Object risk assessment method and device, electronic equipment and readable storage medium

Abstract

The object risk assessment method and device, the electronic device and the readable storage medium provided by the present disclosure can be applied to the computer technology field, the data processing technology field and the financial field. The object risk assessment method comprises the following steps: in response to receiving a service request, obtaining to-be-processed data corresponding to an object identifier in the service request according to the object identifier; sending a first to-be-processed sub-data set to a first computing node; receiving a first evaluation value from the first computing node, wherein the first evaluation value is obtained by the first computing node processing the first to-be-processed sub-data set; sending a second to-be-processed sub-data set to a second computing node; receiving a second evaluation value from the second computing node, wherein the second evaluation value is obtained by the second computing node processing the second to-be-processed sub-data set; and determining an object risk assessment result corresponding to the object identifier according to the first evaluation value and the second evaluation value.

Description

Technical Field

[0001] This disclosure relates to the fields of computer technology, data processing technology, and finance, and more specifically, to a method and apparatus for object risk assessment, electronic equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] With the development of computer technology, privacy computing technology has emerged to ensure the security of network behavior information flow related to users. Privacy computing technology can refer to a set of technologies that enable data analysis and computation while protecting the data itself from being disclosed to the outside world.

[0003] In realizing the concept disclosed herein, the inventors discovered at least the following problems in the related technology: due to the inability of multiple resource providers to effectively share data in privacy computing, the real-time performance of data processing and the security of data cannot be guaranteed. Summary of the Invention

[0004] In view of this, the present disclosure provides a method and apparatus for object risk assessment, an electronic device, a computer-readable storage medium, and a computer program product.

[0005] According to one aspect of this disclosure, an object risk assessment method is provided, applied on a server side, including:

[0006] In response to receiving a business request, based on the object identifier in the business request, the data to be processed corresponding to the object identifier is obtained, wherein the object identifier is used to represent the target object, and the data to be processed includes a first set of sub-data to be processed and a second set of sub-data to be processed.

[0007] Send the aforementioned first set of sub-data to be processed to the first computing node;

[0008] Receive a first evaluation value from the first computing node, wherein the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed;

[0009] Send the aforementioned second set of sub-data to be processed to the second computing node;

[0010] Receive a second evaluation value from the second computing node, wherein the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed; and

[0011] Based on the first assessment value and the second assessment value mentioned above, the risk assessment result of the object corresponding to the object identifier is determined.

[0012] According to embodiments of this disclosure, the above-mentioned response to receiving a service request, and obtaining the data to be processed corresponding to the object identifier in the service request, includes:

[0013] In response to receiving the above business request, based on the above object identifier, obtain the risk assessment threshold corresponding to the above object identifier and at least one entity identifier;

[0014] Based on at least one of the above entity identifiers, determine the number of entities corresponding to the above object identifiers;

[0015] Based on the number of entities mentioned above, the risk assessment threshold is split to obtain at least one risk assessment sub-threshold.

[0016] Send each of the above-mentioned at least one risk assessment sub-thresholds to the entity objects corresponding to each of the above-mentioned at least one entity identifier;

[0017] Receive candidate sub-data to be processed from entity objects corresponding to each of the above-mentioned at least one entity identifier; and

[0018] The data to be processed is determined based on the candidate data to be processed of the entity objects corresponding to each of the above at least one entity identifier.

[0019] According to embodiments of this disclosure, determining the data to be processed based on candidate data to be processed corresponding to the entity objects corresponding to each of the at least one entity identifier includes:

[0020] Among the candidate sub-data to be processed of the entity objects corresponding to each of the above at least one entity identifier, at least one first sub-data to be processed and at least one second sub-data to be processed are determined.

[0021] Based on at least one first sub-data to be processed, the set of first sub-data to be processed is determined;

[0022] For each of the at least one second sub-data to be processed mentioned above,

[0023] The second sub-data to be processed is inverted to obtain the third sub-data to be processed; and

[0024] The set of second sub-data to be processed is determined based on the third sub-data corresponding to each of the above-mentioned at least one second sub-data to be processed.

[0025] According to embodiments of this disclosure, the aforementioned candidate sub-data to be processed is obtained in the following manner:

[0026] For each of the at least one entity identifier mentioned above,

[0027] Determine the target data corresponding to the aforementioned entity identifiers;

[0028] Based on the aforementioned risk assessment sub-thresholds and target data, the target difference is determined; and

[0029] The aforementioned target difference is determined as the aforementioned candidate sub-data to be processed.

[0030] According to embodiments of this disclosure, determining the object risk assessment result corresponding to the object identifier based on the first assessment value and the second assessment value includes:

[0031] Based on a predetermined algorithm, the first evaluation value and the second evaluation value are processed to obtain a comparison result;

[0032] If the above comparison results indicate that the first assessment value is greater than the second assessment value, then the object risk assessment result indicating that the target object has failed the object risk assessment is determined; and

[0033] If the comparison results indicate that the first assessment value is less than or equal to the second assessment value, the object risk assessment result indicating that the target object has failed the object risk assessment is determined.

[0034] According to embodiments of this disclosure, the method further includes, after determining the object risk assessment result corresponding to the object identifier based on the first assessment value and the second assessment value:

[0035] If the above object risk assessment results indicate that the target object has passed the object risk assessment, a prompt message will be output to grant permission to execute the above business request; and

[0036] If the above object risk assessment results indicate that the target object has failed the object risk assessment, a warning message will be output prohibiting the execution of the above business request.

[0037] According to another aspect of this disclosure, an object risk assessment method is provided, applied to a first computing node, comprising:

[0038] Receive a first set of sub-data to be processed from the server, wherein the first set of sub-data to be processed includes at least one first sub-data to be processed;

[0039] The first sub-data to be processed is processed to obtain a first evaluation value; and

[0040] The first assessment value is sent to the server so that the server can perform an object risk assessment on the target object based on the first assessment value.

[0041] According to embodiments of this disclosure, the above-mentioned processing of at least one first sub-data to be processed to obtain a first evaluation value includes:

[0042] The above-mentioned at least one first sub-data to be processed is accumulated to obtain a first accumulated value; and

[0043] Based on the aforementioned first accumulated value, the aforementioned first evaluation value is determined.

[0044] According to another aspect of this disclosure, an object risk assessment method is provided, applied to a second computing node, comprising:

[0045] Receive a second set of sub-data to be processed from the server, wherein the second set of sub-data to be processed includes at least one second sub-data to be processed;

[0046] The above-mentioned at least one second sub-data to be processed is processed to obtain a second evaluation value; and

[0047] The second assessment value is sent to the server so that the server can conduct an object risk assessment on the target object based on the second assessment value.

[0048] According to embodiments of this disclosure, the above-described processing of at least one second sub-data to be processed to obtain a second evaluation value includes:

[0049] The above-mentioned at least one second sub-data to be processed is accumulated to obtain a second accumulated value; and

[0050] Based on the aforementioned second accumulated value, the aforementioned second evaluation value is determined.

[0051] According to another aspect of this disclosure, an object risk assessment device is provided, applied on a server side, comprising:

[0052] The first acquisition module is used to respond to a received business request and acquire the data to be processed corresponding to the object identifier in the business request. The object identifier is used to represent the target object, and the data to be processed includes a first sub-data set to be processed and a second sub-data set to be processed.

[0053] The first sending module is used to send the aforementioned first set of sub-data to be processed to the first computing node;

[0054] The first receiving module is configured to receive a first evaluation value from the first computing node, wherein the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed.

[0055] The second sending module is used to send the aforementioned second set of sub-data to be processed to the second computing node;

[0056] The second receiving module is configured to receive a second evaluation value from the second computing node, wherein the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed; and

[0057] The determination module is used to determine the object risk assessment result corresponding to the object identifier based on the first assessment value and the second assessment value.

