CN110599098A - Logistics industry-based block chain credit investigation management method and system - Google Patents
Logistics industry-based block chain credit investigation management method and system Download PDFInfo
- Publication number
- CN110599098A CN110599098A CN201910875096.9A CN201910875096A CN110599098A CN 110599098 A CN110599098 A CN 110599098A CN 201910875096 A CN201910875096 A CN 201910875096A CN 110599098 A CN110599098 A CN 110599098A
- Authority
- CN
- China
- Prior art keywords
- data
- credit
- logistics
- block chain
- credit investigation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0835—Relationships between shipper or supplier and carriers
Abstract
The invention discloses a credit investigation management method and a credit investigation management system of a block chain based on the logistics industry, and relates to the field of credit investigation. The credit investigation management method based on the block chain comprises the steps that at least one third-party node and a plurality of logistics transportation nodes are located in the same block chain network, and credit investigation data related to the third-party node and credit data related to each logistics transportation node are stored in the block chain network; the credit investigation management method based on the block chain comprises the following steps: acquiring credit data and credit investigation data corresponding to logistics participants from the block chain network; and calculating the credit level of the logistics participants according to the credit data and the weight value corresponding to the credit investigation data. The invention gives corresponding credit levels to each logistics participant through the data provided by each node connected to the block chain network and multi-dimensional consideration, and the provided credit levels are real and reliable based on the technical characteristics that the block chain technology is not falsifiable and can be shared.
Description
Technical Field
The invention relates to the field of credit investigation, in particular to a credit investigation management method and system of a block chain based on the logistics industry.
Background
The logistics industry has long transportation chain, and many small and medium-sized enterprises and individual drivers have the phenomena of improper competition and frequent dispute, so that the whole transportation order is disordered, and the rights and interests of legal management main bodies cannot be effectively guaranteed.
The trust between the upstream and the downstream of the freight platform is lost, the transaction party can only use the freight platform as a guarantee, and the credit condition of the other party is known through the transaction data on the freight platform where the transaction party is located. And the trade contract default cost of the logistics industry is low, the default date of one party brings huge economic loss to the other party, the actual credit investigation data of the trading party can not be effectively reflected only by the mutual trade data on one freight platform, and the real credit situation can not be mastered, so that the mutual cooperation has higher trade risk.
At present, based on a third-party credit investigation system, each centralized logistics freight platform and the long-tailed freight and transportation enterprises related to the logistics freight platform, an information island exists, credit data which are mutually assessed and accumulated in business only exist in respective business systems, due to various reasons, the data cannot be shared, so that the communication cost is high, and a huge improvement space exists for the efficiency of the whole industry.
Disclosure of Invention
In order to solve the current situation that a system in the logistics industry is isolated and credit investigation data has an island, the invention provides a credit investigation management method and system based on a block chain in the logistics industry.
The technical scheme provided by the invention is as follows:
at least one third-party node and a plurality of logistics transportation nodes are located in the same block chain network, and credit investigation data related to the third-party node and credit data related to each logistics transportation node are stored in the block chain network; the credit investigation management method based on the block chain comprises the following steps: acquiring credit data and credit investigation data corresponding to logistics participants from the block chain network; and calculating the credit level of the logistics participants according to the credit data and the weight value corresponding to the credit investigation data.
In the technical scheme, the data provided by each node connected to the blockchain network is considered in a multi-dimensional mode, the corresponding credit level is provided for each logistics participant, the provided credit level is real and reliable based on the technical characteristics that the blockchain technology cannot be tampered and can be shared, the provided credit level can be called by each node in the blockchain network in real time, the communication cost among different nodes is omitted, and the fair, open and benign competitive transportation order is provided.
Further, the acquiring credit data and credit investigation data corresponding to the logistics participants from the blockchain network includes: when a logistics participant joins the block chain network for the first time, giving a unique identity to the logistics participant; and acquiring credit data and credit investigation data corresponding to the identity from the block chain network.
In the technical scheme, the source of the data is accurately identified through the unique identity, so that the authenticity of the data is verified, inquiry and calling of credit investigation data are further performed, and convenience and rapidness are realized.
Further, the block chain network also stores service data related to each logistics transportation node; wherein the credit data of the logistics participants changes along with the update of the business data of the logistics participants.
In the technical scheme, the credit data changes in real time along with the service data, so that the trueness and reliability of the credit level are ensured.
Further, the credit investigation management method based on the block chain of the logistics industry further comprises the following steps: when credit data or credit investigation data of a logistics participant change and at least one periodic condition is met, updating the weight values corresponding to the credit data and the credit investigation data; the periodic conditions include: periodically adjusting time points, and adding a third party node or a logistics transportation node in a block chain network; and recalculating the credit level of the logistics participants according to the updated weight value corresponding to each credit data and each credit investigation data.
In the technical scheme, the logistics participants can improve the credit level of themselves by improving the service level of themselves so as to obtain more services in the transaction process.
Further, the credit investigation data comprises any one or more of the following data: the system comprises the following steps of (1) industrial and commercial administration penalty data, bank loan default data, road administration overrun data, tax stealing and leaking data, identity data, crime data and violation data; the credit data includes any one or more of: credit point data and grade data corresponding to each freight platform.
In the technical scheme, various data are stored in the block chain network, so that the provision of multi-dimensional data is ensured, and the calculated credit level is more reliable and real.
