Data processing method and device based on transaction bill and server

Abstract

The invention provides a transaction bill-based data processing method and device and a server, which can be used in the technical field of big data. Based on the method, a target business category can be determined according to a target sample screening request related to a transaction bill; determining a matched target processing rule according to the target business type, and obtaining a corresponding target initial table set from a system database according to the matched target processing rule; according to the target initial table set, determining bill information of a target transaction bill corresponding to the target transaction packet and related target transaction business data; and according to the target processing rule and the bill information of the target transaction bill, detecting and processing interference sample data in the target transaction business data to obtain target sample business data meeting requirements. Therefore, the method can be well adapted to a transaction business scene based on big data, and target sample business data meeting requirements can be efficiently, accurately and automatically screened out by distinguishing different business types.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a data processing method, device and server based on transaction notes. Background Art

[0002] In financial business scenarios, users often come into contact with a large number of transaction bill business products involving transaction bills (for example, commercial bills, etc.).

[0003] For this type of transaction bill business product, users usually need to first screen relevant sample transaction business data from a large amount of relevant transaction business data; then use the above-mentioned relevant sample transaction business data to construct a corresponding transaction bill business curve (for example, a commercial bill yield curve); and then use the transaction bill business curve as an auxiliary reference to guide specific transaction business decisions.

[0004] However, existing methods often rely on users to manually sort through massive amounts of transaction business data to screen out sample transaction business data that meets the requirements in order to construct the corresponding transaction bill business curve. This has technical problems such as cumbersome user operations, low processing efficiency, and prone to errors.

[0005] To address the above problems, no effective solution has been proposed yet. Summary of the invention

[0006] The present specification provides a data processing method, device and server based on transaction notes, which can be well adapted to transaction business scenarios based on big data. By distinguishing different business categories and based on corresponding rules, it can effectively eliminate abnormal interference samples, and then can automatically screen out target sample business data that meets the requirements efficiently and accurately, so as to construct a target transaction note business curve with high reference value and small error.

[0007] This specification provides a data processing method based on a transaction note, including:

[0008] Obtaining a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and relevant information of the target transaction package; the transaction indicated by the target transaction package is related to the transaction bill;

[0009] Determine the target business category according to the target sample screening request; wherein the target business category includes: discount business or rediscount business;

[0010] According to the target business category, determine the matching target processing rules; and according to the target processing rules, obtain the corresponding target initial table set from the system database;

[0011] Determine the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set;

[0012] According to the target processing rules and the bill information of the target transaction bill, the interference sample data in the target transaction business data is detected and processed to obtain the target sample business data that meets the requirements; wherein the target sample business data is used to generate the target transaction bill business curve.

[0013] In one embodiment, the bill information includes at least one of the following: bill denomination, acceptor information, drawee information, bill category, bill expiration date, and discounter information;

[0014] The bill types include at least one of the following: bank bills, commercial bills, and financial bills.

[0015] In one embodiment, when the target business category is a discount business, the target processing rule is a first preset processing rule based on the discount business;

[0016] Correspondingly, according to the target processing rules, the institution information table, the bill information table, the transaction and bill association table, and the discount behavior table are obtained from the system database as the target initial table set.

[0017] In one embodiment, when the target business category is a rediscount business, the target processing rule is a second preset processing rule based on the rediscount business;

[0018] Correspondingly, according to the target processing rules, the institution information table, the bill information table, the transaction and bill association table, and the rediscount behavior table are obtained from the system database as the target initial table set.

[0019] In one embodiment, when the target business category is a discount business, the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package are determined according to the target initial table set, including:

[0020] Determine, according to the target transaction package and relevant information of the target transaction package, a plurality of initial transaction business data and a plurality of initial transaction identifiers corresponding to the plurality of initial transaction business data;

[0021] Using the initial transaction identifier and the rediscount behavior table to match the transaction identifier, determine the initial transaction identifier that matches successfully as the target transaction identifier; and based on the target transaction identifier, screen out the target transaction business data involving the rediscount behavior from the multiple initial transaction business data;

[0022] According to the target transaction identifier, query the transaction and bill association table to determine the bill identifier of the target transaction bill associated with the target transaction business data;

[0023] According to the bill identifier of the target transaction bill, the bill information table is queried to obtain the corresponding bill information of multiple target transaction bills.

[0024] In one embodiment, according to the target processing rules and the ticket information of the target transaction ticket, the interference sample data in the target transaction business data is detected and processed to obtain the target sample business data that meets the requirements, including:

[0025] According to the first preset processing rule, the note denomination, acceptor information, and note category of the target transaction note are combined to determine the characteristic combination type of the target transaction business data;

[0026] According to the characteristic combination type of the target transaction business data, a preset curve basic table is queried to obtain the corresponding target curve basic parameters; wherein the preset curve basic table stores a plurality of preset curve basic parameters corresponding to the plurality of characteristic combination types;

[0027] According to the first preset processing rule and the target curve basic parameters, detect whether there is a first type of interference sample data in the target transaction business data; wherein the first type of interference sample data includes at least one of the following: transaction business data whose amount ratio does not meet the requirements, transaction business data whose term difference does not meet the requirements, and transaction business data whose deviation does not meet the requirements;

[0028] When it is determined that the target transaction business data contains the first type of interference sample data, the first type of interference sample data is eliminated to obtain the target sample business data that meets the requirements.

[0029] In one embodiment, according to the target processing rules and the ticket information of the target transaction ticket, the interference sample data in the target transaction business data is detected and processed to obtain the target sample business data that meets the requirements, including:

[0030] According to the second preset processing rule, the bill denomination, acceptor information, discounter information, and bill category of the target transaction bill are combined to determine the characteristic combination type of the target transaction business data;

[0031] According to the characteristic combination type of the target transaction business data, a preset curve basic table is queried to obtain the corresponding target curve basic parameters; wherein the preset curve basic table stores a plurality of preset curve basic parameters corresponding to the plurality of characteristic combination types;

[0032] According to the second preset processing rule and the target curve basic parameters, detect whether there is a second type of interference sample data in the target transaction business data; wherein the second type of interference sample data includes at least one of the following: transaction business data whose amount ratio does not meet the requirements, transaction business data whose term difference does not meet the requirements, transaction business data whose deviation does not meet the requirements, internal transaction business data, arbitrage transaction business data, and bridge transaction business data;

[0033] When it is determined that the target transaction business data contains the second type of interference sample data, the second type of interference sample data is eliminated to obtain the target sample business data that meets the requirements.

[0034] This specification also provides a data processing device based on a transaction ticket, comprising:

[0035] A first acquisition module is used to acquire a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and relevant information of the target transaction package; and the transaction indicated by the target transaction package is related to the transaction bill;

[0036] A first determination module is used to determine a target business category according to a target sample screening request; wherein the target business category includes: a discount business or a rediscount business;

[0037] The second acquisition module is used to determine the matching target processing rules according to the target business category; and obtain the corresponding target initial table set from the system database according to the target processing rules;

[0038] A second determination module is used to determine the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set;

[0039] The processing module is used to detect and process the interference sample data in the target transaction business data according to the target processing rules and the bill information of the target transaction bill, and obtain the target sample business data that meets the requirements; wherein the target sample business data is used to generate the target transaction bill business curve.

