CN112348675A

CN112348675A - Intelligent risk assessment method and device for providing standardized comments and electronic equipment

Info

Publication number: CN112348675A
Application number: CN202011131975.XA
Authority: CN
Inventors: 刘寒; 王书生
Original assignee: Shanghai Qiyue Information Technology Co Ltd
Current assignee: Shanghai Qiyue Information Technology Co Ltd
Priority date: 2020-10-21
Filing date: 2020-10-21
Publication date: 2021-02-09

Abstract

The invention provides an intelligent risk assessment method and device for providing standardized comments and electronic equipment. The method comprises the following steps: establishing a risk comment knowledge base according to a risk auditing strategy and historical business data, wherein the risk comment knowledge base comprises a risk analysis rule and a risk comment rule; acquiring a risk case according to the risk analysis rule, and carrying out risk splitting on the risk case; generating a standardized comment corresponding to the risk case according to the risk comment rule; and automatically forming a comprehensive risk assessment result based on the standardized comments. The invention can realize the intelligent auditing auxiliary function and can give consideration to the accuracy and auditing efficiency of manual processing results; the manual judgment time is saved, and the manual auditing efficiency is improved; the problems of non-standard operation, risk omission and low efficiency caused by the existing mode of manually mining risk information data and remarking are solved.

Description

Intelligent risk assessment method and device for providing standardized comments and electronic equipment

Technical Field

The invention relates to the field of computer information processing, in particular to an intelligent risk assessment method and device for providing standardized comments and electronic equipment.

Background

Risk control (wind control for short) means that a risk manager takes various measures and methods to eliminate or reduce various possibilities of occurrence of a risk case, or a risk controller reduces losses caused when a risk case occurs. The risk control is generally applied to the financial industry, such as risk control on company transactions, merchant transactions or personal transactions and the like.

In the prior art, the main purpose of financial risk assessment is how to distinguish good customers from bad customers, and assess the risk condition of users, so as to reduce financial risk and realize profit maximization. In fact, as an important part of the auditing process, good risk assessment plays an indispensable role in improving the processing accuracy, the operation normalization and the note readability of the wind control personnel. At present, wind control personnel need to identify case risk points independently for auditing and manually add annotation contents, but the annotation form is inconvenient for subsequent case review and risk tracking.

Therefore, there is a need for an intelligent risk assessment method that can provide standardized comments.

Disclosure of Invention

The method aims to solve the problems of non-standard operation, risk omission and efficiency caused by the existing mode of manually mining risk information data and remarking. The invention provides an intelligent risk assessment method for providing standardized comments, which is used for automatically assessing risk of risk cases in business and comprises the following steps: establishing a risk comment knowledge base according to a risk auditing strategy and historical business data, wherein the risk comment knowledge base comprises a risk analysis rule and a risk comment rule; acquiring a risk case according to the risk analysis rule, and carrying out risk splitting on the risk case; generating a standardized comment corresponding to the risk case according to the risk comment rule; and automatically forming a comprehensive risk assessment result based on the standardized comments.

Preferably, the risk analysis rules include: the risk analysis method comprises a risk case screening rule and identification rules of risk points and risk features in risk cases, wherein the risk case screening rule is used for classifying the risk cases to determine the risk cases to be analyzed.

Preferably, the risk splitting the risk case comprises: risk splitting the risk case to form a plurality of risk factors.

Preferably, the risk annotation rules comprise annotation rules corresponding to each risk factor.

Preferably, according to the risk comment rule, generating a standardized comment corresponding to a risk case comprises: and identifying abnormal patterns in the risk factors according to the risk comment rules, and generating corresponding standardized comments according to the abnormal patterns.

Preferably, said automatically forming a composite risk assessment result based on said standardized comments comprises: and combining the multiple standardized comments of different factors to generate a comprehensive standardized comment as a comprehensive risk assessment result.

Preferably, the method further comprises the following steps: configuring a merging rule, wherein the merging rule comprises a many-to-one corresponding relation, a one-to-one corresponding relation, a many-to-many corresponding relation and a priority order; and carrying out merging and matching processing according to the many-to-one corresponding relation, the one-to-one corresponding relation and the many-to-many corresponding relation, and determining an optimal sequence for merging and matching.

Preferably, the method further comprises the following steps: and providing the automatically formed comprehensive risk assessment result for the user, receiving the operation information of the user, and recording the risk assessment result confirmed by the user.

