Anti-money laundering security processing method and device, electronic equipment and storage medium

Abstract

The invention provides an anti-money laundering preservation processing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining an execution letter document, and carrying out the scanning recognition of the execution letter document, and obtaining an execution letter document recognition text; performing semantic recognition on the executive document recognition text, and generating an executive application form corresponding to the executive document based on a semantic recognition result; and analyzing the execution application form, generating a preservation processing instruction for assets owned by the executed user, performing preservation processing according to the preservation processing instruction, and generating an execution result of the preservation processing. Compared with the prior art, according to the embodiment of the invention, the scanning recognition and semantic recognition of the execution letter document are automatically processed, so that the manual processing time can be shortened, and the processing efficiency can be remarkably improved; by means of automatic processing, errors and omissions possibly occurring in manual operation can be avoided, and the accuracy and uniformity of data are guaranteed.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to an anti-money laundering security processing method and device, electronic equipment and storage medium. Background Art

[0002] In the current anti-money laundering work, the important link of "checking and freezing" mainly relies on manual operation. Specifically, relevant information is collected manually and processed by email, telephone contact, etc., and the preservation work and the generation of execution result instructions are also completed manually. However, this traditional method has many disadvantages. First, each institution conducts "checking and freezing" statistics on its own, lacking unified standards and specifications, resulting in omissions and missing statistical data, and different data standards make it difficult to effectively integrate and analyze. Secondly, manual operation is not only complicated and cumbersome, inefficient, but also prone to errors, and cannot meet the strict requirements of accuracy and timeliness of anti-money laundering work. In addition, due to the lack of a complete automated process, the entire "checking and freezing" process is time-consuming and labor-intensive, seriously affecting the quality and efficiency of the work. Summary of the invention

[0003] The present invention provides a method and device for anti-money laundering security processing, an electronic device and a storage medium, and its main purpose is to solve the problem that the query, freezing, deduction and other operations in the current anti-money laundering work are performed manually.

[0004] According to a first aspect of the present disclosure, there is provided a method for anti-money laundering security processing, comprising:

[0005] Obtaining the execution letter document, and scanning and identifying the execution letter document to obtain the execution letter document identification text;

[0006] Performing semantic recognition on the recognized text of the execution letter document, and generating an execution application form corresponding to the execution letter document based on the semantic recognition result;

[0007] The execution application form is parsed to generate a preservation processing instruction for the assets owned by the executed user, and preservation processing is performed according to the preservation processing instruction to generate an execution result of the preservation processing.

[0008] Optionally, the performing semantic recognition on the recognized text of the execution letter document and generating an execution application form corresponding to the execution letter document based on the semantic recognition result includes:

[0009] Inputting the recognized text of the execution letter document into a semantic recognition model to perform semantic recognition to obtain a semantic text;

[0010] Parse the semantic text to determine the preservation processing type corresponding to the execution letter document, and search for the corresponding execution application template according to the preservation processing type, wherein the preservation processing type includes: query processing, freezing processing and deduction processing;

[0011] Based on the semantic information in the semantic text, the execution application template is filled to generate the execution application form, wherein the execution application form includes: a query application form, a freeze application form and a deduction application form.

[0012] Optionally, after performing semantic recognition on the recognized text of the execution letter document and generating an execution application form corresponding to the execution letter document based on the semantic recognition result, the method further includes:

[0013] In response to the execution application form verification instruction, check whether the execution application form meets the preset format, and modify the execution application form that does not meet the preset format.

[0014] Optionally, parsing the execution application form to generate a preservation instruction for the assets owned by the executed user includes:

[0015] Parsing the execution application form to obtain the preservation processing type corresponding to the execution application form and the information of the executed user in the execution application form;

[0016] The security processing instruction is generated based on the executed user information and the security processing type.

[0017] Optionally, the preservation item instruction includes: a query instruction, a freezing instruction and a deduction instruction;

[0018] The performing of the security processing according to the security processing instruction and generating the execution result of the security processing includes:

[0019] If the security processing instruction is the query instruction, querying the account information of the executed user based on the executed user information and generating a account record file, and generating the execution result based on the account record file;

[0020] If the preservation processing instruction is the freezing instruction, query the asset information of the executed user based on the executed user information, freeze the asset account of the executed user according to the freezing period in the execution application form, and generate the execution result;

[0021] If the preservation processing instruction is the deduction instruction, the assets owned by the executed user are deducted according to the deduction amount in the execution application form to generate the execution result.