[0040] The present specification also provides a server, comprising a processor and a memory for storing processor executable instructions, wherein the processor implements the steps of the transaction ticket-based data processing method when executing the instructions.

[0041] The present specification also provides a computer-readable storage medium on which computer instructions are stored. When the instructions are executed by a processor, the relevant steps of the transaction ticket-based data processing method are implemented.

[0042] Based on the data processing method, device and server based on transaction bills provided in this specification, when it is necessary to construct a corresponding target transaction bill business curve, after obtaining the target sample screening request, the target business category can be determined according to the relevant information of the target transaction package involving the transaction bill; then, according to the target business category, the corresponding target initial table set can be determined and obtained from the system database according to the matching target processing rules; then, according to the target initial table set, the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package can be determined; according to the target processing rules and the bill information of the target transaction bill, the interference sample data in the target transaction business data can be detected and processed to obtain the target sample business data suitable for generating the corresponding target transaction bill business curve. Thus, it can be better adapted to the transaction business scenario based on big data, by distinguishing different business categories, based on the corresponding rules, effectively eliminating abnormal interference samples, and then being able to efficiently and accurately automatically screen out the target sample business data with good effect and meeting the requirements, so that the target sample business data can be used to generate the target transaction bill business curve with high reference value and small error for users in the future, thereby effectively simplifying user operations and improving overall processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of this specification, the drawings required for use in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a flowchart of a data processing method based on a transaction note provided by an embodiment of this specification;

[0045] Figure 2 It is a schematic diagram of an embodiment of a data processing method based on a transaction ticket provided by an embodiment of this specification, in a scenario example;

[0046] Figure 3 It is a schematic diagram of an embodiment of a data processing method based on a transaction ticket provided by an embodiment of this specification, in a scenario example;

[0047] Figure 4 It is a schematic diagram of an embodiment of a data processing method based on a transaction ticket provided by an embodiment of this specification, in a scenario example;

[0048] Figure 5 It is a schematic diagram of an embodiment of a data processing method based on a transaction ticket provided by an embodiment of this specification, in a scenario example;

[0049] Figure 6 It is a schematic diagram of the structure of a server provided by an embodiment of this specification;

[0050] Figure 7 It is a schematic diagram of the structural composition of a data processing device based on transaction notes provided in one embodiment of the present specification. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0052] It should be noted that the user-related information and data involved in the embodiments of this specification are all information and data authorized by the user or fully authorized by relevant parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users or relevant parties to choose to authorize or refuse.

[0053] It should also be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0054] Taking into account the increasing activity of bill transactions with the continuous development of the financial market, some irregular trading behaviors involving bill transactions have gradually begun to appear in the trading activities involving bill transactions. The above irregular trading behaviors will affect the calculation of business curves such as the yield curve based on the rediscount of the bill transaction, introduce some sample data that have no reference value, and then lead to large errors and low references in the final calculated business curve. In view of the above situation, more attention is usually paid to the compliance of the transaction, and the deep-seated reasons that interfere with the calculation of the business curve often lack in-depth analysis and screening, which makes it difficult to accurately and comprehensively eliminate the interference samples that affect the generation of the business curve.

[0055] In response to the above-mentioned problems and the root causes of the above-mentioned problems, the applicant, after creative thinking, proposed to distinguish different business categories and, based on corresponding rules, conduct targeted screening of transaction business data in different situations in combination with multiple dimensions, so as to effectively propose interference samples with abnormalities, and then use the target transaction business data after elimination to generate a target transaction bill business curve with higher reference value and smaller error for users.

[0056] See also Figure 1 As shown, the embodiment of this specification provides a data processing method based on transaction notes. Among them, the method is specifically applied to the server side. When implemented specifically, the method may include the following contents:

[0057] S101: Obtain a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and relevant information of the target transaction package; the transaction indicated by the target transaction package is related to the transaction bill;

[0058] S102: Determine a target business category according to the target sample screening request; wherein the target business category includes: discount business or rediscount business;

[0059] S103: Determine a matching target processing rule according to the target business category; and obtain a corresponding target initial table set from a system database according to the target processing rule;

[0060] S104: Determine the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set;

[0061] S105: According to the target processing rules and the bill information of the target transaction bill, detect and process the interference sample data in the target transaction business data to obtain the target sample business data that meets the requirements; wherein the target sample business data is used to generate the target transaction bill business curve.

[0062] The target transaction bill business curve can be specifically understood as a curve data that can reflect the changes in relevant data of transactions involving transaction bills and can provide reference for users' decisions. For example, the transaction bill yield curve, or the transaction bill market price change curve, etc. The following mainly takes the transaction bill yield curve as an example for specific explanation.

[0063] Among them, the above-mentioned transaction notes can be specifically understood as a kind of negotiable and tradable valuable certificate, such as bills of exchange, bank drafts and checks.

[0064] Taking a bill of exchange as an example, the above-mentioned bill of exchange can specifically be a note issued by the drawer, entrusting the payee to unconditionally pay a certain amount of resource data (for example, funds, etc.) to the payee or holder on a specified date.

[0065] Furthermore, the above-mentioned transaction bills may specifically include at least one of the following: bank bills, commercial bills, financial bills, etc.

[0066] Specifically, the above-mentioned silver bill can be understood as a bill of exchange issued by a bank with the bank as the acceptor. The above-mentioned financial bill can be understood as a bill of exchange issued by a financial company with the financial company as the acceptor. The above-mentioned commercial bill can be understood as a bill of exchange issued by an enterprise with the enterprise as the acceptor.

[0067] It should be noted that the above-mentioned different types of bills of exchange may differ in liquidity, risk, profitability (for example, discount rate), etc. due to different acceptors.

[0068] Of course, it should be noted that the transaction notes listed above are only a schematic illustration. In specific implementation, according to specific application scenarios and processing requirements, the transaction notes may also include other types of notes. This specification does not limit this.

[0069] Among them, the above-mentioned target business categories may specifically include: discount business or rediscount business, etc.

[0070] Specifically, the above-mentioned discounting business can be understood as the bill behavior in which the holder of the transaction bill transfers the relevant rights of the transaction bill to the bank by paying a certain interest before the bill matures in order to obtain relevant resource data such as funds.

[0071] The above-mentioned rediscount business can be understood as the act of a bank, in certain circumstances, transferring discounted but unexpired transaction bills to other banks or related discounting institutions for discounting in order to obtain relevant resource data such as funds.

[0072] It should be noted that the above-mentioned different categories of business activities, due to the differences in the participants and data processing processes involved, will lead to differences in the analysis and processing of relevant data involving transaction notes.