In addition, the invention also provides an intelligent risk assessment device for providing standardized comments, which is used for automatically assessing the risk of the risk case in the business, and comprises the following steps: the risk assessment system comprises an establishing module, a risk assessment module and a risk assessment module, wherein the establishing module is used for establishing a risk assessment knowledge base according to a risk audit strategy and historical business data, and the risk assessment knowledge base comprises a risk analysis rule and a risk assessment rule; the risk splitting module is used for acquiring risk cases according to the risk analysis rule and carrying out risk splitting on the risk cases; the generating module generates a standardized comment corresponding to the risk case according to the risk comment rule; and the evaluation module automatically forms a comprehensive risk evaluation result based on the standardized comments.

Preferably, the system further comprises a setting module, wherein the setting module is used for setting risk analysis rules; the risk analysis rules include: the risk analysis method comprises a risk case screening rule and identification rules of risk points and risk features in risk cases, wherein the risk case screening rule is used for classifying the risk cases to determine the risk cases to be analyzed.

Preferably, the risk splitting module further comprises: risk splitting the risk case to form a plurality of risk factors.

Preferably, the system further comprises an identification module, wherein the identification module identifies an abnormal mode in each risk factor according to the risk comment rule and generates a corresponding standardized comment according to the abnormal mode.

Preferably, the system further comprises a processing module for merging the plurality of standardized comments of different factors to generate a comprehensive standardized comment as a comprehensive risk assessment result.

In addition, the present invention also provides an electronic device, wherein the electronic device includes: a processor; and a memory storing computer-executable instructions that, when executed, cause the processor to perform the intelligent risk assessment method of providing standardized comments of the present invention.

Furthermore, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs which, when executed by a processor, implement the intelligent risk assessment method of providing standardized comments of the present invention.

Advantageous effects

Compared with the prior art, the intelligent risk assessment method realizes automatic identification of risk cases by establishing a risk comment knowledge base, ensures the accuracy of intelligent grabbing risk characteristics to the maximum extent, automatically generates standardized format comments, and recommends standardized comments and preprocessing results to assist the wind control personnel to give accurate decisions (i.e. give artificial optimal processing suggestions) after the processing of the auditing result judgment rules, thereby realizing an intelligent auditing auxiliary function and considering the accuracy and auditing efficiency of manual processing results; the manual judgment time is saved, and the manual auditing efficiency is improved; the problems of non-standard operation, risk omission and low efficiency caused by the existing mode of manually mining risk information data and remarking are solved.

Drawings

In order to make the technical problems solved by the present invention, the technical means adopted and the technical effects obtained more clear, the following will describe in detail the embodiments of the present invention with reference to the accompanying drawings. It should be noted, however, that the drawings described below are only illustrations of exemplary embodiments of the invention, from which other embodiments can be derived by those skilled in the art without inventive faculty.

FIG. 1 is a flowchart of an example of an intelligent risk assessment method of providing standardized comments, embodiment 1 of the present invention.

FIG. 2 is a flowchart of another example of an intelligent risk assessment method of providing standardized comments, embodiment 1 of the present invention.

FIG. 3 is a flowchart of yet another example of an intelligent risk assessment method of providing standardized comments, embodiment 1 of the present invention.

FIG. 4 is a schematic diagram of an example of an intelligent risk assessment device that provides standardized comments in embodiment 2 of the present invention.

FIG. 5 is a schematic diagram of another example of an intelligent risk assessment device that provides standardized comments, embodiment 2 of the present invention.

FIG. 6 is a schematic diagram of yet another example of an intelligent risk assessment device that provides standardized comments, embodiment 2 of the present invention.

Fig. 7 is a block diagram of an exemplary embodiment of an electronic device according to the present invention.

Fig. 8 is a block diagram of an exemplary embodiment of a computer-readable medium according to the present invention.

Detailed Description

Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals denote the same or similar elements, components, or parts in the drawings, and thus their repetitive description will be omitted.

Features, structures, characteristics or other details described in a particular embodiment do not preclude the fact that the features, structures, characteristics or other details may be combined in a suitable manner in one or more other embodiments in accordance with the technical idea of the invention.

In describing particular embodiments, the present invention has been described with reference to features, structures, characteristics or other details that are within the purview of one skilled in the art to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific features, structures, characteristics, or other details.

The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.

The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.

