An approach to financial information analysis by the Brazilian Federal Police

IF 1.1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Renato Kettner Filho, D. D. J. D. Macedo
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引用次数: 0

Abstract

INTRODUCTION: One of the tasks performed by the Federal Police is the verification and cross-referencing of data contained in Financial Intelligence Reports (FIRs) produced and forwarded by the Financial Activities Control Council (COAF) - an activity in which, among the police involved, the absence of a standard system of execution. OBJECTIVES: The present work aims to present a study on the form currently in use within the scope of the Federal Police Station regarding the analysis of FIRs from the COAF, then presenting a methodology suggestion, aiming to speed up the process. Regarding open sources, the objective is to carry out a survey of possible complementary repositories not yet used and to expose ways of implementing queries. METHODS: Pointing out the workflow currently used (displaying it in graphic form) as well as identifying the data sources consulted (open sources and closed sources) during the process, CONCLUSION: understanding how the FIR analysis system is currently carried out, identifying possible aspects for improvement, and suggesting a methodology to be used, indicating for this the use of files in a specific format (.CSV), exclusion of queries in similar repositories (System “A”) and, mainly, the automation of part of the procedure (with the use of the RIBOT prototype software).
巴西联邦警察对金融信息分析的方法
简介:联邦警察执行的任务之一是核查和交叉引用由金融活动控制委员会(COAF)制作和转发的金融情报报告(FIRs)中包含的数据-在参与这项活动的警察中,缺乏标准的执行系统。目的:本工作旨在对联邦警察局范围内目前使用的表格进行研究,以分析来自COAF的first,然后提出一项方法建议,旨在加快这一进程。关于开放源代码,目标是对尚未使用的可能的补充存储库进行调查,并公开实现查询的方法。方法:指出目前使用的工作流程(以图形形式显示),并确定在此过程中参考的数据源(开放源和封闭源)。了解FIR分析系统目前是如何进行的,确定可能需要改进的方面,并建议使用一种方法,指出使用特定格式的文件(. csv),排除类似存储库中的查询(系统“a”),主要是部分程序的自动化(使用RIBOT原型软件)。
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来源期刊
EAI Endorsed Transactions on Scalable Information Systems
EAI Endorsed Transactions on Scalable Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.80
自引率
15.40%
发文量
49
审稿时长
10 weeks
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