[0073] The above-mentioned target transaction business data can be specifically understood as the full transaction business data involving the target transaction bill and a large amount of data. The above-mentioned interference sample data can be specifically understood as the transaction business data that contains errors and interferences in the target transaction business data, or is not suitable for constructing the corresponding target transaction bill business curve. The above-mentioned target sample business data can be specifically understood as the transaction business data that is screened from the target transaction business data, has a small error, a high reference value, a good effect, and is suitable for constructing the corresponding target transaction bill business curve.

[0074] For specific implementation, see Figure 2 As shown, when a user (including individual users or institutional users, etc.) is interested in a transaction business (or financial product) involving a transaction bill and wants to analyze the revenue of the transaction in order to make a decision on subsequent operations, the user terminal held by the user can first initiate a corresponding target sample screening request about the target transaction bill business curve to the server. Accordingly, the server can respond to the target sample screening request, apply the data processing method based on transaction bills provided in this specification, distinguish different business categories, query the bill information of the target transaction bill involved, and the full amount of target transaction business data; and based on the matching target processing rules, combined with the bill information of the target transaction bill, automatically detect and process a large amount of target transaction business data, so as to find and eliminate the interference sample data that subsequently affects the accuracy and reliability of the target transaction bill business curve, and screen out the target sample business data that meets the requirements; and feed back the above target sample business data to the user terminal.

[0075] The user terminal can display the target sample business data and related prompt information to the user. After the user confirms, the user terminal can further initiate a request to the server to generate a target transaction bill business curve based on the above target sample business data. Correspondingly, the server can respond to the request to generate the target transaction bill business curve, use the above target sample business data through data fitting, and generate a target transaction bill business curve that meets the user's needs; and feed back the target transaction bill business curve to the user terminal.

[0076] The user terminal can display the target transaction bill business curve to the user, and the user can also use the user terminal to initiate a target analysis and prediction request about the target transaction bill business curve to the server. Accordingly, the server can respond to the target analysis and prediction request, first call the pre-trained curve image recognition model to process the target transaction bill business curve, and obtain a target analysis result that can reflect the changes in the relevant data (for example, yield) of the relevant transactions involving the target transaction bill indicated by the target transaction bill business curve at various key time points in history, as well as the reasons for the changes; further, combine the target analysis result and the target transaction bill business curve to obtain the combined data; and use the pre-trained curve trend prediction model to process the above combined data to obtain a target prediction result that can reflect the changes in the relevant data of the relevant transactions involving the target transaction bill indicated by the target transaction bill business curve in a future time period (for example, the next month); then use the mulberry tree target analysis result and the target combination result together to generate a corresponding target analysis and prediction report; and feed the target analysis and prediction report back to the user terminal.

[0077] The user terminal can display the target analysis and forecast report to the user. The user can use the target analysis and forecast report as a reference to make decisions on subsequent operations. For example, determine whether to purchase related financial products involving the target transaction bill, or whether to sell related financial products involving the target transaction bill, etc.

[0078] The server may include a background server applied to a transaction service platform and capable of realizing functions such as data transmission and data processing. Specifically, the server may be, for example, an electronic device having data calculation, storage and network interaction functions. Alternatively, the server may also be a software program running in the electronic device to provide support for data processing, storage and network interaction. In this embodiment, the number of servers is not specifically limited. The server may be one server, several servers, or a server cluster formed by several servers.

[0079] The user terminal may specifically include a front end applied to the user side and capable of realizing functions such as data collection and data transmission. Specifically, the user terminal may be, for example, an electronic device such as a desktop computer, a tablet computer, a laptop computer, a smart phone, etc. Alternatively, the user terminal may also be a software application that can run in the above electronic devices.

[0080] Based on the above embodiments, it can be better adapted to transaction business scenarios based on big data. By distinguishing different business categories, it can automatically and efficiently screen out target sample business data that meets the requirements, so that the above target sample business data can be used to subsequently generate a target transaction bill business curve with higher reference value and smaller error for users.

[0081] In some embodiments, the bill information may specifically include at least one of the following: bill denomination, acceptor information, drawee information, bill category, bill expiration date, discounter information, etc.;

[0082] The bill types may specifically include at least one of the following: bank bills, commercial bills, financial bills, etc.

[0083] Of course, it should be noted that the above-listed bill information is only a schematic illustration. In specific implementation, according to specific application scenarios and processing requirements, the above-listed bill information may also include other types of related information. This specification does not limit this.

[0084] In some embodiments, before specific implementation, the server may collect a large number of data processing records of historical transaction bills on the transaction service platform; and cluster the data processing records of the above historical transaction bills based on business categories to obtain two processing feature data groups; wherein the above two processing feature data groups correspond to the discount business and the rediscount business, respectively, and respectively contain the common processing characteristics of the corresponding business categories when screening and processing sample business data; according to the above two processing feature data groups, the corresponding first preset processing rules and second preset processing rules are respectively constructed; wherein the first preset processing rule corresponds to the discount business, and the second preset processing rule corresponds to the rediscount business.

[0085] Based on the above-mentioned first preset processing rule and second preset processing rule, different business situations such as discount business and rediscount business can be effectively distinguished, and the bill information and transaction business data of relevant transaction bills can be obtained and processed in a targeted manner, so as to be able to automatically detect and process the corresponding interference sample data efficiently and accurately, and screen out sample business data that is suitable for the corresponding business, with better effects and smaller errors.

[0086] Furthermore, the server can also obtain and obtain multiple historical transaction bill business curves based on a large number of historical transaction bill business curve generation records on the transaction service platform; then, based on the corresponding historical user feedback records, select the historical transaction bill business curve with a positive evaluation value from the above multiple historical transaction bill business curves as the sample transaction bill business curve; then, based on the corresponding historical transaction bill business curve generation record, obtain the bill information of the transaction bill involved in the sample transaction bill business curve, and cluster the above bill information and the sample transaction bill business curve corresponding to the bill information to obtain the curve configuration parameters corresponding to the transaction bill business curve of multiple characteristic combination types obtained based on the bill information; then, combined with the platform requirements and expert experience, the above curve configuration parameters are adjusted accordingly to obtain multiple preset curve basic parameters; wherein each preset curve basic parameter corresponds to at least one characteristic combination type, and each preset curve basic parameter includes the critical reference value of the relevant parameters of the transaction bill business curve of the corresponding characteristic combination type, such as the amount ratio threshold, the term difference threshold, the spread critical threshold, the standard deviation multiple of the deviation, etc. The above multiple preset curve basic parameters can be stored in the preset curve basic table. Please refer to Figure 3 shown.

[0087] In specific implementation, the transaction service platform can access the business data occurring on the platform in real time, and access the business data occurring on other platforms at regular intervals; based on the above business data, extract the required data information, and classify the above data information; based on the classified data information, create and update the platform's business data information table. Among them, the business data information table at least includes: institution information table, bill information table, transaction and bill association table, discount behavior table, rediscount behavior table, etc. For details, please refer to Figure 3 shown.

