本文選題：反洗錢 + 大數(shù)據(jù)��； 參考：《北京郵電大學(xué)》2016年碩士論文

【摘要】：隨著全球經(jīng)濟的快速發(fā)展,金融交易越來越頻繁,交易手段不斷更新,交易處理的自動化、電子化的水平越來越高�，F(xiàn)代金融產(chǎn)品在為廣大用戶提供便利的同時,也為洗錢犯罪帶來了可乘之機。洗錢活動日益猖厥,引起國際社會的普遍關(guān)注,各國政府和金融監(jiān)管機構(gòu)也加大了對洗錢犯罪的打擊力度。我國從上世紀(jì)末就開始從國家層面實施反洗錢建設(shè),當(dāng)前反洗錢監(jiān)管部門建立了金融交易報告制度,為反洗錢工作的開展積累了大量數(shù)據(jù)。如何有效分析金融機構(gòu)的海量交易數(shù)據(jù)和客戶賬戶數(shù)據(jù)進而識別出洗錢交易,是反洗錢工作的關(guān)鍵。但是隨著金融業(yè)的快速發(fā)展和金融領(lǐng)域信息化的不斷深入,傳統(tǒng)的反洗錢方式在處理能力和處理精度上越來越不能滿足需求,同時“棱鏡門”事件的爆發(fā)也暴露了 IOE等傳統(tǒng)技術(shù)架構(gòu)所隱含的安全性問題,商業(yè)銀行需要一套安全、穩(wěn)定、高可用的技術(shù)方案來提升自己的反洗錢能力。本文是一篇工程型論文,是以解決實際應(yīng)用問題為導(dǎo)向的。在總結(jié)當(dāng)前商業(yè)銀行反洗錢業(yè)務(wù)的實際需求的基礎(chǔ)上,對當(dāng)前可用的大數(shù)據(jù)處理技術(shù)進行適用性分析,提出了一套適用于商業(yè)銀行的大數(shù)據(jù)反洗錢架構(gòu),實現(xiàn)了基于Hadoop的反洗錢規(guī)則計算方案。總體上,本文完成了以下幾個工作:(1)研究反洗錢工作在我國的進展和整體布局,總結(jié)商業(yè)銀行在整個反洗錢系統(tǒng)中的的定位;研究商業(yè)銀行的業(yè)務(wù)體系,分析商業(yè)銀行反洗錢的實際需求,總結(jié)銀行在反洗錢領(lǐng)域的不足之處;對比研究當(dāng)前大數(shù)據(jù)領(lǐng)域的相關(guān)技術(shù),剖析數(shù)據(jù)分析、數(shù)據(jù)存儲等場景下不同大數(shù)據(jù)技術(shù)的適用情況,針對銀行的實際業(yè)務(wù)需求和應(yīng)用場景,設(shè)計了一套商業(yè)銀行反洗錢適用的大數(shù)據(jù)處理框架。(2)研究中國人民銀行關(guān)于商業(yè)銀行反洗錢的相關(guān)規(guī)定,以法律法規(guī)為指導(dǎo)原則,結(jié)合實際的業(yè)務(wù)場景對客戶行為進行分析。設(shè)計一套結(jié)合實際業(yè)務(wù)的客戶行為分析指標(biāo),量化反洗錢的預(yù)警邏輯,形成一套便于計算的洗錢行為指標(biāo)預(yù)警體系。(3)結(jié)合商業(yè)銀行實際的業(yè)務(wù)系統(tǒng)和中國人民銀行的監(jiān)管上報要求,設(shè)計了一套反洗錢規(guī)則計算方案。將洗錢功能對業(yè)務(wù)系統(tǒng)進行解耦,為反洗錢的監(jiān)管上報提供了數(shù)據(jù)接口,設(shè)計并完成基于Hadoop的反洗錢規(guī)則計算方案。另外,針對Hive的特性,提出了在數(shù)據(jù)模式設(shè)計、HQL代碼編寫、集群配置等方面的優(yōu)化方案,充分釋放大數(shù)據(jù)平臺的數(shù)據(jù)處理能力,完成了一套高效、實用、可擴展的反洗錢規(guī)則處理系統(tǒng)。
[Abstract]:With the rapid development of the global economy, financial transactions become more and more frequent, the means of transaction are constantly updated, the automation of transaction processing and the level of electronization are becoming higher and higher. Modern financial products not only provide convenience for users, but also bring opportunities for money laundering crime. Money laundering is becoming more and more rampant, which has caused widespread concern in the international community. Governments and financial regulators have also stepped up the fight against money laundering. Since the end of last century, China began to carry out anti-money laundering construction at the national level. At present, the anti-money laundering supervision department has established the financial transaction reporting system, which has accumulated a lot of data for the development of anti-money laundering work. How to effectively analyze the massive transaction data and customer account data of financial institutions and identify money laundering transactions is the key to anti-money laundering work. However, with the rapid development of financial industry and the deepening of financial information, the traditional anti-money laundering method can not meet the demand in terms of processing ability and precision. At the same time, the outbreak of "Prism Gate" also exposed the security problems implied by the traditional technical framework such as IOE. Commercial banks need a set of safe, stable and high available technical solutions to enhance their anti-money laundering capability. This paper is an engineering paper, which is oriented to solve practical application problems. On the basis of summarizing the actual demand of the current commercial banks' anti-money laundering business, this paper analyzes the applicability of the current available big data processing technology, and puts forward a set of big data anti-money laundering framework suitable for commercial banks. The calculation scheme of anti-money laundering rules based on Hadoop is realized. As a whole, this paper has completed the following work: (1) to study the progress and overall layout of anti-money laundering in China, to summarize the position of commercial banks in the whole anti-money laundering system, to study the business system of commercial banks, This paper analyzes the actual demand of commercial banks in anti-money laundering, summarizes the shortcomings of banks in the field of anti-money laundering, compares and studies the relevant technologies in the current big data field, analyzes the application of different big data technologies in the scenarios of data analysis, data storage, and so on. According to the actual business needs and application scenarios of banks, this paper designs a set of big data framework for commercial banks to deal with anti-money laundering. (2) We study the relevant regulations of the people's Bank of China on anti-money laundering of commercial banks, and take the laws and regulations as the guiding principles. Combined with the actual business scenario to analyze the customer behavior. Design a set of customer behavior analysis indicators combined with actual business to quantify the early warning logic of anti-money laundering. (3) combining the actual business system of commercial banks and the supervision and reporting requirements of the people's Bank of China, a set of calculation scheme of anti-money laundering rules is designed. The money laundering function is decoupled from the business system, which provides a data interface for the supervision and reporting of anti-money laundering, and designs and completes the calculation scheme of anti-money laundering rules based on Hadoop. In addition, according to the characteristic of Hive, this paper puts forward the optimized scheme of data pattern design in HQL coding, cluster configuration and so on, which fully releases the data processing ability of big data platform, and completes a set of efficient and practical. Extensible anti-money laundering rule processing system.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：F832.2;TP311.13

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本文編號：2086914