the weighting parameter of the second data object;
recording the first reference value and the second reference value to generate the pooling record.
Optionally, the method further includes:
acquiring a difference value between the first data object and the second data object according to the first reference value and the second reference value;
in response to the first reference value being greater than the second reference value, sending the differentiated value to the first node;
in response to the first reference value being less than the second reference value, obtaining the difference value from the first node.
Optionally, determining the rank parameter of the first node and the second node includes:
determining the grade parameter of the first node according to all data objects of the first node and the grade parameters of the nodes on the digital offer chain where the first node is located, wherein all data objects of the first node comprise all first data objects and all second data objects, and at least two nodes on the digital offer chain have digital offers;
and determining the grade parameter of the second node according to all the data objects of the second node and the grade parameters of all the nodes on the digital offer chain where the second node is located.
Optionally, the method further includes:
and adjusting data object parameters of the first node according to at least one first data object and at least one second data object of the first node, wherein the data object parameters are used for representing the proportion of all the first data objects and the second data objects in the first node.
Optionally, adjusting the data object parameter of the first node according to the at least one first data object and the at least one second data object of the first node includes:
obtaining an expected value of a data object parameter of the first node;
determining at least one data object group from at least one first data object and at least one second data object of the first node according to the expected value, wherein the data object group comprises a first data object and a second data object which are matched;
processing the at least one set of data objects such that the at least one set of data objects enters the data pool to adjust data object parameters of the first node.
In a second aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, where the memory is used to store one or more computer instructions, and the processor executes the one or more computer instructions to perform the method described above.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, the computer program being executed by a processor to implement the above-mentioned method.
According to the embodiment of the invention, the level parameters of the first node and the second node are obtained, the weighting parameters of the first data object and the second data object of the first node are determined according to the level parameters, and the pool entry record is generated according to the weighting parameters of the first data object and the second data object, so that the combination of the first data object and the second data object of the first node enters the data pool, and therefore, the first data object and the second data object of the first node can be flushed, so that the first node can be separated from the digital offer chain, and meanwhile, the data object parameters of the first node can be adjusted.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram of a data processing system of an embodiment of the present invention;
figure 2 is a schematic diagram of a creditor relationship chain of an embodiment of the present invention;
FIG. 3 is a flow chart of a data processing method of an embodiment of the present invention;
FIG. 4 is a flow chart of another data processing method of an embodiment of the present invention;
fig. 5 is a schematic diagram of an electronic device of an embodiment of the invention.
Detailed Description
The present invention will be described below based on examples, but the present invention is not limited to only these examples. In the following detailed description of the present invention, certain specific details are set forth. It will be apparent to one skilled in the art that the present invention may be practiced without these specific details. Well-known methods, procedures, components and circuits have not been described in detail so as not to obscure the present invention.
Further, those of ordinary skill in the art will appreciate that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.
Unless the context clearly requires otherwise, throughout the description and the claims, the words "comprise", "comprising", and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, what is meant is "including, but not limited to".
In the description of the present invention, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified.
FIG. 1 is a schematic diagram of a data processing system of an embodiment of the present invention. Among them, the data processing system 1 of the present embodiment includes a server 12 and a plurality of clients 11 and the like connected to each other through a network 10. The server 12 includes a central database, and the data processing method of the present embodiment is based on the central database of the server 12. The server 12 creates a plurality of nodes and data objects of the nodes in a central database, and performs data processing on the data objects of the nodes. Wherein a plurality of nodes created in the central database respectively correspond to a plurality of clients 11 and the like. In a plurality of nodes, a digital offer is formed between two nodes, so that data objects of the two nodes relative to the digital offer can be created, and it is easily understood that data objects created from the same digital offer correspond to each other.