[0088] Specifically, the above-mentioned bill information table may record the bill information of each transaction bill. The above-mentioned transaction and bill association table may record the transaction business data related to each transaction bill. The above-mentioned rediscount behavior table may record the transaction identifier (for example, transaction number) involved in the rediscount behavior. The above-mentioned discount behavior table may record the transaction identifier involved in the discount behavior. The above-mentioned institution information table may record the institution information (for example, credit rating parameters of the institution, type label of the institution, etc.) of the institution (for example, drawer, acceptor, discounter, etc.) related to the transaction bill.

[0089] In addition, the server can also combine the fitting records when generating the transaction bill business curve with historical fitting, determine the linear segmentation configuration parameters for fitting the curve that are suitable for different feature combination types (including: segmentation key term points, segmentation length, fitting model used for segmentation, etc.), and generate the corresponding linear segmentation configuration table.

[0090] In some embodiments, the target sample screening request may carry relevant information of the target transaction package, wherein the transaction indicated by the target transaction package is related to the transaction ticket.

[0091] Specifically, the relevant information of the target transaction package may include the transaction identifier of the transaction concerned by the user and involving the transaction ticket, and the introduction of the transaction. The target transaction package may include relevant transaction business data.

[0092] Furthermore, the target sample screening request may also carry a category indication parameter that is set by the user to indicate the target service category. The category indication parameter may be set in a specified field in the request header of the target sample screening request.

[0093] Accordingly, in specific implementation, the server can obtain the target transaction package and related information of the target transaction package by parsing the target sample screening request; at the same time, extract and determine the target business category based on the category indication parameter in the request header.

[0094] Furthermore, the relevant transaction business data may be determined based on the target transaction package and the relevant information of the target transaction package, with a corresponding transaction identifier.

[0095] In addition, the above-mentioned target sample screening request may also carry the user's customized parameters, so that the user's customized parameters can be introduced and combined for sample business data screening in the future to meet the user's diverse individual needs.

[0096] In some embodiments, during specific implementation, a matching processing rule may be determined from the first preset processing rule and the second preset processing rule according to the target service category as the target processing rule.

[0097] In some embodiments, when the target business category is a discount business, the target processing rule may specifically be a first preset processing rule based on the discount business;

[0098] Correspondingly, according to the target processing rules, the institution information table, the bill information table, the transaction and bill association table, and the discount behavior table can be obtained from the system database as the target initial table set.

[0099] In some embodiments, when the target business category is a rediscount business, the target processing rule is a second preset processing rule based on the rediscount business;

[0100] Correspondingly, according to the target processing rules, the institution information table, the bill information table, the transaction and bill association table, and the rediscount behavior table can be obtained from the system database as the target initial table set.

[0101] Based on the above embodiments, different business categories can be effectively distinguished and matching target processing rules can be selected; at the same time, matching business data information tables can be selected and used for combination to obtain corresponding target initial tables.

[0102] In some embodiments, see Figure 4 As shown, in the case where the target business category is a discount business, the above-mentioned determination of the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set may include the following contents during specific implementation:

[0103] S1: determining, according to a target transaction package and relevant information of the target transaction package, a plurality of initial transaction business data and a plurality of initial transaction identifiers corresponding to the plurality of initial transaction business data;

[0104] S2: Matching the transaction identifiers using the initial transaction identifier and the rediscount behavior table, determining the initial transaction identifier that matches successfully as the target transaction identifier; and screening the target transaction business data involving the rediscount behavior from the multiple initial transaction business data according to the target transaction identifier;

[0105] S3: According to the target transaction identifier, query the transaction and bill association table to determine the bill identifier of the target transaction bill associated with the target transaction business data;

[0106] S4: According to the bill identifier of the target transaction bill, query the bill information table to obtain the corresponding bill information of multiple target transaction bills.

[0107] For the rediscount business, the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package can be determined according to the target initial table set in a similar manner as described above.

[0108] Specifically, the determined bill information and target transaction business data of the target transaction bill may be cached in a temporary table for subsequent reading and use.

[0109] Based on the above embodiments, the bill information and target transaction business data of the target transaction bill associated with the target transaction bill business curve can be obtained more efficiently and comprehensively.

[0110] In some embodiments, see Figure 5 As shown, for the discount business, the above detection and processing of interference sample data in the target transaction business data according to the target processing rules and the bill information of the target transaction bill, to obtain target sample business data that meets the requirements, may include the following contents during specific implementation:

[0111] S1: According to the first preset processing rule, the bill denomination, acceptor information, and bill category of the target transaction bill are combined to determine the characteristic combination type of the target transaction business data;

[0112] S2: According to the characteristic combination type of the target transaction business data, query the preset curve basic table to obtain the corresponding target curve basic parameters; wherein the preset curve basic table stores a plurality of preset curve basic parameters corresponding to a plurality of characteristic combination types;

[0113] S3: According to the first preset processing rule and the target curve basic parameters, detect whether there is a first type of interference sample data in the target transaction business data; wherein the first type of interference sample data includes at least one of the following: transaction business data whose amount ratio does not meet the requirements, transaction business data whose term difference does not meet the requirements, and transaction business data whose deviation does not meet the requirements;

[0114] S4: When it is determined that the target transaction business data contains the first type of interference sample data, the first type of interference sample data is eliminated to obtain target sample business data that meets the requirements.

[0115] Based on the above embodiment, for the discount business, according to the first preset processing rule, the first type of interference sample data can be accurately and quickly detected and identified from a large amount of target transaction business data, so as to screen out the target sample business data suitable for constructing the target transaction bill business curve of this business category.

[0116] Specifically, for discount business, the above-mentioned characteristic combination type may be a combination of the acceptor's credit rating parameter (a kind of acceptor information) and the bill category, for example, AAA+ bank bill.

[0117] The above AAA can be understood as a credit rating parameter of the acceptor. Generally, for the acceptor, its credit rating parameter set can specifically include the following multiple levels: AAA, AA, A, B, C.

[0118] In specific implementation, the bill denomination, credit rating parameters of the acceptor, and bill category of the target transaction bill can be first extracted from the bill information of the target transaction bill according to the first preset processing rule; then the ratio of the local bill denomination of different combinations of the acceptor's credit rating parameters and bill categories to the total bill denomination of the target transaction bill can be calculated to obtain the proportion of the bill amount of each combination; then, the combination with the largest proportion value is selected from multiple combinations as the corresponding feature combination type (for example, AAA+silver bill).

