CN114529202A

CN114529202A - Project evaluation method and device, electronic equipment and storage medium

Info

Publication number: CN114529202A
Application number: CN202210161126.1A
Authority: CN
Inventors: 张建安; 陈雨
Original assignee: Agricultural Bank of China
Current assignee: Agricultural Bank of China
Priority date: 2022-02-22
Filing date: 2022-02-22
Publication date: 2022-05-24

Abstract

The invention discloses a project evaluation method, a project evaluation device, electronic equipment and a storage medium. The method comprises the following steps: acquiring initial risk data of a project; acquiring historical loss distribution of the project in a preset time interval, performing random simulation based on the historical loss distribution in the preset time interval to obtain a loss simulation result obtained by simulating preset simulation times, and determining the current predicted loss of the project based on the loss simulation result of the preset simulation times; determining a risk level for the project based on the initial risk data and the current predicted loss. By the technical scheme, the problem of low accuracy of the evaluation grade of the project risk grade is solved, and the accuracy of the project evaluation is improved.

Description

Project evaluation method and device, electronic equipment and storage medium

Technical Field

The present invention relates to the field of data processing technologies, and in particular, to a project evaluation method and apparatus, an electronic device, and a storage medium.

Background

With the development of technologies such as big data and intelligent information management and control, risk monitoring is widely applied to financial institutions at all levels, and risk early warning and intelligent management and control can be performed on abnormal business conditions of the financial institutions through the risk monitoring.

In the prior art, an expert evaluation method is usually adopted to predict the risk level of a project, the method has strong subjectivity, and the accuracy of the evaluation level of the risk level of the project is low.

Disclosure of Invention

The invention provides a project evaluation method, a project evaluation device, electronic equipment and a storage medium, which are used for solving the problem of low accuracy of the evaluation level of the risk level of a project and improving the accuracy of the evaluation of the project.

According to an aspect of the present invention, there is provided a project evaluation method including:

acquiring initial risk data of a project;

acquiring historical loss distribution of the project in a preset time interval, performing random simulation based on the historical loss distribution in the preset time interval to obtain a loss simulation result obtained by simulating preset simulation times, and determining the current predicted loss of the project based on the loss simulation result of the preset simulation times;

determining a risk level for the project based on the initial risk data and the current predicted loss.

According to another aspect of the present invention, there is provided a project evaluation apparatus, characterized by comprising:

the data acquisition module is used for acquiring initial risk data of the project;

the loss prediction module is used for acquiring historical loss distribution of the project in a preset time interval, carrying out random simulation based on the historical loss distribution in the preset time interval to obtain a loss simulation result obtained by simulating preset simulation times, and determining the current prediction loss of the project based on the loss simulation result of the preset simulation times;

a level determination module to determine a risk level for the project based on the initial risk data and the current predicted loss.

According to another aspect of the present invention, there is provided an electronic apparatus including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform a project evaluation method according to any of the embodiments of the present invention.

According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement a project evaluation method according to any one of the embodiments of the present invention when the computer instructions are executed.

According to the technical scheme of the embodiment of the invention, the acquisition of the current evaluation data is realized by acquiring the initial risk data of the project; further, historical loss distribution of the project in a preset time interval is obtained, historical data are obtained, random simulation is carried out on the historical loss distribution in the preset time interval, a loss simulation result obtained by simulation of preset simulation times is obtained, current prediction loss of the project is determined based on the loss simulation result of the preset simulation times, and prediction of the current loss is achieved; and then determining the risk level of the project through the initial risk data and the current predicted loss, and realizing quantitative evaluation of the risk level, so that the problems of strong subjectivity and low accuracy of the project risk level evaluation level of the existing evaluation method are solved, and the accuracy of the project evaluation is improved.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present invention, nor do they necessarily limit the scope of the invention. Other features of the present invention will become apparent from the following description.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a flow chart of a project evaluation method according to an embodiment of the present invention;

FIG. 2 is a flowchart of a project evaluation method according to a second embodiment of the present invention;