In response to agreed-upon contracts being made between entities corresponding to a plurality of clients 11 in a data processing system, a node may form at least one digital offer with a plurality of other nodes in a central database of a server 12, whereby if there is a digital offer between at least two of the plurality of nodes, the digital offers between the plurality of nodes form a chain of digital offers. Taking a node b in the central database as an example, the node b has a digital offer with a node a and a node c respectively, when the digital offer is formed between the node b and the node a, the central database creates a data object ax1 corresponding to the node a and a data object bx2 corresponding to the node b, and similarly, when the digital offer is formed between the node b and the node c respectively, the central database creates a data object bx1 corresponding to the node b and a data object cx2 corresponding to the node c. Node b has corresponding data objects bx1 and bx2, whereby, assuming that the data objects bx1 and bx2 correspond to the same value, the client 11 corresponding to node b may request that the data objects bx1 and bx2 be brought into the server's data pool, such that the data objects bx1 and bx2 of node b form a hedge, thereby causing node b to come out of the digital offer with nodes a and c. When the node b requests to make the data objects bx1 and bx2 enter the data pool of the server, the server creates an entry pool record in the central database according to a predetermined instruction.
The data processing method according to the embodiment of the present invention is described below by taking the relationship of the claims and the debts as an example. It should be understood that the present embodiment is not limited thereto. In this embodiment, the entities corresponding to the plurality of clients 11 are enterprises, that is, the entities corresponding to the nodes in the central database are enterprises, the digital offers between the node a and the node b may be creditor and debt digital offers, then the data objects created after the formation of the digital offers are accounts receivable of the node a and accounts payable of the node b, respectively, and the digital offer chain formed by the digital offers between the nodes is a creditor-related chain. In this embodiment, the combination of accounts receivable and accounts payable of a node is entered into the data pool of the server, so that at least part of accounts receivable and accounts payable of the node are hedged, and the node is separated from the digital debt offer of the at least part of accounts receivable and accounts payable, thereby avoiding problems such as the period of the debt and debt is prolonged, improving the processing efficiency of data objects such as the debt and debt, and adjusting the structure of the assets and debt of the node. In an alternative implementation, the server may be an SPV (Special Purpose Vehicle). SPV has two main manifestations, a special-purpose company and a special-purpose trust, whose assets and liabilities are substantially identical.
Figure 2 is a schematic diagram of a creditor relationship chain of an embodiment of the present invention. As shown in fig. 2, the creditor relationship chain 2 comprises creditor relationships between nodes a-F, it being readily understood that only a portion of the creditor liability digital offers for nodes a-F are listed in fig. 2. The corresponding creditor relationship table of the creditor relationship chain 2 in the central database is shown as table (1).
Watch (1)
Thus, if the node B-E packages the accounts payable corresponding to the node B-E into the data pool of the SPV (i.e., packages and sells to the SPV), the node B-E will be separated from the chain of creditor-rights relationship 2, and only the first and last nodes a and F have a creditor-creditor relationship, that is, the node a has 100 ten thousand accounts payable and the node F has 100 ten thousand accounts receivable. Therefore, the chain problem caused by debt delay of the intermediate node in the chain of debt-right relations (for example, the node C can not recover 40 ten thousand accounts receivable from the node B and can not pay 40 ten thousand accounts payable of the node E) can be avoided, and meanwhile, the asset load structure of the node can be adjusted (for example, a part of the nodes can pack and sell the accounts receivable).