[0022] Optionally, the method further includes:

[0023] The execution result and the execution application form are used to perform risk rating processing on the executed user to generate a risk assessment level of the executed user.

[0024] According to a second aspect of the present disclosure, there is provided an anti-money laundering security processing device, comprising:

[0025] A scanning unit, used to obtain an execution letter document, and scan and identify the execution letter document to obtain an execution letter document identification text;

[0026] A recognition unit, used for performing semantic recognition on the recognition text of the execution letter document, and generating an execution application form corresponding to the execution letter document based on the semantic recognition result;

[0027] The parsing unit is used to parse the execution application form, generate a preservation processing instruction for the assets owned by the executed user, perform preservation processing according to the preservation processing instruction, and generate an execution result of the preservation processing.

[0028] Optionally, the identification unit includes:

[0029] A recognition module, used for inputting the recognition text of the execution letter document into a semantic recognition model to obtain a semantic text;

[0030] A determination module is used to parse the semantic text, determine the preservation processing type corresponding to the execution letter document, and search for the corresponding execution application template according to the preservation processing type, wherein the preservation processing type includes: query processing, freezing processing and deduction processing;

[0031] The first generation module is used to fill in the execution application template based on the semantic information in the semantic text to generate the execution application form, wherein the execution application form includes: a query application form, a freeze application form and a deduction application form.

[0032] Optionally, the device further comprises:

[0033] A checking unit is used to check whether the execution application form meets the preset format in response to the execution application form verification instruction after the recognition unit performs semantic recognition on the execution letter document recognition text and generates an execution application form corresponding to the execution letter document based on the semantic recognition result, and to modify the execution application form that does not meet the preset format.

[0034] Optionally, the parsing unit includes:

[0035] A parsing module, used to parse the execution application form, obtain the preservation processing type corresponding to the execution application form and the executed user information in the execution application form;

[0036] The second generating module is used to generate the security processing instruction based on the executed user information and the security processing type.

[0037] Optionally, the preservation item instruction includes: a query instruction, a freezing instruction and a deduction instruction;

[0038] The parsing unit comprises:

[0039] A first execution module, configured to query the ledger information of the executed user based on the executed user information and generate a ledger record file when the security processing instruction is the query instruction, and generate the execution result based on the ledger record file;

[0040] A second execution module is used for, when the preservation processing instruction is the freezing instruction, querying the asset information of the executed user based on the executed user information, freezing the asset account of the executed user according to the freezing period in the execution application form, and generating the execution result;

[0041] The third execution module is used for deducting the assets owned by the executed user according to the deduction amount in the execution application form when the preservation processing instruction is the deduction instruction, and generating the execution result.

[0042] Optionally, the device further comprises:

[0043] The rating unit is used to use the execution result and the execution application form to perform risk rating processing on the executed user and generate a risk assessment level of the executed user.

[0044] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0045] at least one processor; and

[0046] a memory communicatively connected to the at least one processor; wherein,

[0047] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0048] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0049] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0050] The present disclosure provides a method and device for anti-money laundering preservation processing, an electronic device and a storage medium, which obtains an execution letter document, scans and identifies the execution letter document, obtains the execution letter document identification text; performs semantic identification on the execution letter document identification text, and generates an execution application form corresponding to the execution letter document based on the semantic identification result; parses the execution application form, generates a preservation processing instruction for the assets owned by the executed user, and performs preservation processing according to the preservation processing instruction to generate an execution result of the preservation processing. Compared with the related art, the embodiment of the present disclosure can reduce the time of manual processing and significantly improve the processing efficiency by automatically processing the scanning identification and semantic identification of the execution letter document; the automated processing can avoid errors and omissions that may occur in manual operations and ensure the accuracy and uniformity of the data.