[0058] According to another aspect of this disclosure, an object risk assessment apparatus is provided, applied to a first computing node, comprising:

[0059] The third receiving module is used to receive a first set of sub-data to be processed from the server, wherein the first set of sub-data to be processed includes at least one first sub-data to be processed.

[0060] A first processing module is configured to process at least one first sub-data to be processed to obtain a first evaluation value; and

[0061] The third sending module is used to send the first evaluation value to the server so that the server can perform object risk assessment on the target object based on the first evaluation value.

[0062] According to another aspect of this disclosure, an object risk assessment apparatus is provided, applied to a second computing node, comprising:

[0063] The fourth receiving module is used to receive a second set of sub-data to be processed from the server, wherein the second set of sub-data to be processed includes at least one second sub-data to be processed.

[0064] The second processing module is used to process at least one of the second sub-data to be processed to obtain a second evaluation value; and

[0065] The fourth sending module is used to send the second evaluation value to the server so that the server can perform an object risk assessment on the target object based on the second evaluation value.

[0066] According to another aspect of this disclosure, an electronic device is provided, comprising:

[0067] One or more processors;

[0068] Memory, used to store one or more instructions.

[0069] When one or more of the above instructions are executed by one or more processors, the one or more processors cause the one or more processors to implement the method as described in this disclosure.

[0070] According to another aspect of this disclosure, a computer-readable storage medium is provided having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described in this disclosure.

[0071] According to another aspect of this disclosure, a computer program product is provided, which includes computer-executable instructions that, when executed, are used to perform the methods described in this disclosure.

[0072] According to embodiments of this disclosure, since the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed, and the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed, the data processing security is improved by using dual computing nodes to process the sub-data sets to be processed separately. Furthermore, by using the first and second evaluation values, the object risk assessment result corresponding to the object identifier is automatically determined, thus avoiding the technical problem in related technologies where multiple resource providers cannot effectively share data, ensuring the real-time performance of data processing, and thereby improving the accuracy of object risk assessment. Attached Figure Description

[0073] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0074] Figure 1 This illustration schematically shows a system architecture to which an object risk assessment method can be applied according to an embodiment of the present disclosure;

[0075] Figure 2 A flowchart illustrating an object risk assessment method according to an embodiment of the present disclosure is shown schematically;

[0076] Figure 3 This illustration schematically shows an example of a process according to an embodiment of the present disclosure of obtaining data to be processed corresponding to an object identifier in a service request in response to receiving the service request.

[0077] Figure 4 This illustration schematically shows an example of the process of sending a first set of sub-data to be processed to a first computing node and a second set of sub-data to be processed to a second computing node according to an embodiment of the present disclosure.

[0078] Figure 5 This illustration schematically shows an example diagram of an object risk assessment process according to an embodiment of the present disclosure;

[0079] Figure 6 A flowchart illustrating an object risk assessment method according to another embodiment of this disclosure is shown schematically;

[0080] Figure 7 A flowchart illustrating an object risk assessment method according to another embodiment of this disclosure is shown schematically;

[0081] Figure 8 This illustration schematically shows an example diagram of an object risk assessment process according to another embodiment of the present disclosure;

[0082] Figure 9 A block diagram of an object risk assessment apparatus according to an embodiment of the present disclosure is shown schematically;

[0083] Figure 10 A block diagram of an object risk assessment apparatus according to another embodiment of the present disclosure is shown schematically;

[0084] Figure 11 A block diagram of an object risk assessment apparatus according to another embodiment of the present disclosure is schematically shown; and

[0085] Figure 12 A block diagram of an electronic device suitable for implementing an object risk assessment method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0086] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0087] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0088] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0089] When using expressions such as "at least one of A, B, and C," the expression should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or systems having A, B, and C, etc.). Similarly, when using expressions such as "at least one of A, B, or C," the expression should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, or C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or systems having A, B, and C, etc.).

[0090] In the technical solution disclosed herein, the acquisition, storage, and application of user personal information comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and there is no violation of public order and good morals.

[0091] In the technical solution disclosed herein, the user's authorization or consent is obtained before acquiring or collecting the user's personal information.

[0092] When processing information such as video, audio, images, graphics, text, numerical data, and ubiquitous network behavioral information streams, privacy computing technology can be used to describe, measure, evaluate, and fuse the privacy information involved, forming privacy computing theories, algorithms, and application technologies with quantitative evaluation standards, so as to support privacy information protection for multi-system integration.

[0093] Privacy-preserving computation techniques may include at least one of the following: Secure Multi-party Computation (MPC), Federated Learning (FL), Trusted Execution Environment (TEE), and Multi-party Intermediary Computation (MPIC).

[0094] Network behavior information flow can include loan business information flow. Loan business can include personal loans. Personal loans can refer to loans in local or foreign currencies issued by banks or other financial institutions to eligible individuals for personal consumption, production and business operations, etc.

[0095] However, due to considerations such as compliance, trade secrets, and user privacy protection, multiple loan providers cannot directly share user loan information. This means that effective collaboration and information sharing among multiple loan providers is hindered, resulting in insufficient real-time loan approval. Furthermore, centralized data processing methods pose a risk of data leakage, thus compromising data security.

[0096] To at least partially address the technical problems existing in related technologies, this disclosure provides an object risk assessment method and apparatus, electronic device, and readable storage medium, which can be applied to the fields of computer technology, data processing technology, and finance. The object risk assessment method includes: in response to receiving a business request, obtaining data to be processed corresponding to the object identifier in the business request, wherein the object identifier is used to characterize a target object, and the data to be processed includes a first sub-data set to be processed and a second sub-data set to be processed; sending the first sub-data set to be processed to a first computing node; receiving a first evaluation value from the first computing node, wherein the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed; sending the second sub-data set to be processed to a second computing node; receiving a second evaluation value from the second computing node, wherein the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed; and determining an object risk assessment result corresponding to the object identifier based on the first evaluation value and the second evaluation value.

[0097] It should be noted that the object risk assessment method and apparatus provided in this disclosure can be used in the fields of computer technology, data processing technology, and finance, such as in the field of internet technology. The object risk assessment method and apparatus provided in this disclosure can also be used in any field other than computer technology, data processing technology, and finance, such as in the field of information security technology. The application fields of the object risk assessment method and apparatus provided in this disclosure are not limited.

[0098] Figure 1 The illustration schematically depicts a system architecture to which an object risk assessment method can be applied according to embodiments of this disclosure. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0099] like Figure 1As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0100] Users can interact with server 105 via network 104 using at least one of the first terminal device 101, second terminal device 102, and third terminal device 103 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, second terminal device 102, and third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0101] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0102] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0103] It should be noted that the object risk assessment method provided in this disclosure embodiment can generally be executed by server 105. Correspondingly, the object risk assessment device provided in this disclosure embodiment can generally be located in server 105. The object risk assessment method provided in this disclosure embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the object risk assessment device provided in this disclosure embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0104] Alternatively, the object risk assessment method provided in this embodiment of the disclosure can also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Correspondingly, the object risk assessment device provided in this embodiment of the disclosure can also be disposed in the first terminal device 101, the second terminal device 102, or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103.

[0105] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0106] It should be noted that the sequence numbers of the operations in the following methods are for descriptive purposes only and should not be considered as indicating the execution order of the operations. Unless explicitly stated otherwise, the method does not need to be executed in the exact order shown.

[0107] Figure 2 A flowchart illustrating an object risk assessment method according to an embodiment of the present disclosure is shown schematically.

[0108] like Figure 2 As shown, the risk assessment method for this object includes operations S210 to S260.

[0109] In operation S210, in response to receiving a business request, the data to be processed corresponding to the object identifier in the business request is obtained. The object identifier is used to represent the target object, and the data to be processed includes a first set of sub-data to be processed and a second set of sub-data to be processed.