FIG. 3 is a flowchart of a project evaluation method according to a third embodiment of the present invention;

FIG. 4 is a schematic structural diagram of a project evaluation apparatus according to a fourth embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device implementing the project evaluation method according to the embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It is noted that the terms "initial", "target", and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example one

Fig. 1 is a flowchart of a project evaluation method according to an embodiment of the present invention, where the present embodiment is applicable to a situation where risk level evaluation is performed according to initial risk data and historical loss distribution of a project, and the method may be performed by a project evaluation apparatus according to an embodiment of the present invention, where the apparatus may be implemented by software and/or hardware, and the apparatus may be configured on an electronic computing device, such as a terminal and/or a server. The method specifically comprises the following steps:

and S110, acquiring initial risk data of the project.

The item refers to a business item to be subjected to risk level assessment, such as a business item that a company needs to implement or operate. The items may include, but are not limited to, main items and sub items. The sub-items may include multiple levels of sub-items for further partitioning of the items or sub-items; the initial risk data refers to a risk evaluation score of the project according to an expert evaluation method, and the initial risk data can be used for evaluating the risk degree of the current project. The initial risk data may be directly obtained from a preset storage location, or may be obtained by calculating basic data of the project, which is not limited herein.

Illustratively, taking a business project of a financial company as an example, the multi-level sub-project may include, but is not limited to, a first-level sub-project and a second-level sub-project, the second-level sub-project being a sub-project of the first-level sub-project. The primary sub-projects may include, but are not limited to, personnel, internal processes, systems, and external environments, and the secondary sub-projects may include, but are not limited to, employee morality, occupational competencies, macro environments and policies, external fraudulent theft, and the like. The content of the sub-items is only an example, and the specific items can be selected or set according to the actual situation of the items, which is not limited.

On the basis of the above embodiment, the initial risk data of the project may be obtained by performing weighted calculation based on the sub-project weight and the sub-project risk data in the project.

Specifically, initial risk data of the project, namely an initial project risk score, can be obtained by performing stepwise weighted summary calculation on the weight of each sub-project and the sub-project score in the project, so that a reference basis is provided for risk grade evaluation of the project.

On the basis of the above embodiment, after obtaining the initial risk data of the project, the method further comprises: and judging the initial risk data based on a preset risk threshold to obtain an initial risk grade.

The preset risk threshold may be a judgment threshold set according to experience, and may be used to judge the initial risk data, so as to determine an initial risk level corresponding to the initial risk data.

In some embodiments, the preset risk threshold may include a first risk threshold and a second risk threshold, the second risk threshold is smaller than the first risk threshold, and the risk levels may be divided into three levels, i.e., low, medium, and high. If the initial risk data is greater than the first risk threshold, the risk level is a high risk level; if the initial risk data is smaller than the first risk threshold and larger than the second risk threshold, the risk grade is a medium risk grade; if the initial risk data is less than the second risk threshold, the risk level is a low risk level. In some embodiments, the number of the preset risk thresholds may be more than two, and the risk levels are further divided. The setting manner of the preset risk threshold in the embodiment of the present invention is not limited herein.

S120, obtaining historical loss distribution of the project in a preset time interval, carrying out random simulation based on the historical loss distribution in the preset time interval to obtain a loss simulation result obtained by simulating preset simulation times, and determining the current predicted loss of the project based on the loss simulation result of the preset simulation times.

In the embodiment of the present invention, the historical loss distribution refers to loss data of an item in a preset time interval, and may include, but is not limited to, historical risk frequency and historical risk loss, the historical risk frequency refers to frequency of occurrence of the item, the historical risk loss refers to loss caused by occurrence of the item, and the loss may include, but is not limited to, monetary loss, resource loss, and the like. The historical loss distribution may be statistically obtained directly from a preset storage location, for example, the preset storage location may be a database storing the historical loss distribution. The random simulation refers to performing test statistics on historical loss distribution in a preset time interval, the preset simulation times can be set according to experience, and it can be understood that the prediction precision of the obtained current predicted loss is gradually increased along with the increase of the random simulation times. The historical loss distribution can be used for estimating the loss of the project in the future in each random simulation, and the loss simulation result corresponding to the current random simulation is obtained. Furthermore, the current predicted loss of the project can be obtained by counting and summarizing the loss simulation results corresponding to the random simulations and screening. The loss simulation result refers to a loss set generated by multiple random simulations. The current predicted loss refers to a loss value obtained by screening a loss simulation result.

