本文選題：反洗錢(qián)系統(tǒng) + 風(fēng)險(xiǎn)等級(jí)模型　； 參考：《電子科技大學(xué)》2014年碩士論文

【摘要】：全球經(jīng)濟(jì)一體化進(jìn)程的快速發(fā)展使得金融領(lǐng)域的洗錢(qián)行為日益猖獗,極大地影響了經(jīng)濟(jì)的正常運(yùn)行。世界各國(guó)都在積極制定相關(guān)法律法規(guī),并要求各個(gè)金融機(jī)構(gòu)針對(duì)洗錢(qián)行為開(kāi)發(fā)相應(yīng)的反洗錢(qián)系統(tǒng)。本文在這種背景下,以實(shí)際開(kāi)發(fā)的銀行反洗錢(qián)系統(tǒng)為依據(jù),研究了反洗錢(qián)的相關(guān)模式,并將反洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型研究成果應(yīng)用于反洗錢(qián)系統(tǒng)。本文的研究?jī)?nèi)容著重于數(shù)據(jù)挖掘技術(shù)在反洗錢(qián)系統(tǒng)中的應(yīng)用這一課題,提出了一種洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型。洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型使用數(shù)據(jù)挖掘技術(shù)中的歸納分類(lèi)技術(shù),本文設(shè)計(jì)了一種基于決策樹(shù)歸納和規(guī)則歸納的組合分類(lèi)器,洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型利用構(gòu)建的組合分類(lèi)器對(duì)銀行客戶信息屬性進(jìn)行洗錢(qián)風(fēng)險(xiǎn)等級(jí)類(lèi)型預(yù)測(cè)分類(lèi),分別將客戶洗錢(qián)風(fēng)險(xiǎn)等級(jí)分為高風(fēng)險(xiǎn)、中等風(fēng)險(xiǎn)和低風(fēng)險(xiǎn)三種等級(jí)。同時(shí)針對(duì)洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型建立的組合分類(lèi)器進(jìn)行相應(yīng)的樹(shù)剪枝優(yōu)化和Adaboost提升優(yōu)化。本文對(duì)洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型進(jìn)行實(shí)驗(yàn)評(píng)估,使用客戶信息驗(yàn)證集數(shù)據(jù)對(duì)洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型進(jìn)行測(cè)試,選用合理的評(píng)估度量標(biāo)準(zhǔn)比較各種基分類(lèi)器以及組合分類(lèi)器的性能,實(shí)驗(yàn)結(jié)果表明該組合分類(lèi)器與單個(gè)分類(lèi)器模型比較,具有較高的預(yù)測(cè)分類(lèi)準(zhǔn)確性。本文分析了銀行現(xiàn)有反洗錢(qián)系統(tǒng)的結(jié)構(gòu)與各個(gè)功能組件之間的關(guān)系,分析了SMBC-AML反洗錢(qián)系統(tǒng)的功能,目前反洗錢(qián)系統(tǒng)中存在的問(wèn)題,介紹了按照國(guó)家反洗錢(qián)法的規(guī)定對(duì)大額、可疑、重點(diǎn)可疑等客戶的識(shí)別,進(jìn)而將洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型以模塊化的設(shè)計(jì)方式整合進(jìn)當(dāng)前的銀行反洗錢(qián)系統(tǒng)中。實(shí)踐表明該洗錢(qián)風(fēng)險(xiǎn)等級(jí)模型具有良好的應(yīng)用前景。
[Abstract]:With the rapid development of global economic integration, money laundering in financial field is increasingly rampant, which greatly affects the normal operation of economy. Countries all over the world are actively making relevant laws and regulations, and all financial institutions are required to develop the corresponding anti-money laundering system. Under this background, based on the bank anti-money laundering system developed in practice, this paper studies the relevant models of anti-money laundering, and applies the research results of anti-money laundering risk level model to the anti-money laundering system. This paper focuses on the application of data mining technology in anti-money laundering system and proposes a risk level model for money laundering. In this paper, a combined classifier based on decision tree induction and rule induction is designed. The money laundering risk rating model uses the combined classifier to predict and classify the bank customer information attributes into three categories: high risk, medium risk and low risk. At the same time, the combined classifier based on money laundering risk grade model is optimized by tree pruning and Adaboost upgrading. This paper carries on the experimental evaluation to the money laundering risk grade model, uses the customer information verification set data to carry on the test to the money laundering risk grade model, selects the reasonable appraisal metric to compare the performance of various base classifier and the combination classifier. The experimental results show that the combined classifier is more accurate than the single classifier model. This paper analyzes the relationship between the structure of the existing anti-money laundering system of the bank and each functional component, analyzes the function of the SMBC-AML anti-money laundering system, the problems existing in the current anti-money laundering system, and introduces the large amount of money in accordance with the provisions of the National Anti-Money-Laundering Law. The identification of suspicious and key suspicious customers, and then the risk level model of money laundering is integrated into the current bank anti-money laundering system by modularized design. Practice shows that the model has a good application prospect.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：F832.2;TP311.13

【共引文獻(xiàn)】

相關(guān)期刊論文 前1條

1 費(fèi)笑松;王玉屏;邵帥;;構(gòu)建我國(guó)商業(yè)銀行可疑交易報(bào)告體系的探討[J];金融縱橫;2014年11期

相關(guān)碩士學(xué)位論文 前5條

1 司麗娟;論網(wǎng)絡(luò)洗錢(qián)犯罪[D];廣西大學(xué);2014年

2 劉小九;跨國(guó)洗錢(qián)犯罪法律對(duì)策研究[D];新疆大學(xué);2014年

3 秦立;M銀行反洗錢(qián)自主監(jiān)測(cè)系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)[D];湖南大學(xué);2014年

4 唐帥;某基層央行反洗錢(qián)監(jiān)測(cè)與管理系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)[D];湖南大學(xué);2014年

5 范慈家;中國(guó)與東盟地區(qū)的反洗錢(qián)合作機(jī)制研究[D];上海師范大學(xué);2015年

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本文編號(hào)：1797925