[0110] In operation S220, the first set of sub-data to be processed is sent to the first computing node.

[0111] In operation S230, a first evaluation value is received from the first computing node, wherein the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed.

[0112] In operation S240, the second set of sub-data to be processed is sent to the second computing node.

[0113] In operation S250, a second evaluation value is received from the second computing node, wherein the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed.

[0114] In operation S260, the object risk assessment result corresponding to the object identifier is determined based on the first assessment value and the second assessment value.

[0115] According to embodiments of this disclosure, the object risk assessment method can be applied to the interaction process between a server, a first computing node, and a second computing node. The server may include a server or a server cluster. The first and second computing nodes may refer to trusted computing nodes. The first computing node may include a first network node and a first router. The second computing node may include a second network node and a second router.

[0116] According to embodiments of this disclosure, the server, the first computing node, and the second computing node can interact based on a communication protocol. The communication protocol may include at least one of the following: WebSocket (a full-duplex communication protocol based on Transmission Control Protocol), Hypertext Transfer Protocol (HTTP), Hypertext Transfer Protocol Secure (HTTPS), Transmission Control Protocol / Internet Protocol (TCP / IP), and Message Queuing Telemetry Transport (MQTT).

[0117] According to embodiments of this disclosure, the code for generating business requests can be pre-written into a script. In response to detecting a business transaction operation initiated by a target object, the client can run the script to generate a business request message. The client can then send this business request message to the server, allowing the server to perform an object risk assessment on the target object corresponding to the business transaction operation based on the business request message.

[0118] According to embodiments of this disclosure, a service request may include an object identifier corresponding to a target object. The object identifier can be used to characterize the identity of the target object. The specific form of the object identifier can be set according to actual business needs and is not limited herein. For example, the object identifier may include one of the following: the target object's IdentityDocument (ID) number and Internet Protocol Address (IP).

[0119] According to embodiments of this disclosure, after the server receives a business request, it can retrieve the data to be processed corresponding to the object identifier from the data source. The data source may include at least one of the following: a local database, a cloud database, and network resources. For example, a data interface can be called to retrieve the data to be processed corresponding to the object identifier from the data source.

[0120] According to embodiments of this disclosure, the data to be processed may include a first set of sub-data to be processed and a second set of sub-data to be processed. The first set of sub-data to be processed may include at least one first sub-data to be processed. The second set of sub-data to be processed may include at least one second sub-data to be processed. The at least one first sub-data to be processed may be determined from at least one candidate sub-data to be processed. After obtaining at least one first sub-data to be processed, the second sub-data to be processed can be determined based on data from the at least one candidate sub-data to be processed, excluding the first sub-data to be processed. The first sub-data to be processed in the first set of sub-data to be processed and the second sub-data to be processed in the second set of sub-data to be processed may be the same or different.

[0121] According to embodiments of this disclosure, after obtaining the data to be processed, the server can send a first set of sub-data to be processed to a first computing node and a second set of sub-data to be processed to a second computing node. Upon receiving the first set of sub-data to be processed, the first computing node can process it to obtain a first evaluation value. After obtaining the first evaluation value, the first computing node can send the first evaluation value to the server. Similarly, upon receiving the second set of sub-data to be processed, the second computing node can process it to obtain a second evaluation value. After obtaining the second evaluation value, the second computing node can send the second evaluation value to the server.

[0122] According to embodiments of this disclosure, after receiving the first evaluation value and the second evaluation value, the server can perform a privacy comparison on the first and second evaluation values ​​to obtain a comparison result. The privacy comparison refers to obtaining the magnitude relationship between the values ​​of the first and second computing nodes without exposing their specific values. The comparison result can be used to characterize the numerical relationship between the first and second evaluation values. After obtaining the comparison result, the object risk assessment result corresponding to the object identifier can be determined based on the comparison result. The object risk assessment result can be used to characterize whether the target object passes the object risk assessment.

[0123] According to embodiments of this disclosure, since the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed, and the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed, the data processing security is improved by using dual computing nodes to process the sub-data sets to be processed separately. Furthermore, by using the first and second evaluation values, the object risk assessment result corresponding to the object identifier is automatically determined, thus avoiding the technical problem in related technologies where multiple resource providers cannot effectively share data, ensuring the real-time performance of data processing, and thereby improving the accuracy of object risk assessment.

[0124] The following is for reference. Figures 3-5 The object risk assessment method 200 according to an embodiment of the present invention will be further described.

[0125] According to embodiments of this disclosure, operation S210 may include the following operations.

[0126] In response to a received business request, the system retrieves a risk assessment threshold corresponding to the object identifier and at least one entity identifier. Based on the at least one entity identifier, it determines the number of entities corresponding to each object identifier. Based on the number of entities, it breaks down the risk assessment threshold into at least one risk assessment sub-threshold. It then sends each of the at least one risk assessment sub-threshold to the entity object corresponding to its respective entity identifier. The system receives candidate pending data from the entity objects corresponding to each of the at least one entity identifier. Based on the candidate pending data from the entity objects corresponding to each of the at least one entity identifier, it determines the data to be processed.

[0127] According to embodiments of this disclosure, after receiving a business request, the server can retrieve a risk assessment threshold corresponding to the object identifier and at least one entity identifier from the data source based on the object identifier. The risk assessment threshold can be used as the basis for risk assessment of the business transaction status of the target object. Each of the at least one entity identifier can correspond to an entity object. The entity object can refer to a financial institution.

[0128] According to embodiments of this disclosure, after obtaining a risk assessment threshold and at least one entity identifier, the server can determine the number of entities corresponding to an object identifier based on the at least one entity identifier. The number of entities can be used as a basis for splitting the risk assessment threshold. After obtaining the number of entities, the server can split the risk assessment threshold based on the number of entities to obtain at least one risk assessment sub-threshold.

[0129] According to embodiments of this disclosure, the specific method of splitting the processing can be set according to actual business needs and is not limited here, as long as the relationship between at least one risk assessment sub-threshold and the risk assessment threshold meets a predetermined condition. The predetermined condition may include one of the following: the cumulative value of at least one risk assessment sub-threshold is equal to the risk assessment threshold, and the difference between the cumulative value of at least one risk assessment sub-threshold and the risk assessment threshold is less than a predetermined threshold.

[0130] According to embodiments of this disclosure, the risk assessment threshold can be represented using M, and at least one entity identifier can be represented using (B1, B2, ..., B...). N Representation. It can be based on at least one entity identifier (B1, B2, ..., B...). N The number of entities N corresponding to the object identifier is determined. Based on the number of entities N, the risk assessment threshold M is split to obtain at least one risk assessment sub-threshold (M1, M2, ..., M...). N M = M1 + M2 + ... + M N In this case, at least one risk assessment sub-threshold (M1, M2, ..., M...) can be used. N ) respectively sent to at least one entity identifier (B1, B2, ..., B N Each of these corresponds to a specific entity object.

[0131] According to embodiments of this disclosure, determining the data to be processed based on candidate data to be processed corresponding to entity objects corresponding to at least one entity identifier may include the following operations.

[0132] From the candidate sub-data to be processed corresponding to the entity objects corresponding to at least one entity identifier, at least one first sub-data to be processed and at least one second sub-data to be processed are determined. Based on the at least one first sub-data to be processed, a set of first sub-data to be processed is determined. For each of the at least one second sub-data to be processed, the second sub-data to be processed is inverted to obtain a third sub-data to be processed. Based on the third sub-data corresponding to each of the at least one second sub-data to be processed, a set of second sub-data to be processed is determined.

[0133] According to embodiments of this disclosure, as described above, candidate sub-data to be processed for entity objects corresponding to at least one entity identifier can be used (J1, J2, ..., J...). N It can be characterized by at least one candidate sub-data to be processed (J1, J2, ..., J...). N The data is grouped to obtain at least one first sub-data to be processed and at least one second sub-data to be processed.