Fig. 3 is a flowchart of a data processing method of an embodiment of the present invention. As shown in fig. 3, the data processing method of the present embodiment includes the following steps:
step S100, a request for entering a data pool by a combination of a first data object and a second data object of a first node is received. Taking the first node as node B and the server as SPV, for example, as shown in fig. 2, there is a digital offer between node B and node a, the data object of node a created according to the digital offer is 100 ten thousand accounts payable corresponding to node B, the data object of node B is 100 ten thousand accounts receivable corresponding to node a, and similarly, the data object of node B created according to the digital offer between node B and node C is 40 ten thousand accounts payable corresponding to node C, and the data object of node C is 40 ten thousand accounts receivable corresponding to node B. The client corresponding to node B requests from the SPV to pool a combination of 40 ten thousand accounts receivable corresponding to node a and 40 ten thousand accounts payable corresponding to node C. That is, the first data object is node B corresponding to 40 ten thousand accounts receivable for node a, and the second data object is node B corresponding to 40 ten thousand accounts payable for node C. In this embodiment, the data object may be resolved, in the central database, from the resolution of the data object for node B (corresponding to 100 ten thousand accounts receivable for node A) into data object B1 (corresponding to 60 ten thousand accounts receivable for node A) and data object B2 (corresponding to 40 ten thousand accounts receivable for node A), requesting data object B2 to be combined with accounts payable corresponding to node C into a pool.
Step S200, determining a corresponding third data object according to the first data object, wherein the third data object belongs to the second node, and the first data object and the third data object correspond to the same digital offer between the first node and the second node. As shown in fig. 2, in this embodiment, the second node is node a, the first data object is node B corresponding to 40 ten thousand accounts receivable of node a, and the third data object is node a corresponding to 40 ten thousand accounts payable of node B. The first data object and the third data object correspond to the same creditor liability digital offer between node a and node B.
Step S300, responding to the state of the third data object as the entered pool, determining the level parameters of the first node and the second node. In this embodiment, the SPV may determine the pooling state of the third data object according to the pooling record in the database, and allow the combination of the first data object and the second data object to be pooled after determining that the state of the third data object corresponding to the first data object is pooled.
In this embodiment, before the combination of the first data object and the second data object is pooled, the ranking parameters of the first node and the second node are first determined. In an alternative implementation, the SPV determines the rating parameter of the first node from all data objects of the first node and the rating parameters of each node on the digital offer chain in which the first node is located. The digital offer chain in which the first node is located is a digital offer including at least one first node and other nodes on the digital offer chain. All data objects of the first node include all first data objects and all second data objects, e.g., all first data objects of node B include 100 ten thousand payables for node a and all second data objects include 40 ten thousand payables for node C and 60 ten thousand payables for node D. And the SPV determines the grade parameter of the second node according to the grade parameters of each data object of the second node and each node on the digital offer chain where the second node is located.
As shown in fig. 2, taking the first node as node B and the second node as node a as an example, the SPV determines the level parameter (e.g., credit level) of node B according to all accounts receivable and accounts payable of node B and the level parameters of other nodes (e.g., node a) on the creditor relationship chain 2 where node B is located. That is, the level parameter of the node B is related to the business situation of the node B and the business situation of the node a corresponding to the receivable. For example, when all accounts receivable of node B is much larger than all accounts payable, the level parameter of node B is higher, and when the level parameter of node a corresponding to the accounts receivable of node B is higher, the level parameter of node B is also relatively higher. On the contrary, if all accounts receivable of the node B are far smaller than all accounts payable, the level parameter of the node B is lower, and when the level parameter of the node a corresponding to the accounts receivable of the node B is lower, the level parameter of the node B is also relatively lower. Similarly, the ranking parameter of the second node may be determined in the same way.
Optionally, when the combination of the accounts receivable (the first data object) and the accounts payable (the second data object) of the node is packaged into the data pool, the state of the accounts payable (the third data object) corresponding to the accounts receivable (the third data object) is the state of the accounts payable, and therefore, in this embodiment, the tracing of the level parameters of the node may be implemented, as shown in fig. 2, assuming that the level parameters of the node a and the node D are higher, and the creditor assets sold by the node B have the accounts payable corresponding to the node a, the level parameters of the node B may be traced to the node a, that is, the level parameters of the node a may affect the determination of the level parameters of the node B. The creditor assets transferred by the node C have receivable accounts corresponding to the node B, and the grade parameters of the node C can be traced to the node A through the node B, namely the grade parameters of the node A can influence the determination of the grade parameters of the node C. The creditor transferred by the node E has receivable corresponding to the node C, and the grade parameter of the node E can be traced to the node A through the node B and the node C, namely the grade parameter of the node A can influence the determination of the grade parameter of the node E. The creditor assigned by the node F has receivable accounts corresponding to the node E and the node D, and the level parameter of the node D is higher and can be used as a source for tracing the level parameter, so that the level parameter of the node F can be traced to the node A through the node B, C, E and can be traced to the node D, and when the node F is subjected to level parameter evaluation, the influence degree of the node D is higher than that of the node A. Therefore, the grade parameter of each node in the liability relation chain can be determined more accurately.
