CN109377378B

CN109377378B - Industry relevancy risk determination device and system

Info

Publication number: CN109377378B
Application number: CN201811511498.2A
Authority: CN
Inventors: 李夫路; 梁爽; 任建畅; 崔峰
Original assignee: Taikang Insurance Group Co Ltd
Current assignee: Taikang Insurance Group Co Ltd
Priority date: 2018-12-11
Filing date: 2018-12-11
Publication date: 2021-06-18
Anticipated expiration: 2038-12-11
Also published as: CN109377378A

Abstract

The invention discloses a method and a device for determining industry association degree and risk, a storage medium and electronic equipment, and relates to the technical field of block chains. The industry association degree determining method comprises the following steps: storing financial index information of a plurality of industries through a block chain network; wherein the plurality of industries comprise a first industry and a second industry of which the association degree of the industries is to be determined; determining floating information of financial indexes of the first industry and floating information of financial indexes of the second industry based on financial index information of a plurality of industries stored by the blockchain network; and comparing the floating information of the financial indexes of the first industry with the floating information of the financial indexes of the second industry, and determining the association degree of the first industry and the second industry according to the comparison result. The present disclosure may determine a degree of association between industries, and may utilize the degree of association to determine whether an industry is at risk.

Description

Industry relevancy risk determination device and system

Technical Field

The present disclosure relates to the field of blockchain technologies, and in particular, to a blockchain-based industry association degree determining method, a blockchain-based industry risk determining method, a blockchain-based industry association degree determining apparatus, a blockchain-based industry risk determining apparatus, a storage medium, and an electronic device.

Background

With the improvement of living standard of people, more and more people start to buy investment objects such as stocks, funds, bonds and the like to manage money. Wherein, the investment object can correspond to an industry. When a user manages money, the user often selects an investment object through news information and the trend of the investment object. However, this approach only considers the investment objects themselves, and the existing method has difficulty in providing investment advice to the user when one investment object is trended depending on another investment object.

In addition, for an enterprise within an industry, when a failure occurs in the industry related to the industry, the industry may be reached, in which case the enterprise risks economic loss. Currently, inter-industry dependencies can be determined by industry downstream relationships. However, this method of determining correlation is not accurate enough and is prone to omissions.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

The purpose of the present disclosure is to provide an industry association degree determining method based on a blockchain, an industry risk determining method based on a blockchain, an industry association degree determining device based on a blockchain, an industry risk determining device based on a blockchain, a storage medium, and an electronic device, thereby overcoming, at least to some extent, the problem of inaccurate industry association determination.

According to one aspect of the present disclosure, there is provided a block chain-based industry association degree determination method, including: storing financial index information of a plurality of industries through a block chain network; wherein the plurality of industries comprise a first industry and a second industry of which the association degree of the industries is to be determined; determining floating information of financial indexes of the first industry and floating information of financial indexes of the second industry based on financial index information of a plurality of industries stored by the blockchain network; and comparing the floating information of the financial indexes of the first industry with the floating information of the financial indexes of the second industry, and determining the association degree of the first industry and the second industry according to the comparison result.

In an exemplary embodiment of the present disclosure, determining the floating information of the financial indicators of the first industry and the floating information of the financial indicators of the second industry includes: determining financial index information of the first industry and financial index information of the second industry within a preset time period from financial index information of a plurality of industries stored in the blockchain network; and determining the floating information of the financial indexes of the first industry in the preset time period and the floating information of the financial indexes of the second industry in the preset time period.

In an exemplary embodiment of the present disclosure, the floating information includes first floating information and second floating information; wherein comparing the floating information of the financial indicators of the first industry with the floating information of the financial indicators of the second industry comprises: comparing the first floating information of the financial indicators of the first industry with the first floating information of the financial indicators of the second industry; and/or comparing the second floating information of the financial index of the first industry with the second floating information of the financial index of the second industry.

In an exemplary embodiment of the present disclosure, in a case where only the first floating information of the financial index of the first industry is compared with the first floating information of the financial index of the second industry, determining the association degree of the first industry with the second industry according to a result of the comparison includes: calculating the support degree and the confidence degree which meet the preset association rule; determining a degree of association of the first industry with the second industry based on the support degree and the confidence degree; wherein the predetermined association rule is: and when the financial index of the first industry has first floating information, determining that the financial index of the second industry has the first floating information.

In an exemplary embodiment of the present disclosure, determining the association of the first industry with the second industry based on the support and the confidence comprises: and carrying out weighted summation on the support degree and the confidence degree, and determining the result of the weighted summation as the association degree of the first industry and the second industry.

In an exemplary embodiment of the present disclosure, in a case where the first floating information of the financial index of the first industry is compared with the first floating information of the financial index of the second industry and the second floating information of the financial index of the first industry is compared with the second floating information of the financial index of the second industry, determining the association degree of the first industry with the second industry according to a result of the comparison includes: calculating the support degree and the confidence degree which meet the first association rule; determining a first association degree of the first industry with the second industry based on the support degree and the confidence degree which satisfy the first association rule; calculating the support degree and the confidence degree which meet the second association rule; determining a second association degree of the first industry with the second industry based on the support degree and the confidence degree which satisfy the second association rule; determining the association degree of the first industry and the second industry according to the first association degree and the second association degree; wherein the first association rule is: when the financial index of the first industry has first floating information, determining that the financial index of the second industry has the first floating information; the second association rule is: and when the financial index of the first industry has second floating information, determining that the financial index of the second industry has the second floating information.