[0134] According to embodiments of this disclosure, at least one first sub-data to be processed may include, for example, J1, J2, ..., J... N / 2 It can be based on at least one first sub-data J1, J2, ..., J N / 2 Determine the first sub-data set to be processed (J1, J2, ..., J...). N / 2 At least one second sub-data to be processed may, for example, include J. (N / 2)+1 J (N / 2)+2 , ..., J N It can process at least one second sub-data J. (N / 2)+1 J (N / 2)+2 , ..., J N Perform inversion on each data point to obtain at least one third sub-data point -J. (N / 2)+1 -J (N / 2)+2 ,...,-J N It can be based on at least one third sub-data to be processed -J (N / 2)+1 -J (N / 2)+2 ,...,-J N Determine the second sub-data set to be processed (-J) (N / 2)+1 -J (N / 2)+2 ,...,-J N ).

[0135] Figure 3 The illustration shows an example of a process according to an embodiment of the present disclosure of obtaining data to be processed corresponding to an object identifier in a service request in response to receiving the service request.

[0136] like Figure 3 As shown in 300, in response to receiving a business request 301, a risk assessment threshold 302 and at least one entity identifier 303 corresponding to the object identifier 301_1 can be obtained based on the object identifier 301_1 in the business request 301.

[0137] After obtaining the risk assessment threshold 302 and at least one entity identifier 303, the number of entities 304 corresponding to the object identifier 301_1 can be determined based on the at least one entity identifier 303. Based on the number of entities 304, the risk assessment threshold 302 is split to obtain at least one risk assessment sub-threshold 305.

[0138] After obtaining at least one risk assessment sub-threshold 305, the at least one risk assessment sub-threshold 305 can be sent to the entity object corresponding to each of the at least one entity identifier. Candidate pending sub-data 306 is received from the entity objects corresponding to each of the at least one entity identifier.

[0139] Based on the candidate sub-data 306 corresponding to the entity objects corresponding to at least one entity identifier, at least one first sub-data 306_1 and at least one second sub-data 306_2 can be determined from the candidate sub-data 306 corresponding to the entity objects corresponding to at least one entity identifier. A first set of sub-data 307 can be determined based on at least one first sub-data 306_1.

[0140] For each of the at least one second sub-data 306_2 to be processed, the second sub-data 306_2 is inverted to obtain a third sub-data 306_3 to be processed. Based on the third sub-data 306_3 corresponding to each of the at least one second sub-data 306_2, a set of second sub-data 308 to be processed is determined.

[0141] According to embodiments of this disclosure, candidate sub-data to be processed can be obtained in the following manner.

[0142] For each entity identifier in at least one entity identifier, determine the target data corresponding to that entity identifier. Based on the risk assessment sub-threshold and the target data, determine the target difference. Identify the target difference as candidate sub-data to be processed.

[0143] According to embodiments of this disclosure, each of the at least one entity objects, after receiving a risk assessment sub-threshold, can determine target data corresponding to an object identifier. The target data can be used to characterize the net loan amount of the target object within that entity object. After obtaining the target data, the entity object can determine candidate sub-data to be processed based on the risk assessment sub-threshold and the target data. After obtaining the candidate sub-data to be processed, the entity object can send the candidate sub-data to be processed to the server. Upon receiving the candidate sub-data to be processed from the entity objects corresponding to at least one entity identifier, the server can determine the data to be processed based on the candidate sub-data to be processed from the entity objects corresponding to at least one entity identifier.

[0144] According to embodiments of this disclosure, target data corresponding to at least one entity object can be (L1, L2, ..., L...). N Characterization. For example, entity object 1 can determine the target difference L1-M1 based on the target data L1 and the risk assessment sub-threshold M1, and can identify the target difference L1-M1 as candidate sub-data J1 to be processed. Entity object 2 can determine the target difference L2-M2 based on the target data L2 and the risk assessment sub-threshold M2, and can identify the target difference L2-M2 as candidate sub-data J2 to be processed.

[0145] Similarly, entity object n can be based on target data L.n and risk assessment sub-threshold M n Determine the target difference L n -M n The target difference L can be... n -M n J is identified as a candidate sub-data to be processed. n Similarly, entity object N can be based on target data L. N and risk assessment sub-threshold M N Determine the target difference L N -M N The target difference L can be... N -M N J is identified as a candidate sub-data to be processed. N In this case, the total net loans of the target group can be represented by L, where L = L1 + L2 + ... + L N .

[0146] Figure 4 The illustration shows an example of a process of sending a first set of sub-data to be processed to a first computing node and a second set of sub-data to be processed to a second computing node according to an embodiment of the present disclosure.

[0147] like Figure 4 As shown, in 400, taking server S_1, first computing node C_1 and second computing node C_2 as examples, at least one entity object may include entity object B_1, entity object B_2, ..., entity object B_n, ..., entity object B_N.

[0148] For example, risk assessment sub-threshold M1 can be sent to entity object B_1 corresponding to entity identifier B1, risk assessment sub-threshold M2 can be sent to entity object B_2 corresponding to entity identifier B2, ..., risk assessment sub-threshold M... n Send to entity identifier B n The corresponding entity objects B_n, ..., will have risk assessment sub-thresholds M. N Send to entity identifier B N The corresponding entity object B_N.

[0149] Entity object B_1 can determine the target difference L1-M1 based on the target data L1 and the risk assessment sub-threshold M1, and designate the target difference L1-M1 as candidate sub-data J1 to be processed. Entity object B_1 can send the candidate sub-data J1 to the first computing node C_1.

[0150] Entity object B_N / 2 can be based on target data L N / 2 and risk assessment sub-threshold M N / 2 Determine the target difference L N / 2 -MN / 2 , target difference L N / 2 -M N / 2 L was identified as a candidate sub-data to be processed. N / 2 Entity object B_N / 2 can handle candidate sub-data J to be processed. N / 2 Send to the first computing node C_1.

[0151] Entity object B_(N / 2+1) can be based on target data L (N / 2+1) and risk assessment sub-threshold M (N / 2+1) Determine the target difference L (N / 2+1) -M (N / 2+1) , target difference L (N / 2+1) -M (N / 2+1) J is identified as a candidate sub-data to be processed. (N / 2+1) Entity object B_(N / 2+1) can process candidate sub-data J. (N / 2+1) Send to the first compute node C_2.

[0152] Entity object B_N can be based on target data L N and risk assessment sub-threshold M N Determine the target difference L N -M N , target difference L N -M N J is identified as a candidate sub-data to be processed. N Entity object B_N can process candidate sub-data J. N Send to the first compute node C_2.

[0153] According to embodiments of this disclosure, operation S260 may include the following operations.

[0154] Based on a predetermined algorithm, the first and second evaluation values ​​are processed to obtain a comparison result. If the comparison result indicates that the first evaluation value is greater than the second evaluation value, the object risk assessment result is determined to be that the target object has passed the object risk assessment. If the comparison result indicates that the first evaluation value is less than or equal to the second evaluation value, the object risk assessment result is determined to be that the target object has failed the object risk assessment.

[0155] According to embodiments of this disclosure, after obtaining the first evaluation value and the second evaluation value, the first evaluation value and the second evaluation value can be processed based on a predetermined algorithm. The predetermined algorithm may include one of the following: a privacy comparison algorithm or a multi-party secure computation algorithm. Alternatively, after obtaining the first evaluation value and the second evaluation value, the first computing node and the second computing node may also directly process the first evaluation value and the second evaluation value based on the predetermined algorithm.