Step S400, determining weighting parameters of the first data object and the second data object according to the level parameters of the first node and the second node. In this embodiment, the weighting parameters of the first data object and the second data object may be a discount rate of accounts receivable and a discount rate of accounts payable of the first node. In an alternative implementation, the discount rate of accounts receivable and the discount rate of accounts payable of the first node are determined based on a CAMP (capital asset Pricing Model) according to the level parameters of the first and second nodes, the amounts of accounts receivable and accounts payable, the expiration time, and the like. Taking the node B in fig. 2 as an example, assuming that the level parameter of the node a is higher, the discount rate of accounts payable corresponding to the node a calculated by CAMP may be 99%, the level parameter of the node B is lower, and the discount rate of accounts payable calculated by CAMP may be 100%. That is, node B may account for 99 ten thousand of the accounts receivable of node a (i.e., node B sells 99 ten thousand accounts receivable corresponding to node a to the SPV, which pays 100 thousand cash to node B), and 100 thousand of the accounts payable of node B may account for 100 thousand (i.e., node B sells 100 thousand accounts payable corresponding to node a to the SPV, which needs to pay 100 thousand cash to the SPV).
Step S500, generating a pool entry record according to the weighting parameters of the first data object and the second data object. In an optional implementation manner, a first reference value corresponding to the first data object is determined according to the weighting parameter of the first data object, a second reference value corresponding to the second data object is determined according to the weighting parameter of the second data object, and the first reference value and the second reference value are recorded to generate the pool entry record. Optionally, after the first reference value and the second reference value are obtained, a pooling record is generated at a preset time (for example, an instant and an expiration date of accounts receivable) in response to a predetermined instruction and stored in the central database.
Taking the example of the combination of node B corresponding to node a's 40 ten thousand accounts receivable (the first data object) and node C's 40 ten thousand accounts receivable (the second data object) in fig. 2, assume that node B has a weighting parameter corresponding to node a's 40 ten thousand accounts receivable (i.e., a discount rate) of 99% and node B's accounts payable weighting parameter of 100%. Node B has a first reference value of 40 × 99% ═ 39.6 ten thousand for 40 ten thousand receivable charges for node a, and node B has a second reference value of 40 × 100% ═ 40 ten thousand for 40 ten thousand receivable charges for node C. For the accounts receivable of the node B, the SPV generates an accounts payable (an instant pool entry record) corresponding to the accounts receivable of the node B according to a predetermined instruction, when the accounts receivable expires, the node B transfers the corresponding accounts receivable to the SPV, and the SPV generates an accounts receivable (a pool entry record on an expiration date) corresponding to the accounts receivable of the node B according to a predetermined instruction. For the accounts payable of node B, the SPV generates an accounts receivable (an instant pool entry) corresponding to the accounts payable of node B according to a predetermined instruction, and when the accounts payable expires, the SPV transfers the corresponding accounts payable to node C, and the SPV generates an accounts payable (a pool entry on the due date) corresponding to the accounts payable of node B according to a predetermined instruction. Wherein the pooling record includes instant accounts payable and due date accounts receivable corresponding to accounts receivable by the node B, and instant accounts payable and due date accounts payable corresponding to accounts payable by the node B.