In an exemplary embodiment of the present disclosure, determining a first association degree of the first industry with the second industry based on the support degree and the confidence degree that satisfy the first association rule includes: carrying out weighted summation on the support degree and the confidence degree which meet the first association rule, and determining the result of the weighted summation as the first association degree of the first industry and the second industry; and/or determining a second association degree of the first industry with the second industry based on the support degree and the confidence degree that satisfy the second association rule comprises: and performing weighted summation on the support degree and the confidence degree which meet the second association rule, and determining the result of the weighted summation as a second association degree of the first industry and the second industry.

In an exemplary embodiment of the present disclosure, determining the association of the first industry with the second industry according to the first association and the second association comprises: and carrying out weighted summation on the first relevance and the second relevance, and determining the result of the weighted summation as the relevance of the first industry and the second industry.

According to an aspect of the present disclosure, there is provided a block chain-based industry risk determination method, including: determining the association degree of the first industry and the second industry by using the industry association degree determination method based on the block chain in any one of the above exemplary embodiments; judging whether the association degree of the first industry and the second industry meets a preset association degree requirement or not; and under the condition that the association degree of the first industry and the second industry meets the preset association degree requirement, if the fact that the financial emergency information of the first industry is input into the block chain network is detected, determining whether the second industry has risks according to the financial emergency information of the first industry.

According to one aspect of the disclosure, an industry association degree determining device based on a block chain is provided and comprises an information storage module, a floating information determining module and an association degree determining module.

Specifically, the information storage module is used for storing financial index information of a plurality of industries through a block chain network; wherein the plurality of industries comprise a first industry and a second industry of which the association degree of the industries is to be determined; the floating information determining module is used for determining floating information of the financial indexes of the first industry and floating information of the financial indexes of the second industry based on the financial index information of a plurality of industries stored in the block chain network; the relevancy determining module is used for comparing the floating information of the financial indexes of the first industry with the floating information of the financial indexes of the second industry and determining the relevancy of the first industry and the second industry according to a comparison result.

In an exemplary embodiment of the present disclosure, the floating information determining module includes an information determining unit and a floating information determining unit.

Specifically, the information determining unit is configured to determine, from financial index information of multiple industries stored in the blockchain network, financial index information of the first industry and financial index information of the second industry within a preset time period; the floating information determination unit is used for determining floating information of the financial indexes of the first industry in the preset time period and floating information of the financial indexes of the second industry in the preset time period.

In an exemplary embodiment of the present disclosure, the floating information includes first floating information and second floating information; the relevance determining module comprises a first comparing unit and/or a second comparing unit.

Specifically, the first comparing unit is configured to compare first floating information of the financial index of the first industry with first floating information of the financial index of the second industry; the second comparing unit is used for comparing the second floating information of the financial index of the first industry with the second floating information of the financial index of the second industry.

In an exemplary embodiment of the present disclosure, the association determination module is configured to: calculating a support degree and a confidence degree satisfying a predetermined association rule in a case where only the first floating information of the financial index of the first industry is compared with the first floating information of the financial index of the second industry; determining a degree of association of the first industry with the second industry based on the support degree and the confidence degree; wherein the predetermined association rule is: and when the financial index of the first industry has first floating information, determining that the financial index of the second industry has the first floating information.

In an exemplary embodiment of the present disclosure, the association determination module is configured to: and carrying out weighted summation on the support degree and the confidence degree, and determining the result of the weighted summation as the association degree of the first industry and the second industry.

In an exemplary embodiment of the present disclosure, the association determination module is configured to: calculating support and confidence that a first association rule is satisfied in a case where first floating information of the financial index of the first industry is compared with first floating information of the financial index of the second industry and second floating information of the financial index of the first industry is compared with second floating information of the financial index of the second industry; determining a first association degree of the first industry with the second industry based on the support degree and the confidence degree which satisfy the first association rule; calculating the support degree and the confidence degree which meet the second association rule; determining a second association degree of the first industry with the second industry based on the support degree and the confidence degree which satisfy the second association rule; determining the association degree of the first industry and the second industry according to the first association degree and the second association degree; wherein the first association rule is: when the financial index of the first industry has first floating information, determining that the financial index of the second industry has the first floating information; the second association rule is: and when the financial index of the first industry has second floating information, determining that the financial index of the second industry has the second floating information.

In an exemplary embodiment of the present disclosure, the association determination module is configured to: carrying out weighted summation on the support degree and the confidence degree which meet the first association rule, and determining the result of the weighted summation as the first association degree of the first industry and the second industry; and/or carrying out weighted summation on the support degree and the confidence degree meeting the second association rule, and determining the result of the weighted summation as the second association degree of the first industry and the second industry.

