CN111783432A - Generation method and device of credit certificate examination key point list - Google Patents

Generation method and device of credit certificate examination key point list Download PDF

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CN111783432A
CN111783432A CN202010612015.9A CN202010612015A CN111783432A CN 111783432 A CN111783432 A CN 111783432A CN 202010612015 A CN202010612015 A CN 202010612015A CN 111783432 A CN111783432 A CN 111783432A
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credit
message
letter
rule base
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叶瑛锋
李伟良
王虹
康宏宇
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Industrial and Commercial Bank of China Ltd ICBC
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Abstract

The invention provides a method and a device for generating a credit card examination and examination key point list. The method comprises the following steps: acquiring a credit card message and a document examination rule base; identifying terms in the letter of credit message through natural language processing to obtain an identification result; and generating an examination order checking key point list according to the identification result and the examination order rule base. Based on the natural language processing technology, the invention carries out full-automatic and intelligent identification on the key points of the documentary credit examination, accurately identifies the key points of the examination, obtains a list of key points of the examination of the documentary credit examination, provides guidance for the follow-up document consistency examination and the document consistency examination, ensures that an importer can receive goods on schedule, and avoids transaction risks.

Description

Generation method and device of credit certificate examination key point list
Technical Field
The invention relates to the technical field of letter of credit examination and examination, in particular to a method and a device for generating a letter of credit examination and examination key point list.
Background
The documentary credit is the most widely used international trade payment mode, and the main collection mode of export trade in China is the documentary credit. The letter of credit examination refers to the legal action that the bank audits the documents such as freight documents, draft, commercial invoices, insurance documents, packing documents, origin certificates, and check certificates submitted by the beneficiary or legal holders of the letter of credit to determine whether the documents conform to the stipulations and requirements of the letter of credit. The credit card is independent of international goods buying and selling contracts and is a simple document service, when a bank processes the credit card service, the stipulation of the credit card is used as a unique basis, and the goods condition under the contract item is not asked, so the normal action of the credit card is determined by the document examination standard. The traditional bank mainly relies on the manual identification of the bank business personnel for examining the receipt of the letter of credit, so that the mistake of examining the receipt due to the professional skill and experience difference of the bank business personnel is easy to occur, the importer cannot receive goods according to the requirement of the contract, and the economic loss is generated.
Disclosure of Invention
The embodiment of the invention mainly aims to provide a method and a device for generating a key point list for the examination of a letter of credit examination, which ensure that the key point of the examination is identified, provide the reference of the examination for a teller and reduce the trade risk of an importer.
In order to achieve the above object, an embodiment of the present invention provides a method for generating a bill of credit examination and checking gist list, where the method includes:
acquiring a credit card message and a document examination rule base;
identifying terms in the letter of credit message through natural language processing to obtain an identification result;
and generating an examination order checking key point list according to the identification result and the examination order rule base.
Optionally, in an embodiment of the present invention, the method further includes: collecting international convention information and expert experience information; carrying out standardization processing on the international convention information and the expert experience information; and integrating the standardized international routine information and the expert experience information into an examination rule base.
Optionally, in an embodiment of the present invention, the identifying, through natural language processing, a term in the letter of credit message to obtain an identification result includes: carrying out data preprocessing on the credit message; and identifying the preprocessed credit card message by using an identification model to obtain an identification result.
Optionally, in an embodiment of the present invention, the performing data preprocessing on the credit message includes: and segmenting the sentences in the letter of credit message according to the separators.
Optionally, in an embodiment of the present invention, the generating a list of examination order checking points according to the identification result and the examination order rule base includes: and integrating the identification result and the rules in the examination order rule base to generate an examination order checking key point list.
The embodiment of the invention also provides a device for generating the letter-of-credit examination and checking gist list, which comprises the following components:
the data acquisition module is used for acquiring the credit card message and the examination rule base;
the clause identification module is used for identifying clauses in the letter of credit message through natural language processing to obtain an identification result;
and the list generating module is used for generating a list of examination order checking key points according to the identification result and the examination order rule base.
Optionally, in an embodiment of the present invention, the apparatus further includes: the rule generating module is used for acquiring international routine information and expert experience information; carrying out standardization processing on the international convention information and the expert experience information; and integrating the standardized international routine information and the expert experience information into an examination rule base.
Optionally, in an embodiment of the present invention, the clause identifying module includes: the preprocessing unit is used for preprocessing the data of the credit card message; and the clause identification unit is used for identifying the preprocessed credit card message by using the identification model to obtain an identification result.