It will be understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, or sections, these terms should not be construed as limiting. These phrases are used to distinguish one from another. For example, a first device may also be referred to as a second device without departing from the spirit of the present invention.

The term "and/or" and/or "includes any and all combinations of one or more of the associated listed items.

The method aims to solve the problems of non-standard operation, risk omission and efficiency caused by the existing mode of manually mining risk information data and remarking. The invention provides an intelligent risk assessment method, which is characterized in that a risk comment knowledge base is established to automatically identify abnormal labels of risk cases, so that the accuracy of intelligent risk grabbing characteristics is guaranteed to the maximum extent, standardized format comments are automatically generated, and after the processing of a check result judgment rule, standardized comments and a preprocessing result are recommended to assist a wind control worker to give an accurate decision (namely, a manual best processing suggestion is given). The specific evaluation process will be described in detail below.

Example 1

An embodiment of the intelligent risk assessment method of the present invention that provides standardized comments will be described below with reference to fig. 1 to 3.

FIG. 1 is a flow chart of an intelligent risk assessment method of the present invention that provides standardized comments. As shown in fig. 1, an intelligent risk assessment method includes the following steps.

Step S101, establishing a risk comment knowledge base according to a risk auditing strategy and historical business data, wherein the risk comment knowledge base comprises a risk analysis rule and a risk comment rule.

And S102, acquiring a risk case according to the risk analysis rule, and carrying out risk splitting on the risk case.

And step S103, generating a standardized comment corresponding to the risk case according to the risk comment rule.

And step S104, automatically forming a comprehensive risk assessment result based on the standardized comments.

First, in step S101, a risk assessment knowledge base is established according to a risk auditing policy and historical business data, where the risk assessment knowledge base includes risk analysis rules and risk assessment rules.

In the example, a series of knowledge text data from the beginning to the end of the risk auditing process is formed according to the risk auditing strategy, historical business data, auditing related data and manual processing experience data.

Specifically, based on the knowledge text data, a combined induction is performed to form a risk comment knowledge base.

Preferably, the risk comment knowledge base can be continuously updated and iterated along with online strategies and business development, and further optimization and adjustment are performed. Such as making optimal adjustments set within a particular time period, by adding comments, modifying or deleting existing comments, etc., to gradually refine the risk comment knowledge base, thereby providing more flexibility.

Specifically, a risk comment knowledge base is established based on the knowledge text.

Further, the risk comment knowledge base comprises risk analysis rules and risk comment rules, wherein the risk analysis rules comprise risk case screening rules and identification rules of risk points and risk features in risk cases; and the risk comment rule is used for automatically generating a corresponding risk comment according to a risk analysis result.

More specifically, the risk case screening rules are used to classify risk cases to determine the risk cases to be analyzed.

In the example, the method further comprises the step of marking abnormal labels on the historical sample cases based on the risk comment knowledge base so as to realize automatic identification of the abnormal labels, and the accuracy of intelligent risk feature capturing is guaranteed to the greatest extent, so that the problems of irregular operation, risk omission, low efficiency and the like caused by manual review are avoided.

Preferably, the method further comprises performing cluster analysis on the related data of the historical risk cases to determine a plurality of risk points in the risk cases and risk coefficients thereof.

Further, risk factors corresponding to different risk points are further determined according to the risk points.

It should be noted that, for the clustering algorithm, for example, K-means algorithm, probability distribution-based algorithm, EM algorithm, etc. However, the present invention is not limited to the above, and the above description is only given as a preferable example, and the present invention is not to be construed as being limited thereto.

Next, in step S102, a risk case is obtained according to the risk analysis rule, and the risk case is risk split.

In this example, when a risk user comes, the risk cases of the risk user are obtained, filtering or screening is performed on the risk cases according to the risk case screening rule and the risk identification rule, the risk cases are identified and classified, and the risk cases to be analyzed are determined.

Further, risk splitting is carried out on the risk cases.

Specifically, the risk feature identification rule includes identifying whether there are preset risk points, the number of preset risk points, whether there are new risk points, the number of new risk points, and a risk coefficient (in the case of a plurality of preset risk points, a weighted risk coefficient). Thus, the risk features are extracted and the intelligent risk assessment device will generate corresponding annotation tags (including anomaly tags) and risk classifications.

Preferably, the screening rule includes determining whether the risk coefficient exceeds a specific threshold value, so as to screen the risk case of the current user for a non-target case and a target case (i.e. a risk case to be analyzed).