In an exemplary embodiment of the present disclosure, the association determination module is configured to: and carrying out weighted summation on the first relevance and the second relevance, and determining the result of the weighted summation as the relevance of the first industry and the second industry.

According to one aspect of the disclosure, an industry risk determination device based on a block chain is provided, which includes an association degree determination device, an association degree judgment module and a risk determination module.

Specifically, the association degree determining apparatus is configured to determine the association degree between the first industry and the second industry by using the industry association degree determining method based on the blockchain according to any one of the above exemplary embodiments; the association degree judging module is used for judging whether the association degree of the first industry and the second industry meets a preset association degree requirement or not; the risk determining module is used for determining whether the second industry has risks according to the financial emergency information of the first industry if the fact that the financial emergency information of the first industry is input into the block chain network is detected under the condition that the association degree of the first industry and the second industry meets the preset association degree requirement.

According to an aspect of the present disclosure, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the blockchain-based industry association determination method or the blockchain-based industry risk determination method described above in any one of the above-described exemplary embodiments.

According to an aspect of the present disclosure, there is provided an electronic device including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the block chain based industry association determination method or the block chain based industry risk determination method according to any one of the above exemplary embodiments via executing the executable instructions.

In the technical solution provided by some embodiments of the present disclosure, financial index information of a plurality of industries including a first industry and a second industry is stored through a blockchain network, floating information of a financial index of the first industry and floating information of a financial index of the second industry are determined based on information stored in the blockchain network, the determined floating information is compared, and a degree of association between the first industry and the second industry is determined according to a result of the comparison. Based on the association between the first industry and the second industry, whether the second industry is at risk or not can be determined in response to financial emergencies of the first industry. On one hand, based on the scheme of the disclosure, the association degree between industries can be effectively determined, and whether the industries concerned by the user have risks can be determined based on the conditions of the associated industries; on the other hand, the financial index information is stored in the blockchain network, so that the financial index information can be guaranteed to be not falsified through the blockchain network, the traceable processing of the financial index information can be realized based on the storage of the blockchain network, and the safe sharing of the financial index information can be effectively guaranteed; in another aspect, the disclosure may determine the industry association degree based on the financial index information stored in the blockchain network, and may determine the industry risk based on the determined association degree, which is helpful for promoting effective popularization of the blockchain technology in the aspect of industry association risk management.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:

fig. 1 schematically illustrates a flow chart of a blockchain-based industry association determination method according to an exemplary embodiment of the present disclosure;

FIG. 2 schematically illustrates a flow chart of a blockchain-based industry risk determination method according to an exemplary embodiment of the present disclosure;

FIG. 3 schematically illustrates a block diagram of a blockchain-based industry risk determination system according to an exemplary embodiment of the present disclosure;

FIG. 4 schematically illustrates a block diagram of a blockchain-based industry association determination apparatus according to an exemplary embodiment of the present disclosure;

FIG. 5 schematically illustrates a block diagram of a floating information determination module according to an exemplary embodiment of the present disclosure;

FIG. 6 schematically illustrates a block diagram of an association determination module according to an exemplary embodiment of the present disclosure;

FIG. 7 schematically illustrates a block diagram of a blockchain-based industry risk determination apparatus according to an exemplary embodiment of the present disclosure;

FIG. 8 shows a schematic diagram of a storage medium according to an example embodiment of the present disclosure; and

fig. 9 schematically shows a block diagram of an electronic device according to an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. 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 devices and/or microcontroller devices.

The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the steps. For example, some steps may be decomposed, and some steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.

Both the blockchain-based industry relevancy determination method and the blockchain-based industry risk determination method described below may be implemented by a server, in which case, the blockchain-based industry relevancy determination apparatus and the blockchain-based industry risk determination apparatus of the present disclosure may be configured within the server. However, the method described in the present disclosure may also be implemented by a terminal device, which is not particularly limited in this exemplary embodiment. In addition, the terms "first" and "second" described below are for distinguishing purposes only and should not be construed as limiting the present disclosure.

Fig. 1 schematically illustrates a flowchart of a blockchain-based industry association determination method according to an exemplary embodiment of the present disclosure. Referring to fig. 1, the industry association degree determining method based on a block chain may include the following steps:

s12, storing financial index information of multiple industries through a block chain network; wherein the plurality of industries comprise a first industry and a second industry of which the industry association is to be determined.

In an exemplary embodiment of the present disclosure, the financial index information may include stock prices of the listed businesses within each industry, revenue situations for the listed businesses to determine status within the industry, emergencies of the listed businesses in the stock market, and the like. The enterprises playing a leading role in the industry can be determined according to the revenue situation of each enterprise on the market in the industry, and the financial indexes of the enterprises can be used for mapping the financial indexes of the industry.

In addition, although the financial index characterizing the industry by stock price is explained below, it should be understood that the financial index may also include a short term capital inflow situation, a future issue situation, and the like, which is not particularly limited in the present exemplary embodiment.

