Online dynamic credit evaluation method based on seller credit point value

Abstract

The invention discloses an online dynamic credit evaluation method based on a seller credit point value. According to the invention, a seller, a buyer and an online credit evaluation platform are included. The online credit evaluation platform or the seller quantifies and converts price of the goods bought by the buyer in a single transaction and represents the price in the form of a credit pointvalue which is owned by the buyer. The buyer autonomously adjusts the owned credit point value to serve as the real-time evaluation expression for the credit of the seller by the buyer according to descriptions of the goods or services, the commitments and realization conditions of the seller, and acquires corresponding evaluation dividends according to the owned credit point value after the own deadline of the buyer expires. According to the invention, dynamic real expression and depiction of online credit are facilitated; the buyer and the seller are promoted to grow together; the buyer is motivated to actively participate in evaluation objectively; and dynamic real-time monitoring and risk and fraud identification of online credit markets are quite facilitated.

Description

technical field [0001] The invention relates to the field of Internet credit system construction, in particular to an online dynamic credit evaluation method based on a seller's credit integral value. Background technique [0002] E-commerce has turned the traditional "acquaintance society" into a modern "stranger society". Compared with the traditional market, the fast-growing e-commerce market has a higher degree of information asymmetry. Therefore, the unique virtuality of online transactions can easily lead to dishonest behavior in the e-commerce market. According to the "Research Report on China's Online Shopping Market" released by CNNIC in 2015, as of December 2015, the number of online shopping users in my country reached 413 million. The online retail transaction volume reached 3.88 trillion yuan, and the total number of transactions in the online shopping market reached 25.6 billion. Website / business reputation has become one of the most concerned factors when onli...

AI Technical Summary

Problems solved by technology

[0005] (1) The credit evaluation method of simply accumulating weighted credit points is greatly affected by the transaction volume, and it is very easy to induce the seller to maliciously swipe the order

However, the simple accumulation of this amount only shows part of the dynamic changes in the seller's overall credit, and cannot effectively reflect the more detailed and dynamic changes in the seller's credit in the process of a single transaction.

[0006] (2) The existing online credit evaluation methods only use fixed values ​​to score and adjust the seller's credit, which limits the buyer's expression of the seller's credit

The index setting of the platform is greatly affected by subjective factors, and there is a large deviation between the evaluation results and their intrinsic values. The evaluation process is easily disturbed by human factors, resulting in the lack of authenticity of the credit evaluation results

[0007] (3) In the online credit evaluation method under the current C2C model, the credit evaluation results have no direct interest relationship with the buyer, which leads to the lack of enthusiasm for the buyer to participate in the evaluation, and the seller interferes with the buyer's evaluation behavior through unreasonable means, and the buyer will also cooperate due to personal interests. Seller makes fake reviews

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