The invention also provides a credit investigation management system of the block chain based on the logistics industry, which comprises the following components: the system comprises at least one third-party node and a plurality of logistics transportation nodes, wherein the at least one third-party node and the plurality of logistics transportation nodes are located in the same block chain network, and credit data related to the third-party node and credit data related to each logistics transportation node are stored in the block chain network; the block chain-based credit investigation management system comprises: the acquisition module is used for acquiring credit data and credit investigation data corresponding to the logistics participants from the block chain network; and the evaluation module is used for calculating the credit level of the logistics participant according to the credit data and the weight value corresponding to the credit investigation data.
Further, still include: the identity module is used for endowing a logistics participant with a unique identity when the logistics participant joins the block chain network for the first time; the obtaining module is configured to obtain credit data and credit investigation data corresponding to the logistics participants from the blockchain network, where the credit data and credit investigation data include: the acquisition module is used for acquiring credit data and credit investigation data corresponding to the identity corresponding to the logistics participant from the block chain network.
Further, the block chain network also stores service data related to each logistics transportation node; wherein the credit data of the logistics participants changes along with the update of the business data of the logistics participants.
Further, the credit investigation management system based on the block chain of the logistics industry further comprises: the updating module is used for updating the weight values corresponding to the credit data and the credit investigation data when the credit data or the credit investigation data of a logistics participant changes and at least one periodic condition is reached; the periodic conditions include: periodically adjusting time points, and adding a third party node or a logistics transportation node in a block chain network; the evaluation module is further configured to recalculate the credit level of the logistics participant according to the updated weight value corresponding to each credit data and the credit investigation data.
Further, the credit investigation data comprises any one or more of the following data: the system comprises the following steps of (1) industrial and commercial administration penalty data, bank loan default data, road administration overrun data, tax stealing and leaking data, identity data, crime data and violation data; the credit data includes any one or more of: credit point data and grade data corresponding to each freight platform.
Compared with the prior art, the credit investigation management method and system of the block chain based on the logistics industry have the advantages that:
according to the invention, through data provided by each node connected into the blockchain network and multi-dimensional consideration, corresponding credit levels are provided for each logistics participant, based on the technical characteristics that the blockchain technology can not be tampered and can be shared, the provided credit levels are real and reliable, and can be called by each node in the blockchain network in real time, so that the communication cost among different nodes is saved, and a fair and open benign competitive transportation order is provided, thereby improving the transportation efficiency of the whole logistics industry.
Drawings
The above features, technical features, advantages and implementation manners of a block chain credit investigation management method and system based on the logistics industry will be further described in the following preferred embodiments in a clearly understandable manner with reference to the accompanying drawings.
Fig. 1 is a flowchart of an embodiment of a block chain-based credit investigation method according to the present invention;
fig. 2 is a flowchart of another embodiment of a block chain-based credit investigation method according to the present invention;
FIG. 3 is a block-chain network architecture according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an embodiment of a block chain-based credit investigation management system of the present invention;
fig. 5 is a schematic structural diagram of another embodiment of the block chain-based credit investigation management system according to the present invention.
The reference numbers illustrate:
1. the system comprises logistics transportation nodes, 2 block chain networks, 3 third party nodes, 41 acquisition modules, 42 evaluation modules, 43 identity modules and 44 updating modules.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
For the sake of simplicity, the drawings only schematically show the parts relevant to the present invention, and they do not represent the actual structure as a product. In addition, in order to make the drawings concise and understandable, components having the same structure or function in some of the drawings are only schematically illustrated or only labeled. In this document, "one" means not only "only one" but also a case of "more than one".
First, to better understand the present solution, terms that may be involved in the following embodiments are explained as follows:
the logistics transportation node refers to the node that each logistics participant corresponds, and the logistics participant includes: shippers, carriers, shipping platforms, and the like.
The cargo owner refers to an enterprise or an individual who issues a cargo source demand by using a network platform of a freight enterprise, and can set a corresponding number of logistics transportation nodes according to the traffic volume, for example: one (enterprise) goods owner corresponds to one logistics transportation node; a special logistics transportation node corresponds to all the individual owners of goods and the like.
The carrier, a carrier enterprise or an independent carrier driver, is responsible for the transportation and carrying of the actual business. A corresponding number of logistics transportation nodes can be set according to the traffic volume, for example: one (enterprise) carrier corresponds to one logistics transportation node, and one logistics transportation node is specially deployed to manage all independent carrier drivers.
The freight platform, also called network freight operator (policy agreement), develops the platform-type enterprise for carrying, has independent network platform (TMS, web end, app, small program, etc.) to develop the on-line business, and is responsible for docking the upstream and downstream of the transportation. Optionally, one freight platform corresponds to one logistics transportation node.
The logistics industry-based block chain credit investigation management method and system store data related to each logistics transportation node and a third party node to a block chain network by using a block chain technology, evaluate credit levels of each logistics participant in a multi-dimensional manner based on a mechanism that data stored in the block chain network can be shared in real time, and ensure authenticity and reliability of given credit levels due to the fact that the data stored in the block chain network cannot be tampered and deleted at will.
The process of storing information into the blockchain network by each node in the blockchain network is as follows: each node has its corresponding blockchain ledger, and because the nodes are in the same blockchain network, the data (or information) stored on the blockchain ledger of each node is the same. When one node needs to store new information, the node writes the information into one block, broadcasts the information to other nodes, and enables each node to update the block chain account book of the node.
When each node writes data, a rule when a new block is generated is that any one of the following rules is satisfied:
1. according to the information storage capacity limit of one block. For example: assuming that the information storage capacity of one block is 500k at most, when one block is full, one block needs to be regenerated.