[0119] In addition, in some cases, according to the first preset processing rule, after extracting the bill denomination, the credit rating parameters of the acceptor, and the bill category of the target transaction bill from the bill information of the target transaction bill, the total bill denomination of the target transaction bill, the partial bill denomination of the target transaction bill corresponding to the credit rating parameters of different types of acceptors, and the partial bill denomination of the target transaction bill corresponding to different bill categories can be counted first; then, by calculating the partial bill denomination of the target transaction bill corresponding to the credit rating parameters of different types of acceptors and the total bill denomination of the target transaction bill, the amount ratio of the credit rating parameters of various types of acceptors can be obtained. At the same time, by calculating the partial bill denomination of the target transaction bill corresponding to different bill categories and the total bill denomination of the target transaction bill, the amount ratio of each bill category can be obtained; finally, the credit rating parameter of the acceptor corresponding to the largest amount ratio is screened out from the amount ratios of the credit rating parameters of multiple acceptors, and the bill category with the largest value is screened out from the amount ratios of multiple bill categories, and they are combined according to the corresponding combination identifiers to obtain the corresponding feature combination type.

[0120] In this way, the feature combination type that is highly representative of the target transaction business data can be accurately determined, and then according to the above feature combination type, the preset curve basic table can be queried to distinguish different feature combination types, and find the corresponding preset curve basic parameters as the target curve basic parameters, so that the first type of interference sample data can be accurately detected and identified in the subsequent processing according to the first preset processing rule and using the target curve basic parameters as a reference standard.

[0121] Specifically, the found basic parameters of the target curve may be cached in an intermediate table for subsequent reading and use.

[0122] During specific implementation, according to the first preset processing rule and the target curve basic parameters, it can be detected in the following manner whether there is transaction business data in the target transaction business data whose amount ratio does not meet the requirements: detect whether the amount ratio of each target transaction business data in the target transaction data to the total bill face value of the target transaction bill is less than the amount ratio threshold in the target curve basic parameters; if so, the target transaction business data is determined as transaction business data whose amount ratio does not meet the requirements, that is, a first type of interference sample data (which can be recorded as first type of interference sample data 1).

[0123] In specific implementation, according to the first preset processing rule and the target curve basic parameters, it can be detected in the following manner whether there is transaction business data in the target transaction business data whose term difference does not meet the requirements: obtain the maturity date of each transaction bill involved in the target transaction business data, and screen out the maturity date closest to the current time and the maturity date longest from the current time, which are recorded as the first maturity date and the second maturity date respectively; then calculate the term difference between the second maturity date and the first maturity date; and detect whether the term difference is greater than the term difference threshold in the target curve basic parameters; if so, determine the target transaction business data as transaction business data whose term difference does not meet the requirements, that is, another type of first-class interference sample data (which can be recorded as first-class interference sample data 2).

[0124] In specific implementation, according to the first preset processing rule and the target curve basic parameters, whether there is transaction business data whose deviation does not meet the requirements in the target transaction business data can be detected in the following manner: according to the characteristic combination type of the target transaction business data, the corresponding linear segmentation configuration parameters are determined from the linear segmentation configuration table; according to the linear segmentation configuration parameters, the weighted average remaining term of the transaction bills in the target transaction business data is matched according to the starting endpoint and the ending endpoint of each segment to obtain the segment corresponding to the target transaction business data; then, according to the target transaction business data, the local transaction business data falling into each segment is determined and used. The mean discount rate of the data is used to calculate the standard deviation of the corresponding segment; then the standard deviation multiples of the deviation in the basic parameters of the target curve are queried; the product of the standard deviation of each segment and the standard deviation multiple is calculated to obtain the deviation critical value of each segment; then the deviation critical value is used to detect whether the difference between the discount rate of each segment in the target transaction business data and the mean discount rate is greater than the deviation critical value; if so, the segmented business data in the target transaction business data is determined as transaction business data whose deviation does not meet the requirements, that is, another type of first-class interference sample data (which can be recorded as first-class interference sample data 3).

[0125] In some embodiments, after detecting and identifying the first type of interference sample data in the target transaction business data in the above manner, the first type of interference sample data can be removed from the target transaction business data, and the target sample business data that meets the requirements can be screened and retained.

[0126] In specific implementation, the first type of interference sample data 1 and the first type of interference sample data 2 in the target transaction business data can be detected and eliminated to obtain the processed target transaction business data; then based on the processed target transaction business data, the first type of interference sample data 3 can be detected and eliminated. In this way, the amount of data processing when detecting and processing the first type of interference sample data 3 can be effectively reduced, and the overall data processing efficiency can be improved.

[0127] In addition, after the first type of interference sample data 3 is removed from the target transaction business data and the target sample business data is obtained, the above process can be repeated to perform the second and third rounds of detection and processing on the first type of interference sample data 3 on the target sample business data. In this way, target sample business data with relatively better effect and relatively smaller error can be obtained.

[0128] In some embodiments, for the conversion discount business, the above-mentioned detection and processing of interference sample data in the target transaction business data according to the target processing rules and the bill information of the target transaction bill to obtain target sample business data that meets the requirements may include the following contents during specific implementation:

[0129] S1: According to the second preset processing rule, the bill denomination, acceptor information, discounter information, and bill category of the target transaction bill are combined to determine the characteristic combination type of the target transaction business data;

[0130] S2: According to the characteristic combination type of the target transaction business data, query the preset curve basic table to obtain the corresponding target curve basic parameters; wherein the preset curve basic table stores a plurality of preset curve basic parameters corresponding to a plurality of characteristic combination types;

[0131] S3: According to the second preset processing rule and the target curve basic parameters, detect whether there is a second type of interference sample data in the target transaction business data; wherein the second type of interference sample data includes at least one of the following: transaction business data whose amount ratio does not meet the requirements, transaction business data whose term difference does not meet the requirements, transaction business data whose deviation does not meet the requirements, internal transaction business data, arbitrage transaction business data, and bridge transaction business data;

[0132] S4: When it is determined that the target transaction business data contains the second type of interference sample data, the second type of interference sample data is eliminated to obtain the target sample business data that meets the requirements.

[0133] Based on the above embodiment, for the rediscount business, according to the second preset processing rule, the second type of interference sample data can be accurately and quickly detected and identified from a large amount of target transaction business data, so as to screen out the target sample business data suitable for constructing the target transaction bill business curve of this business category.

[0134] In specific implementation, the bill denomination, credit rating parameters of the acceptor, credit rating parameters of the discounter, and bill category of the target transaction bill can be first extracted from the bill information of the target transaction bill according to the second preset processing rule; then the ratio of the local bill denomination of different combinations of the acceptor's credit rating parameters, the discounter's credit rating parameters and the bill category to the total bill denomination of the target transaction bill can be calculated to obtain the proportion of the bill amount of each combination; then, the combination with the largest proportion value is selected from multiple combinations as the corresponding feature combination type (for example, AAA+non-AAA+bank bill).

[0135] In specific implementation, according to the second preset processing rule, it can be detected in the following manner whether there is internal transaction business data in the target transaction business data: according to the second preset processing rule, locate and extract the corresponding internal and external transaction indication field in the identification field of the target transaction business data; detect whether the internal and external transaction indication field indicates an internal transaction; if so, determine the target transaction business data as internal transaction business data, that is, a second type of interference sample data.