[0051] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0053] Figure 1 A flowchart of an anti-money laundering security processing method provided by an embodiment of the present disclosure;

[0054] Figure 2 A flowchart of another anti-money laundering security processing method provided by an embodiment of the present disclosure;

[0055] Figure 3 A schematic diagram of a frozen button check processing flow;

[0056] Figure 4 A schematic diagram of the structure of an anti-money laundering security processing device provided by an embodiment of the present disclosure;

[0057] Figure 5 A schematic diagram of the structure of another anti-money laundering security processing device provided by an embodiment of the present disclosure;

[0058] Figure 6 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0059] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0060] The following describes the anti-money laundering security processing method and device, electronic device and storage medium according to the embodiments of the present disclosure with reference to the accompanying drawings.

[0061] Figure 1 A flowchart of an anti-money laundering security processing method provided in an embodiment of the present disclosure.

[0062] like Figure 1 As shown, the method comprises the following steps:

[0063] Step 101, obtain the execution letter document, and scan and identify the execution letter document to obtain the execution letter document identification text.

[0064] In the embodiments of the present disclosure, the execution letter document is usually a paper or electronic version of the execution letter document text sent by the judicial authority. After receiving the "Chadongkou" execution letter document from the judicial authority, these documents are scanned and recognized in a refined manner using image / text recognition technology, such as optical character recognition (OCR) technology. OCR technology can automatically recognize key information such as text, numbers, symbols, etc. on the document and convert it into a computer-readable text format, namely, the execution letter document recognition text. This conversion process can reduce the workload of manual input while improving the accuracy and processing efficiency of information.

[0065] The execution letter document recognition text obtained by scanning and identifying with OCR technology can not only contain the basic information of the execution letter, such as case number, law enforcement agency name, execution requirements, etc., but also detailed customer information and insurance policy information, providing a solid data foundation for subsequent intelligent processing procedures.

[0066] Step 102, performing semantic recognition on the recognized text of the execution letter document, and generating an execution application form corresponding to the execution letter document based on the semantic recognition result.

[0067] In the embodiment of the present disclosure, during the implementation of the anti-money laundering investigation and freezing management method, when receiving the "investigation and freezing" execution letter document from the judicial authority, this document is first processed by image / text recognition, and the execution letter document is scanned and recognized using OCR technology, and the paper or electronic version of the document content is converted into an editable text format. Through in-depth analysis of the recognized execution letter document recognition text, the semantic information therein is understood, including but not limited to the type of execution letter (inquiry, freezing, deduction), the agency information involved, the law enforcement agency information and assistance requirements, the customer information involved in the "investigation and freezing", the policy information and related attachment instructions, etc. This process can ensure that the intention and requirements of the execution letter document can be accurately understood.

[0068] Based on the results of semantic recognition, the "check freezing and deduction" execution application form corresponding to the execution letter document is further automatically generated. This application form not only contains all the key information in the execution letter, but also automatically fills in the necessary fields and details based on the results of semantic recognition, such as application type, execution object, execution amount (for deduction applications), execution time (for freezing applications, including freezing and unfreezing time), etc. Through such a process, the system realizes the automatic conversion from execution letter documents to execution application forms. It should be noted that the execution letter documents include document texts of various styles, and the execution application form is a unified format application document (text) generated based on the execution letter documents; by identifying and converting the execution letter documents, the processing efficiency and accuracy can be improved, providing a solid foundation for subsequent preservation processing and other links.

[0069] Step 103, parsing the execution application form, generating a preservation processing instruction for the assets owned by the executed user, performing preservation processing according to the preservation processing instruction, and generating an execution result of the preservation processing.

[0070] In the embodiments of the present disclosure, the execution application form is parsed and processed in detail. This process covers reading various types of information in the application form, including but not limited to the identity information of the executed user, the details of the insurance policy involved, and the specific preservation type (inquiry, freezing, deduction) and corresponding requirements. For different types of preservation applications, the core system will intelligently generate corresponding preservation processing instructions. During the entire preservation processing process, the core system ensures the accuracy, timeliness and compliance of the operation, effectively improves the efficiency and accuracy of "inquiry, freezing and deduction" management, and reduces the company's compliance risks.

