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Legal status (The legal standing is an assumption and isn't a legal conclusion. Current Assignee (The listed assignees could also be inaccurate. Priority date (The precedence date is an assumption and is not a authorized conclusion. The invention discloses a wind management data monitoring method based mostly on a block chain, and pertains to the technical discipline of knowledge monitoring. The strategy contains the following steps: building a block chain; earlier than loan implementation starts, the data source node uploads wind control information to a server of a block chain, a credit score evaluation node calculates a credit score of a borrower, and then chain link is performed on the credit score rating, and the mortgage node judges whether loan is launched or not and chain hyperlink is carried out on a judgment result; in the mortgage implementation course of, the loan node uploads the repayment document of a borrower to a server of the block chain; after the mortgage is implemented, inquiring whether overdue repayment and/or interrupted repayment exists or not, feeding again an inquiry outcome to the credit score evaluation mannequin, and sending the inquiry outcome to a server of the block chain for chaining; the credit analysis model incorporates components that are affected by the query outcomes.

The invention can monitor the wind control knowledge tracking of the entire mortgage course of, so that the chance control is extra good and the loan reservation judgment is extra accurate. The invention relates to the technical field of information tracking, in particular to a block chain-based mostly wind control data monitoring technique, anti-loss gadget terminal tools and a storage medium. In the traditional wind management know-how, experience control is performed in a handbook mode by the wind management team of every mechanism. However, with the steady growth of web technology, the whole society is significantly accelerated, and the normal wind management mode can't support the enterprise growth of the mechanism; the massive data can be utilized for intelligently processing multidimensional and huge quantity of information, and batch and standardized execution processes can better meet the event requirements of the wind control enterprise in the knowledge growth era; more and more intense trade competitors can also be the essential motive for ItagPro as we speak's large information to manage such fires.

Big knowledge wind control, namely huge knowledge risk control, refers to the chance control and threat prompt of a borrower through the use of a technique of constructing a model by massive information. Different from the original artificial expertise kind wind management on the borrowing enterprise or anti-loss gadget the borrower, the massive data wind control for finishing up knowledge modeling by acquiring various indexes of a lot of borrowers or the borrowing enterprise is extra scientific and efficient. However, the invention patent solely displays the data of the enterprise before the loan is carried out, but doesn't relate to the data monitoring after the implementation, and a feedback mechanism after the loan is lacked, so that the control on the chance will not be excellent, and the scenario that the judgment is just not correct enough often occurs. Therefore, methods to develop a wind management data tracking technique capable of realizing the whole loan course of is one in all the problems to be solved urgently.

In order to resolve at the very least one technical drawback talked about in the background art, an object of the present invention is to supply a block chain-based wind control knowledge tracking technique, a terminal anti-loss gadget, and a storage medium, which may monitor wind management knowledge monitoring of a mortgage full course of, in order that risk control is extra complete and loan determination is more correct. Further, if a plurality of information source nodes provide the identical merchandise of wind management knowledge, setting confidence degrees aiming at the merchandise of wind management knowledge for the plurality of information supply nodes respectively; when the credit evaluation mannequin calculates the credit score rating, choosing the credit analysis node with the very best confidence coefficient to offer corresponding item wind management data; and when the overdue payment and/or the interrupted fee exist in a certain knowledge chain, performing confidence punishment on all knowledge supply nodes taking part in offering the wind management data in the information chain, and/or when the overdue cost and the interrupted payment do not exist in the certain data chain, ItagPro performing confidence reward on all knowledge source nodes collaborating in offering the wind control information in the info chain.

Further, the arrogance penalty technique is as follows: when overdue repayment exists in a certain information chain however interrupted repayment does not exist, lowering the boldness levels of all information supply nodes participating in offering the wind control knowledge in the info chain by a first step size, and/or decreasing the boldness degrees of all information source nodes participating in providing the wind management knowledge in the info chain by a second step size when interrupted repayment exists within the sure data chain; step one size is smaller than the second step measurement. Further, the boldness reward method is as follows: and when the situations of overdue repayment and interrupted repayment do not exist in a sure information chain, increasing the confidence levels of all information supply nodes taking part in providing the wind management data in the data chain by a third step size. Further, within the technique of deciding on the credit analysis node offering the wind management knowledge, one of the credit score analysis nodes is selected if the credit analysis node with the best confidence coefficient is supplied.