[0156] For example, S1 can be used to represent the first evaluation value, and S2 can be used to represent the second evaluation value. The first computing node can determine the public key and inform the second computing node of the public key. The second computing node can determine a random integer x, encrypt x using the public key, and obtain ciphertext K. The second computing node can calculate c = K - S2 based on the ciphertext K and the second evaluation value S2. The second computing node can then send c to the first computing node.

[0157] According to embodiments of this disclosure, after receiving c, the first computing node can decrypt c+1, c+2, ..., c+10 respectively to obtain c1, c2, ...c 10 The first computation node can be a prime number p of appropriate size, where c1, c2, ..., c 10 The remainders obtained by dividing each of them by a prime number p are denoted as d1, d2, ..., dp. 10 d j = x mod p. The first compute node can be x mod p. 10 The first S1 values ​​remain unchanged, and d1, d2, ..., d... 10 Increment the value after S1 to get d1′, d2′, ..., d 10 The first computation node can compute d1′, d2′, ..., d′. 10 Send to the second computing node.

[0158] According to embodiments of this disclosure, the second computing node can receive d1′, d2′, ..., d 10 After that, check the S2-th value. If the value is equal to x mod p, we can determine that the value was not incremented by one, so S1 > S2. If the value is not equal to x mod p, we can determine that the value was incremented by one, so S1 ≤ S2.

[0159] According to embodiments of this disclosure, the object risk assessment method 200 may further include the following operations.

[0160] If the object risk assessment result indicates that the target object has passed the object risk assessment, a prompt message will be output granting permission to execute the business request. If the object risk assessment result indicates that the target object has failed the object risk assessment, a warning message will be output prohibiting the execution of the business request.

[0161] According to embodiments of this disclosure, when the comparison result indicates that the first assessment value S1 is less than or equal to the second assessment value S2, i.e., S1≤S2, the inequality rule shows that S1-S2≤0, and S1-S2=LM, thus it can be deduced that LM≤0, i.e., L≤M. It can be determined that the net loan amount of the target object exceeds the risk assessment threshold, and an object risk assessment result indicating that the target object has not passed the object risk assessment can be obtained. In this case, a prompt message requesting permission to execute the business can be output.

[0162] According to embodiments of this disclosure, when the comparison result indicates that the first assessment value S1 is greater than the second assessment value S2, i.e., S1 > S2, the inequality rule shows that S1 - S2 > 0, and S1 - S2 = LM. Therefore, it can be deduced that LM > 0, i.e., L > M. It can be determined that the net loan amount of the target object exceeds the risk assessment threshold, and an object risk assessment result indicating that the target object has failed the object risk assessment can be obtained. In this case, a warning message prohibiting the execution of business requests can be output.

[0163] Figure 5 The illustration shows an example schematic diagram of an object risk assessment process according to an embodiment of the present disclosure.

[0164] like Figure 5 As shown in 500, in response to receiving a service request 501, the pending data 502 corresponding to the object identifier 501_1 in the service request 501 can be obtained. The pending data 502 may include a first pending sub-data set 502_1 and a second pending sub-data set 502_2.

[0165] The first sub-data set to be processed 502_1 can be sent to the first computing node, and the first evaluation value 503 can be received from the first computing node. The second sub-data set to be processed 502_2 can be sent to the second computing node, and the second evaluation value 504 can be received from the second computing node.

[0166] After obtaining the first evaluation value 503 and the second evaluation value 504, the first evaluation value 503 and the second evaluation value 504 can be processed based on a predetermined algorithm to obtain a comparison result 505. After obtaining the comparison result 505, operation S510 can be executed.

[0167] In operation S510, is the first evaluation value less than or equal to the second evaluation value?

[0168] If so, the object risk assessment result 506, indicating that the target object has passed the object risk assessment, can be determined. If the object risk assessment result 506 indicates that the target object has passed the object risk assessment, a prompt message 507 can be output to grant permission to execute the business request.

[0169] If not, then it can be determined that the target object has failed the object risk assessment (result 508). If object risk assessment result 508 indicates that the target object has failed the object risk assessment, a warning message (509) prohibiting the execution of business requests can be output.

[0170] Figure 6 A flowchart illustrating an object risk assessment method according to another embodiment of this disclosure is shown schematically.

[0171] like Figure 6 As shown, the object risk assessment method 600 includes operations S610 to S630.

[0172] In operation S610, a first set of sub-data to be processed is received from the server, wherein the first set of sub-data to be processed includes at least one first sub-data to be processed.

[0173] In operation S620, at least one first sub-data to be processed is processed to obtain a first evaluation value.

[0174] In operation S630, the first assessment value is sent to the server so that the server can perform an object risk assessment on the target object based on the first assessment value.

[0175] According to embodiments of this disclosure, the object risk assessment method 600 can be applied to a first computing node. The first computing node may include a first network node and a first router.

[0176] According to embodiments of this disclosure, a first computing node can receive a first set of sub-data to be processed from a server. After receiving the first set of sub-data to be processed, the first computing node can process the first set of sub-data to be processed to obtain a first evaluation value. After obtaining the first evaluation value, the first computing node can send the first evaluation value to the server so that the server can perform an object risk assessment on the target object based on the first evaluation value.

[0177] According to embodiments of this disclosure, operation S620 may include the following operations.

[0178] At least one first sub-data to be processed is accumulated to obtain a first accumulated value. Based on the first accumulated value, a first evaluation value is determined.

[0179] According to embodiments of this disclosure, as described above, at least one first sub-data to be processed may include J1, J2, ..., J... N / 2 The first computing node can be represented by C1. The first computing node C1 can handle at least one first sub-data J1, J2, ..., J... N / 2 Perform accumulation processing to obtain the first accumulated value J1+J2+...+JN / 2 It can be calculated based on the first accumulated value J1+J2+...+J N / 2 Determine the first evaluation value S1 = J1 + J2 + ... + J N / 2 .

[0180] Figure 7 A flowchart illustrating an object risk assessment method according to another embodiment of this disclosure is shown schematically.

[0181] like Figure 7 As shown, the risk assessment method for this object includes operations S710 to S730.

[0182] In operation S710, a second set of sub-data to be processed is received from the server, wherein the second set of sub-data to be processed includes at least one second sub-data to be processed.

[0183] In operation S720, at least one second sub-data to be processed is processed to obtain a second evaluation value.

[0184] During operation S730, the second assessment value is sent to the server so that the server can perform object risk assessment on the target object based on the second assessment value.

[0185] According to embodiments of this disclosure, the object risk assessment method 700 can be applied to a second computing node. The second computing node may include a second network node and a second router.

[0186] According to embodiments of this disclosure, a second computing node can receive a second set of sub-data to be processed from a server. After receiving the second set of sub-data to be processed, the second computing node can process the second set of sub-data to obtain a second evaluation value. After obtaining the second evaluation value, the second computing node can send the second evaluation value to the server so that the server can perform an object risk assessment on the target object based on the second evaluation value.

[0187] According to embodiments of this disclosure, operation S720 may include the following operations.

[0188] At least one second sub-data to be processed is accumulated to obtain a second accumulated value.

[0189] The second evaluation value is determined based on the second accumulated value.

[0190] According to embodiments of this disclosure, as described above, at least one second sub-data to be processed may include -J (N / 2)+1 -J (N / 2)+2 ,...,-J N The second computing node can be represented using C2. The second computing node C2 can handle at least one second sub-data item to be processed, and may include -J. (N / 2)+1-J (N / 2)+2 ,...,-J N The accumulation process is performed to obtain the second accumulated value -J. (N / 2)+1 -J (N / 2)+2 ...-J N It can be based on the second accumulated value -J (N / 2)+1 -J (N / 2)+2 ...-J N Determine the second evaluation value S2 = -J (N / 2)+1 -J (N / 2)+2 ...-J N .

[0191] Figure 8 The illustration shows an example schematic diagram of an object risk assessment process according to another embodiment of the present disclosure.