2. According to the number of pieces of information in one block. For another example: assuming that the number of pieces of information stored in one block is 100 at most, when the number of pieces of information stored in one block reaches 100, one block needs to be regenerated.
3. The generation time interval of each block. For another example: assuming that the generation time interval of each tile is 5 minutes, a new tile is generated every 5 minutes.
In an embodiment of the present invention, as shown in fig. 3, in a block chain-based credit investigation management method, at least one third party node 3 and a plurality of logistics transportation nodes 1 are located in the same block chain network 2, and credit investigation data related to the third party node 3 and credit data related to each logistics transportation node 1 are stored in the block chain network 2.
Specifically, the third-party node refers to a node other than the logistics participant. The objects corresponding to the third party nodes may be: a third party credit investigation institution (such as sesame credit, bank credit investigation, etc.), a public security system, a road administration system, a bank system, a tax system, etc.
Each system can set one or more corresponding third-party nodes to be connected into the block chain network according to actual requirements.
For example: the block chain network comprises a third-party node of a public security system, a third-party node of a business recruitment bank system and a third-party node of an agricultural bank system.
Each third-party node stores the related credit investigation data to the block chain network to realize data sharing.
Each third-party node is different according to the corresponding object, and the category of the credit investigation data is also different. For example: if the third-party node A is a public security system, the credit investigation data related to the third-party node A is identity data and crime data; if the third-party node B is a road administration system, the credit investigation data related to the third-party node B is violation data (such as overspeed and red light running), road administration overrun data (such as whether a ticket is paid on time) and the like; if the third-party node C is a tax system, the credit collection data related to the third-party node C is tax evasion data.
Thus, the credit data includes any one or more of: the system comprises the following data of industrial and commercial administration penalty data, bank loan default data, road administration overrun data, tax stealing and leaking data, identity data, crime data and violation data.
The credit data related to the logistics transportation node refers to data corresponding to a credit system used by each freight transportation platform. For example: the credit system used by the freight platform A is credit points, and the logistics transportation nodes corresponding to the freight platform A store the credit points of all logistics participants to the block chain network; and if the credit system used by the freight platform B is the credit level, the logistics transportation node corresponding to the freight platform B stores the credit level of each logistics participant to the block chain network.
Accordingly, the credit data includes any one or more of: credit point data and grade data corresponding to each freight platform.
As shown in fig. 1, the credit investigation management method based on the block chain of the logistics industry includes:
s101, credit data and credit investigation data corresponding to the logistics participants are obtained from the block chain network.
S102, calculating the credit level of the logistics participant according to the credit data and the weight value corresponding to the credit investigation data.
Specifically, each node stores the related credit investigation data and credit data in a block chain network, which can be shared, so that the data can be used for comprehensively evaluating each logistics participant (namely each cargo owner, each carrier and each freight platform) to give a credit level considering multiple dimensions, and the reliability of the credit level is improved.
The credit data and the credit investigation data have different weights respectively. Optionally, the weight of the credit data is less than the weight of the credit data.
The credit data is obtained by self evaluation of the freight platform according to the business data, and the public trust strength of the credit data is less than that of an official party, so that smaller weight is given. And the credit investigation data is given by a third-party node, most of the credit investigation data is official data, the credit investigation data has larger public trust strength, and the credit investigation data is given higher weight to effectively reflect the credit condition of the logistics participant.
Optionally, the credit data is assigned with different weights according to different sources of the credit data. For example: the credit data includes 1) tax evasion data from the tax system, 2) loan default data from the banking system, and 3) violation data from the road administration system, 1) and 2) are assigned higher weights, and 3) are assigned relatively lower weights.
For example: the credit investigation data corresponding to a logistics participant in the block chain comprises: tax evasion data, loan default data and violation data, and the corresponding credit data comprises: the credit points of the freight platform A and the credit levels of the freight platform B are distributed with different weights, and the calculated credit levels are as follows: 0.1 credit points of the platform a +0.1 credit rating of the platform B +0.2 violation data +0.3 tax evasion data +0.3 debit default data.
It should be noted that the above example only exemplarily shows that each data may be assigned with different weights, and is not an actual operation formula, and when the data is actually applied, different weights may be assigned in other ways (for example, a credit level model is established by using an existing machine learning algorithm, etc.), and is not limited herein.
After the credit rating of each logistics participant is calculated according to credit investigation data and credit data stored in the block chain network, all the persons can check the credit rating, and when a transaction exists, both transaction parties can know the credit rating of the other party, so that the transaction can be generally known, and the subsequent promotion of the transaction is facilitated.
Optionally, the step S101 of acquiring credit data and credit investigation data corresponding to the logistics participants from the blockchain network includes:
when a logistics participant joins the block chain network for the first time, giving a unique identity to the logistics participant;
and acquiring credit data and credit investigation data corresponding to the identity from the block chain network.
Specifically, when all logistics participants join the blockchain network for the first time, the corresponding unique identity is given (or can be understood as being distributed), so that subsequent data query, call and verification are facilitated.
For example: when the logistics participant is an individual, the identity card number of the logistics participant can be based, and when the logistics participant is an enterprise, the uniqueness of the unified social credit code of the logistics participant can be based, and corresponding main bodies joining the block chain network are endowed with secret key CA certificates (namely identity marks) by using a block chain cryptography mechanism, so that the secret key CA certificates are used for verifying the data behind the main bodies. Ensuring that the data is produced by the subject rather than being forged or tampered with while achieving cryptographic privacy of the data.
When the credit level of each logistics participant is calculated subsequently, the corresponding credit data and credit investigation data can be obtained through the identity, and the inquiry speed is high, and the method is real and reliable.