Optionally, in an embodiment of the present invention, the preprocessing unit is specifically configured to segment the sentence in the letter of credit message according to the separator.
Optionally, in an embodiment of the present invention, the list generating module is specifically configured to integrate the identification result and the rule in the examination order rule base, and generate an examination order checking key point list.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the program.
The present invention also provides a computer-readable storage medium storing a computer program for executing the above method.
Based on the natural language processing technology, the invention carries out full-automatic and intelligent identification on the key points of the documentary credit examination, accurately identifies the key points of the examination, obtains a list of key points of the examination of the documentary credit examination, provides guidance for the follow-up document consistency examination and the document consistency examination, ensures that an importer can receive goods on schedule, and avoids transaction risks.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flowchart of a method for generating a letter of credit examination and checking gist list according to an embodiment of the present invention;
FIG. 2 is a flow chart of generating an examination rule base in an embodiment of the present invention;
FIG. 3 is a flow chart of identifying the terms of a letter of credit message in an embodiment of the invention;
FIG. 4 is a schematic diagram of a processing flow of a bidirectional LSTM-CRF model according to an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating the principle of the generation of the document of credit approval in an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of an apparatus for generating a letter-of-credit examination and checking gist list according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a method and a device for generating a credit certificate examination and examination key point list.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart illustrating a method for generating a list of document of credit examination essences according to an embodiment of the present invention, where the method includes:
and step S1, obtaining the letter of credit message and the examination rule base.
Specifically, after the import letter of credit is opened, for the letter of credit, the terms are embodied in the messages SWIFT700 and 701, for the letter of credit, the terms are embodied in the letter of credit text, the SWIFT message and the letter of credit text are used as the input letter of credit message to identify the letter of credit terms, and the information contained in the message is shown in table 1.
TABLE 1
Figure BDA0002562380370000041
In addition, an examination rule base can be formed by collecting international practice and expert experience and according to credit card terms, the type of the examined document, the checking method and the like corresponding to the examination document.
And step S2, identifying the clauses in the letter of credit message through natural language processing to obtain an identification result.
Specifically, when the input letter of credit message is 700/701 message, if the clause content is 43P, 44C, 32B and other message items of non-large text, the clause content is directly intercepted to complete clause identification. When the input letter of credit message is 700/701 message, if the clause content is 45A, 46A, 47A, etc. message item of large text, it needs to identify the specific clause entity content contained in the large text through natural language processing, and check whether the entity corresponding to the rule is contained.
The natural language processing process for the large text information comprises the following steps:
data preprocessing: the method comprises the steps of firstly segmenting sentences of large texts, and then segmenting the sentences, wherein the international business texts are all English, so that data preprocessing can be realized according to separators such as punctuations, spaces and the like.
Model identification: the model adopted is a bidirectional LSTM-CRF model, and the preprocessed data are identified to obtain corresponding identification results.
And step S3, generating an examination order checking point list according to the identification result and the examination order rule base.
And processing item by item according to rules in the examination bill rule base, and forming an examination bill checking key point list by the identification result of the credit card terms and the examination bill rules.
As an embodiment of the present invention, as shown in fig. 2, the process of generating the examination-order rule base specifically includes:
and step S21, collecting international routine information and expert experience information.
The international convention information and the expert experience information may be UCP600, ISBP, and expert examination experience.
And step S22, carrying out standardization processing on the international convention information and the expert experience information.
Specifically, the UCP600, the ISBP and the expert billing experience are abstracted to form a series of billing rules, as shown in table 2.
TABLE 2
Figure BDA0002562380370000051
And (3) standardizing the descriptive rules to form an examination order rule base which can be analyzed and identified by an examination order module, wherein the standardized rules are shown in a table 3.
TABLE 3
Figure BDA0002562380370000052
Figure BDA0002562380370000061
And step S23, integrating the standardized international convention information and expert experience information into an examination rule base.
As an embodiment of the present invention, as shown in fig. 3, the identifying the clause in the letter of credit message by natural language processing, and the obtaining the identification result includes:
and step S31, carrying out data preprocessing on the credit message.
In this embodiment, the data preprocessing the credit message includes: and segmenting the sentences in the letter of credit message according to the separators. The method comprises the steps of segmenting a sentence of a large text, and then segmenting the sentence, wherein the international business text is English, so that data preprocessing can be realized according to separators such as punctuations, spaces and the like.
And step S32, recognizing the preprocessed credit card message by using the recognition model to obtain a recognition result.