S130, determining the risk level of the project based on the initial risk data and the current prediction loss.

The initial risk data is current data of a project, the current prediction loss is data obtained through prediction according to historical data, the risk level of the project is determined according to the initial risk data and the current prediction loss, namely the risk level of the project is determined by using the prediction data of the current data and the historical data, the real-time performance of the data is guaranteed, the prediction data based on the historical data is referred, and the accuracy of the risk level is improved.

The embodiment of the invention provides a project evaluation method, which is used for acquiring the current evaluation data by acquiring the initial risk data of a project; further, historical loss distribution of the project in a preset time interval is obtained, historical data are obtained, random simulation is carried out on the historical loss distribution in the preset time interval, a loss simulation result obtained by simulation of preset simulation times is obtained, current prediction loss of the project is determined based on the loss simulation result of the preset simulation times, and prediction of the current loss is achieved; and then determining the risk level of the project through the initial risk data and the current predicted loss, and realizing quantitative evaluation of the risk level, so that the problems of strong subjectivity and low accuracy of the project risk level evaluation level of the existing evaluation method are solved, and the accuracy of the project evaluation is improved.

Example two

Fig. 2 is a flow chart diagram of a project evaluation method according to a second embodiment of the present invention, and based on the second embodiment, further refinements are made to "obtain historical loss distribution of the project in a preset time interval, perform random simulation based on the historical loss distribution in the preset time interval, obtain a loss simulation result obtained by simulation of a preset simulation number, and determine a current predicted loss of the project based on the loss simulation result of the preset simulation number". The specific implementation manner of the method can be seen in the detailed description of the technical scheme. The technical terms that are the same as or corresponding to the above embodiments are not repeated herein. As shown in fig. 2, the method of the embodiment of the present invention specifically includes the following steps:

and S210, acquiring initial risk data of the project.

S220, obtaining historical loss distribution of the project in a preset time interval, fitting historical risk frequency of the event corresponding to the random simulation in the preset time interval to obtain frequency probability distribution data, and fitting historical risk loss of the event corresponding to the random simulation in the preset time interval to obtain risk loss distribution data.

The event corresponding to random simulation refers to a historical risk event called by random simulation each time, and in each preset simulation frequency, at least one of items, historical risk frequency and historical risk loss of the event corresponding to random simulation is different, so that frequency probability distribution data and risk loss distribution data generated by simulation each time are different. In the embodiment of the invention, the random simulation can be a Monte Carlo simulation, and the Monte Carlo simulation can estimate the future loss of the project by using historical loss distribution, so as to predict the current predicted loss of the project and make up the defect of evaluating the risk level of the project by using initial risk data.

Specifically, a frequency fitting function can be adopted to fit the historical risk frequency of the simulation corresponding event in a preset time interval to obtain frequency probability distribution data; and fitting the historical risk loss of the random simulation corresponding event in a preset time interval by adopting a loss fitting function to obtain risk loss distribution data. The frequency probability distribution data and the risk loss distribution data can effectively reflect the historical risk frequency of the historical event and the distribution of the historical risk loss, and provide reliable parameters for the prediction of the subsequent current prediction loss.

On the basis of the above embodiment, fitting the historical risk frequency of the random simulation corresponding event in the preset time interval to obtain frequency probability distribution data, and fitting the historical risk loss of the random simulation corresponding event in the preset time interval to obtain risk loss distribution data, includes: and fitting the historical risk frequency of the random simulation corresponding event in the preset time interval according to Poisson distribution to obtain frequency probability distribution data, and fitting the historical risk loss of the random simulation corresponding event in the preset time interval according to lognormal distribution to obtain risk loss distribution data.

