Internet evaluation method for foreign exchange dealers based on big data algorithm

Abstract

The invention discloses an internet evaluation method for foreign exchange dealers based on a big data algorithm. The method comprises the steps: collecting public data of the foreign exchange dealersthrough the internet, and obtaining a scoring result through the data according to the following algorithm formula: Z= a*P +b*Y + c*R + d*F + e*J, wherein a is the weight of the license plate score in the total score, P is a license plate score, b is the weight of the service score in the total score, y is a service score, c is the weight of the software score in the total score, R is a softwarescore, d is the weight of the risk control score in the total score, f is a risk control score, e is the weight of the supervision score in the total score, j is a supervision score, the total score and the related sub-items adopt a tenth system, and the score interval is [0.00, 10.00]. In the score calculation process, an accurate calculation value is reserved. The sub-items and the total score result are stored in a rounded-in mode and reserved for two bits. The result can be used as a reference for a foreign exchange dealer to select a foreign exchange dealer.

Description

technical field [0001] The present invention relates to Internet information processing and big data algorithms, and in particular to a method for scoring foreign exchange dealers based on Internet information processing for five types of data, including license, business, risk control, software, and supervision, through core algorithms Background technique [0002] Since the beginning of 2019, as the country has repeatedly issued signals of "continuing to expand the opening up of the financial industry and promoting high-quality economic development", more and more financial investment industries have gradually been accepted by the public. The latest Bank for International Settlements (BIS) According to the report (April 2016), the global trading volume of various foreign exchange products remained at 5.1 trillion US dollars per day, which was slightly lower than the 5.3 trillion US dollars in 2013. The Bank for International Settlements publishes a survey on foreign exchan...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the problems existing in the prior art, the present invention aims to solve the problems of difficult data sources for foreign exchange traders, incomplete information, and easy contamination of data samples. By providing an original algorithm system, the algorithm utilizes license, business, Risk control, software, supervision and other five types of data comprehensively score foreign exchange dealers, and summarize them to form the total score of foreign exchange dealers. The results can be used as a reference for foreign exchange traders to choose foreign exchange dealers