It should be noted that, for the preset risk point and the risk feature identification rule, adjustment may be performed according to the business requirement. The foregoing is by way of preferred example only and is not to be construed as limiting the present invention.

Further, risk splitting is carried out on the screened target risk cases to form a plurality of risk factors.

In this example, the risk factors include group intermediaries, false information, economic factors (i.e., indicating whether the user's economic condition is deteriorating), accidents, whether the user's account is logged on normally, and so on.

For example, for a group partner intermediary, the unusual patterns are, for example, frequent calls, a high percentage of blacklisted users in frequent contacts, or a high percentage of blacklisted users in frequent contacts, etc.

For another example, the abnormal pattern determination of the economic factor includes determining whether the economic status of a certain user is deteriorated according to no-movement behavior within a specific time (e.g., within about 6 months), whether the number of overdue times of resource return is greater than two, and the like, calculating the overdue probability or default probability of the user within about 6 months, and determining whether the overdue probability or default probability of the user within about two years is greater.

Further, for the target risk case, identifying risk points included in the case, and splitting the case into a plurality of risk factors corresponding to the risk points based on the identified risk points.

Next, in step S103, a standardized comment corresponding to a risk case is generated according to the risk comment rule.

As shown in fig. 2, a step S201 of presetting a risk comment rule is further included.

In step S201, a risk comment rule is preset. And setting risk point comments corresponding to different risk points and risk factor comments corresponding to each risk factor based on the risk auditing strategy and the cluster analysis of the historical service data.

Preferably, the auditor configures risk annotation rules according to the business requirements and the business parameters, wherein the risk annotation rules comprise annotation rules corresponding to the risk factors.

Specifically, for each risk factor, the intelligent risk assessment device generates a corresponding note or comment according to the set comment rule so as to save the event that the examiner fills in the note, optimize the note writing mode and standardize the note.

Preferably, an abnormal pattern in each risk factor is identified according to the risk comment rule, and a corresponding standardized comment is generated according to the abnormal pattern.

For example, the risk points of the target risk case include risk point d1 (risk coefficient 0.5), risk point d3 (risk coefficient 0.8), two risk points, risk point d1 includes two risk factors of factors z1 and z2, and risk point d3 includes three risk factors of factors z3, z4, and z 5.

For example, the risk factors are sorted in descending order, for example, the risk factor is sorted into a risk point d3 and a risk point d1, and each risk point comment corresponds to a risk point comment, and each risk point comment includes a weighted risk factor, the number of risk factors, and a comment of each risk factor. In this example, the target risk event includes two risk point comments and five risk factor comments. Thereby, a standardized comment corresponding to the target risk case is generated.

Next, in step S104, a composite risk assessment result is automatically formed based on the standardized comments.

In this example, multiple standardized comments for different factors are combined to generate a generalized standardized comment as a composite risk assessment result.

As shown in fig. 3, a step S301 of configuring a merge rule is further included.

In step S301, a merge rule is configured. Specifically, the merge rule includes a many-to-one correspondence, a one-to-one correspondence, a many-to-many correspondence, and a priority order.

Specifically, the merging and matching process is performed according to the many-to-one correspondence, the one-to-one correspondence, and the many-to-many correspondence, and the preferred sequence is determined to perform merging and matching.

For example, set risk point comments corresponding to different combinations of risk factors are preset. Further, the actual risk point comments of the risk factors after simple combination are matched with the risk point comments to add or delete corresponding contents.

Preferably, the number of risk factors and the risk coefficients for the same risk point are calculated to determine a weighted risk coefficient score. And determining a priority order according to the weighted risk coefficients of the risk points, and sequentially and respectively integrating a plurality of risk factor comments corresponding to the risk points into a risk point comment according to a many-to-one (or one-to-one) correspondence.

Furthermore, comprehensive intelligent evaluation is carried out on the multiple risk point comments, and an integrated standardized review comment is provided.

In this example, the integrated standardized audit comment is automatically subjected to intelligent evaluation by the intelligent risk evaluation device to form a comprehensive risk evaluation result.

Preferably, the method further comprises the following steps: and providing the automatically formed comprehensive risk assessment result for the user, receiving the operation information of the user, and recording the risk assessment result confirmed by the user, wherein the risk assessment result comprises a pass or reject.