Specifically, in the data processing of the above due combination into the pool of the intermediate node B, the pool entry record includes:
1. and (5) accounting due immediately: SPV-node B, 39.6 ten thousand (account receivable for node B)
2. Accounting due to due date: node B-SPV, node B receives actual accounts receivable from node A (node B accounts receivable)
3. Accounting of instant receivable accounts: node B-SPV, 40 ten thousand (accounts payable of node B)
4. Accounting due date: SPV-node C, node B actual accounts payable to node C (accounts payable for node B)
Thus, the server writes the pool records into the central database through a preset command. The server can instantly generate the pool entry records 1 and 3 at the time of the receivable and payable pool processing through 4 instructions, respectively, generate the pool entry record 2 at the due date of the accounts receivable of the node B, and generate the pool entry record 4 at the due date of the accounts payable of the node B.
Further optionally, the data processing method of this embodiment further includes step S600, where the SPV obtains a difference value between the first data object and the second data object according to the first reference value and the second reference value. The SPV sends a differential worth value to the first node in response to the first reference value being greater than the second reference value, and obtains the differential worth value from the first node in response to the first reference value being less than the second reference value. As described above, the first reference value for receivable funds of the node B is 40 × 99% ═ 39.6 ten thousand, and the second reference value for payable funds is 40 × 100% ═ 40 ten thousand. Therefore, when the combination of accounts receivable and accounts payable is pooled, node B needs to pay (40-39.6) ═ 0.4 ten thousand to the SPV. Thus, node B packages and sells a combination of 40 ten thousand accounts receivable corresponding to node a and 40 ten thousand accounts payable corresponding to node C to SPV, node B departs from the creditor-creditor relationship, when 40 ten thousand accounts payable corresponding to node C expires, node C is paid the corresponding accounts payable by SPV to node C, and when the accounts payable corresponding to node a expires, node B transfers the accounts payable received from node a to SPV.
In this embodiment, the level parameters of the first node and the second node are obtained, the weighting parameters of the first data object and the second data object of the first node are determined according to the level parameters, and the pool entry record is generated according to the weighting parameters of the first data object and the second data object, so that the combination of the first data object and the second data object of the first node enters the data pool, and thus, the first data object and the second data object of the first node can be hedged, so that the first node can be separated from the digital offer chain.
In an optional implementation manner, the embodiment of the present invention further includes step S700: the data object parameters of the first node are adjusted in dependence on the at least one first data object and the at least one second data object of the first node. Wherein the data object parameter is used to characterize the proportion of all first data objects and second data objects in the first node. Optionally, first, an expected value of the data object parameter of the first node is obtained, at least one data object group is determined from at least one first data object and at least one second data object of the first node according to the expected value, and the at least one data object group is processed so that the at least one data object group enters the data pool, so as to adjust the data object parameter of the first node, so that the adjusted data object parameter reaches or approximately reaches the expected value. Wherein the set of data objects comprises a first data object and a second data object which match.
Taking the creditor relationship as an example, the data object parameter of the node may be a rate of assets and liabilities, the client corresponding to the node may send a desired rate of assets and liabilities to the SPV, the SPV determines a combination of at least one receivable and accounts payable from all receivable and accounts payable of the node according to the desired rate of assets and liabilities, and the node a puts the determined combination of at least one receivable and accounts payable into the pool, whereby the total amount of receivable and account payable amounts of the node a may be reduced to reach or approach the rate of assets and liabilities desired by the node. Optionally, the asset liability rate of the node satisfies the following formula:
P＝(L+e*A)/(1+e)
wherein, P is the transaction price due (i.e. the amount due to be combined and packed into the pool), L is the total liability of the node, A is the total asset of the node, and e is the expected rate of the asset liability.
Thus, the embodiment can determine the amount of the portfolio due into the pool according to the expected rate of the assets and liabilities of the node, so that the node reaches or approximately reaches the expected rate of the assets and liabilities, and the structure of the assets and liabilities of the node can be optimized.
