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Legal status (The legal standing is an assumption and is not a authorized conclusion. Current Assignee (The listed assignees may be inaccurate. Priority date (The precedence date is an assumption and is not a legal conclusion. The invention discloses a wind control information tracking method based on a block chain, and pertains to the technical field of information monitoring. The strategy contains the next steps: building a block chain; before loan implementation starts, the info supply node uploads wind management knowledge to a server of a block chain, a credit analysis node calculates a credit score rating of a borrower, and then chain link is carried out on the credit score rating, and the mortgage node judges whether loan is launched or not and chain link is carried out on a judgment end result; in the loan implementation process, the loan node uploads the repayment document of a borrower to a server of the block chain; after the loan is carried out, inquiring whether overdue repayment and/or interrupted repayment exists or not, feeding again an inquiry outcome to the credit score analysis mannequin, and sending the inquiry consequence to a server of the block chain for chaining; the credit evaluation mannequin incorporates components that are affected by the question outcomes.



The invention can monitor the wind management data monitoring of the whole loan process, in order that the chance management is extra excellent and the loan reservation judgment is extra accurate. The invention pertains to the technical subject of information tracking, specifically to a block chain-based wind control information tracking technique, terminal equipment and a storage medium. In the normal wind management technology, expertise control is carried out in a manual mode by the wind control staff of each mechanism. However, with the steady development of internet technology, the whole society is greatly accelerated, ItagPro and the traditional wind management mode can't assist the business enlargement of the mechanism; the large information can be used for intelligently processing multidimensional and enormous amount of information, and batch and standardized execution processes can better meet the event requirements of the wind control business in the knowledge growth period; more and more intense business competitors can be the necessary motive for today's large information to control such fires.



Big data wind management, specifically massive knowledge danger management, iTagPro locator refers to the chance management and danger immediate of a borrower by utilizing a way of constructing a model by massive data. Different from the original synthetic experience sort wind control on the borrowing enterprise or iTagPro geofencing the borrower, the large data wind control for carrying out data modeling by acquiring varied indexes of a lot of borrowers or the borrowing enterprise is extra scientific and efficient. However, the invention patent solely screens the information of the enterprise before the loan is applied, however does not relate to the info monitoring after the implementation, and a suggestions mechanism after the loan is lacked, so that the control on the chance isn't good, and the state of affairs that the judgment just isn't correct enough often occurs. Therefore, the best way to develop a wind control information tracking methodology able to realizing the whole loan process is one in all the problems to be solved urgently.



So as to solve at least one technical downside talked about in the background art, an object of the current invention is to supply a block chain-based mostly wind control information tracking methodology, a terminal device, and a storage medium, which may monitor wind control knowledge monitoring of a mortgage full course of, in order that threat control is more complete and loan determination is more accurate. Further, if a plurality of data supply nodes present the identical merchandise of wind management information, ItagPro setting confidence levels aiming on the item of wind management data for the plurality of information supply nodes respectively; when the credit analysis mannequin calculates the credit score rating, selecting the credit score evaluation node with the best confidence coefficient to provide corresponding merchandise wind control information; and when the overdue cost and/or the interrupted fee exist in a certain data chain, performing confidence punishment on all knowledge source nodes collaborating in offering the wind control knowledge in the information chain, and/or when the overdue payment and the interrupted cost don't exist in the certain data chain, performing confidence reward on all knowledge supply nodes taking part in providing the wind management data in the info chain.



Further, the boldness penalty methodology is as follows: when overdue repayment exists in a sure knowledge chain but interrupted repayment does not exist, reducing the confidence levels of all data source nodes participating in providing the wind control information in the info chain by a primary step length, and/or reducing the boldness levels of all knowledge source nodes collaborating in providing the wind control information in the data chain by a second step size when interrupted repayment exists within the sure knowledge chain; step one size is smaller than the second step measurement. Further, the boldness reward technique is as follows: and when the situations of overdue repayment and iTagPro geofencing interrupted repayment don't exist in a sure knowledge chain, growing the arrogance degrees of all information source nodes taking part in offering the wind control knowledge in the info chain by a third step length. Further, in the technique of deciding on the credit score evaluation node offering the wind management data, one of many credit score analysis nodes is chosen if the credit evaluation node with the very best confidence coefficient is supplied.

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