[0136] During specific implementation, according to the second preset processing rule, it can be detected in the following manner whether there is back-to-back transaction business data in the target transaction business data: according to the second preset processing rule, first use the bill information of the target transaction bill to screen out two target transaction business data involving the same batch of target transaction bills (for example, the total bill amount of the transactions involved is the same, the weighted average remaining term is the same, and the transaction date is the same), and record them as the first candidate transaction business data and the second candidate transaction business data respectively; detect whether the receiving object of the first candidate transaction business data is the same as the initiating object of the second candidate transaction business data, and whether the initiating object of the first candidate transaction business data is the same as the receiving object of the second candidate transaction business data; if both are the same, then the above-mentioned first candidate transaction business data and the second candidate transaction business data are determined as corresponding back-to-back transaction business data, that is, another type of second interference sample data.

[0137] In specific implementation, according to the second preset processing rule, whether there is bridge transaction business data in the target transaction business data can be detected in the following manner: according to the second preset processing rule, first use the bill information of the target transaction bill to screen out two target transaction business data involving the same batch of target transaction bills, and record them as the first candidate transaction business data and the second candidate transaction business data respectively; then, according to the initiating object and receiving object of the first candidate transaction business data, and the initiating object and receiving object of the second candidate transaction business data, determine whether there is a continuation relationship between the first candidate transaction business data and the second candidate transaction business data. Specifically, if the initiating object of the first candidate transaction business data is the same as the receiving object of the second candidate transaction business data, and the initiating object of the second candidate transaction business data is different from the receiving object of the first candidate transaction business data; or, the receiving object of the first candidate transaction business data is the same as the initiating object of the second candidate transaction business data, and the receiving object of the second candidate transaction business data is different from the initiating object of the first candidate transaction business data, then it is determined that there is a continuation relationship. If the first candidate transaction business data and the second candidate transaction business data have a succession relationship, the rediscount rate spread of the two transactions can be calculated based on the above-mentioned first candidate transaction business data and the second candidate transaction business data, and it can be detected whether the rediscount rate spread is greater than the spread critical threshold in the target curve basic parameters; if so, the above-mentioned first candidate transaction business data and the second candidate transaction business data can be determined as corresponding bridge transaction business data, that is, another second type of interference sample data.

[0138] During specific implementation, according to detecting and processing the transaction business data whose amount ratio in the target transaction business data does not meet the requirements, the transaction business data whose term difference does not meet the requirements, and the transaction business data whose deviation does not meet the requirements, you can refer to the above-mentioned relevant embodiments for the discount business, and this specification will not go into details.

[0139] In some embodiments, after detecting and processing the interference sample data in the target transaction business data in the above manner to obtain the target sample business data that meets the requirements, a corresponding target transaction bill business curve can also be generated based on the target sample business data.

[0140] In specific implementation, the linear segmentation configuration table can be queried according to the characteristic combination type of the target transaction business data to determine the matching target linear segmentation configuration parameters; then, according to the target linear segmentation configuration parameters, the segmentation key term points are determined in the target sample business data; other scatter points with term as the horizontal axis are determined according to the target sample business data, and the segmentation key term points and scatter points are divided into multiple segments according to the linear segmentation configuration table; then, linear regression is performed on the data in each segment to obtain the yield of each segmentation key term point; then, based on the yield of each segmentation key term, the corresponding segmentation fitting model (for example, the Hermite fitting model) is used to perform curve fitting to calculate the yield of other term points; then, the yields of the above term points are combined and used to fit the required target transaction bill business curve.

[0141] In some embodiments, after obtaining the target transaction bill business curve, the target transaction bill business curve can also be used to analyze and determine changes in relevant data of the target transaction bill at various key time points in history, and / or changes in relevant data in a future time period.

[0142] In addition, the target transaction bill business curve can be used to determine whether the target transaction business data involving the target transaction bill has relevant transaction risks by analyzing and following the changing trend of relevant data.

[0143] Therefore, the target transaction bill business curve can be used to provide an effective reference for the user's operations.

[0144] As can be seen from the above, based on the data processing method based on transaction bills provided in the embodiment of this specification, after obtaining the target sample screening request, the target business category can be determined first according to the target sample screening request involving the transaction bill; then, according to the target business category, the corresponding target initial table set is determined and obtained from the system database according to the matching target processing rules; then, according to the target initial table set, the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package are determined; according to the target processing rules and the bill information of the target transaction bill, the interference sample data in the target transaction business data is detected and processed to obtain the target sample business data suitable for generating the corresponding target transaction bill business curve. Thus, it can be better adapted to the transaction business scenario based on big data, and by distinguishing different business categories, it can automatically and efficiently screen out the target sample business data that meets the requirements, so that the target sample business data can be used to generate the target transaction bill business curve with high reference value and small error for users in the future.

[0145] This specification embodiment provides a server, referring to Figure 6The server includes a network communication port 601, a processor 602 and a memory 603, and the above structures are connected through internal cables so that each structure can perform specific data interaction.

[0146] The network communication port 601 may be used to obtain a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and relevant information of the target transaction package; the transaction indicated by the target transaction package is related to the transaction bill;

[0147] The processor 602 can be specifically used to determine the target business category based on the target sample screening request; wherein the target business category includes: discount business or rediscount business; according to the target business category, determine the matching target processing rule; and according to the target processing rule, obtain the corresponding target initial table set from the system database; according to the target initial table set, determine the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package; according to the target processing rule and the bill information of the target transaction bill, detect and process the interference sample data in the target transaction business data to obtain the target sample business data that meets the requirements; wherein the target sample business data is used to generate the target transaction bill business curve.

[0148] The memory 603 may be specifically used to store corresponding instruction programs, as well as relevant data such as the bill information of the target transaction bill, the target transaction business data, etc.

[0149] Based on the above method, the relevant structural performance of the server can be effectively utilized, the data processing speed of the electronic device can be improved, and data processing based on transaction tickets can be efficiently realized.

[0150] In this embodiment, the network communication port 601 can be a virtual port that is bound to different communication protocols so that different data can be sent or received. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. In addition, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM, CDMA, etc.; it can also be a Wifi chip; it can also be a Bluetooth chip.

[0151] In this embodiment, the processor 602 may be implemented in any appropriate manner. For example, the processor may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) executable by the (micro)processor, a logic gate, a switch, an application specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, etc. This specification does not limit this.