FIG. 4 is a flow chart of another data processing method of an embodiment of the invention. The present embodiment takes the processing of the creditability and debt relationship between nodes as an example for explanation. As shown in fig. 4, the data processing method of the present embodiment includes the following steps:
in step S1, the client corresponding to node X sends a combination of accounts receivable and accounts payable to the SPV to request the data pool. Wherein, the node X is a node in a certain creditor relationship chain.
In step S2, the SPV determines accounts payable for accounts receivable for node X. As shown in fig. 2, assuming that node X is node B, which requests that a combination of 40 ten thousand accounts receivable corresponding to node a and 40 ten thousand accounts payable corresponding to node C be pooled, the accounts payable corresponding to the accounts receivable of node X is 40 ten thousand accounts payable corresponding to node B.
In step S3, the SPV determines the status of accounts payable corresponding to accounts receivable at node X according to the pool entry record stored in the central database. If the status of the accounts payable corresponding to the accounts receivable of the node X is not in the pool, the data processing process is ended, i.e., the request of the node X for the accounts payable combination to enter the pool is failed. When the accounts payable corresponding to the accounts receivable of the node X is in the pool, step S4 is executed.
In step S4, when the accounts payable corresponding to the accounts receivable of node X is in the pool, the level parameters of node X and node Y are determined. Wherein, the node Y is a node to which accounts payable corresponding to accounts receivable of the node X belongs. As shown in FIG. 2, assume node X is node B and node Y is node A. In an alternative implementation, taking the first node as node B and the second node as node a as an example, the SPV determines the level parameter (e.g., credit level, etc.) of node B according to all accounts receivable and accounts payable of node B and the level parameters of other nodes (e.g., node a, etc.) on the creditor-related chain 2 where node B is located. That is, the level parameter of the node B is related to the business situation of the node B and the business situation of the node a corresponding to the receivable. For example, when all accounts receivable of node B is much larger than all accounts payable, the level parameter of node B is higher, and when the level parameter of node a corresponding to the accounts receivable of node B is higher, the level parameter of node B is also relatively higher. On the contrary, if all accounts receivable of the node B are far smaller than all accounts payable, the level parameter of the node B is lower, and when the level parameter of the node a corresponding to the accounts receivable of the node B is lower, the level parameter of the node B is also relatively lower. Similarly, the rank parameter of node a may be determined in the same way.
In step S5, the receivable and payable weighting parameters of node X are determined according to the level parameters of node X and node Y. In this embodiment, the weighting parameters of receivable and accounts payable of node X may be the discount rate of receivable and the discount rate of accounts payable of node X. In an alternative implementation, the discount rate of accounts receivable and the discount rate of accounts payable for node X are determined based on CAMP (Capital Asset Pricing Model) according to the level parameters of node X and node Y, the amounts and expiration times of accounts receivable and accounts payable, and so on. Taking node X as node B in fig. 2 as an example, assuming that the level parameter of node a is higher, the discount rate of accounts payable corresponding to node a of node B calculated according to CAMP may be 99%, the level parameter of node B is lower, and the discount rate of accounts payable calculated according to CAMP may be 100%. That is, node B may account for 99 ten thousand of the accounts receivable of node a (i.e., node B sells 99 ten thousand accounts receivable corresponding to node a to the SPV, which pays 100 thousand cash to node B), and 100 thousand of the accounts payable of node B may account for 100 thousand (i.e., node B sells 100 thousand accounts payable corresponding to node a to the SPV, which needs to pay 100 thousand cash to the SPV).