[0071] The present disclosure provides a method for anti-money laundering preservation processing, which includes obtaining an execution letter document, scanning and identifying the execution letter document, obtaining the execution letter document identification text; performing semantic recognition on the execution letter document identification text, and generating an execution application form corresponding to the execution letter document based on the semantic recognition result; parsing the execution application form, generating a preservation processing instruction for the assets owned by the executed user, and performing preservation processing according to the preservation processing instruction to generate an execution result of the preservation processing. Compared with the related art, the embodiment of the present disclosure can reduce the time of manual processing and significantly improve processing efficiency by automatically processing the scanning and semantic recognition of the execution letter document; automated processing can avoid errors and omissions that may occur in manual operations and ensure the accuracy and uniformity of data.

[0072] In order to clearly illustrate the embodiments of the present disclosure, this embodiment provides a flowchart of another anti-money laundering security processing method.

[0073] like Figure 2 As shown, the method comprises the following steps:

[0074] Step 201, obtain the execution letter document, and scan and identify the execution letter document to obtain the execution letter document identification text.

[0075] Specifically, in step 201, the execution letter document is scanned and recognized using OCR technology, which can automatically recognize key information such as text, numbers, and symbols on the document and convert it into a computer-readable text format, namely, the execution letter document recognition text. This conversion process can reduce the workload of manual input and improve the accuracy and processing efficiency of information. Figure 3 This is a schematic diagram of the process of checking and freezing the seized items. After obtaining the execution letter document sent by the judicial authority, it is input into the image / text recognition module for OCR recognition.

[0076] The execution letter document recognition text obtained by scanning and identifying with OCR technology can not only contain the basic information of the execution letter, such as case number, law enforcement agency name, execution requirements, etc., but also detailed customer information and insurance policy information, providing a solid data foundation for subsequent intelligent processing procedures.

[0077] Step 202, inputting the execution letter document recognition text into a semantic recognition model to perform semantic recognition to obtain semantic text.

[0078] Specifically, in step 202, the text recognized by the OCR technology is used as input and sent to a pre-trained semantic recognition model. This semantic recognition model can deeply understand the text content and identify key information therein, such as the execution agency, execution type (query, freeze, deduction), customer information involved, policy information, and specific execution requirements, etc., and extract this information in a structured form to form a semantic text.

[0079] This step not only ensures that the recognized text information is accurate, but also provides more accurate and comprehensive data support for the subsequent anti-money laundering system to automatically generate "check freeze and deduction" applications. At the same time, the introduction of the semantic recognition model also enhances the system's adaptability to complex and changeable execution letters and documents, making the entire "check freeze and deduction" management process more intelligent and efficient.

[0080] Step 203, parse the semantic text to determine the preservation processing type corresponding to the execution letter document, and search for the corresponding execution application template according to the preservation processing type, wherein the preservation processing type includes: query processing, freezing processing and deduction processing.

[0081] Specifically, in step 203, the semantic text is carefully parsed by the preset semantic analysis engine to accurately judge and determine the specific preservation treatment type corresponding to the execution letter document. These preservation treatment types are clearly divided into three categories: query processing, freezing processing and deduction processing. For each type of preservation processing, the system will search for the corresponding execution application template in the internal database according to the predefined rules. These templates are pre-designed and contain all the necessary fields and information structures required for different types of preservation processing to ensure the integrity and consistency of information in the subsequent process. For example, for applications of the "query processing" type, the template will mainly focus on the data required for basic inquiries such as collection agency information, law enforcement agency information and assistance requirements, and customer information involved in "investigation, freezing and deduction"; while for applications of the "freezing processing" and "deduction processing" types, the template will be further expanded to include all insurance policy information under the customer's name, specific requirements and amounts for freezing / deduction, and other detailed information.

[0082] Through such a template matching mechanism, the system can efficiently and accurately generate corresponding execution application forms for different types of "check frozen deductions" tasks, laying a solid foundation for subsequent automated processing procedures.

[0083] Step 204, based on the semantic information in the semantic text, fill in the execution application template and generate the execution application form, wherein the execution application form includes: a query application form, a freeze application form and a deduction application form.

[0084] Specifically, in step 204, in the core process of the anti-money laundering investigation, freezing and deduction management method, when the OCR technology completes the image / text recognition of the execution letter document and further semantic analysis based on the semantic recognition model, the system will accurately determine the type of preservation processing corresponding to the execution letter document based on the semantic information obtained by the analysis. These preservation processing types are clearly divided into query processing, freezing processing and deduction processing, and each type corresponds to specific business logic and operation procedures.