Wherein, the communication with the computer by using the natural language relates to the natural language processing. Natural language processing is the field of computer science, artificial intelligence, linguistics focusing on the direct interaction of computer and human language. The present training model for natural language processing and machine learning in the industry includes FastText, TextCNN, ULMFit, BERT, CRF, bidirectional LSTM-CRF, etc. the model adopted in the invention is bidirectional LSTM-CRF model, the combination of the Bi-LSTM and CRF model not only reuses the advantage that Bi-LSTM captures longer distance dependence relation according to the front and back sequence of words in sentences, but also can obtain globally optimal output sequence by using CRF, thus achieving the optimal effect of entity recognition. The schematic diagram of the bidirectional LSTM-CRF model is shown in FIG. 4, wherein B-Person in the base represents the first word of the name of a Person, I-Person represents the middle word of the name of the Person, B-organization represents the first word of the name of a institution, I-organization represents the middle word of the name of the institution, and O represents other entities.
Specifically, X ═ X (X) for each input1，x2，…，xn) Obtaining a predicted label sequence y ═ (y)1，y2，…，yn) Defining the score of this prediction as:
Figure BDA0002562380370000071
wherein,
Figure BDA0002562380370000072
output of softmax for the ith position as yiThe probability of (a) of (b) being,
Figure BDA0002562380370000074
is from yiTo yi+1When the number of tag (B-person, B-location) is n, the transition probability matrix is (n +2) × (n +2), because a start position and an end position are additionally added. The scoring function S well compensates for the deficiency of the conventional BiLSTM because when a predicted sequence has a high score, it is not the label corresponding to the maximum probability value output by softmax at every position, but it is also considered that the transition probability is added to the maximum, i.e. the output rule is met (B cannot be followed by B), for example, if the most likely sequence output by BiLSTM is bbibioo, because the transition probability matrix isMiddle B->B has a small or even negative probability, such sequences will not get the highest score, i.e. not the desired sequence, according to the s-score.
As an embodiment of the present invention, generating an examination order checking point list according to the recognition result and the examination order rule base includes: and integrating the identification result and the rules in the examination order rule base to generate an examination order checking key point list. The resulting partial order gist list is shown in table 4.
TABLE 4
Figure BDA0002562380370000073
Figure BDA0002562380370000081
IN a specific embodiment of THE present invention, FOR example, according to expert experience, whether THE number of copies of document and THE terms IN THE document examination process are consistent or not needs to be checked, THE experience is abstracted into a document examination rule to form a document examination rule base, which includes a document loading list copy number check rule, THE rule check entity is PACKING LIST (i.e. THE document loading list), THE message 46A is input into a natural language parsing module to perform entity recognition, THE PACKING LIST credit terms are extracted, and THE obtained term content "PACKINGLIST/WEIGHT MEMO IN 2 organic document inquiring quality/GROSS AND NET WEIGHTS authority PACKAGE AND PACKING CONDITIONS AS CALLED BY way L/C" generates THE key point of document examination shown IN table 4 AS PACKING LIST.
In an embodiment of the present invention, as shown in fig. 5, the process in the figure specifically includes:
1. establishing an examination rule base
Collecting international practice and expert experience, and forming a document examination rule base according to credit terms, audit document types, inspection methods and the like corresponding to the document examination.
2. Entering the terms of a letter of credit
After the import letter of credit is opened, for the letter of credit, the terms are embodied in SWIFT700 and 701 messages, for the letter of credit, the terms are embodied in a letter of credit text, and the document examination key point generation module needs to take the SWIFT message and the letter of credit text as input letter of credit messages to identify the letter of credit terms.
3. Generation of document review points
And identifying each clause of the letter of credit text through natural language processing, and generating a bill of examination key point list by combining an expert rule base.
(1) Rule parsing
And loading an expert rule base, and processing the rules one by one. And when the corresponding clause of the rule letter of credit is 'none', directly generating the key point of the examination order.
And when the corresponding clause of the regular letter of credit is not empty, calling a letter of credit clause library identification program to identify whether the letter of credit clause contains the entity corresponding to the rule check item.
(2) Credit card term identification
When the credit card terms need to be used in rule analysis, loading the key points of the examination order, processing the message or the credit card text source text by adopting a natural language, and extracting the information according to the following scenes:
(a) for the input of 700/701 messages, if the clause content is 43P, 44C, 32B and other message items with non-large texts, the clause content is obtained by directly intercepting.