It should be noted that, the data distribution state of the frequency probability distribution data obtained by poisson distribution calculation is a state with a thick middle and thin two sides, and the state is in accordance with the distribution state of the actual occurrence frequency of the project; the risk loss distribution data obtained through the lognormal distribution calculation has a data distribution state of thick front and thin back, and the state is in accordance with the distribution state of loss actually generated by the project, so that reliable calculation parameters are provided for follow-up.

And S230, multiplying the frequency probability distribution data and the risk loss distribution data of the random simulation corresponding event to obtain a plurality of risk losses, and adding the risk losses to obtain the cumulative loss of the random simulation corresponding event.

Specifically, a corresponding number of random number samples can be generated according to the frequency probability distribution data, and in each random number sample, the frequency probability distribution data of the random simulation corresponding event and the risk loss distribution data are multiplied to obtain the risk loss corresponding to the random number sample; further, a plurality of risk losses corresponding to each random number sample are added to obtain an accumulated loss of the event corresponding to the random simulation, where the accumulated loss may be an accumulated loss value of a next time interval of the event corresponding to the current random simulation.

S240, counting the accumulated loss of each random simulation corresponding event to obtain a loss simulation result obtained by simulation of preset simulation times, and determining the current prediction loss of the project based on the loss simulation result of the preset simulation times, wherein in each preset simulation time, at least one of the project, the historical risk frequency and the historical risk loss of the random simulation corresponding event is different.

For example, the preset simulation times may be N times, and the cumulative loss of the N events corresponding to the random simulation is counted to obtain a loss simulation result including the cumulative loss of the N events corresponding to the random simulation, where the loss simulation result may be stored in a distribution array.

On the basis of the above embodiment, the determining the current predicted loss of the project based on the loss simulation result of the preset simulation times includes: and determining the loss simulation result of the preset simulation times in a preset confidence interval as the current predicted loss.

The preset confidence interval can be set according to the screening precision. Illustratively, the preset confidence interval may be a 99% confidence interval, and the loss simulation result within the 99% confidence interval is determined as the current predicted loss, which has a higher confidence level, so as to effectively improve the reliability of the risk level of the project.

S250, determining the risk level of the project based on the initial risk data and the current prediction loss.

The embodiment of the invention provides a project evaluation method, which comprises the steps of fitting historical risk frequency of a random simulation corresponding event in a preset time interval to obtain frequency probability distribution data, fitting historical risk loss of the random simulation corresponding event in the preset time interval to obtain risk loss distribution data, and providing reliable parameters for prediction of subsequent accumulative loss; furthermore, multiplying the frequency probability distribution data of the random simulation corresponding event with the risk loss distribution data to obtain a plurality of risk losses, and adding the risk losses to obtain the cumulative loss of the random simulation corresponding event, so that the quantitative evaluation of the cumulative loss is realized, and the reliability of project evaluation is improved.

EXAMPLE III

Fig. 3 is a schematic flow chart of a project evaluation method provided in a third embodiment of the present invention, and the third embodiment of the present invention and various alternatives in the foregoing embodiments may be combined. In this embodiment of the present invention, optionally, the determining the risk level of the project based on the initial risk data and the current predicted loss includes: multiplying the initial risk data corresponding to each monitoring rule with the current prediction loss to obtain a risk evaluation score corresponding to each monitoring rule; and sequencing the risk evaluation scores corresponding to the monitoring rules, and judging the sequencing result based on a preset grade threshold to obtain the risk grade of the project.

As shown in fig. 3, the method of the embodiment of the present invention specifically includes the following steps:

and S310, acquiring initial risk data of the project.

S320, obtaining historical loss distribution of the project in a preset time interval, carrying out random simulation based on the historical loss distribution in the preset time interval to obtain a loss simulation result obtained by simulating preset simulation times, and determining the current predicted loss of the project based on the loss simulation result of the preset simulation times.

S330, multiplying the initial risk data corresponding to each monitoring rule with the current prediction loss to obtain a risk evaluation score corresponding to each monitoring rule.