[0085] According to the determined preservation treatment type, the corresponding execution application template is automatically retrieved and matched from the preset template library. These templates are designed in advance according to business needs and contain the necessary fields and format requirements for different treatment types, ensuring that the generated execution application form not only complies with business specifications, but also facilitates subsequent review and execution.

[0086] Based on the specific information parsed from the semantic text, such as institutional information, law enforcement agency information and assistance requirements, customer information involved in "investigation and freezing", insurance policy information, etc., it is automatically filled into the corresponding execution application template. For query processing, the system will generate a query application form containing the relevant insurance policy ledger information and PDF screenshots under the customer's name; for freezing processing, a freezing application form containing freezing operation requirements, set thawing time and other information is generated; for deduction processing, a deduction application form containing deduction amount, deduction rules and other information is generated.

[0087] This process can not only improve the automation level of the "check and freeze" processing, reduce the errors and delays that may be caused by manual intervention, but also ensure the accuracy and standardization of the execution application form.

[0088] Step 205, in response to the execution application form verification instruction, check whether the execution application form meets the preset format, and modify the execution application form that does not meet the preset format.

[0089] Specifically, in step 205, in response to the triggering of the execution application form verification instruction, the system will first automatically perform a strict format verification on the received "check freeze and deduction" execution application form. The verification process is intended to ensure that each application form meets the pre-set standard format requirements, which include but are not limited to: the type identification of the application form (such as inquiry, freezing, deduction), the completeness of the required fields (such as institutional information, law enforcement agency information, customer information involved in "check freeze and deduction", insurance policy information, etc.), the format of specific fields (such as date format, amount format, etc.) and the compliance of attachments (such as file type, size limit, etc.).

[0090] If the application form meets the preset format requirements, the system will directly push it to the next processing link; however, for execution application forms that do not meet the preset format, the system will automatically mark them and start the modification process. In the modification process, the system will intelligently identify the fields or contents that do not meet the format requirements according to the preset rules or prompt information, and try to automatically correct some common errors (such as incorrect date format, inconsistent amount digital format, etc.). For errors that cannot be automatically corrected, the system will issue clear modification suggestions or error prompts to the anti-money laundering reviewer, who will make necessary modifications and improvements manually. After the modification is completed, the system will verify the modified execution application form again to ensure that all problems have been resolved and meet the preset format requirements. This process not only improves the standardization and efficiency of "checking and freezing" management, but also effectively reduces processing delays and errors caused by format errors. In this way, the system can ensure that each execution application form can accurately enter the subsequent processing link, providing a solid foundation for subsequent preservation execution and risk management.

[0091] Step 206: parse the execution application form to obtain the security processing type corresponding to the execution application form and the information of the executed user in the execution application form.

[0092] Specifically, in step 206, in the "check, freeze and deduction" management process, after the execution application form passes the format check, the system will further analyze it in depth. The analysis process aims to extract key information from the application form so as to carry out accurate preservation processing later. Specifically, the system will first identify the preservation processing type corresponding to the execution application form, that is, determine whether the application belongs to "inquiry", "freeze" or "deduction".

[0093] At the same time, the system will also parse the execution application form to obtain detailed information about the executed user, including but not limited to the user's identity information, policy information, and any specific requirements or conditions related to this "check freeze" operation. This information will be used in subsequent data queries, policy operations, and result feedback to ensure the accuracy and compliance of the entire processing process.

[0094] Step 207: Generate the security processing instruction based on the executed user information and the security processing type.

[0095] Specifically, in step 207, in the "check, freeze and deduction" management process, once the system completes the parsing of the execution application form and successfully obtains the detailed information of the executed user and the corresponding preservation processing type (ie "query", "freeze" or "deduction"), it will then automatically generate corresponding preservation processing instructions based on this information.

[0096] For "inquiry" type applications, the system will generate a query instruction based on the identity information and policy information of the executed user. The instruction will guide the system to query and organize the relevant policy ledger information and PDF screenshots under the user's name so that they can be provided to judicial authorities or relevant reviewers later.

[0097] For "freeze" applications, in addition to obtaining the identity information and policy information of the executed user, the system will also pay special attention to the specific requirements of the freeze (such as the freezing period, etc.) and generate a freezing instruction accordingly. The instruction will instruct the system to freeze the specified policy and set the corresponding unfreezing time to ensure the accuracy and compliance of the operation.