When in transaction, the two parties of the transaction positioned in the blockchain network can check and see the credit rating calculated based on the multiple dimensions for evaluation, thereby reducing the transaction risk.
Optionally, the block chain network further includes a supervisory node; and the supervision node supervises each data in the blockchain network through the corresponding blockchain account book.
Specifically, when the government wants to monitor the data of all the logistics participants in a unified manner, corresponding monitoring nodes can be directly set to be connected into the block chain network, unified monitoring is achieved according to the corresponding block chain account book, data do not need to be taken from all the logistics participants, and monitoring efficiency and reliability are improved.
In this embodiment, the credit investigation management method for the block chain based on the logistics industry gives a corresponding credit level to each logistics participant through data provided by each node connected to the block chain network in consideration of multiple dimensions, and based on the technical characteristics that the block chain technology is not falsifiable and can be shared, the provided credit level is real and reliable, and can be called by each node in the block chain network in real time, thereby omitting communication cost among different nodes, and providing a fair and open transportation order of benign competition.
In another embodiment of the present invention, in a block chain credit investigation management method based on the logistics industry, at least one third party node and a plurality of logistics transportation nodes are located in the same block chain network, and credit investigation data related to the third party node, credit data related to each logistics transportation node, and business data related to each logistics transportation node are stored in the block chain network; wherein the credit data of the logistics participants changes along with the update of the business data of the logistics participants. And the credit investigation data related to the third-party node is updated according to the actual situation.
Specifically, the logistics transportation node generates a large amount of service data, and the credit data related to the logistics transportation node is calculated according to the service data, so that the credit data of the logistics participants can change along with the change of the service data.
For example: the carrier A accepts the business on the freight platform B, the freight platform B gives out the corresponding credit data according to the business data of the carrier A, and the business data comprises but is not limited to: waybill information, owner information, driver information, reconciliation information, vehicle transportation track, default information on the freight platform, and the like.
Optionally, in an actual process that the logistics transportation node writes data into the blockchain network, the blockchain network further includes: and each logistics transportation node submits the service data updated in real time and the credit data updated according to the service to the sequencing node through a corresponding application interface, and the sequencing node establishes a block and writes the block according to the sequenced data after sequencing the received service data and the credit data according to time, and stores the block into the block chain network after verification. The actual operation steps stored in the blockchain network are as follows: and the sequencing node broadcasts to other nodes, and after verification, other nodes update the block chain accounts corresponding to the other nodes, so that the information stored in the block chain accounts corresponding to each node is the same.
As shown in fig. 2, the credit investigation management method based on the block chain of the logistics industry includes:
s201, acquiring credit data and credit investigation data corresponding to logistics participants from the block chain network;
s202, calculating the credit level of the logistics participant according to the credit data and the weight value corresponding to the credit investigation data;
s203, when credit data or credit investigation data of a logistics participant change and reach at least one periodic condition, updating weight values corresponding to the credit data and the credit investigation data; the periodic conditions include: periodically adjusting time points, and adding a third party node or a logistics transportation node in a block chain network;
when any periodic condition is not met, the weight values corresponding to the credit data and the credit investigation data are not updated;
s204, recalculating the credit rating of the logistics participant according to the updated weight value corresponding to each (changed) credit data and the (changed) credit assessment data.
Specifically, the logistics participant can increase its credit level by trying to complete the service even if the initial credit level is not ideal, and thus, it is set to adjust the weight value according to the number of goodwill.
The credit investigation data comprises any one or more of the following: the system comprises the following steps of (1) industrial and commercial administration penalty data, bank loan default data, road administration overrun data, tax stealing and leaking data, identity data, crime data and violation data;
the credit data includes any one or more of: credit point data and grade data corresponding to each freight platform.
For example: the periodic adjustment time point is 1 month and 1 day every year, when the credit data or credit investigation data of a logistics participant changes and reaches 1 month and 1 day, the time that the weight can be adjusted every year is shown, the weight values corresponding to the logistics participant credit data and the credit investigation data are updated according to comprehensive consideration of all nodes of the whole network, and the calculated credit level is in accordance with the actual situation when in use, so that the level is not excessively low or excessively high.
For another example: when a new node is added into the block chain network, the considered data is increased by one, and the weight value needs to be redistributed.
The reason why the periodic condition is judged when the credit data or credit investigation data of the logistics participants change is to ensure the real-time performance of the credit level of the logistics participants, if the credit data or credit investigation data is not updated all the time, it is indicated that the logistics participants are inactive for a long time, and the weight values are updated, so that the logistics participants do not need to update the weight values, and only occupy more system resources.
Optionally, the weight value corresponding to the credit data has an upper limit, that is, no matter how the weight value of the credit data is adjusted, it does not exceed the upper limit.
Similarly, the weight value corresponding to the credit investigation data has a lower limit, and no matter how the weight value of the credit investigation data is reduced, the weight value is not lower than the lower limit.
As an implementation manner, the manner of increasing the weight value corresponding to the credit data may be adjusted by adopting a preset first step value; similarly, the manner of reducing the weight value corresponding to the credit investigation data can also be adjusted by adopting the manner of presetting the second step value. The preset first step value and the preset second step value may be set to be the same or different, and are determined according to actual conditions.
As another embodiment, the weight values corresponding to the credit data and the credit investigation data are automatically learned and adjusted by a machine learning algorithm, so that the adjusted weight can be used for objectively calculating a credit level which tends to be reasonable. The machine learning algorithm is adopted for adjustment, manual participation is not needed, multi-dimensional consideration can be achieved, the adjusted weighted value is more reasonable and accurate, and the accuracy of the calculated credit level is improved.