Therefore, the invention establishes the risk flat comment knowledge base autonomously, builds the risk analysis rule on the basis of the knowledge base, realizes the extraction of the risk characteristics of the case and provides the standardized comments, and recommends the standardized comments and the preprocessing result to assist the wind control personnel to give accurate decisions (i.e. give the artificial best processing suggestion) after the processing of the auditing result judgment rule (i.e. after the intelligent evaluation), thereby realizing the intelligent auditing auxiliary function and taking the accuracy and the auditing efficiency of the artificial processing result into consideration.

It should be noted that the above-mentioned embodiments are only preferred embodiments, and should not be construed as limiting the present invention.

Those skilled in the art will appreciate that all or part of the steps to implement the above-described embodiments are implemented as programs (computer programs) executed by a computer data processing apparatus. When the computer program is executed, the method provided by the invention can be realized. Furthermore, the computer program may be stored in a computer readable storage medium, which may be a readable storage medium such as a magnetic disk, an optical disk, a ROM, a RAM, or a storage array composed of a plurality of storage media, such as a magnetic disk or a magnetic tape storage array. The storage medium is not limited to centralized storage, but may be distributed storage, such as cloud storage based on cloud computing.

Example 2

Embodiments of the apparatus of the present invention are described below, which may be used to perform method embodiments of the present invention. The details described in the device embodiments of the invention should be regarded as complementary to the above-described method embodiments; reference is made to the above-described method embodiments for details not disclosed in the apparatus embodiments of the invention.

Referring to fig. 4, 5 and 6, the present invention further provides an intelligent risk assessment device 400 for providing standardized comments, which is used for performing automated risk assessment on risk cases in business, and comprises: the establishing module 401 is used for establishing a risk comment knowledge base according to the risk auditing strategy and the historical service data, wherein the risk comment knowledge base comprises a risk analysis rule and a risk comment rule; a risk splitting module 402, configured to obtain risk cases according to the risk analysis rules, and perform risk splitting on the risk cases; a generating module 403, which generates a standardized comment corresponding to the risk case according to the risk comment rule; an evaluation module 404, automatically forming a composite risk evaluation result based on the standardized comments.

As shown in fig. 5, the system further includes a setting module 501, where the setting module 501 is configured to set risk analysis rules; the risk analysis rules include: the risk analysis method comprises a risk case screening rule and identification rules of risk points and risk features in risk cases, wherein the risk case screening rule is used for classifying the risk cases to determine the risk cases to be analyzed.

Preferably, the risk splitting module 402 further comprises: risk splitting the risk case to form a plurality of risk factors.

As shown in fig. 6, the system further includes an identification module 601, where the identification module 601 identifies an abnormal pattern in each risk factor according to the risk annotation rule, and generates a standardized annotation corresponding to the abnormal pattern.

Preferably, a processing module 602 is further included, wherein the processing module 602 is configured to combine multiple standardized comments of different factors to generate a combined standardized comment as a combined risk assessment result.

In embodiment 2, the same portions as those in embodiment 1 are not described.

Those skilled in the art will appreciate that the modules in the above-described embodiments of the apparatus may be distributed as described in the apparatus, and may be correspondingly modified and distributed in one or more apparatuses other than the above-described embodiments. The modules of the above embodiments may be combined into one module, or further split into multiple sub-modules.

Compared with the prior art, the intelligent risk assessment device disclosed by the invention has the advantages that the risk case is automatically identified by establishing the risk comment knowledge base, the accuracy of intelligent grabbing risk characteristics is ensured to the maximum extent, the standardized format comments are automatically generated, and after the processing of the audit result judgment rule, the standardized comments and the preprocessing result are recommended to assist the wind control personnel to give accurate decisions (namely giving artificial optimal processing suggestions), so that the intelligent audit auxiliary function can be realized, and the accuracy and the audit efficiency of the manual processing result can be considered; standardized comments are provided, and pre-judgment results are given, so that the manual judgment time is saved, and the manual review efficiency is improved; the problems of non-standard operation, risk omission and low efficiency caused by the existing mode of manually mining risk information data and remarking are solved.

Example 3

In the following, embodiments of the electronic device of the present invention are described, which may be regarded as specific physical implementations for the above-described embodiments of the method and apparatus of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or apparatus described above; for details which are not disclosed in embodiments of the electronic device of the invention, reference may be made to the above-described embodiments of the method or the apparatus.