[0152] In this embodiment, the memory 603 may include multiple levels. In a digital system, anything that can store binary data can be a memory; in an integrated circuit, a circuit with a storage function but no physical form is also called a memory, such as RAM, FIFO, etc.; in a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0153] The embodiment of the present specification also provides a computer-readable storage medium based on the above-mentioned transaction bill-based data processing method, the computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed, it realizes: obtaining a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and related information of the target transaction package; the transaction indicated by the target transaction package is related to the transaction bill; determining a target business category according to the target sample screening request; wherein the target business category includes: discount business or rediscount business; determining a matching target processing rule according to the target business category; and obtaining a corresponding target initial table set from a system database according to the target processing rule; determining the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set; detecting and processing interference sample data in the target transaction business data according to the target processing rule and the bill information of the target transaction bill, and obtaining target sample business data that meets the requirements; wherein the target sample business data is used to generate a target transaction bill business curve.

[0154] In this embodiment, the storage medium includes, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a cache, a hard disk (HDD), or a memory card. The memory may be used to store computer program instructions. The network communication unit may be an interface for network connection communication set in accordance with the standard specified by the communication protocol.

[0155] In this embodiment, the functions and effects specifically implemented by the program instructions stored in the computer-readable storage medium can be explained in comparison with other implementations and will not be described in detail here.

[0156] The embodiments of the present specification also provide a computer program product, which at least includes a computer program, and when the computer program is executed by a processor, it implements the following method steps: obtaining a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and related information of the target transaction package; the transaction indicated by the target transaction package is related to the transaction bill; determining a target business category according to the target sample screening request; wherein the target business category includes: discount business or rediscount business; determining a matching target processing rule according to the target business category; and obtaining a corresponding target initial table set from a system database according to the target processing rule; determining the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set; detecting and processing interference sample data in the target transaction business data according to the target processing rule and the bill information of the target transaction bill to obtain target sample business data that meets the requirements; wherein the target sample business data is used to generate a target transaction bill business curve.

[0157] See also Figure 7 As shown, the embodiment of this specification also provides a data processing device based on transaction notes, which may specifically include the following structural modules:

[0158] The first acquisition module 701 may be specifically used to acquire a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and relevant information of the target transaction package; and the transaction indicated by the target transaction package is related to the transaction bill;

[0159] The first determination module 702 may be specifically configured to determine a target business category according to a target sample screening request; wherein the target business category includes: a discount business or a rediscount business;

[0160] The second acquisition module 703 may be specifically used to determine a matching target processing rule according to the target business category; and obtain a corresponding target initial table set from the system database according to the target processing rule;

[0161] The second determination module 704 may be specifically configured to determine the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set;

[0162] The processing module 705 can be specifically used to detect and process interference sample data in the target transaction business data according to the target processing rules and the bill information of the target transaction bill, and obtain target sample business data that meets the requirements; wherein the target sample business data is used to generate the target transaction bill business curve.

[0163] In some embodiments, the bill information may include at least one of the following: bill denomination, acceptor information, issuer information, bill category, bill expiration date, discounter information, etc.;

[0164] The bill types may include at least one of the following: bank bills, commercial bills, financial bills, etc.

[0165] In some embodiments, when the target business category is a discount business, the target processing rule may specifically be a first preset processing rule based on the discount business;

[0166] Accordingly, when the second acquisition module 703 is implemented, the institution information table, bill information table, transaction and bill association table, and discount behavior table can be acquired from the system database as the target initial table set according to the target processing rule.

[0167] In some embodiments, when the target business category is a rediscount business, the target processing rule may be a second preset processing rule based on the rediscount business;

[0168] Accordingly, when the second acquisition module 703 is implemented, the institution information table, the bill information table, the transaction and bill association table, and the rediscount behavior table can be obtained from the system database as the target initial table set according to the target processing rule.

[0169] In some embodiments, when the target business category is a discount business, when the above-mentioned second determination module 704 is specifically implemented, the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package can be determined according to the target initial table set in the following manner: according to the target transaction package and the relevant information of the target transaction package, multiple initial transaction business data and multiple initial transaction identifiers corresponding to the multiple initial transaction business data are determined; the transaction identifier is matched using the initial transaction identifier and the rediscount behavior table, and the initial transaction identifier that matches successfully is determined as the target transaction identifier; and according to the target transaction identifier, the target transaction business data involving the rediscount behavior is screened out from the multiple initial transaction business data; according to the target transaction identifier, the transaction and bill association table is queried to determine the bill identifier of the target transaction bill associated with the target transaction business data; according to the bill identifier of the target transaction bill, the bill information table is queried to obtain the bill information of the corresponding multiple target transaction bills.

[0170] In some embodiments, when the above-mentioned processing module 705 is specifically implemented, the interference sample data in the target transaction business data can be detected and processed according to the target processing rules and the bill information of the target transaction bill in the following manner to obtain the target sample business data that meets the requirements: according to the first preset processing rule, the bill denomination, acceptor information, and bill category of the target transaction bill are combined to determine the characteristic combination type of the target transaction business data; according to the characteristic combination type of the target transaction business data, the preset curve basic table is queried to obtain the corresponding target curve basic parameters; wherein the preset curve basic table stores a plurality of preset curve basic parameters corresponding to the plurality of characteristic combination types; according to the first preset processing rule and the target curve basic parameters, it is detected whether there is a first type of interference sample data in the target transaction business data; wherein the first type of interference sample data includes at least one of the following: transaction business data whose amount ratio does not meet the requirements, transaction business data whose term difference does not meet the requirements, and transaction business data whose deviation does not meet the requirements; when it is determined that the first type of interference sample data exists in the target transaction business data, the first type of interference sample data is eliminated to obtain the target sample business data that meets the requirements.

[0171] In some embodiments, when the above-mentioned processing module 705 is specifically implemented, the interference sample data in the target transaction business data can be detected and processed according to the target processing rules and the bill information of the target transaction bill in the following manner to obtain the target sample business data that meets the requirements: according to the second preset processing rule, the bill denomination, acceptor information, discounter information, and bill category of the target transaction bill are combined to determine the characteristic combination type of the target transaction business data; according to the characteristic combination type of the target transaction business data, the preset curve basic table is queried to obtain the corresponding target curve basic parameters; wherein the preset curve basic table stores a plurality of preset curve basic parameters corresponding to the plurality of characteristic combination types; according to the second preset processing rule and the target curve basic parameters, whether there is a second type of interference sample data in the target transaction business data; wherein the second type of interference sample data includes at least one of the following: transaction business data whose amount ratio does not meet the requirements, transaction business data whose term difference does not meet the requirements, transaction business data whose deviation does not meet the requirements, internal transaction business data, back-to-back transaction business data, and bridge transaction business data; when it is determined that the second type of interference sample data exists in the target transaction business data, the second type of interference sample data is eliminated to obtain the target sample business data that meets the requirements.

[0172] It should be noted that the units, devices or modules described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above devices are described separately by functions divided into various modules. Of course, when implementing this specification, the functions of each module can be implemented in the same or more software and / or hardware, or the modules that implement the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0173] It can be seen from the above that the data processing device based on transaction notes provided in the embodiment of this specification can be better adapted to transaction business scenarios based on big data. By distinguishing different business categories, it can automatically and efficiently screen out target sample business data that meets the requirements, so that the above-mentioned target sample business data can be used to generate a target transaction note business curve with higher reference value and smaller error for users.