The industries described in this disclosure may be widely understood industry concepts, for example, industries may include, but are not limited to, engineering construction, electrical power, computers, electronic information, real estate, textile clothing, steel, chemical fiber, transportation facilities, banks, travel hotels, business chains, building materials, machinery, medicine, security dealer, communications, transportation logistics, insurance, and the like. The first industry and the second industry can be any two of a plurality of industries, and the first industry and the second industry can be determined according to the scene of the correlation degree determined by actual needs. For example, if one wants to determine the relevance of the building material industry to the steel industry, the building material industry and the steel industry can be determined as the first industry and the second industry of the present disclosure.

Taking financial indexes of a stock price representation industry as an example, the server can acquire financial index information from a financial transaction platform and send the financial index information to each node of the block chain network in a block form. For example, in units of days, the server may upload the stock price (e.g., closing price), whether an emergency (e.g., stop, pick-up, fine, etc.) and revenue to the blockchain network.

In addition, the server can upload pictures, videos and the like which are helpful for further confirming the industry relevance to the blockchain network.

The financial index information is stored in the blockchain network, so that the financial index information can be guaranteed to be not falsified through the blockchain network, traceable processing of the financial index information can be realized based on the storage of the blockchain network, and safe sharing of the financial index information can be effectively guaranteed.

S14, determining the floating information of the financial indexes of the first industry and the floating information of the financial indexes of the second industry based on the financial index information of the plurality of industries stored in the block chain network.

In an exemplary embodiment of the present disclosure, the floating information of the financial index may be information for characterizing a change of the financial index. Taking stock prices as an example, the float information may indicate that stock prices are rising or falling. In addition, the float information may include a first float information and a second float information, and in the following description, the first float information may represent a rise and is denoted as 1, and the second float information may represent a fall and is denoted as 0. However, the rise may be written as 0 and the fall may be written as 1.

According to some embodiments of the present disclosure, first, the server may determine financial index information of a first industry and financial index information of a second industry within a preset time period from among financial index information of a plurality of industries stored in the blockchain network. The preset time period may be set manually, for example, 200 trading days before the current day, in which case, the stock price of the first industry and the stock price of the second industry may be obtained for each of the 200 trading days.

Next, floating information of the financial index of the first industry for a preset time period and floating information of the financial index of the second industry for the preset time period may be determined. For example, the determined floating information of the financial index of the first industry and the floating information of the financial index of the second industry may be regarded as a numeric string consisting of 1 and 0 recorded in units of days.

And S16, comparing the floating information of the financial indexes of the first industry with the floating information of the financial indexes of the second industry, and determining the association degree of the first industry and the second industry according to the comparison result.

Based on the above, the floating information may include first floating information and second floating information, and thus, comparing the floating information of the financial index of the first industry with the floating information of the financial index of the second industry may include three cases. In a first case, only the first floating information of the financial index of the first industry is compared with the first floating information of the financial index of the second industry; in a second case, only the second floating information of the financial index of the first industry is compared with the second floating information of the financial index of the second industry; in a third case, the first floating information of the financial index of the first industry is compared with the first floating information of the financial index of the second industry, and the second floating information of the financial index of the first industry is compared with the second floating information of the financial index of the second industry.

The following will exemplarily explain the above three cases, respectively.

In the first floating of only the first floating information of the financial index of the first industry and the financial index of the second industry Examples of information comparisons:

first, the server may calculate a support degree and a confidence degree that a predetermined association rule is satisfied. Wherein, the predetermined association rule may be: and when the first floating information appears in the financial index of the first industry, determining that the first floating information appears in the financial index of the second industry. Taking the floating of the stock price as an example, the predetermined association rule is that the stock price of a certain day in the first industry rises, and the stock price of the day in the second industry also rises. In order to distinguish from the following rule, the predetermined association rule in the present embodiment may be denoted as a first association rule.

The support degree can represent that: the ratio of the recorded number of the first floating information of the financial index of the first industry to the total recorded number of the financial index of the second industry is simultaneously the first floating information of the financial index of the first industry. The total number of records may be the preset time period, that is, the total number of records is 200 in the case of taking 200 transaction days.

The confidence level may represent: the ratio of the recorded number of the first floating information of the financial index of the first industry and the first floating information of the financial index of the second industry to the first floating information of the financial index of the first industry is simultaneously obtained.

The support and confidence of the present disclosure are illustrated by taking table 1 as an example.

TABLE 1

Number of days	Floating information for a first industry	Float information for a second industry
			Day 1	1	0
Day 2	1	1
			Day 3	1	0
Day 4	1	1
			Day 5	0	0
Day 6	1	1

Wherein, the first floating information representation rises to be marked as 1. As can be seen from table 1, the dates of the stock price increase of the first industry and the stock price increase of the second industry are day 2, day 4 and day 6. Thus, the support was 3/6 and the confidence was 3/5.

Next, the server may determine a degree of association of the first industry with the second industry based on the calculated support and confidence levels. According to some embodiments of the present disclosure, the support degree and the confidence degree may be weighted and summed, and the result of the weighted and summed may be determined as the association degree of the first industry and the second industry.

Specifically, the following formula can be used to calculate the degree of association:

a＝w1*S+w2*C

wherein, a is the association degree of the first industry and the second industry, S is the support degree, C is the confidence degree, and w1 and w2 are corresponding weights. According to one embodiment, the weights may be set by a developer. According to another embodiment, w1 and w2 can be determined by setting up samples and fitting. This is not particularly limited in the present exemplary embodiment.