(b) For the input of 700/701 message, if the clause content is 45A, 46A, 47A and other message items of large text, natural language processing needs to be adopted, the specific clause entity content contained in the large text is identified, and whether the entity corresponding to the rule is contained is checked.
(c) For letter certificate text, the text item is actually the same as the message input, and the processing mode is also the same as the message.
(3) Natural language processing
For the extraction of large text information, the natural language processing process is as follows:
(a) data preprocessing: the method comprises the steps of firstly segmenting sentences of large texts, and then segmenting the sentences, wherein the international business texts are all English, so that data preprocessing can be realized according to separators such as punctuations, spaces and the like.
(b) Model identification: the model adopted is a bidirectional LSTM-CRF model, and the preprocessed data are identified to obtain corresponding identification results.
Based on the natural language processing technology, the invention carries out full-automatic and intelligent identification on the key points of the documentary credit examination, accurately identifies the key points of the examination, obtains a list of key points of the examination of the documentary credit examination, provides guidance for the follow-up document consistency examination and the document consistency examination, ensures that an importer can receive goods on schedule, and avoids transaction risks.
Fig. 6 is a schematic structural diagram of an apparatus for generating a list of document of credit examination notes according to an embodiment of the present invention, where the apparatus includes:
and the data acquisition module 10 is used for acquiring the credit card message and the examination rule base.
Specifically, after the import letter of credit is opened, for the letter of credit, the terms are embodied in the messages SWIFT700 and 701, for the letter of credit, the terms are embodied in the letter of credit text, and the SWIFT message and the letter of credit text are used as the input letter of credit message to identify the letter of credit terms.
In addition, an examination rule base can be formed by collecting international practice and expert experience and according to credit card terms, the type of the examined document, the checking method and the like corresponding to the examination document.
And the clause identification module 20 is used for identifying the clauses in the letter of credit message through natural language processing to obtain an identification result.
Specifically, when the input letter of credit message is 700/701 message, if the clause content is 43P, 44C, 32B and other message items of non-large text, the clause content is directly intercepted to complete clause identification. When the input letter of credit message is 700/701 message, if the clause content is 45A, 46A, 47A, etc. message item of large text, it needs to identify the specific clause entity content contained in the large text through natural language processing, and check whether the entity corresponding to the rule is contained.
The natural language processing process for the large text information comprises the following steps:
data preprocessing: the method comprises the steps of firstly segmenting sentences of large texts, and then segmenting the sentences, wherein the international business texts are all English, so that data preprocessing can be realized according to separators such as punctuations, spaces and the like.
Model identification: the model adopted is a bidirectional LSTM-CRF model, and the preprocessed data are identified to obtain corresponding identification results.
And the list generating module 30 is configured to generate a list of examination order checking key points according to the identification result and the examination order rule base.
And processing item by item according to rules in the examination bill rule base, and forming an examination bill checking key point list by the identification result of the credit card terms and the examination bill rules.
As an embodiment of the present invention, the apparatus further comprises: the rule generating module is used for acquiring international routine information and expert experience information; carrying out standardization processing on the international convention information and the expert experience information; and integrating the standardized international routine information and the expert experience information into an examination rule base.
As an embodiment of the present invention, the clause identifying module includes: the preprocessing unit is used for preprocessing the data of the credit card message; and the clause identification unit is used for identifying the preprocessed credit card message by using the identification model to obtain an identification result.
In this embodiment, the preprocessing unit is specifically configured to segment the sentence in the letter of credit message according to the delimiter.
As an embodiment of the present invention, the list generating module is specifically configured to integrate the identification result and the rule in the examination order rule base to generate an examination order checking key point list.
Based on the same application concept as the method for generating the key point list for the letter-of-credit examination, the invention also provides a device for generating the key point list for the letter-of-credit examination. The principle of the device for generating the credit certificate examination key point list for solving the problems is similar to that of a method for generating the credit certificate examination key point list, so that the implementation of the device for generating the credit certificate examination key point list can refer to the implementation of the method for generating the credit certificate examination key point list, and repeated parts are not repeated.
Based on the natural language processing technology, the invention carries out full-automatic and intelligent identification on the key points of the documentary credit examination, accurately identifies the key points of the examination, obtains a list of key points of the examination of the documentary credit examination, provides guidance for the follow-up document consistency examination and the document consistency examination, ensures that an importer can receive goods on schedule, and avoids transaction risks.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the program.
The present invention also provides a computer-readable storage medium storing a computer program for executing the above method.