[0174] Although the present specification provides method operation steps as described in the embodiments or flow charts, more or less operation steps may be included based on conventional or non-creative means. The order of steps listed in the embodiments is only one way of executing the order of many steps, and does not represent a unique execution order. When the device or client product in practice is executed, it can be executed in sequence or in parallel according to the method shown in the embodiments or the drawings (for example, a parallel processor or a multi-threaded processing environment, or even a distributed data processing environment). The term "include", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, product or device including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such a process, method, product or device. In the absence of more restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or device including the elements. The first, second, etc. words are used to represent the name, and do not represent any particular order.

[0175] Those skilled in the art also know that, in addition to implementing the controller in a purely computer-readable program code, the controller can be made to implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered as a hardware component, and the devices for implementing various functions included therein can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules for implementing the method and structures within the hardware component.

[0176] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer-readable storage media including storage devices.

[0177] Through the description of the above embodiments, it can be known that those skilled in the art can clearly understand that the present specification can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present specification can essentially be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods described in each embodiment of the present specification or some parts of the embodiments.

[0178] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. This specification can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0179] Although the present specification is described through embodiments, those skilled in the art will appreciate that there are many modifications and changes to the present specification without departing from the spirit of the present specification, and it is intended that the appended claims include these modifications and changes without departing from the spirit of the present specification.

Claims

1. A data processing method based on transaction notes, characterized in that: include: Obtaining a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and relevant information of the target transaction package; the transaction indicated by the target transaction package is related to the transaction bill; Determine a target business category according to the target sample screening request; wherein the target business category includes: discount business or rediscount business; According to the target business category, determine the matching target processing rules; and according to the target processing rules, obtain the corresponding target initial table set from the system database; Determine the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set; According to the target processing rules and the bill information of the target transaction bill, the interference sample data in the target transaction business data is detected and processed to obtain the target sample business data that meets the requirements; wherein the target sample business data is used to generate the target transaction bill business curve.

2. The method according to claim 1, characterized in that The bill information includes at least one of the following: bill denomination, acceptor information, drawee information, bill category, bill maturity date, and discounter information; The bill types include at least one of the following: bank bills, commercial bills, and financial bills.

3. The method according to claim 2, characterized in that In the case where the target business category is a discount business, the target processing rule is a first preset processing rule based on the discount business; Correspondingly, according to the target processing rules, the institution information table, the bill information table, the transaction and bill association table, and the discount behavior table are obtained from the system database as the target initial table set.

4. The method according to claim 2, characterized in that: In the case where the target business category is rediscount business, the target processing rule is a second preset processing rule based on the rediscount business; Correspondingly, according to the target processing rules, the institution information table, the bill information table, the transaction and bill association table, and the rediscount behavior table are obtained from the system database as the target initial table set.

5. The method according to claim 3, characterized in that: When the target business category is a discount business, the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package are determined according to the target initial table set, including: Determine, according to the target transaction package and relevant information of the target transaction package, a plurality of initial transaction business data and a plurality of initial transaction identifiers corresponding to the plurality of initial transaction business data; Using the initial transaction identifier and the rediscount behavior table to match the transaction identifier, determine the initial transaction identifier that matches successfully as the target transaction identifier; and based on the target transaction identifier, screen out the target transaction business data involving the rediscount behavior from the multiple initial transaction business data; According to the target transaction identifier, query the transaction and bill association table to determine the bill identifier of the target transaction bill associated with the target transaction business data; According to the bill identifier of the target transaction bill, the bill information table is queried to obtain the corresponding bill information of multiple target transaction bills.

6. The method according to claim 3, characterized in that According to the target processing rules and the bill information of the target transaction bill, the interference sample data in the target transaction business data is detected and processed to obtain the target sample business data that meets the requirements, including: According to the first preset processing rule, the note denomination, acceptor information, and note category of the target transaction note are combined to determine the characteristic combination type of the target transaction business data; According to the characteristic combination type of the target transaction business data, a preset curve basic table is queried to obtain the corresponding target curve basic parameters; wherein the preset curve basic table stores a plurality of preset curve basic parameters corresponding to the plurality of characteristic combination types; According to the first preset processing rule and the target curve basic parameters, detect whether there is a first type of interference sample data in the target transaction business data; wherein the first type of interference sample data includes at least one of the following: transaction business data whose amount ratio does not meet the requirements, transaction business data whose term difference does not meet the requirements, and transaction business data whose deviation does not meet the requirements; When it is determined that the target transaction business data contains the first type of interference sample data, the first type of interference sample data is eliminated to obtain the target sample business data that meets the requirements.

7. The method according to claim 4, characterized in that According to the target processing rules and the bill information of the target transaction bill, the interference sample data in the target transaction business data is detected and processed to obtain the target sample business data that meets the requirements, including: According to the second preset processing rule, the bill denomination, acceptor information, discounter information, and bill category of the target transaction bill are combined to determine the characteristic combination type of the target transaction business data; According to the characteristic combination type of the target transaction business data, a preset curve basic table is queried to obtain the corresponding target curve basic parameters; wherein the preset curve basic table stores a plurality of preset curve basic parameters corresponding to the plurality of characteristic combination types; According to the second preset processing rule and the target curve basic parameters, detect whether there is a second type of interference sample data in the target transaction business data; wherein the second type of interference sample data includes at least one of the following: transaction business data whose amount ratio does not meet the requirements, transaction business data whose term difference does not meet the requirements, transaction business data whose deviation does not meet the requirements, internal transaction business data, arbitrage transaction business data, and bridge transaction business data; When it is determined that the target transaction business data contains the second type of interference sample data, the second type of interference sample data is eliminated to obtain the target sample business data that meets the requirements.

8. A data processing device based on transaction notes, characterized in that: include: A first acquisition module is used to acquire a target sample screening request for a target transaction bill business curve; wherein the target sample screening request carries at least a target transaction package and relevant information of the target transaction package; and the transaction indicated by the target transaction package is related to the transaction bill; A first determination module is used to determine a target business category according to a target sample screening request; wherein the target business category includes: a discount business or a rediscount business; The second acquisition module is used to determine the matching target processing rules according to the target business category; and obtain the corresponding target initial table set from the system database according to the target processing rules; A second determination module is used to determine the bill information and target transaction business data of the target transaction bill corresponding to the target transaction package according to the target initial table set; The processing module is used to detect and process the interference sample data in the target transaction business data according to the target processing rules and the bill information of the target transaction bill, and obtain the target sample business data that meets the requirements; wherein the target sample business data is used to generate the target transaction bill business curve.

9. A server, characterized in that: The method comprises a processor and a memory for storing processor-executable instructions, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the instructions.

10. A computer-readable storage medium, characterized in that: Computer instructions are stored thereon, and when the instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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