Optionally, when credit data or credit investigation data of a logistics participant changes, the credit level of the logistics participant is recalculated according to the changed credit data and the weight value corresponding to the credit investigation data.
Specifically, the credit data or credit investigation data of the logistics participants can change along with the behavior of the logistics participants, and if the credit data or credit investigation data changes, the corresponding credit level of the logistics participants can be updated in real time, so that the real-time performance of the credit level of the logistics participants is guaranteed.
Optionally, the weight of the credit data is less than the weight of the credit data.
In this embodiment, the logistics participants can increase their credit levels by trying to increase their service levels, which is convenient for obtaining more services and business values in the logistics industry.
Practical examples are as follows:
the THL of a certain logistics enterprise joins a block chain network which is dominant by the enterprise in a month of 2019, and the method is equivalent to a credit investigation platform. And adding the block chain network to perform enterprise identity authentication to obtain a unique identity mark. And the block link network simultaneously establishes a data transmission channel at a third party including deployment nodes of an industrial and commercial administration department, each big bank, a road administration system, a tax administration and the like, acquires related credit investigation data of the THL in the organizations, including information such as normal transaction data and bad records, and if the credit investigation data does not have the credit investigation data of the related logistics transportation nodes, the credit investigation data does not exist. This information is cross-validated (i.e., considered together) over the blockchain network and a score is derived from which the confidence level of THL is assessed. The THG of a certain logistics enterprise joins the blockchain network in the same month and gets the credit level according to the above steps. The credit levels of each other's enterprises in the blockchain network may be reviewed to each other upon collaboration of THL with THG negotiations to determine a collaboration risk. The credit rating is high, the natural credit is good, the popularity is high, and the commercial environment is purified according to the superiority and the inferiority.
It should be understood that, in the above embodiments, the size of the sequence number of each step does not mean the execution sequence, and the execution sequence of each step should be determined by functions and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In an embodiment of the credit investigation management system based on the block chain of the logistics industry, the credit investigation management system comprises: the system comprises at least one third-party node and a plurality of logistics transportation nodes, wherein the at least one third-party node and the plurality of logistics transportation nodes are located in the same block chain network, and credit data related to the third-party node and credit data related to each logistics transportation node are stored in the block chain network.
Specifically, the third-party node refers to a node other than the logistics participant. The objects corresponding to the third party nodes may be: third party credit bureaus (e.g., sesame credit), public security systems, road administration systems, banking systems, tax systems, etc.
Each system can set one or more corresponding third-party nodes to be connected into the block chain network according to actual requirements. Each third-party node stores the related credit investigation data to the block chain network to realize data sharing.
Each third-party node is different according to the corresponding object, and the category of the credit investigation data is also different. For example: if the third-party node A is a public security system, the credit investigation data related to the third-party node A is identity data and crime data; if the third-party node B is a road administration system, the credit investigation data related to the third-party node B is violation data (such as overspeed and red light running), road administration overrun data (such as whether a ticket is paid on time) and the like; if the third-party node C is a tax system, the credit collection data related to the third-party node C is tax evasion data.
Thus, the credit data includes any one or more of: the system comprises the following data of industrial and commercial administration penalty data, bank loan default data, road administration overrun data, tax stealing and leaking data, identity data, crime data and violation data.
The credit data related to the logistics transportation node refers to data corresponding to a credit system used by each freight transportation platform. For example: the credit system used by the freight platform A is credit points, and the logistics transportation nodes corresponding to the freight platform A store the credit points of all logistics participants to the block chain network; and if the credit system used by the freight platform B is the credit level, the logistics transportation node corresponding to the freight platform B stores the credit level of each logistics participant to the block chain network.
Accordingly, the credit data includes any one or more of: credit point data and grade data corresponding to each freight platform.
As shown in fig. 4, the credit investigation management system based on the block chain of the logistics industry includes:
an obtaining module 41, configured to obtain credit data and credit investigation data corresponding to the logistics participants from the blockchain network;
and the evaluation module 42 is configured to calculate a credit level of the logistics participant according to each credit data and a weight value corresponding to the credit investigation data.
Specifically, each node stores the related credit investigation data and credit data in a block chain network, which can be shared, so that the data can be used for comprehensively evaluating each logistics participant (namely each cargo owner, each carrier and each freight platform) to give a credit level considering multiple dimensions, and the reliability of the credit level is improved.
The credit data and the credit investigation data have different weights respectively. Optionally, the weight of the credit data is less than the weight of the credit data.
The credit data is obtained by self evaluation of the freight platform according to the business data, and the public trust strength of the credit data is less than that of an official party, so that smaller weight is given. And the credit investigation data is given by a third-party node, most of the credit investigation data is official data, the credit investigation data has larger public trust strength, and the credit investigation data is given higher weight to effectively reflect the credit condition of the logistics participant.
Optionally, the credit data is assigned with different weights according to different sources of the credit data.
After the credit rating of each logistics participant is calculated according to credit investigation data and credit data stored in the block chain network, all the persons can check the credit rating, and when a transaction exists, both transaction parties can know the credit rating of the other party, so that the transaction can be generally known, and the subsequent promotion of the transaction is facilitated.
Optionally, the credit investigation management system based on the block chain of the logistics industry further includes:
an identity module 43, configured to give a unique identity to a logistics participant when the logistics participant joins the blockchain network for the first time;
the obtaining module 41 is configured to obtain credit data and credit investigation data corresponding to the logistics participants from the blockchain network, where the obtaining module is configured to:
the obtaining module 41 is configured to obtain credit data and credit investigation data corresponding to the identity identifier corresponding to the logistics participant from the blockchain network.