As shown in fig. 7, the electronic device 600 may further include: communication module 110, input unit 120, audio processing unit 130, display 160, power supply 170. It is noted that the electronic device 600 does not necessarily include all of the components shown in fig. 7; furthermore, the electronic device 600 may also comprise components not shown in fig. 7, which may be referred to in the prior art.
As shown in fig. 7, the central processor 100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, the central processor 100 receiving input and controlling the operation of the various components of the electronic device 600.
The memory 140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 100 may execute the program stored in the memory 140 to realize information storage or processing, etc.
The input unit 120 provides input to the cpu 100. The input unit 120 is, for example, a key or a touch input device. The power supply 170 is used to provide power to the electronic device 600. The display 160 is used to display an object to be displayed, such as an image or a character. The display may be, for example, an LCD display, but is not limited thereto.
The memory 140 may be a solid state memory such as Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 140 may also be some other type of device. Memory 140 includes buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application/function storage section 142, and the application/function storage section 142 is used to store application programs and function programs or a flow for executing the operation of the electronic device 600 by the central processing unit 100.
The memory 140 may also include a data store 143, the data store 143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by the electronic device. The driver storage portion 144 of the memory 140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging application, address book application, etc.).
The communication module 110 is a transmitter/receiver 110 that transmits and receives signals via an antenna 111. The communication module (transmitter/receiver) 110 is coupled to the central processor 100 to provide an input signal and receive an output signal, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132 to implement general telecommunications functions. Audio processor 130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, an audio processor 130 is also coupled to the central processor 100, so that recording on the local can be enabled through a microphone 132, and so that sound stored on the local can be played through a speaker 131.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (12)

1. A method for generating a letter of credit examination and checking gist list is characterized by comprising the following steps:
acquiring a credit card message and a document examination rule base;
identifying terms in the letter of credit message through natural language processing to obtain an identification result;
and generating an examination order checking key point list according to the identification result and the examination order rule base.
2. The method of claim 1, further comprising:
collecting international convention information and expert experience information;
carrying out standardization processing on the international convention information and the expert experience information;
and integrating the standardized international routine information and the expert experience information into an examination rule base.
3. The method of claim 1, wherein identifying the terms in the LC message through natural language processing to obtain the identification result comprises:
carrying out data preprocessing on the credit message;
and identifying the preprocessed credit card message by using an identification model to obtain an identification result.
4. The method of claim 3, wherein the pre-processing the credit message comprises: and segmenting the sentences in the letter of credit message according to the separators.
5. The method of claim 1, wherein generating a list of examination notes checking points based on the identification results and the examination rules library comprises: and integrating the identification result and the rules in the examination order rule base to generate an examination order checking key point list.
6. An apparatus for generating a list of letter of credit checks checking points, the apparatus comprising:
the data acquisition module is used for acquiring the credit card message and the examination rule base;
the clause identification module is used for identifying clauses in the letter of credit message through natural language processing to obtain an identification result;
and the list generating module is used for generating a list of examination order checking key points according to the identification result and the examination order rule base.
7. The apparatus of claim 6, further comprising: the rule generating module is used for acquiring international routine information and expert experience information; carrying out standardization processing on the international convention information and the expert experience information; and integrating the standardized international routine information and the expert experience information into an examination rule base.
8. The apparatus of claim 6, wherein the clause identification module comprises:
the preprocessing unit is used for preprocessing the data of the credit card message;
and the clause identification unit is used for identifying the preprocessed credit card message by using the identification model to obtain an identification result.
9. The apparatus according to claim 8, wherein the preprocessing unit is specifically configured to segment the sentence in the LC message according to a separator.
10. The apparatus of claim 6, wherein the manifest generation module is specifically configured to integrate the recognition results and the rules in the document examination rule base to generate a document examination and review gist manifest.
11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 5 when executing the program.
12. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 5.
CN202010612015.9A 2020-06-30 2020-06-30 Generation method and device of credit certificate examination key point list Pending CN111783432A (en)

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CN112801627A (en) * 2021-02-04 2021-05-14 台州银行股份有限公司 Credit document making and auditing method
CN113159932A (en) * 2021-05-14 2021-07-23 中国工商银行股份有限公司 Credit certificate verification data processing method and device based on block chain
CN114219443A (en) * 2021-12-16 2022-03-22 中国建设银行股份有限公司 Document data processing method, device and equipment
CN115049362A (en) * 2022-06-14 2022-09-13 中国建设银行股份有限公司 Auditing method and system for documentary credit

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CN112801627A (en) * 2021-02-04 2021-05-14 台州银行股份有限公司 Credit document making and auditing method
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