[0192] like Figure 8 As shown, in 800, the object risk assessment process may include operations S801 to S814.

[0193] When operating S801, the server responds to the received business request and can obtain the data to be processed corresponding to the object identifier in the business request.

[0194] When operating S802, the server can send the first set of sub-data to be processed to the first computing node.

[0195] When operating S803, the first compute node can receive the first set of sub-data to be processed from the server.

[0196] In operation S804, the first computing node can perform accumulation processing on at least one first sub-data to be processed to obtain a first accumulated value.

[0197] In operation S805, the first computing node can determine the first evaluation value based on the first accumulated value.

[0198] When operating S806, the first computing node can send the first evaluation value to the server.

[0199] When operating S807, the server can receive the first evaluation value from the first computing node.

[0200] When operating S808, the server can send the second set of data to be processed to the second computing node.

[0201] When operating S809, the second computing node can receive a second set of sub-data to be processed from the server.

[0202] In operation S810, the second computing node can perform accumulation processing on at least one second sub-data to be processed to obtain a second accumulated value.

[0203] In operation S811, the second computing node can determine the second evaluation value based on the second accumulated value.

[0204] When operating S812, the second computing node can send the second evaluation value to the server.

[0205] When operating S813, the server can receive a second evaluation value from the second computing node.

[0206] In operation S814, the server can determine the object risk assessment result corresponding to the object identifier based on the first assessment value and the second assessment value.

[0207] The above are merely exemplary embodiments, but are not limited thereto. Other object risk assessment methods known in the art may also be included, as long as they can ensure the security and real-time performance of data processing and improve the accuracy of object risk assessment.

[0208] Figure 9 A block diagram of an object risk assessment apparatus according to an embodiment of the present disclosure is shown schematically.

[0209] like Figure 9 As shown, the object risk assessment device 900 applied to the server may include a first acquisition module 910, a first sending module 920, a first receiving module 930, a second sending module 940, a second receiving module 950, and a determination module 960.

[0210] The first acquisition module 910 is used to respond to a received business request and acquire the data to be processed corresponding to the object identifier in the business request. The object identifier is used to represent the target object, and the data to be processed includes a first set of sub-data to be processed and a second set of sub-data to be processed.

[0211] The first sending module 920 is used to send the first set of sub-data to be processed to the first computing node.

[0212] The first receiving module 930 is used to receive a first evaluation value from the first computing node, wherein the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed.

[0213] The second sending module 940 is used to send the second set of sub-data to be processed to the second computing node.

[0214] The second receiving module 950 is used to receive a second evaluation value from the second computing node, wherein the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed.

[0215] The determination module 960 is used to determine the object risk assessment result corresponding to the object identifier based on the first assessment value and the second assessment value.

[0216] According to embodiments of this disclosure, the first acquisition module 910 may include a first acquisition unit, a first determination unit, a first processing unit, a first sending unit, a first receiving unit, and a second determination unit.

[0217] The first acquisition unit is used to, in response to receiving a business request, acquire a risk assessment threshold corresponding to the object identifier and at least one entity identifier based on the object identifier.

[0218] The first determining unit is used to determine the number of entities corresponding to the object identifier based on at least one entity identifier.

[0219] The first processing unit is used to split the risk assessment threshold according to the number of entities to obtain at least one risk assessment sub-threshold.

[0220] The first sending unit is used to send at least one risk assessment sub-threshold to the entity object corresponding to at least one entity identifier.

[0221] The first receiving unit is used to receive candidate sub-data to be processed from entity objects corresponding to at least one entity identifier.

[0222] The second determining unit is used to determine the data to be processed based on the candidate data to be processed of the entity objects corresponding to at least one entity identifier.

[0223] According to embodiments of this disclosure, the second determining unit may include a first determining subunit, a second determining subunit, a processing subunit, and a third determining subunit.

[0224] The first determining sub-unit is used to determine at least one first sub-data to be processed and at least one second sub-data to be processed from the candidate sub-data to be processed of entity objects corresponding to at least one entity identifier.

[0225] The second determining sub-unit is used to determine the first set of sub-data to be processed based on at least one first sub-data to be processed.

[0226] The processing subunit is used to perform inversion processing on each of the at least one second sub-data to be processed to obtain a third sub-data to be processed.

[0227] The third determining sub-unit is used to determine the set of second sub-data to be processed based on the third sub-data to be processed corresponding to each of the at least one second sub-data to be processed.

[0228] According to embodiments of this disclosure, candidate sub-data to be processed can be obtained in the following manner.

[0229] For each entity identifier in at least one entity identifier, determine the target data corresponding to that entity identifier. Based on the risk assessment sub-threshold and the target data, determine the target difference. Identify the target difference as candidate sub-data to be processed.

[0230] According to embodiments of this disclosure, the determining module 960 may include a second processing unit, a third determining unit, and a fourth determining unit.

[0231] The second processing unit is used to process the first evaluation value and the second evaluation value based on a predetermined algorithm to obtain a comparison result.

[0232] The third determining unit is used to determine the object risk assessment result that the target object has failed the object risk assessment when the comparison result indicates that the first assessment value is greater than the second assessment value.

[0233] The fourth determining unit is used to determine the object risk assessment result indicating that the target object has not passed the object risk assessment when the comparison result indicates that the first assessment value is less than or equal to the second assessment value.

[0234] According to embodiments of this disclosure, the object risk assessment device 900 applied to the server may further include a first output unit and a second output unit.

[0235] The first output unit is used to output a prompt message indicating that the target object has passed the object risk assessment, when the object risk assessment result indicates that the target object has passed the object risk assessment.

[0236] The second output unit is used to output a warning message prohibiting the execution of business requests when the object risk assessment result indicates that the target object has failed the object risk assessment.

[0237] Figure 10 A block diagram of an object risk assessment apparatus according to another embodiment of the present disclosure is shown schematically.

[0238] like Figure 10 As shown, the object risk assessment device 1000 applied to the first computing node may include a third receiving module 1010, a first processing module 1020 and a third sending module 1030.

[0239] The third receiving module 1010 is used to receive a first set of sub-data to be processed from the server, wherein the first set of sub-data to be processed includes at least one first sub-data to be processed.

[0240] The first processing module 1020 is used to process at least one first sub-data to be processed to obtain a first evaluation value.

[0241] The third sending module 1030 is used to send the first evaluation value to the server so that the server can perform object risk assessment on the target object based on the first evaluation value.

[0242] According to embodiments of this disclosure, the first processing module 1020 may include a third processing unit and a fifth determining unit.

[0243] The third processing unit is used to perform accumulation processing on at least one first sub-data to be processed to obtain a first accumulated value.

[0244] The fifth determining unit is used to determine the first evaluation value based on the first accumulated value.

[0245] Figure 11 A block diagram of an object risk assessment apparatus according to another embodiment of the present disclosure is shown schematically.

[0246] like Figure 11 As shown, the object risk assessment device 1100 applied to the second computing node may include a fourth receiving module 1110, a second processing module 1120, and a fourth sending module 1130.

[0247] The fourth receiving module 1110 is used to receive a second set of sub-data to be processed from the server, wherein the second set of sub-data to be processed includes at least one second sub-data to be processed.

[0248] The second processing module 1120 is used to process at least one second sub-data to obtain a second evaluation value.

[0249] The fourth sending module 1130 is used to send the second evaluation value to the server so that the server can perform object risk assessment on the target object based on the second evaluation value.

[0250] According to embodiments of this disclosure, the second processing module 1120 may include a fourth processing unit and a sixth determining unit.

[0251] The fourth processing unit is used to perform accumulation processing on at least one second sub-data to be processed to obtain a second accumulated value.

[0252] The sixth determining unit is used to determine the second evaluation value based on the second accumulated value.