It should be appreciated that in the case where the first floating information represents an increase in stock price, the determined degree of association is a degree of association between the first industry and the second industry.

In the second floating of only the second floating information of the financial index of the first industry and the financial index of the second industry Examples of information comparisons:

similarly, first, the server may calculate a support degree and a confidence degree that satisfy another predetermined association rule (denoted as a second association rule) that is: and when the financial index of the first industry has second floating information, determining that the financial index of the second industry has the second floating information. In addition, the definitions of the support degree and the confidence degree are similar to the above description, and are not repeated herein.

Next, the server may determine a degree of association of the first industry with the second industry based on the calculated support and confidence levels. It should be understood that, in the case that the second floating information represents a stock price drop, the determined association degree in the embodiment is the association degree of the stock price drop of the first industry and the second industry.

The first floating message of the financial index of the first industry and the first floating message of the financial index of the second industry are combined The information is compared and second float information of the financial indicators of the first industry is compared with a second float of the financial indicators of the second industry In the embodiment of dynamic information comparison:

first, the support degree and the confidence degree satisfying the first association rule may be calculated, and the first association degree between the first industry and the second industry, that is, the association degree calculated in the first case, may be determined based on the support degree and the confidence degree satisfying the first association rule.

Next, the support degree and the specification degree satisfying the second association rule may be calculated, and the second association degree between the first industry and the second industry, that is, the association degree calculated in the second case, may be determined based on the support degree and the confidence degree satisfying the second association rule.

The server may then determine a degree of association of the first industry with the second industry based on the first degree of association and the second degree of association. Specifically, the first relevance degree and the second relevance degree may be subjected to weighted summation, and a result of the weighted summation may be determined as the relevance degree of the first industry and the second industry. Similarly, the weights herein may be set by a developer, and may also be determined by way of fitting, and the disclosure is not limited in this regard.

Further, the present example embodiment also provides an industry risk determination method based on a block chain.

Fig. 2 schematically illustrates a flowchart of a blockchain-based industry risk determination method of an exemplary embodiment of the present disclosure. Referring to fig. 2, the block chain-based industry risk determination method may include the steps of:

and S22, determining the association degree of the first industry and the second industry by using an industry association degree determination method based on the block chain.

In an exemplary embodiment of the present disclosure, the association degree between the first industry and the second industry may be determined by using the above industry association degree determination method based on the blockchain, and details are not repeated here.

And S24, judging whether the association degree of the first industry and the second industry meets the preset association degree requirement.

In an exemplary embodiment of the present disclosure, the preset association degree requirement may include determining whether the association degree of the first industry and the second industry is greater than a preset association degree threshold. And if the correlation degree is larger than the preset correlation degree threshold value, determining that the preset correlation degree requirement is met. The preset association threshold may be set manually. In addition, the association degree determined by the industry association degree determination method based on the block chain can be normalized to facilitate comparison.

S26, under the condition that the association degree of the first industry and the second industry meets the preset association degree requirement, if the fact that the financial emergency information of the first industry is input into the block chain network is detected, determining whether the second industry has risks according to the financial emergency information of the first industry.

And under the condition that the association degree of the first industry and the second industry meets the preset association degree requirement, indicating that the association degree of the first industry and the second industry is tight. In this case, if a financial emergency (e.g., a drop stop) occurs in the first industry, it may be determined that the second industry is also at risk of a stock price drop. Even if the oscillation of the stock prices of the second industry is not severe, the enterprises in the second industry should take high-risk preventive measures.

In addition, under the condition that the relevance between the first industry and the second industry is strong, when the first industry has risks, the alarm information can be sent to the enterprises of the second industry, so that the enterprises of the second industry can carry out risk prevention deployment in advance.

In addition, for individual investment, the risk determination method can also be used for determining whether the industry or the enterprise has risks so as to avoid investment loss.

It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

A blockchain-based industry risk determination system of an exemplary embodiment of the present disclosure will be described below with reference to fig. 3.

Referring to fig. 3, the blockchain-based industry risk determination system in an exemplary embodiment of the present disclosure may include a blockchain network building subsystem 310, a data format definition subsystem 320, a financial index information storage subsystem 330, an industry risk determination subsystem 340, and a system performance evaluation subsystem 350.

Specifically, the blockchain network building subsystem 310 is used for building, updating and maintaining mechanisms of blockchain nodes and building, updating and maintaining a blockchain network. For example, a blockchain network may be constructed with insurance company base business as a minimum node and based on the participation of one or more insurance groups/companies.

The data format definition subsystem 320 may store information referred to in the present disclosure according to predefined data structures to ensure high efficiency of information storage and information processing. The input may be the daily stock price of the listed enterprise, the sudden events (stop, pick, fine, etc.) of the listed enterprise in the stock market, the revenue of the listed enterprise, and the public key and signature of the related personnel. The output can be storage links of related certificate materials related to the disclosure, association degree of industries, sending out a reminder to related professionals when association of enterprises and industries is abnormally changed, public keys (account addresses) of related information visitors and the like.

