【摘要】：隨著互聯(lián)網(wǎng)金融的發(fā)展,P2P網(wǎng)貸、眾籌融資等給人們帶來便利的同時,也使人們面臨著巨大的信用風(fēng)險(xiǎn)等一系列弊端,解決這些問題,為用戶帶來更安全、更便捷的交易環(huán)境成為研究的熱點(diǎn)。在P2P網(wǎng)貸(Peer-to-Peer)中,借貸雙方不可能像傳統(tǒng)金融中那樣彼此深度了解,信息不對稱性尤為突出。解決這個問題的一個有效辦法就是盡量準(zhǔn)確評估借貸主體的信用,即建立有效的P2P用戶征信體系。本文在研究了國內(nèi)外學(xué)者對于P2P網(wǎng)貸用戶的信用評判方法后,發(fā)現(xiàn)國內(nèi)學(xué)者對通過用戶信用評估指標(biāo)來評判P2P網(wǎng)貸用戶信用的研究方法甚少,而且其研究方法操作大多較復(fù)雜,信用評估值也不一定很好。本文提出了一種研究信用評估指標(biāo)的信用評判方法——綜合評判法,其求得的信用評估值是通過對用戶的信用評估指標(biāo)進(jìn)行分層以及多次綜合加權(quán)考慮后得到,不僅操作簡單、省時,而且具有一定的可信度。并用融360的數(shù)據(jù)對其進(jìn)行了實(shí)驗(yàn)驗(yàn)證。從本質(zhì)上講,當(dāng)我們知道的借款人各方面的信息越多,就會對其信用進(jìn)行更準(zhǔn)確的評判,因此想到將信息融合技術(shù)運(yùn)用到P2P網(wǎng)貸用戶信用評估中。本文在近似認(rèn)知計(jì)算系統(tǒng)這一理論信息融合思想的啟發(fā)下,首次將信息融合技術(shù)運(yùn)到P2P網(wǎng)貸中,提出了基于粒計(jì)算的信息融合方法。該方法融合了用戶多方面信息,不僅避免了用戶以虛假信息得到較高信用評估值的可能,而且能夠?qū)τ脩舻男庞眠M(jìn)行全面、準(zhǔn)確的評判。同樣也用融360的數(shù)據(jù)以及收集到的用戶的第三方數(shù)據(jù)(如各部門的執(zhí)法數(shù)據(jù)等)對其進(jìn)行實(shí)驗(yàn)驗(yàn)證。區(qū)塊鏈?zhǔn)腔ヂ?lián)網(wǎng)金融的底層技術(shù)構(gòu)架,具有去中心化,信息高度透明等特點(diǎn),并且其本質(zhì)上就是各方信任機(jī)制建設(shè)的一個完美的數(shù)學(xué)解決方案。本文在對其進(jìn)行研究后,提出了將區(qū)塊鏈技術(shù)運(yùn)用到P2P網(wǎng)貸用戶信用評估中的設(shè)想,初次建立了基于區(qū)塊鏈技術(shù)的模型并就其對用戶信用驗(yàn)證的底層驗(yàn)證機(jī)制進(jìn)行了算法設(shè)計(jì)。或許在不久的將來能夠在一定程度上減少用戶信用值不真實(shí)的現(xiàn)象。
[Abstract]:With the development of Internet finance, P2P network loan, crowdfunding and so on bring convenience to people, at the same time, it also makes people face a series of malpractices such as huge credit risk, solve these problems, and bring more security to users. More convenient trading environment has become the focus of research. In P2P network loan (Peer-to-Peer), it is impossible for both parties to understand each other in depth as in traditional finance, especially in information asymmetry. An effective way to solve this problem is to evaluate the credit of the borrowers as accurately as possible, that is, to establish an effective P2P user credit system. After studying the domestic and foreign scholars' credit evaluation methods for P2P network loan users, it is found that domestic scholars have few research methods to judge the P2P network loan users' credit through the user credit evaluation index, and most of the research methods are complicated. Credit ratings are not necessarily good either. In this paper, a credit evaluation method, which is used to study the credit evaluation index, is put forward. The credit evaluation value is obtained by stratifying the credit evaluation index of the user and considering the credit evaluation index for many times. It is not only simple to operate. Save time, and have certain credibility. It is verified by the data of Rong 360. In essence, the more information we know about the borrower, the more accurate the credit evaluation will be, so we think of applying the information fusion technology to the credit evaluation of P2P network loan users. Inspired by the theoretical information fusion idea of approximate cognitive computing system, the information fusion technology is transported to P2P network loan for the first time in this paper, and a method of information fusion based on granular computing is proposed. This method not only avoids the possibility that users can obtain higher credit evaluation value by false information, but also can comprehensively and accurately judge the credit of users. It is also tested with 360 data and third-party data collected from users (such as law enforcement data from various departments). Block chain is the underlying technical framework of Internet finance, which has the characteristics of decentralization and high transparency of information. In essence, it is a perfect mathematical solution for the construction of trust mechanism of all parties. In this paper, we put forward the idea of applying the blockchain technology to the credit evaluation of the users in P2P network, and establish the model based on the block-chain technology for the first time, and design the algorithm for the underlying verification mechanism of the user's credit verification. Perhaps in the near future can reduce to some extent the user credit value untrue phenomenon.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F832.4;F724.6

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