S340, ranking the risk evaluation scores corresponding to the monitoring rules, and judging the ranking result based on a preset ranking threshold to obtain the risk ranking of the project.

The monitoring rules can be set according to the items and the sub-items thereof. Specifically, any project can be provided with sub-projects with indexes of different hierarchies, types and the like, and various monitoring rules can be set according to the difference of the sub-projects. In the embodiment of the invention, the project grades are evaluated according to different monitoring rules, so that various evaluation results can be obtained, and the diversity of the evaluation results is improved.

In the embodiment of the invention, the risk evaluation score can be obtained by multiplying the current prediction loss of the initial risk data, so that the combination of the current data and the historical prediction data is realized; furthermore, the risk evaluation scores corresponding to the monitoring rules are sorted, the maximum or minimum risk evaluation score is selected from the multiple risk evaluation scores, and the risk evaluation scores are judged according to a preset grade threshold, so that the item risk grade is obtained.

The embodiment of the invention provides a project evaluation method, which is characterized in that the combination of current data and historical prediction data is realized by multiplying the initial risk data corresponding to each monitoring rule by the current prediction loss, so that the obtained risk evaluation score is more accurate; furthermore, the risk evaluation scores corresponding to the monitoring rules are sorted, and then the sorting result is judged according to a preset grade threshold value to obtain the risk grade of the project, so that the quantitative evaluation of the risk grade is realized, and the reliability of the project evaluation is improved.

Example four

Fig. 4 is a schematic structural diagram of a project evaluation device according to a fourth embodiment of the present invention, where the project evaluation device provided in this embodiment may be implemented by software and/or hardware, and may be configured in a terminal and/or a server to implement the project evaluation method according to the fourth embodiment of the present invention. The device may specifically include: a data acquisition module 410, a loss prediction module 420, and a rank determination module 430.

The data acquisition module 410 is configured to acquire initial risk data of a project; the loss prediction module 420 is configured to obtain historical loss distribution of the project within a preset time interval, perform random simulation based on the historical loss distribution within the preset time interval to obtain a loss simulation result obtained by simulating a preset simulation time, and determine a current predicted loss of the project based on the loss simulation result of the preset simulation time; a level determination module 430 for determining a risk level for the project based on the initial risk data and the current predicted loss.

The embodiment of the invention provides a project evaluation device, which can be used for acquiring current evaluation data by acquiring initial risk data of a project; further, historical loss distribution of the project in a preset time interval is obtained, historical data are obtained, random simulation is carried out on the historical loss distribution in the preset time interval, a loss simulation result obtained by simulation of preset simulation times is obtained, current prediction loss of the project is determined based on the loss simulation result of the preset simulation times, and prediction of the current loss is achieved; and then determining the risk level of the project through the initial risk data and the current predicted loss, and realizing quantitative evaluation of the risk level, so that the problems of strong subjectivity and low accuracy of the project risk level evaluation level of the existing evaluation method are solved, and the accuracy of the project evaluation is improved.

On the basis of any optional technical scheme in the embodiment of the present invention, optionally, the initial risk data of the project is obtained by performing weighted calculation based on the sub-project weight and the sub-project risk data in the project.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the apparatus further includes:

and the initial risk grade determining module is used for judging the initial risk data based on a preset risk threshold to obtain an initial risk grade.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the historical loss distribution includes historical risk frequency and historical risk loss, and the loss prediction module 420 includes:

the frequency data acquisition unit is used for fitting the historical risk frequency of the random simulation corresponding event in a preset time interval to obtain frequency probability distribution data;

the loss data acquisition unit is used for fitting the historical risk loss of the random simulation corresponding event in a preset time interval to obtain risk loss distribution data;

the cumulative loss calculation unit is used for multiplying the frequency probability distribution data and the risk loss distribution data of the corresponding random simulation event to obtain a plurality of risk losses, and adding the risk losses to obtain the cumulative loss of the corresponding random simulation event;

