library(knitr)        # @xie2014
library(ggplot2)      # wickham2016
library(QuantileNPCI) # hutson2019
library(tm)           # feinerer2015
library(wordcloud)    # fellows2018
library(RColorBrewer) # neuwirth2014
library(DT)           # xie2020
library(openxlsx)     # schauberger2020

opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE)

RESULTADOS DE LAS EVALUACIONES MUTUAS

WORDCLOUD DE LOS TEXTOS DE LOS REPORTES DE EVALUACIONES MUTUAS Y SEGUIMIENTO A LAS EVALUACIONES MUTUAS PUBLICADOS POR EL FATF

El resultado del análisis realizado por los grupos de evaluadores a la efectividad del régimen preventivo de una determinada jurisdicción, se plasma en un documento conocido como el “Reporte de Evaluación Mutua” (MER, por sus siglas en inglés).

La nube de palabras que se presenta a continuación fue construida utilizando los reportes que se citan en la sección de referencias.

DISTANCIA ENTRE DOCUMENTOS

La tabla que se presenta a continuación muestra la distancia euclideana entre documentos, con base en la matriz de términos construida anteriormente:

Las evaluaciones que presentan la menor distancia entre ellas (excluyendo las distancias en la diagonal de la matriz) son las correspondientes a MEXICO (2022) y LITHUANIA (2020/06).

PENDIENTES

  • Poner el país de los documentos con la menor distancia.
  • Ver Martinez and Martinez (2005), sección 1.4.1, sobre la técnica de BPM para aplicarla a los textos.
  • Resultados de las evaluaciones mutuas.
  • Nube de palabras por año.
    • Cercanía entre documentos por año.
  • Nube de palabras por región.
    • Cercanía entre documentos por región.

REFERENCIAS

“2nd Enhanced Follow-up Report for Tunisia: Re-Ratings Request.” 2017. Middle East; North Africa Financial Action Task Force.
“Anti-Money Laundering and Counter-Terrorist Financing Measures Lithuania: 1st Enhanced Follow-up Report & Technical Compliance Re-Rating.” 2020. Follow-up report. Committee of Experts on the Evaluation of Anti-money laundering measures; the financing of terrorism.
Asia/Pacific Group on Money Laundering. 2016. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Fiji: Mutual Evaluation Report.”
———. 2017. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Cambodia: Mutual Evaluation Report.”
Caribbean Financial Action Task Force. 2023. “Anti-money laundering and counter-terrorist financing measures - Jamaica: Mutual Evaluation Report, Third Enhanced Follow-up Report and Fifth Enhanced Follow-up Report.” Caribbean Financial Action Task Force.
Feinerer, Ingo. 2015. “Introduction to the Tm Package, Text Mining in r.”
Fellows, Ian. 2018. Wordcloud: Word Clouds. https://CRAN.R-project.org/package=wordcloud.
Financial Action Task Force. 2016. “Anti-Money Laundering and Counter-Terrorist Financing Measures - United States.” Financial Action Task Force. www.fatf-gafi.org/publications/mutualevaluations/documents/mer-united-states-2016.html.
———. 2017a. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Denmark: Fourth Round Mutual Evaluation Report.” www.fatf-gafi.org/publications/mutualevaluations/documents/mer-denmark-2017.html.
———. 2017b. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Ireland: Fourth Round Mutual Evaluation Report.” http://www.fatf-gafi.org/media/fatf/documents/reports/mer4/MER-Ireland-2017.pdf.
———. 2017c. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Portugal: Fourth Round Mutual Evaluation Report.” http://www.fatf-gafi.org/media/fatf/documents/reports/mer4/MER-Portugal-2017.pdf.
———. 2017d. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Sweden: Fourth Round Mutual Evaluation Report.” www.fatf-gafi.org/publications/mutualevaluations/documents/mer-sweden-2017.html.
———. 2022. “Anti-money laundering and counter-terrorist financing measures - Mexico: 4th Enhanced Follow-up Report.” Financial Action Task Force. https://www.fatf-gafi.org/media/fatf/documents/reports/fur/Follow-Up-Report-Mexico-2022.pdf.
Financial Action Task Force, and Asia Pacific Group on Money Laundering. 2015. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Malaysia: Fourth Round Mutual Evaluation Report.” Financial Action Task Force; Asia Pacific Group on Money Laundering. www.fatf-gafi.org/publications/mutualevaluations/documents/mer-malaysia-2015.html.
Hutson, Nicholas, Alan Hutson, and Li Yan. 2019. QuantileNPCI: Nonparametric Confidence Intervals for Quantiles. https://CRAN.R-project.org/package=QuantileNPCI.
Martinez, Wendy L., and Angel R. Martinez. 2005. Exploratory Data Analysis with MATLAB. Computer Science and Data Analysis Series. Chapman & Hall/CRC.
MONEYVAL / Financial Action Task Force. 2016. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Serbia.” MONEYVAL / Financial Action Task Force.
———. 2017. “Anti-Money Laundering and Counter-Terrorist Financing Measures - Ukraine.” MONEYVAL / Financial Action Task Force.
Neuwirth, Erich. 2014. RColorBrewer: ColorBrewer Palettes. https://CRAN.R-project.org/package=RColorBrewer.
R Core Team. 2020. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Schauberger, Philipp, and Alexander Walker. 2020. Openxlsx: Read, Write and Edit Xlsx Files. https://CRAN.R-project.org/package=openxlsx.
Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org.
Xie, Yihui. 2014. “Knitr: A Comprehensive Tool for Reproducible Research in R.” In Implementing Reproducible Computational Research, edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng. Chapman; Hall/CRC. http://www.crcpress.com/product/isbn/9781466561595.
Xie, Yihui, Joe Cheng, and Xianying Tan. 2020. DT: A Wrapper of the JavaScript Library ’DataTables’. https://CRAN.R-project.org/package=DT.