Fig. 7 is a block diagram of an exemplary embodiment of an electronic device according to the present invention. An electronic apparatus 200 according to this embodiment of the present invention is described below with reference to fig. 7. The electronic device 200 shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 7, the electronic device 200 is embodied in the form of a general purpose computing device. The components of the electronic device 200 may include, but are not limited to: at least one processing unit 210, at least one memory unit 220, a bus 230 connecting different system components (including the memory unit 220 and the processing unit 210), a display unit 240, and the like.

Wherein the storage unit stores program code executable by the processing unit 210 to cause the processing unit 210 to perform steps according to various exemplary embodiments of the present invention described in the processing method section of the electronic device described above in this specification. For example, the processing unit 210 may perform the steps as shown in fig. 1.

The memory unit 220 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)2201 and/or a cache memory unit 2202, and may further include a read only memory unit (ROM) 2203.

The storage unit 220 may also include a program/utility 2204 having a set (at least one) of program modules 2205, such program modules 2205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 230 may be one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 200 may also communicate with one or more external devices 300 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 200, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 200 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 250. Also, the electronic device 200 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 260. The network adapter 260 may communicate with other modules of the electronic device 200 via the bus 230. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. The computer program, when executed by a data processing apparatus, enables the computer readable medium to carry out the above-described methods of the invention.

As shown in fig. 8, the computer program may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.

Claims

1. An intelligent risk assessment method for providing standardized comments, which is used for automatically assessing risks of risk cases in business, is characterized by comprising the following steps:

establishing a risk comment knowledge base according to a risk auditing strategy and historical business data, wherein the risk comment knowledge base comprises a risk analysis rule and a risk comment rule;

acquiring a risk case according to the risk analysis rule, and carrying out risk splitting on the risk case;

generating a standardized comment corresponding to the risk case according to the risk comment rule;

and automatically forming a comprehensive risk assessment result based on the standardized comments.

2. The intelligent risk assessment method according to claim 1,

the risk analysis rules include: the risk analysis method comprises a risk case screening rule and identification rules of risk points and risk features in risk cases, wherein the risk case screening rule is used for classifying the risk cases to determine the risk cases to be analyzed.

3. The intelligent risk assessment method according to any one of claims 1-2, wherein risk splitting the risk case comprises: risk splitting the risk case to form a plurality of risk factors.

4. The intelligent risk assessment method according to any one of claims 1-3, wherein said risk annotation rules comprise annotation rules corresponding to each risk factor.

5. The intelligent risk assessment method according to any one of claims 1-4, wherein generating standardized comments corresponding to risk cases according to the risk comment rules comprises:

and identifying abnormal patterns in the risk factors according to the risk comment rules, and generating corresponding standardized comments according to the abnormal patterns.

6. The intelligent risk assessment method according to any one of claims 1-5, wherein said automatically forming a composite risk assessment result based on said standardized comments comprises:

and combining the multiple standardized comments of different factors to generate a comprehensive standardized comment as a comprehensive risk assessment result.

7. The intelligent risk assessment method according to any one of claims 1-6, further comprising:

configuring a merging rule, wherein the merging rule comprises a many-to-one corresponding relation, a one-to-one corresponding relation, a many-to-many corresponding relation and a priority order;

and carrying out merging and matching processing according to the many-to-one corresponding relation, the one-to-one corresponding relation and the many-to-many corresponding relation, and determining an optimal sequence for merging and matching.

8. An intelligent risk assessment device for providing standardized comments, which is used for automatically assessing risks of risk cases in business, is characterized by comprising:

the risk assessment system comprises an establishing module, a risk assessment module and a risk assessment module, wherein the establishing module is used for establishing a risk assessment knowledge base according to a risk audit strategy and historical business data, and the risk assessment knowledge base comprises a risk analysis rule and a risk assessment rule;

the risk splitting module is used for acquiring risk cases according to the risk analysis rule and carrying out risk splitting on the risk cases;

the generating module generates a standardized comment corresponding to the risk case according to the risk comment rule;

and the evaluation module automatically forms a comprehensive risk evaluation result based on the standardized comments.

9. An electronic device, wherein the electronic device comprises:

a processor; and the number of the first and second groups,

a memory storing computer-executable instructions that, when executed, cause the processor to perform the intelligent risk assessment method of providing standardized comments of any one of claims 1-7.

10. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the intelligent risk assessment method of providing standardized comments of any one of claims 1-7.