Specifically, when all logistics participants join the blockchain network for the first time, the corresponding unique identity is given (or can be understood as being distributed), so that subsequent data query, call and verification are facilitated.
When the credit level of each logistics participant is calculated subsequently, the corresponding credit data and credit investigation data can be obtained through the identity, and the inquiry speed is high, and the method is real and reliable.
When in transaction, the two parties of the transaction positioned in the blockchain network can check and see the credit rating calculated based on the multiple dimensions for evaluation, thereby reducing the transaction risk.
Optionally, the block chain network further includes a supervisory node; and the supervision node supervises each data in the blockchain network through the corresponding blockchain account book.
Specifically, when the government wants to monitor the data of all the logistics participants in a unified manner, corresponding monitoring nodes can be directly set to be connected into the block chain network, unified monitoring is achieved according to the corresponding block chain account book, data do not need to be taken from all the logistics participants, and monitoring efficiency and reliability are improved.
In this embodiment, the credit investigation management method for the block chain based on the logistics industry gives a corresponding credit level to each logistics participant through data provided by each node connected to the block chain network in consideration of multiple dimensions, and based on the technical characteristics that the block chain technology is not falsifiable and can be shared, the provided credit level is real and reliable, and can be called by each node in the block chain network in real time, thereby omitting communication cost among different nodes, and providing a fair and open transportation order of benign competition.
In another embodiment of the credit investigation management system based on the block chain of the logistics industry, the credit investigation management system comprises: the system comprises at least one third-party node and a plurality of logistics transportation nodes, wherein the at least one third-party node and the plurality of logistics transportation nodes are located in the same block chain network, and credit data related to the third-party node, credit data related to each logistics transportation node and service data related to each logistics transportation node are stored in the block chain network; wherein the credit data of the logistics participants changes along with the update of the business data of the logistics participants. And the credit investigation data related to the third-party node is updated according to the actual situation.
Specifically, the logistics transportation node generates a large amount of service data, and the credit data related to the logistics transportation node is calculated according to the service data, so that the credit data of the logistics participants can change along with the change of the service data.
As shown in fig. 5, the credit investigation management system based on the block chain of the logistics industry includes:
an obtaining module 41, configured to obtain credit data (corresponding to the identity tag) and credit investigation data corresponding to the logistics participant from the blockchain network. Optionally, the identity module 43 is configured to designate an identity tag corresponding to a logistics participant when the logistics participant joins the blockchain network for the first time.
And the evaluation module 42 is configured to calculate a credit level of the logistics participant according to each credit data and a weight value corresponding to the credit investigation data.
The updating module 44 is configured to update the weight values corresponding to the credit data and the credit investigation data when the credit data or the credit investigation data of a logistics participant changes and at least one periodic condition is reached; the periodic conditions include: periodically adjusting time points, and adding a third party node or a logistics transportation node in a block chain network; when any periodic condition is not met, the weight values corresponding to the credit data and the credit investigation data are not updated;
the evaluation module 42 is further configured to recalculate the credit rating of the logistics participant according to each of the (changed) credit data and the updated weight value corresponding to the (changed) credit data.
Specifically, the logistics participant can increase its credit level by trying to complete the service even if the initial credit level is not ideal, and thus, it is set to adjust the weight value according to the number of goodwill.
The credit investigation data comprises any one or more of the following: the system comprises the following steps of (1) industrial and commercial administration penalty data, bank loan default data, road administration overrun data, tax stealing and leaking data, identity data, crime data and violation data;
the credit data includes any one or more of: credit point data and grade data corresponding to each freight platform.
Optionally, the weight value corresponding to the credit data has an upper limit, that is, no matter how the weight value of the credit data is adjusted, it does not exceed the upper limit. Similarly, the weight value corresponding to the credit investigation data has a lower limit, and no matter how the weight value of the credit investigation data is reduced, the weight value is not lower than the lower limit.
As an implementation manner, the manner of increasing the weight value corresponding to the credit data may be adjusted by adopting a preset first step value; similarly, the manner of reducing the weight value corresponding to the credit investigation data can also be adjusted by adopting the manner of presetting the second step value. The preset first step value and the preset second step value may be set to be the same or different, and are determined according to actual conditions.
As another embodiment, the weight values corresponding to the credit data and the credit investigation data are automatically learned and adjusted by a machine learning algorithm, so that the adjusted weight can be used for objectively calculating a credit level which tends to be reasonable. The machine learning algorithm is adopted for adjustment, manual participation is not needed, multi-dimensional consideration can be achieved, the adjusted weighted value is more reasonable and accurate, and the accuracy of the calculated credit level is improved. Optionally, the weight of the credit data is less than the weight of the credit data.
Optionally, the evaluation module 42 is further configured to, when credit data or credit investigation data of a logistics participant changes, recalculate the credit level of the logistics participant according to each changed credit data or weight value corresponding to the credit investigation data.
In this embodiment, the logistics participants can increase their credit levels by trying to increase their service levels, which is convenient for obtaining more services and business values in the logistics industry.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or recited in detail in a certain embodiment.