[0253] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as Field Programmable Gate Arrays (FPGAs), Programmable Logic Arrays (PLAs), Systems-on-Chip, Systems-on-Substrate, Systems-on-Package, Application-Specific Integrated Circuits (ASICs), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0254] For example, any multiple of the first acquisition module 910, first transmission module 920, first reception module 930, second transmission module 940, second reception module 950, and determination module 960 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least some of the functions of one or more of these modules / units / subunits can be combined with at least some of the functions of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the first acquisition module 910, the first transmission module 920, the first receiving module 930, the second transmission module 940, the second receiving module 950, and the determination module 960 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable method of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the first acquisition module 910, the first transmission module 920, the first receiving module 930, the second transmission module 940, the second receiving module 950, and the determination module 960 can be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.

[0255] For example, any plurality of the third receiving module 1010, the first processing module 1020, and the third transmitting module 1030 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the third receiving module 1010, the first processing module 1020, and the third transmitting module 1030 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the third receiving module 1010, the first processing module 1020, and the third sending module 1030 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0256] For example, any plurality of the fourth receiving module 1110, the second processing module 1120, and the fourth transmitting module 1130 may be combined into one module / unit / subunit, or any one of these modules / units / subunits may be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits may be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of the present disclosure, at least one of the fourth receiving module 1110, the second processing module 1120, and the fourth transmitting module 1130 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the fourth receiving module 1110, the second processing module 1120, and the fourth sending module 1130 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0257] It should be noted that the object risk assessment device part in the embodiments of this disclosure corresponds to the object risk assessment method part in the embodiments of this disclosure. The description of the object risk assessment device part is specifically referred to in the object risk assessment method part, and will not be repeated here.

[0258] Figure 12 A block diagram of an electronic device suitable for implementing an object risk assessment method according to an embodiment of the present disclosure is shown schematically. Figure 12 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0259] like Figure 12 As shown, a computer electronic device 1200 according to an embodiment of the present disclosure includes a processor 1201, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1202 or a program loaded from a storage portion 1209 into a random access memory (RAM) 1203. The processor 1201 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1201 may also include onboard memory for caching purposes. The processor 1201 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0260] RAM 1203 stores various programs and data required for the operation of electronic device 1200. Processor 1201, ROM 1202, and RAM 1203 are interconnected via bus 1204. Processor 1201 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 1202 and / or RAM 1203. It should be noted that the programs may also be stored in one or more memories other than ROM 1202 and RAM 1203. Processor 1201 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0261] According to embodiments of this disclosure, the electronic device 1200 may further include an input / output (I / O) interface 1205, which is also connected to the bus 1204. The electronic device 1200 may also include one or more of the following components connected to the I / O interface 1205: an input section 1206 including a keyboard, mouse, etc.; an output section 1207 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1208 including a hard disk, etc.; and a communication section 1209 including a network interface card such as a LAN card, modem, etc. The communication section 1209 performs communication processing via a network such as the Internet. A drive 1210 is also connected to the I / O interface 1205 as needed. A removable medium 1211, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 1210 as needed so that computer programs read from it can be installed into the storage section 1208 as needed.

[0262] According to embodiments of this disclosure, the method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1209, and / or installed from removable medium 1211. When the computer program is executed by processor 1201, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0263] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0264] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0265] For example, according to embodiments of this disclosure, a computer-readable storage medium may include the ROM 1202 and / or RAM 1203 described above and / or one or more memories other than ROM 1202 and RAM 1203.

[0266] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the object risk assessment method provided in the embodiments of this disclosure.

[0267] When the computer program is executed by the processor 1201, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0268] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 1209, and / or installed from the removable medium 1211. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0269] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0270] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features recited in the various embodiments and / or claims of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not expressly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0271] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. An object risk assessment method, applied on the server side, comprising: In response to receiving a business request, based on the object identifier in the business request, obtain a risk assessment threshold corresponding to the object identifier and at least one entity identifier, wherein the object identifier is used to characterize the target object; Based on the at least one entity identifier, determine the number of entities corresponding to the object identifier; Based on the number of entities, the risk assessment threshold is split to obtain at least one risk assessment sub-threshold; Send the at least one risk assessment sub-threshold to the entity object corresponding to each of the at least one entity identifier; The system receives candidate sub-data to be processed from entity objects corresponding to each of the at least one entity identifier. The candidate sub-data to be processed is obtained by: determining target data corresponding to each entity identifier; determining a target difference based on the risk assessment sub-threshold and the target data; and determining the target difference as the candidate sub-data to be processed. Based on the candidate sub-data to be processed corresponding to the entity objects of the at least one entity identifier, the data to be processed is determined, the data to be processed includes a first set of sub-data to be processed and a second set of sub-data to be processed, the second set of sub-data to be processed is determined based on a third set of sub-data to be processed obtained by inverting the second sub-data in the candidate sub-data to be processed; Send the first set of sub-data to be processed to the first computing node; Receive a first evaluation value from the first computing node, wherein the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed; Send the second set of sub-data to be processed to the second computing node; Receive a second evaluation value from the second computing node, wherein the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed; and Based on the first assessment value and the second assessment value, the object risk assessment result corresponding to the object identifier is determined.

2. The method according to claim 1, wherein, The step of determining the data to be processed based on the candidate data to be processed of the entity objects corresponding to each of the at least one entity identifier includes: Among the candidate sub-data to be processed of the entity objects corresponding to the at least one entity identifier, at least one first sub-data to be processed and at least one second sub-data to be processed are determined. The first set of sub-data to be processed is determined based on the at least one first sub-data to be processed; For each of the at least one second sub-data to be processed, The second sub-data to be processed is inverted to obtain the third sub-data to be processed; and The set of second sub-data to be processed is determined based on the third sub-data to be processed corresponding to each of the at least one second sub-data to be processed.

3. The method according to claim 1 or 2, wherein, The step of determining the object risk assessment result corresponding to the object identifier based on the first assessment value and the second assessment value includes: Based on a predetermined algorithm, the first evaluation value and the second evaluation value are processed to obtain a comparison result; If the comparison result indicates that the first evaluation value is greater than the second evaluation value, then the object risk assessment result indicating that the target object has failed the object risk assessment is determined; and If the comparison result indicates that the first evaluation value is less than or equal to the second evaluation value, the object risk assessment result indicating that the target object has passed the object risk assessment is determined.

4. The method according to claim 1 or 2, further comprising, after determining the object risk assessment result corresponding to the object identifier based on the first assessment value and the second assessment value: If the object risk assessment result indicates that the target object has passed the object risk assessment, a prompt message indicating permission to execute the business request will be output; and If the object risk assessment result indicates that the target object has failed the object risk assessment, a warning message is output prohibiting the execution of the business request.

5. An object risk assessment method, applied to a first computing node, comprising: Receive a first set of sub-data to be processed from the server, wherein the first set of sub-data to be processed includes at least one first sub-data to be processed; The at least one first sub-data to be processed is processed to obtain a first evaluation value; and The first assessment value is sent to the server so that the server can perform an object risk assessment on the target object based on the first assessment value. The server is used for: In response to receiving a business request, based on the object identifier in the business request, obtain a risk assessment threshold corresponding to the object identifier and at least one entity identifier, wherein the object identifier is used to characterize the target object; Based on the at least one entity identifier, determine the number of entities corresponding to the object identifier; Based on the number of entities, the risk assessment threshold is split to obtain at least one risk assessment sub-threshold; Send the at least one risk assessment sub-threshold to the entity object corresponding to each of the at least one entity identifier; The system receives candidate sub-data to be processed from entity objects corresponding to each of the at least one entity identifier. The candidate sub-data to be processed is obtained by: determining target data corresponding to each entity identifier; determining a target difference based on the risk assessment sub-threshold and the target data; and determining the target difference as the candidate sub-data to be processed. Based on candidate sub-data to be processed corresponding to the entity objects of each of the at least one entity identifier, data to be processed is determined, wherein the data to be processed includes a first set of sub-data to be processed and a second set of sub-data to be processed, the second set of sub-data to be processed being determined based on a third set of sub-data to be processed obtained by inverting the second set of sub-data in the candidate sub-data to be processed; and The first set of sub-data to be processed is sent to the first computing node.