and the simulation result determining unit is used for counting the accumulated loss of each random simulation corresponding event to obtain a loss simulation result obtained by simulating with preset simulation times, wherein in each preset simulation time, at least one of the items, the historical risk frequency and the historical risk loss of the random simulation corresponding event are different.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the frequency data acquisition unit may be further configured to:

and fitting the historical risk frequency of the random simulation corresponding event in a preset time interval according to the Poisson distribution to obtain frequency probability distribution data.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the loss data acquiring unit may be further configured to:

and fitting the historical risk loss of the random simulation corresponding event in a preset time interval according to the lognormal distribution to obtain risk loss distribution data.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the loss prediction module 420 may further be configured to:

and determining the loss simulation result of the preset simulation times in a preset confidence interval as the current predicted loss.

On the basis of any optional technical solution in the embodiment of the present invention, optionally, the level determining module 430 may further be configured to:

multiplying the initial risk data corresponding to each monitoring rule by the current prediction loss to obtain a risk evaluation score corresponding to each monitoring rule;

and sequencing the risk evaluation scores corresponding to the monitoring rules, and judging the sequencing result based on a preset grade threshold to obtain the risk grade of the project.

The project evaluation device provided by the embodiment of the invention can execute the project evaluation method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.

EXAMPLE five

FIG. 5 illustrates a schematic diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 5, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM)12, a Random Access Memory (RAM)13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM)12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, or the like. The processor 11 performs the various methods and processes described above, such as the project evaluation method.

In some embodiments, the project evaluation method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the project evaluation method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the project evaluation method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.

The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for project evaluation, comprising:

acquiring initial risk data of a project;

2. The method of claim 1, wherein the initial risk data for the project is calculated based on sub-project weights and sub-project risk data for the project.

3. The method of claim 1, wherein after obtaining initial risk data for an item, the method further comprises:

and judging the initial risk data based on a preset risk threshold to obtain an initial risk grade.

4. The method according to claim 1, wherein the historical loss distribution includes historical risk frequency and historical risk loss, and the random simulation is performed based on the historical loss distribution in the preset time interval to obtain a loss simulation result obtained by simulation for a preset simulation number of times, and the method includes:

fitting historical risk frequencies of the random simulation corresponding events in a preset time interval to obtain frequency probability distribution data;

fitting historical risk loss of the random simulation corresponding event in a preset time interval to obtain risk loss distribution data;

multiplying the frequency probability distribution data and risk loss distribution data of the random simulation corresponding events to obtain a plurality of risk losses, and adding the risk losses to obtain the cumulative loss of the random simulation corresponding events;

and counting the accumulated loss of each event corresponding to the random simulation to obtain a loss simulation result obtained by simulating preset simulation times, wherein in each preset simulation time, at least one of the items, the historical risk frequency and the historical risk loss of the event corresponding to the random simulation is different.

5. The method according to claim 4, wherein the fitting is performed on historical risk frequencies of the random simulation corresponding events in a preset time interval to obtain frequency probability distribution data; fitting the historical risk loss of the random simulation corresponding event in a preset time interval to obtain risk loss distribution data, wherein the risk loss distribution data comprises the following steps:

fitting historical risk frequencies of the random simulation corresponding events in a preset time interval according to Poisson distribution to obtain frequency probability distribution data;

6. The method of claim 1, wherein determining the current predicted loss of the project based on the loss simulation results for the preset number of simulations comprises:

7. The method of claim 1, wherein said determining a risk level for the project based on the initial risk data and the current predicted loss comprises:

multiplying the initial risk data corresponding to each monitoring rule with the current prediction loss to obtain a risk evaluation score corresponding to each monitoring rule;

and sequencing the risk evaluation scores corresponding to the monitoring rules, and judging a sequencing result based on a preset grade threshold to obtain the risk grade of the project.

8. An item assessment apparatus, comprising:

9. An electronic device, characterized in that the electronic device comprises:

at least one processor; and

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the project evaluation method of any one of claims 1-7.

10. A computer-readable storage medium having stored thereon computer instructions for causing a processor to, when executed, implement the project evaluation method of any one of claims 1-7.