It should be noted that the above embodiments can be freely combined as necessary. The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A credit investigation management method based on block chains in the logistics industry is characterized in that at least one third-party node and a plurality of logistics transportation nodes are located in the same block chain network, and credit investigation data related to the third-party node and credit data related to each logistics transportation node are stored in the block chain network;
the credit investigation management method based on the block chain comprises the following steps:
acquiring credit data and credit investigation data corresponding to logistics participants from the block chain network;
and calculating the credit level of the logistics participants according to the credit data and the weight value corresponding to the credit investigation data.
2. The credit investigation management method based on the block chain of the logistics industry of claim 1, wherein the obtaining credit data and credit investigation data corresponding to the logistics participants from the block chain network comprises:
when a logistics participant joins the block chain network for the first time, giving a unique identity to the logistics participant;
and acquiring credit data and credit investigation data corresponding to the identity from the block chain network.
3. The credit investigation management method based on the block chain of the logistics industry as claimed in claim 1, wherein the block chain network further stores the service data related to each logistics transportation node;
wherein the credit data of the logistics participants changes along with the update of the business data of the logistics participants.
4. The credit investigation management method based on the block chain of the logistics industry as claimed in claim 3, further comprising:
when credit data or credit investigation data of a logistics participant change and at least one periodic condition is met, updating the weight values corresponding to the credit data and the credit investigation data; the periodic conditions include: periodically adjusting time points, and adding a third party node or a logistics transportation node in a block chain network;
and recalculating the credit level of the logistics participants according to the updated weight value corresponding to each credit data and each credit investigation data.
5. The credit investigation management method based on the block chain of the logistics industry as claimed in claim 1, wherein:
the credit investigation data comprises any one or more of the following data: the system comprises the following steps of (1) industrial and commercial administration penalty data, bank loan default data, road administration overrun data, tax stealing and leaking data, identity data, crime data and violation data;
the credit data includes any one or more of: credit point data and grade data corresponding to each freight platform.
6. A credit investigation management system based on block chain of logistics industry is characterized by comprising: the system comprises at least one third-party node and a plurality of logistics transportation nodes, wherein the at least one third-party node and the plurality of logistics transportation nodes are located in the same block chain network, and credit data related to the third-party node and credit data related to each logistics transportation node are stored in the block chain network;
the block chain-based credit investigation management system comprises:
the acquisition module is used for acquiring credit data and credit investigation data corresponding to the logistics participants from the block chain network;
and the evaluation module is used for calculating the credit level of the logistics participant according to the credit data and the weight value corresponding to the credit investigation data.
7. The credit management system based on block chain of logistics industry as claimed in claim 6, further comprising:
the identity module is used for endowing a logistics participant with a unique identity when the logistics participant joins the block chain network for the first time;
the obtaining module is configured to obtain credit data and credit investigation data corresponding to the logistics participants from the blockchain network, where the credit data and credit investigation data include:
the acquisition module is used for acquiring credit data and credit investigation data corresponding to the identity corresponding to the logistics participant from the block chain network.
8. The credit management system based on the block chain of the logistics industry of claim 6, wherein the block chain network further stores the service data related to each logistics transportation node; wherein the credit data of the logistics participants changes along with the update of the business data of the logistics participants.
9. The credit investigation management system based on block chain of logistics industry as claimed in claim 8, further comprising:
the updating module is used for updating the weight values corresponding to the credit data and the credit investigation data when the credit data or the credit investigation data of a logistics participant changes and at least one periodic condition is reached; the periodic conditions include: periodically adjusting time points, and adding a third party node or a logistics transportation node in a block chain network;
the evaluation module is further configured to recalculate the credit level of the logistics participant according to the updated weight value corresponding to each credit data and the credit investigation data.
10. The credit management system based on block chain of logistics industry as claimed in claim 6, wherein:
the credit investigation data comprises any one or more of the following data: the system comprises the following steps of (1) industrial and commercial administration penalty data, bank loan default data, road administration overrun data, tax stealing and leaking data, identity data, crime data and violation data;
the credit data includes any one or more of: credit point data and grade data corresponding to each freight platform.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910875096.9A CN110599098A (en) | 2019-09-17 | 2019-09-17 | Logistics industry-based block chain credit investigation management method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910875096.9A CN110599098A (en) | 2019-09-17 | 2019-09-17 | Logistics industry-based block chain credit investigation management method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110599098A true CN110599098A (en) | 2019-12-20 |
Family
ID=68860313