[0098] For "deduction" applications, the system needs to further analyze the cash value in the policy of the user being executed and compare it with the deduction amount requested in the application. Based on the comparison results, the system will generate a corresponding deduction instruction, which will clearly instruct the system to deduct a specified amount of funds from the user's policy, or take other processing measures (such as deducting all funds or returning execution failure information, etc.) when the policy cash value is insufficient.

[0099] If the security processing instruction is the query instruction, execute step 208; if the security processing instruction is the freeze instruction, execute step 209; if the security processing instruction is the deduction instruction, execute step 210.

[0100] Step 208: query the account information of the executed user based on the executed user information and generate a account record file, and generate the execution result based on the account record file.

[0101] Step 209: query the asset information of the executed user based on the executed user information, freeze the asset account of the executed user according to the freezing period in the execution application form, and generate the execution result.

[0102] Step 210, deduct the assets owned by the executed user according to the deduction amount in the execution application form, and generate the execution result.

[0103] Specifically, in steps 208 to 210, for "inquiry" type application forms, the core system automatically parses the application form, automatically packages the relevant policy ledger information and PDF screenshots under the name of the executed user according to the agreed rules, generates a preservation to-do list under the security account of the institution to which the executed user belongs, and sends an automatic email reminder. The security post reviews the inquiry application, submits it to the system for execution after the review is passed, and the system transmits the execution result back to the anti-money laundering system.

[0104] For "freeze" application forms, the core system automatically parses the application form, initiates the freezing operation of the insurance policy under the name of the executed user according to the requirements, sets the unfreezing time according to the requirements, generates a preservation to-do in the account of the preservation post of the institution to which the executed user belongs, and sends an automatic email reminder. The preservation post reviews the query application, submits it to the system for execution after the review is passed, and the system returns the execution result to the anti-money laundering system. If the request to freeze the insurance policy is invalid or there is no valid insurance policy under the name of the executed user, the execution result returns "There is no valid and executable insurance policy under the name of the executed user."

[0105] For "deduction" application forms, the core system automatically parses the application form, initiates the deduction operation for the required amount of the insurance policy under the name of the executed user according to the requirements, generates a preservation to-do in the account of the preservation post of the institution to which the executed user belongs, and sends an automatic email reminder. The preservation post reviews this query application, and submits it to the system for execution after the review is passed. The system returns the execution result to the anti-money laundering system. If the cash value of the insurance policy under the name of the executed user is less than the required deduction amount, it will be deducted in full by default. If it is greater than the deduction amount, it will be deducted according to the agreed principle. If the cash value of the insurance policy under the name of the executed user is equal to 0, the execution result returns "There is no valid and executable insurance policy under the name of the executed user."

[0106] Step 211, using the execution result and the execution application form, perform risk rating processing on the executed user to generate a risk assessment level of the executed user.

[0107] Specifically, in step 211, in the subsequent stages of the "check, freeze and deduction" management process, in order to comprehensively evaluate the risk status of the executed user, the system will make full use of the execution results and the original execution application form as a reference. Specifically, the system will automatically analyze the specific execution results returned during the execution process (such as whether the insurance policy has been successfully frozen, whether the deduction amount is in place, whether there is an unexecutable valid insurance policy, etc.), combined with the detailed information of the executed person provided in the execution application form (including identity information, case types involved, law enforcement agency requirements, etc.), through the preset risk assessment model. This assessment process will comprehensively consider multiple dimensions such as the financial status, past behavior records, legal disputes, etc. of the executed user, and ultimately generate an objective and accurate risk assessment level. This level not only reflects the risk level of the executed person in the current "check, freeze and deduction" incident, but also provides an important reference for possible subsequent regulatory measures or risk management strategies.

[0108] As an achievable method of the present disclosure, this embodiment can generate an execution result statement for each execution letter document according to the execution result. The execution result certification module generates an "investigation and freezing" execution result statement for each "investigation and freezing" execution letter according to the system rules, and the statement supports anti-money laundering download and provides it to the judicial authorities.

[0109] It should be noted that the embodiments of the present disclosure may include multiple steps. For the convenience of description, these steps are numbered, but these numbers do not limit the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of the present disclosure do not limit this.