In step S6, the receivable and payable reference values of node X are determined according to the receivable and payable weighting parameters of node X. Taking the example of the combination of node B corresponding to node a's 40 ten thousand accounts receivable (the first data object) and node C's 40 ten thousand accounts receivable (the second data object) in fig. 2, assume that node B has a weighting parameter corresponding to node a's 40 ten thousand accounts receivable (i.e., a discount rate) of 99% and node B's accounts payable weighting parameter of 100%. Node B has a reference value of 40 × 99% ═ 39.6 ten thousand for 40 ten thousand receivable of node a, and node B has a reference value of 40 × 100% ═ 40 ten thousand for 40 ten thousand receivable of node C.
In step S7, a pool entry record is generated based on the accounts receivable and the accounts payable reference values of node X. Taking the example of the combination of node B corresponding to node a's 40 ten thousand accounts receivable (first data object) and node C's 40 ten thousand accounts payable (second data object) in fig. 2, for node B's accounts receivable, the SPV instantaneously generates an account payable corresponding to node B's accounts receivable, upon expiration of the account payable, node B transfers the corresponding accounts receivable to the SPV, which instantaneously generates an account payable corresponding to node B's accounts receivable. For the accounts payable of node B, the SPV instantly generates accounts receivable corresponding to the node, upon expiration of the accounts payable, the SPV transfers the corresponding accounts payable to node C, and the SPV instantly generates accounts payable corresponding to the accounts payable of node B. Wherein the pooling record includes instant accounts payable and due date accounts receivable corresponding to accounts receivable by the node B, and instant accounts payable and due date accounts payable corresponding to accounts payable by the node B.
And step S8, determining a difference value according to the reference values of accounts receivable and accounts payable of the node X. The reference value of accounts receivable at the node X is greater than the reference value of accounts payable, and step S9 is executed, where the reference value of accounts receivable at the node X is less than the reference value of accounts payable.
At step S9, the SPV sends the difference value to node X.
At step S10, node X sends the difference value to the SPV.
As described above, taking the combination of 40 ten thousand receivable accounts (first data object) corresponding to node a and 40 ten thousand receivable accounts (second data object) corresponding to node C as an example in fig. 2, the first reference value corresponding to the receivable accounts of node B is 40 × 99% ═ 39.6 ten thousand, and the second reference value corresponding to the receivable accounts is 40 × 100% ═ 40 ten thousand. Therefore, when the combination of accounts receivable and accounts payable is pooled, node B needs to pay (40-39.6) ═ 0.4 ten thousand to the SPV. Thus, node B packages and sells a combination of 40 ten thousand accounts receivable corresponding to node a and 40 ten thousand accounts payable corresponding to node C to SPV, node B departs from the creditor-creditor relationship, when 40 ten thousand accounts payable corresponding to node C expires, node C is paid the corresponding accounts payable by SPV to node C, and when the accounts payable corresponding to node a expires, node B transfers the accounts payable received from node a to SPV.
In this embodiment, the level parameters of the node X and the node Y are obtained, the weighting parameters of the accounts receivable and the accounts payable of the node X are determined according to the level parameters, and the pool entry record is generated according to the weighting parameters of the accounts receivable and the accounts payable objects, so that the combination of the accounts receivable and the accounts payable of the node X enters the data pool, thereby the accounts receivable and the accounts payable of the node X can be hedged, so that the node X can be separated from the chain of the debt-right chain, the risk of chain reaction caused by debt owing of some nodes on the chain of the debt-right chain is reduced, meanwhile, part of the accounts receivable and the accounts payable of the node X are packaged and sold, the rate of the asset liability of the node X can be adjusted, and the structure of the asset liability of the node X can be optimized.
Fig. 5 is a schematic diagram of an electronic device of an embodiment of the invention. In the present embodiment, the electronic device 5 includes a server, a terminal, and the like. As shown in fig. 5, the electronic device 5 comprises at least one processor 501; and a memory 502 communicatively coupled to the at least one processor 501; and a communication component 503 in communicative connection with the scanning device, the communication component 503 receiving and transmitting data under the control of the processor 501; the memory 502 stores instructions executable by the at least one processor 501, and the instructions are executed by the at least one processor 501 to implement the data processing method.