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910875096.9A Pending CN110599098A (en) | 2019-09-17 | 2019-09-17 | Logistics industry-based block chain credit investigation management method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110599098A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111222955A (en) * | 2020-01-09 | 2020-06-02 | 国网安徽省电力有限公司信息通信分公司 | Supplier supervision method and system based on block chain |
| CN113298455A (en) * | 2020-11-16 | 2021-08-24 | 阿里巴巴集团控股有限公司 | Data processing system, method and electronic equipment |
| CN113379212A (en) * | 2021-05-31 | 2021-09-10 | 交通运输信息安全中心有限公司 | Block chain-based logistics information platform default risk assessment method, device, equipment and medium |
| CN113379211A (en) * | 2021-05-31 | 2021-09-10 | 交通运输信息安全中心有限公司 | Block chain-based logistics information platform default risk management and control system and method |
| CN113535848A (en) * | 2021-06-23 | 2021-10-22 | 国网河北省电力有限公司信息通信分公司 | Block chain-based credit investigation grade determination method, device, equipment and storage medium |
| CN113763150A (en) * | 2021-08-04 | 2021-12-07 | 远光软件股份有限公司 | Financial security protection method and related device |
| CN116664192A (en) * | 2023-08-01 | 2023-08-29 | 北京信大融金教育科技有限公司 | Integration generation and management method, device, equipment and medium based on bank system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651346A (en) * | 2016-11-28 | 2017-05-10 | 上海凯岸信息科技有限公司 | Block chain-based credit investigation data sharing and trading system |
| CN107274096A (en) * | 2017-06-16 | 2017-10-20 | 合肥维天运通信息科技股份有限公司 | The appraisal procedure and system of logistics platform driver's credit index based on big data |
| CN107274130A (en) * | 2017-06-16 | 2017-10-20 | 合肥维天运通信息科技股份有限公司 | A kind of driver's credit investigation system and method based on block chain technology and Logistics Information Platform |
| KR20190075295A (en) * | 2017-12-21 | 2019-07-01 | 중앙대학교 산학협력단 | Logistics management and tracking system of physical assets using block chain technology |
| CN109993527A (en) * | 2019-03-06 | 2019-07-09 | 西安电子科技大学 | A kind of framework method of the personal credit system based on block chain |
-
2019
- 2019-09-17 CN CN201910875096.9A patent/CN110599098A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651346A (en) * | 2016-11-28 | 2017-05-10 | 上海凯岸信息科技有限公司 | Block chain-based credit investigation data sharing and trading system |
| CN107274096A (en) * | 2017-06-16 | 2017-10-20 | 合肥维天运通信息科技股份有限公司 | The appraisal procedure and system of logistics platform driver's credit index based on big data |
| CN107274130A (en) * | 2017-06-16 | 2017-10-20 | 合肥维天运通信息科技股份有限公司 | A kind of driver's credit investigation system and method based on block chain technology and Logistics Information Platform |
| KR20190075295A (en) * | 2017-12-21 | 2019-07-01 | 중앙대학교 산학협력단 | Logistics management and tracking system of physical assets using block chain technology |
| CN109993527A (en) * | 2019-03-06 | 2019-07-09 | 西安电子科技大学 | A kind of framework method of the personal credit system based on block chain |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111222955A (en) * | 2020-01-09 | 2020-06-02 | 国网安徽省电力有限公司信息通信分公司 | Supplier supervision method and system based on block chain |
| CN111222955B (en) * | 2020-01-09 | 2024-04-05 | 国网安徽省电力有限公司信息通信分公司 | Supplier supervision method and system based on blockchain |
| CN113298455A (en) * | 2020-11-16 | 2021-08-24 | 阿里巴巴集团控股有限公司 | Data processing system, method and electronic equipment |
| CN113379212A (en) * | 2021-05-31 | 2021-09-10 | 交通运输信息安全中心有限公司 | Block chain-based logistics information platform default risk assessment method, device, equipment and medium |
| CN113379211A (en) * | 2021-05-31 | 2021-09-10 | 交通运输信息安全中心有限公司 | Block chain-based logistics information platform default risk management and control system and method |
| CN113535848A (en) * | 2021-06-23 | 2021-10-22 | 国网河北省电力有限公司信息通信分公司 | Block chain-based credit investigation grade determination method, device, equipment and storage medium |
| CN113763150A (en) * | 2021-08-04 | 2021-12-07 | 远光软件股份有限公司 | Financial security protection method and related device |
| CN116664192A (en) * | 2023-08-01 | 2023-08-29 | 北京信大融金教育科技有限公司 | Integration generation and management method, device, equipment and medium based on bank system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110599098A (en) | Logistics industry-based block chain credit investigation management method and system | |
| CN110599181B (en) | Data processing method, device and equipment based on block chain and storage medium | |
| US11551216B2 (en) | Transaction security on distributed-ledger based MaaS platform | |
| CN108537667A (en) | Financial asset anti money washing management-control method, equipment and storage medium based on block chain | |
| CN109829767A (en) | A kind of point reward exchanging system and method based on block chain technology | |
| CN107274130A (en) | A kind of driver's credit investigation system and method based on block chain technology and Logistics Information Platform | |
| CN110503547A (en) | Loan administration method and system, financial institution's node based on block chain | |
| CN110472914A (en) | A kind of invoice management method and system based on block chain | |
| CN107657411B (en) | Fourth logistics information platform management method and system based on block chain technology | |
| CN108881165A (en) | A kind of multicenter Verification System with block issue mechanism | |
| KR102103553B1 (en) | Server and system for provding history log and registeration service using blockchain | |
| US20120042354A1 (en) | Entitlement conflict enforcement | |
| CN112001781B (en) | Freight quotation method, system and device | |
| CN110019103B (en) | Cross-chain system and cross-chain implementation method based on block chain | |
| Longo et al. | The unified chart of mobility services: Towards a systemic approach to analyze service quality in smart mobility ecosystem | |
| US20230214791A1 (en) | Method for creating and maintaining a distributed ledger of vehicle gas consumption and wear and tear information | |
| CN108711090A (en) | A kind of non-stop layer chauffeur protocol method and system based on block chain | |
| CN111931245A (en) | Information processing method and device | |
| CN115396442A (en) | Calculation force sharing system and method for urban rail transit | |
| CN115907049A (en) | Air ticket distribution system and method based on block chain | |
| CN112053081A (en) | Credit integral adjusting method and device based on block chain and storage medium thereof | |
| Carlquist | Incentive contracts in Norwegian local public transport: the Hordaland model | |
| CN111882104A (en) | Logistics freight rate prediction method and system based on block chain and Oracle prediction machine | |
| CN112308484A (en) | Whole-course logistics information sharing method and system, equipment and medium | |
| CN110910217A (en) | Electronic ticket settlement method based on block chain |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191220 |
|
| RJ01 | Rejection of invention patent application after publication |