Specifically, for example, the predefined data structure may be as shown in table 2:

TABLE 2

In the data structure shown in table 2, since financial index information materials and other materials usually include some information with a relatively large data size, such as images and documents, in order to improve storage efficiency and solve the problem of excessive block information, in an embodiment of the present invention, the relatively large materials, such as images, may be stored in blocks in a linked form, where the linked value is a hash value obtained by encrypting the materials through a hash function, such as SHA1, and the way of obtaining pointer links through the hash function can ensure that the content is not tampered. The actual materials can be stored in local storage equipment of the block chain nodes and can also be stored in a cloud storage mode. Meanwhile, in order to ensure high reliability of material storage, the material may be stored by using a redundant coding method, such as RS coding (Reed-Solomon codes, which is a forward error correction channel coding that is effective for a polynomial generated by correcting oversampled data) or LDPC (Low Density Parity Check Code) coding.

The financial index information storage subsystem 330 is used to store financial index information. Specifically, each piece of financial index information may be uploaded to the blockchain network in the format of table 2, so that the financial index information storage subsystem 330 stores the financial index information.

The industry risk determination subsystem 340 may determine whether the industry has a risk by using the industry risk determination method, which is not described herein again.

The system performance evaluation subsystem 350 may be configured to evaluate the industry risk determination method, and further evaluate timeliness, effectiveness, and accuracy of industry-associated risk management, so as to effectively implement industry-associated risk management in the blockchain network, thereby strongly promoting effective popularization of the blockchain technology in the industry-associated risk management.

Further, an apparatus for determining industry association degree based on block chain is also provided in this example embodiment.

Fig. 4 schematically illustrates a block diagram of a block chain-based industry association determination apparatus according to an exemplary embodiment of the present disclosure. Referring to fig. 4, the block chain-based industry association degree determining apparatus 4 according to an exemplary embodiment of the present disclosure may include an information storage module 41, a floating information determining module 43, and an association degree determining module 45.

Specifically, the information storage module 41 may be configured to store financial index information of multiple industries through a blockchain network; wherein the plurality of industries comprise a first industry and a second industry of which the association degree of the industries is to be determined; the floating information determining module 43 may be configured to determine floating information of the financial index of the first industry and floating information of the financial index of the second industry based on the financial index information of the plurality of industries stored in the blockchain network; the association degree determining module 45 may be configured to compare the floating information of the financial indexes of the first industry with the floating information of the financial indexes of the second industry, and determine the association degree between the first industry and the second industry according to a result of the comparison.

According to an exemplary embodiment of the present disclosure, referring to fig. 5, the floating information determining module 43 may include an information determining unit 501 and a floating information determining unit 503.

Specifically, the information determining unit 501 may be configured to determine, from financial index information of multiple industries stored in the blockchain network, financial index information of the first industry and financial index information of the second industry within a preset time period; the floating information determination unit 503 is configured to determine floating information of the financial index of the first industry within the preset time period and floating information of the financial index of the second industry within the preset time period.

According to an exemplary embodiment of the present disclosure, the floating information includes first floating information and second floating information; referring to fig. 6, the association degree determining module 45 may include a first comparing unit 601 and a second comparing unit 603.

Specifically, the first comparing unit 601 may be configured to compare first floating information of the financial index of the first industry with first floating information of the financial index of the second industry; the second comparing unit 603 may be configured to compare the second floating information of the financial index of the first industry with the second floating information of the financial index of the second industry.

It should be noted that the relevance determining module 45 may also include only the first comparing unit 601, or the relevance determining module 45 may also include only the second comparing unit 603.

According to an exemplary embodiment of the present disclosure, the association determination module is configured to: calculating a support degree and a confidence degree satisfying a predetermined association rule in a case where only the first floating information of the financial index of the first industry is compared with the first floating information of the financial index of the second industry; determining a degree of association of the first industry with the second industry based on the support degree and the confidence degree; wherein the predetermined association rule is: and when the financial index of the first industry has first floating information, determining that the financial index of the second industry has the first floating information.

According to an exemplary embodiment of the present disclosure, the association determination module is configured to: and carrying out weighted summation on the support degree and the confidence degree, and determining the result of the weighted summation as the association degree of the first industry and the second industry.

According to an exemplary embodiment of the present disclosure, the association determination module is configured to: calculating support and confidence that a first association rule is satisfied in a case where first floating information of the financial index of the first industry is compared with first floating information of the financial index of the second industry and second floating information of the financial index of the first industry is compared with second floating information of the financial index of the second industry; determining a first association degree of the first industry with the second industry based on the support degree and the confidence degree which satisfy the first association rule; calculating the support degree and the confidence degree which meet the second association rule; determining a second association degree of the first industry with the second industry based on the support degree and the confidence degree which satisfy the second association rule; determining the association degree of the first industry and the second industry according to the first association degree and the second association degree; wherein the first association rule is: when the financial index of the first industry has first floating information, determining that the financial index of the second industry has the first floating information; the second association rule is: and when the financial index of the first industry has second floating information, determining that the financial index of the second industry has the second floating information.