6. The method according to claim 5, wherein, The process of processing the at least one first sub-data to be processed to obtain the first evaluation value includes: The at least one first sub-data to be processed is accumulated to obtain a first accumulated value; and The first evaluation value is determined based on the first accumulated value.

7. An object risk assessment method, applied to a second computing node, comprising: Receive a second set of sub-data to be processed from the server, wherein the second set of sub-data to be processed includes at least one second sub-data to be processed; The at least one second sub-data to be processed is processed to obtain a second evaluation value; and The second assessment value is sent to the server so that the server can perform an object risk assessment on the target object based on the second assessment value. The server is used for: In response to receiving a business request, based on the object identifier in the business request, obtain a risk assessment threshold corresponding to the object identifier and at least one entity identifier, wherein the object identifier is used to characterize the target object; Based on the at least one entity identifier, determine the number of entities corresponding to the object identifier; Based on the number of entities, the risk assessment threshold is split to obtain at least one risk assessment sub-threshold; Send the at least one risk assessment sub-threshold to the entity object corresponding to each of the at least one entity identifier; The system receives candidate sub-data to be processed from entity objects corresponding to each of the at least one entity identifier. The candidate sub-data to be processed is obtained by: determining target data corresponding to each entity identifier; determining a target difference based on the risk assessment sub-threshold and the target data; and determining the target difference as the candidate sub-data to be processed. Based on candidate sub-data to be processed corresponding to the entity objects of each of the at least one entity identifier, data to be processed is determined, wherein the data to be processed includes a first set of sub-data to be processed and a second set of sub-data to be processed, the second set of sub-data to be processed being determined based on a third set of sub-data to be processed obtained by inverting the second set of sub-data in the candidate sub-data to be processed; and The second set of data to be processed is sent to the second computing node.

8. The method according to claim 7, wherein, The process of processing the at least one second sub-data to be processed to obtain the second evaluation value includes: The at least one second sub-data to be processed is accumulated to obtain a second accumulated value; and The second evaluation value is determined based on the second accumulated value.

9. An object risk assessment device, applied on a server side, comprising: The first acquisition unit is configured to, in response to receiving a business request, acquire a risk assessment threshold corresponding to the object identifier and at least one entity identifier based on the object identifier in the business request, wherein the object identifier is used to characterize the target object; The first determining unit is configured to determine the number of entities corresponding to the object identifier based on the at least one entity identifier; The first processing unit is used to split the risk assessment threshold according to the number of entities to obtain at least one risk assessment sub-threshold. The first sending unit is used to send the at least one risk assessment sub-threshold to the entity object corresponding to each of the at least one entity identifier; The first receiving unit is configured to receive candidate sub-data to be processed from entity objects corresponding to each of the at least one entity identifier. The candidate sub-data to be processed is obtained by: determining target data corresponding to each entity identifier for each entity identifier; determining a target difference based on the risk assessment sub-threshold and the target data; and determining the target difference as the candidate sub-data to be processed. The second determining unit is used to determine the data to be processed based on the candidate data to be processed of the entity objects corresponding to each of the at least one entity identifier. The data to be processed includes a first set of data to be processed and a second set of data to be processed. The second set of data to be processed is determined based on the third data to be processed obtained by inverting the second data to be processed in the candidate data to be processed. The first sending module is used to send the first set of sub-data to be processed to the first computing node; The first receiving module is configured to receive a first evaluation value from the first computing node, wherein the first evaluation value is obtained by the first computing node processing the first sub-data set to be processed; The second sending module is used to send the second set of sub-data to be processed to the second computing node; The second receiving module is configured to receive a second evaluation value from the second computing node, wherein the second evaluation value is obtained by the second computing node processing the second sub-data set to be processed; and The determination module is used to determine the object risk assessment result corresponding to the object identifier based on the first assessment value and the second assessment value.

10. An object risk assessment device, applied to a first computing node, comprising: The third receiving module is used to receive a first set of sub-data to be processed from the server, wherein the first set of sub-data to be processed includes at least one first sub-data to be processed; A first processing module is configured to process the at least one first sub-data to be processed to obtain a first evaluation value; and The third sending module is used to send the first evaluation value to the server so that the server can perform object risk assessment on the target object based on the first evaluation value. The server is used for: In response to receiving a business request, based on the object identifier in the business request, obtain a risk assessment threshold corresponding to the object identifier and at least one entity identifier, wherein the object identifier is used to characterize the target object; Based on the at least one entity identifier, determine the number of entities corresponding to the object identifier; Based on the number of entities, the risk assessment threshold is split to obtain at least one risk assessment sub-threshold; Send the at least one risk assessment sub-threshold to the entity object corresponding to each of the at least one entity identifier; The system receives candidate sub-data to be processed from entity objects corresponding to each of the at least one entity identifier. The candidate sub-data to be processed is obtained by: determining target data corresponding to each entity identifier; determining a target difference based on the risk assessment sub-threshold and the target data; and determining the target difference as the candidate sub-data to be processed. Based on candidate sub-data to be processed corresponding to the entity objects of each of the at least one entity identifier, data to be processed is determined, wherein the data to be processed includes a first set of sub-data to be processed and a second set of sub-data to be processed, the second set of sub-data to be processed being determined based on a third set of sub-data to be processed obtained by inverting the second set of sub-data in the candidate sub-data to be processed; and The first set of sub-data to be processed is sent to the first computing node.

11. An object risk assessment device, applied to a second computing node, comprising: The fourth receiving module is used to receive a second set of sub-data to be processed from the server, wherein the second set of sub-data to be processed includes at least one second sub-data to be processed; The second processing module is used to process the at least one second sub-data to be processed to obtain a second evaluation value; and The fourth sending module is used to send the second evaluation value to the server so that the server can perform an object risk assessment on the target object based on the second evaluation value. The server is used for: In response to receiving a business request, based on the object identifier in the business request, obtain a risk assessment threshold corresponding to the object identifier and at least one entity identifier, wherein the object identifier is used to characterize the target object; Based on the at least one entity identifier, determine the number of entities corresponding to the object identifier; Based on the number of entities, the risk assessment threshold is split to obtain at least one risk assessment sub-threshold; Send the at least one risk assessment sub-threshold to the entity object corresponding to each of the at least one entity identifier; The system receives candidate sub-data to be processed from entity objects corresponding to each of the at least one entity identifier. The candidate sub-data to be processed is obtained by: determining target data corresponding to each entity identifier; determining a target difference based on the risk assessment sub-threshold and the target data; and determining the target difference as the candidate sub-data to be processed. Based on candidate sub-data to be processed corresponding to the entity objects of each of the at least one entity identifier, data to be processed is determined, wherein the data to be processed includes a first set of sub-data to be processed and a second set of sub-data to be processed, the second set of sub-data to be processed being determined based on a third set of sub-data to be processed obtained by inverting the second set of sub-data in the candidate sub-data to be processed; and The second set of data to be processed is sent to the second computing node.

12. An electronic device, comprising: One or more processors; Memory, used to store one or more instructions. Wherein, when the one or more instructions are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 4, any one of claims 5 to 6, or any one of claims 7 to 8.

13. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 4, any one of claims 5 to 6, or any one of claims 7 to 8.

14. A computer program product comprising computer-executable instructions, which, when executed, are used to implement the method of any one of claims 1 to 4, any one of claims 5 to 6, or any one of claims 7 to 8.

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