[0110] Corresponding to the above-mentioned anti-money laundering security processing method, the present invention also provides an anti-money laundering security processing device. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, the details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be repeated in the present invention.

[0111] Figure 4 A schematic diagram of the structure of an anti-money laundering security processing device provided by the embodiment of the present disclosure, such as Figure 4 As shown, including:

[0112] The scanning unit 31 is used to obtain the execution letter document, and scan and identify the execution letter document to obtain the execution letter document identification text;

[0113] The recognition unit 32 is used to perform semantic recognition on the recognition text of the execution letter document, and generate an execution application form corresponding to the execution letter document based on the semantic recognition result;

[0114] The parsing unit 33 is used to parse the execution application form, generate a preservation processing instruction for the assets owned by the executed user, perform preservation processing according to the preservation processing instruction, and generate an execution result of the preservation processing.

[0115] The present disclosure provides an anti-money laundering preservation processing device, which obtains an execution letter document, scans and identifies the execution letter document, obtains the execution letter document identification text; performs semantic identification on the execution letter document identification text, and generates an execution application form corresponding to the execution letter document based on the semantic identification result; parses the execution application form, generates a preservation processing instruction for the assets owned by the executed user, and performs preservation processing according to the preservation processing instruction to generate an execution result of the preservation processing. Compared with the related art, the embodiment of the present disclosure can reduce the time of manual processing and significantly improve the processing efficiency by automatically processing the scanning identification and semantic identification of the execution letter document; the automated processing can avoid errors and omissions that may occur in manual operations and ensure the accuracy and uniformity of the data.

[0116] Furthermore, in a possible implementation of this embodiment, Figure 5 As shown, the identification unit 32 includes:

[0117] The recognition module 321 is used to input the recognition text of the execution letter document and perform semantic recognition based on the semantic recognition model to obtain semantic text;

[0118] The determination module 322 is used to parse the semantic text, determine the preservation processing type corresponding to the execution letter document, and search for the corresponding execution application template according to the preservation processing type, wherein the preservation processing type includes: query processing, freezing processing and deduction processing;

[0119] The first generating module 323 is used to fill in the execution application template based on the semantic information in the semantic text, and generate the execution application form, wherein the execution application form includes: a query application form, a freeze application form and a deduction application form.

[0120] Furthermore, in a possible implementation of this embodiment, Figure 5 As shown, the device also includes:

[0121] The checking unit 34 is used to check whether the execution application form meets the preset format in response to the execution application form verification instruction after the recognition unit performs semantic recognition on the execution letter document recognition text and generates an execution application form corresponding to the execution letter document based on the semantic recognition result, and modify the execution application form that does not meet the preset format.

[0122] Furthermore, in a possible implementation of this embodiment, Figure 5 As shown, the parsing unit 33 includes:

[0123] The parsing module 331 is used to parse the execution application form, obtain the preservation processing type corresponding to the execution application form and the executed user information in the execution application form;

[0124] The second generating module 332 is used to generate the security processing instruction based on the executed user information and the security processing type.

[0125] Furthermore, in a possible implementation of this embodiment, Figure 5 As shown, the preservation item instructions include: query instructions, freezing instructions and deduction instructions;

[0126] The parsing unit 33 comprises:

[0127] A first execution module 333, configured to query the ledger information of the executed user based on the executed user information and generate a ledger record file when the security processing instruction is the query instruction, and generate the execution result based on the ledger record file;

[0128] The second execution module 334 is used for, when the preservation processing instruction is the freezing instruction, querying the asset information of the executed user based on the executed user information, freezing the asset account of the executed user according to the freezing period in the execution application form, and generating the execution result;

[0129] The third execution module 335 is used for deducting the assets owned by the executed user according to the deduction amount in the execution application form when the preservation processing instruction is the deduction instruction, and generating the execution result.

[0130] Furthermore, in a possible implementation of this embodiment, Figure 5 As shown, the device also includes:

[0131] The rating unit 35 is used to perform risk rating processing on the executed user by using the execution result and the execution application form, and generate a risk assessment level of the executed user.

[0132] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and the principle is the same, which is not limited in this embodiment.