According to an exemplary embodiment of the present disclosure, the association determination module is configured to: carrying out weighted summation on the support degree and the confidence degree which meet the first association rule, and determining the result of the weighted summation as the first association degree of the first industry and the second industry; and/or carrying out weighted summation on the support degree and the confidence degree meeting the second association rule, and determining the result of the weighted summation as the second association degree of the first industry and the second industry.

According to an exemplary embodiment of the present disclosure, the association determination module is configured to: and carrying out weighted summation on the first relevance and the second relevance, and determining the result of the weighted summation as the relevance of the first industry and the second industry.

On the one hand, the association degree between industries can be effectively determined based on the industry association degree determining device based on the block chain; on the other hand, the financial index information is stored in the blockchain network, so that the financial index information can be guaranteed to be not falsified through the blockchain network, traceable processing of the financial index information can be achieved based on the storage of the blockchain network, and then the safe sharing of the financial index information can be effectively guaranteed.

Further, the example embodiment also provides an industry risk determination device based on the block chain.

Fig. 7 schematically illustrates a block diagram of a blockchain-based industry risk determination apparatus according to an exemplary embodiment of the present disclosure. Referring to fig. 7, the block chain based industry risk determination apparatus 7 according to an exemplary embodiment of the present disclosure may include an association degree determination apparatus 71, an association degree judgment module 73, and a risk determination module 75.

Specifically, the association degree determining device 71 may be the above industry association degree determining device 4 based on the block chain, and is configured to determine the association degree between the first industry and the second industry by using the industry association degree determining method based on the block chain according to any one of the above exemplary embodiments; the association degree determining module 73 may be configured to determine whether the association degree between the first industry and the second industry meets a preset association degree requirement; the risk determining module 75 may be configured to, if it is detected that the financial emergency information of the first industry is entered in the blockchain network, determine whether a risk exists in the second industry according to the financial emergency information of the first industry if the association degree of the first industry and the second industry meets the preset association degree requirement.

On one hand, the association degree between industries can be effectively determined, and whether the industry concerned by the user has risks or not can be determined based on the condition of the associated industries; on the other hand, the financial index information is stored in the blockchain network, so that the financial index information can be guaranteed to be not falsified through the blockchain network, the traceable processing of the financial index information can be realized based on the storage of the blockchain network, and the safe sharing of the financial index information can be effectively guaranteed; in another aspect, the disclosure may determine the industry association degree based on the financial index information stored in the blockchain network, and may determine the industry risk based on the determined association degree, which is helpful for promoting effective popularization of the blockchain technology in the aspect of industry association risk management.

Since each functional module of the program operation performance analysis apparatus according to the embodiment of the present invention is the same as that in the embodiment of the present invention, it is not described herein again.

In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above section "exemplary methods" of the present description, when said program product is run on the terminal device.

Referring to fig. 8, a program product 800 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The 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.

A computer readable signal 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 signal 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 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 an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.

An electronic device 900 according to this embodiment of the invention is described below with reference to fig. 9. The electronic device 900 shown in fig. 9 is only an example and should not bring any limitations to the function and scope of use of the embodiments of the present invention.

As shown in fig. 9, the electronic device 900 is embodied in the form of a general purpose computing device. Components of electronic device 900 may include, but are not limited to: the at least one processing unit 910, the at least one storage unit 920, a bus 930 connecting different system components (including the storage unit 920 and the processing unit 910), and a display unit 940.

Wherein the storage unit stores program code that is executable by the processing unit 910 to cause the processing unit 910 to perform steps according to various exemplary embodiments of the present invention described in the above section "exemplary methods" of the present specification. For example, the processing unit 910 may execute step S12 shown in fig. 1: storing financial index information of a plurality of industries through a block chain network; wherein the plurality of industries comprise a first industry and a second industry of which the association degree of the industries is to be determined; step S14: determining floating information of financial indexes of the first industry and floating information of financial indexes of the second industry based on financial index information of a plurality of industries stored by the blockchain network; step S16: and comparing the floating information of the financial indexes of the first industry with the floating information of the financial indexes of the second industry, and determining the association degree of the first industry and the second industry according to the comparison result. Alternatively, the processing unit 910 may execute step S22 shown in fig. 2: determining the association degree of a first industry and a second industry by using an industry association degree determination method based on a block chain; step S24: judging whether the association degree of the first industry and the second industry meets a preset association degree requirement or not; step S26: and under the condition that the association degree of the first industry and the second industry meets the preset association degree requirement, if the fact that the financial emergency information of the first industry is input into the block chain network is detected, determining whether the second industry has risks according to the financial emergency information of the first industry.

The storage unit 920 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM)9201 and/or a cache memory unit 9202, and may further include a read only memory unit (ROM) 9203.

Storage unit 920 may also include a program/utility 9204 having a set (at least one) of program modules 9205, such program modules 9205 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 930 can be any 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 900 may also communicate with one or more external devices 1000 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 900, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 900 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interface 950. Also, the electronic device 900 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 960. As shown, the network adapter 960 communicates with the other modules of the electronic device 900 via the bus 930. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 900, 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 described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the terms of the appended claims.