Specifically, the electronic device includes: one or more processors 501 and a memory 502, with one processor 501 being an example in fig. 5. The processor 501 and the memory 502 may be connected by a bus or other means, and fig. 5 illustrates the connection by the bus as an example. Memory 502, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The processor 501 executes various functional applications of the device and data processing, i.e., implements the above-described data processing method, by executing nonvolatile software programs, instructions, and modules stored in the memory 502.
The memory 502 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store a list of options, etc. Further, the memory 502 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 502 may optionally include memory located remotely from processor 501, which may be connected to an external device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The memory 502 stores one or more modules, which when executed by the processor 501, perform the data processing method in any of the above-described method embodiments.
The product can execute the method provided by the embodiment of the application, has corresponding functional modules and beneficial effects of the execution method, and can refer to the method provided by the embodiment of the application without detailed technical details in the embodiment.
In this embodiment, the level parameters of the first node and the second node are obtained, the weighting parameters of the first data object and the second data object of the first node are determined according to the level parameters, and the pool entry record is generated according to the weighting parameters of the first data object and the second data object, so that the combination of the first data object and the second data object of the first node enters the data pool, and thus, the first data object and the second data object of the first node can be hedged, so that the first node can be separated from the digital offer chain, and meanwhile, the data object parameters of the first node can be adjusted.
Another embodiment of the invention is directed to a non-transitory storage medium storing a computer-readable program for causing a computer to perform some or all of the above-described method embodiments.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A method of data processing, the method comprising:
receiving a request for a combination of a first data object and a second data object of a first node to enter a data pool;
determining a corresponding third data object from the first data object, wherein the third data object is attributed to a second node, the first data object and the third data object corresponding to a same digital offer between the first node and the second node;
determining a level parameter of the first node and the second node in response to the state of the third data object being pooled;
determining weighting parameters of the first data object and the second data object according to the level parameters of the first node and the second node;
and generating a pool entry record according to the weighting parameters of the first data object and the second data object.
2. The method of claim 1, wherein generating the pooling record according to the weighting parameters of the first data object and the second data object comprises:
determining a first reference value corresponding to the first data object according to the weighting parameter of the first data object;
determining a second reference value corresponding to the second data object according to the weighting parameter of the second data object;
recording the first reference value and the second reference value to generate the pooling record.
3. The method of claim 2, further comprising:
acquiring a difference value between the first data object and the second data object according to the first reference value and the second reference value;
in response to the first reference value being greater than the second reference value, sending the differentiated value to the first node;
in response to the first reference value being less than the second reference value, obtaining the difference value from the first node.
4. The method of claim 1, wherein determining the rank parameters of the first node and the second node comprises:
determining the grade parameter of the first node according to all data objects of the first node and the grade parameters of the nodes on the digital offer chain where the first node is located, wherein all data objects of the first node comprise all first data objects and all second data objects, and at least two nodes on the digital offer chain have digital offers;
and determining the grade parameter of the second node according to all the data objects of the second node and the grade parameters of all the nodes on the digital offer chain where the second node is located.
5. The method of claim 1, further comprising:
and adjusting data object parameters of the first node according to at least one first data object and at least one second data object of the first node, wherein the data object parameters are used for representing the proportion of all the first data objects and the second data objects in the first node.
6. The method of claim 5, wherein adjusting the data object parameters of the first node based on at least one first data object and at least one second data object of the first node comprises:
obtaining an expected value of a data object parameter of the first node;
determining at least one data object group from at least one first data object and at least one second data object of the first node according to the expected value, wherein the data object group comprises a first data object and a second data object which are matched;
processing the at least one set of data objects such that the at least one set of data objects enters the data pool to adjust data object parameters of the first node.
7. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer instructions that are executed by the processor to implement the method of any of claims 1-6.
8. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor to implement the method of any of claims 1-6.
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