[0133] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0134] Figure 6 A schematic block diagram of an example electronic device 400 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0135] like Figure 6As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 402 or a computer program loaded from a storage unit 408 to a RAM (Random Access Memory) 403. In the RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An I / O (Input / Output) interface 405 is also connected to the bus 404.

[0136] A number of components in the device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0137] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the method of anti-money laundering security processing. For example, in some embodiments, the method of anti-money laundering security processing may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the aforementioned anti-money laundering security processing method in any other appropriate manner (eg, by means of firmware).

[0138] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a dedicated or general-purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0139] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0140] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or a flash memory, an optical fiber, a CD-ROM (Compact Dis sc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0141] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0142] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0143] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0144] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0145] The various numerical numbers such as first and second involved in the present disclosure are only for the convenience of description and are not used to limit the scope of the embodiments of the present disclosure, but also indicate the order of precedence.

[0146] At least one in the present disclosure may also be described as one or more, and a plurality may be two, three, four or more, which is not limited in the present disclosure. In the embodiments of the present disclosure, for a technical feature, the technical features in the technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no order of precedence or size between the technical features described by the "first", "second", "third", "A", "B", "C" and "D".

[0147] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0148] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for anti-money laundering security processing, characterized in that: include: Obtaining the execution letter document, and scanning and identifying the execution letter document to obtain the execution letter document identification text; Performing semantic recognition on the recognized text of the execution letter document, and generating an execution application form corresponding to the execution letter document based on the semantic recognition result; The execution application form is parsed to generate a preservation processing instruction for the assets owned by the executed user, and preservation processing is performed according to the preservation processing instruction to generate an execution result of the preservation processing.

2. The method according to claim 1, characterized in that: The step of performing semantic recognition on the recognized text of the execution letter document and generating an execution application form corresponding to the execution letter document based on the semantic recognition result includes: Inputting the recognized text of the execution letter document into a semantic recognition model to perform semantic recognition to obtain a semantic text; Parse the semantic text to determine the preservation processing type corresponding to the execution letter document, and search for the corresponding execution application template according to the preservation processing type, wherein the preservation processing type includes: query processing, freezing processing and deduction processing; Based on the semantic information in the semantic text, the execution application template is filled to generate the execution application form, wherein the execution application form includes: a query application form, a freeze application form and a deduction application form.

3. The method according to claim 1, characterized in that After semantic recognition is performed on the execution letter document recognition text, and an execution application form corresponding to the execution letter document is generated based on the semantic recognition result, the method further includes: In response to the execution application form verification instruction, check whether the execution application form meets the preset format, and modify the execution application form that does not meet the preset format.

4. The method according to claim 1, characterized in that The step of parsing the execution application form and generating a preservation instruction for the assets owned by the executed user includes: Parsing the execution application form to obtain the preservation processing type corresponding to the execution application form and the information of the executed user in the execution application form; The security processing instruction is generated based on the executed user information and the security processing type.

5. The method according to claim 4, characterized in that The preservation item instructions include: query instructions, freezing instructions and deduction instructions; The performing of the security processing according to the security processing instruction and generating the execution result of the security processing includes: If the security processing instruction is the query instruction, querying the account information of the executed user based on the executed user information and generating a account record file, and generating the execution result based on the account record file; If the preservation processing instruction is the freezing instruction, query the asset information of the executed user based on the executed user information, freeze the asset account of the executed user according to the freezing period in the execution application form, and generate the execution result; If the preservation processing instruction is the deduction instruction, the assets owned by the executed user are deducted according to the deduction amount in the execution application form to generate the execution result.

6. The method according to claim 1, characterized in that The method further comprises: The execution result and the execution application form are used to perform risk rating processing on the executed user to generate a risk assessment level of the executed user. 7.An anti-money laundering security processing device, characterized in that: include: A scanning unit, used to obtain an execution letter document, and scan and identify the execution letter document to obtain an execution letter document identification text; A recognition unit, used for performing semantic recognition on the recognition text of the execution letter document, and generating an execution application form corresponding to the execution letter document based on the semantic recognition result; The parsing unit is used to parse the execution application form, generate a preservation processing instruction for the assets owned by the executed user, perform preservation processing according to the preservation processing instruction, and generate an execution result of the preservation processing.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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