Claims

1. A blockchain-based industry relevancy determination system, comprising:

the block chain network construction subsystem is used for constructing a block chain network;

the data format definition subsystem is used for defining the format of the information;

the financial index information storage subsystem is used for storing financial index information, the financial index information is acquired from a financial transaction platform, and the financial index information is uploaded to the block chain network in a form of blocks according to a format defined by the data format definition subsystem;

the industry risk determination subsystem is used for determining floating information of financial indexes of a first industry and floating information of financial indexes of a second industry based on the financial index information of the plurality of industries stored in the block chain network, comparing the floating information of the financial indexes of the first industry with the floating information of the financial indexes of the second industry, and determining the association degree of the first industry and the second industry according to the comparison result;

and the system performance evaluation subsystem is used for evaluating the process of performing the industry risk determination by the industry risk determination subsystem.

2. The blockchain-based industry relevancy determination system of claim 1 wherein the process of the industry risk determination subsystem determining the floating information of the financial indicators of the first industry and the floating information of the financial indicators of the second industry comprises:

determining financial index information of the first industry and financial index information of the second industry within a preset time period from financial index information of a plurality of industries stored in the blockchain network;

and determining the floating information of the financial indexes of the first industry in the preset time period and the floating information of the financial indexes of the second industry in the preset time period.

3. The blockchain-based industry relevancy determination system according to claim 1 or 2, wherein the float information includes a first float information and a second float information; wherein the process of the industry risk determination subsystem comparing the floating information of the financial indicators of the first industry with the floating information of the financial indicators of the second industry comprises:

comparing the first floating information of the financial indicators of the first industry with the first floating information of the financial indicators of the second industry; and/or

Comparing the second floating information of the financial indicators of the first industry with the second floating information of the financial indicators of the second industry.

4. The blockchain-based industry relevancy determination system according to claim 3, wherein in the case of comparing only the first floating information of the financial index of the first industry with the first floating information of the financial index of the second industry, the industry risk determination subsystem determines the relevancy of the first industry and the second industry according to the result of the comparison, including:

calculating the support degree and the confidence degree which meet the preset association rule;

determining a degree of association of the first industry with the second industry based on the support degree and the confidence degree;

wherein the predetermined association rule is: and when the financial index of the first industry has first floating information, determining that the financial index of the second industry has the first floating information.

5. The blockchain-based industry association determination system of claim 4, wherein the industry risk determination subsystem determines the association of the first industry with the second industry based on the support and the confidence level comprises:

and carrying out weighted summation on the support degree and the confidence degree, and determining the result of the weighted summation as the association degree of the first industry and the second industry.

6. The blockchain-based industry relevancy determination system according to claim 3, wherein in a case where the first floating information of the financial index of the first industry is compared with the first floating information of the financial index of the second industry and the second floating information of the financial index of the first industry is compared with the second floating information of the financial index of the second industry, the industry risk determination subsystem determines the relevancy of the first industry and the second industry according to a result of the comparison, including:

calculating the support degree and the confidence degree which meet the first association rule;

determining a first association degree of the first industry with the second industry based on the support degree and the confidence degree which satisfy the first association rule;

calculating the support degree and the confidence degree which meet the second association rule;

determining a second association degree of the first industry with the second industry based on the support degree and the confidence degree which satisfy the second association rule;

determining the association degree of the first industry and the second industry according to the first association degree and the second association degree;

wherein the first association rule is: when the financial index of the first industry has first floating information, determining that the financial index of the second industry has the first floating information; the second association rule is: and when the financial index of the first industry has second floating information, determining that the financial index of the second industry has the second floating information.

7. The blockchain-based industry association determination system of claim 6 wherein the industry risk determination subsystem determines a first association of the first industry with the second industry based on the support and confidence level that satisfies the first association rule comprises:

carrying out weighted summation on the support degree and the confidence degree which meet the first association rule, and determining the result of the weighted summation as the first association degree of the first industry and the second industry; and/or

Determining a second association of the first industry with the second industry based on the support and confidence that satisfies the second association rule comprises:

and performing weighted summation on the support degree and the confidence degree which meet the second association rule, and determining the result of the weighted summation as a second association degree of the first industry and the second industry.

8. The blockchain-based industry relevancy determination system according to claim 6 or 7, wherein the process of the industry risk determination subsystem determining the relevancy of the first industry to the second industry according to the first relevancy and the second relevancy includes:

and carrying out weighted summation on the first relevance and the second relevance, and determining the result of the weighted summation as the relevance of the first industry and the second industry.

9. A blockchain-based industry risk determination device, comprising:

the industry risk determination subsystem of any of claims 1 to 8, configured to determine a degree of association of a first industry with a second industry based on financial index information stored by the blockchain network;

the association degree judging module is used for judging whether the association degree of the first industry and the second industry meets a preset association degree requirement or not;

and the risk determining module is used for determining whether the second industry has risks according to the financial emergency information of the first industry if the financial emergency information of the first industry is detected to be input into the block chain network under the condition that the association degree of the first industry and the second industry meets the preset association degree requirement.