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Build Anti-Money Laundering Machine Learning Application
Rating: 3.6 out of 5(26 ratings)
113 students

Build Anti-Money Laundering Machine Learning Application

Get familiar with Anti-Money Laundering, Machine Learning with Python, Tableau and MLNET
Created byKiran Kumar Shah | FCCA,M.A in Eco,DipIFRS,CAMS,CAMS-AUDIT,CFE,CISA,CISSP
Last updated 7/2022
English

What you'll learn

  • Concept of Machine Learning, its types and brief history
  • Concept of Anti-Money Laundering, Transaction Monitoring, Suspicious Transaction
  • Machine learning Model for Anti-Money Laundering
  • Development of Machine Learning algorithm using python in google colab
  • Data analysis visualization tool: Tableau
  • Introduction to ML NET

Course content

7 sections • 22 lectures • 2h 53m total length

  • Introduction1:52
  • Before We Start !!!1:09

    Learn about the Europe review system and the importance of rating this course. Share thoughtful comments on its usefulness and areas to improve to guide future learners.

  • Trainer Introduction1:49

    Meet trainer Kiran Kumar, a certified anti-money laundering specialist, who shares his data science journey and outlines essential math concepts for building AML machine learning applications.

Requirements

  • Zeal to explore and experiment

Description

This is the course that covers almost the majority portion of data science from model building, data visualization and demonstration of the end-to-end application using machine learning.

I have developed this course for beginners who are just starting out in Data Science. This course is mainly focused on leveraging machine learning in the transaction monitoring area of Anti-Money Laundering to identify suspicious transactions. So this course is most beneficial to Compliance and AML/CFT professionals who want to know about Machine Learning and its application in their job arena. This course is also suitable for Data scientists who want to explore opportunities in AML/CFT as AML/CFT is currently a very hot topic. Every Financial Institution all around the world has to implement an Anti-Money Laundering mechanism in their organization or they have to suffer huge penalties.

In this course we are going to cover the following topics:

1. Introduction Machine Learning and its types

2. Brief History of Machine Learning

3. Application of Machine Learning

4. Concept of Anti-Money Laundering

5. Concept of Transaction Monitoring

6. Decision-Making Model for Transaction Monitoring

7. Advantage of Machine Learning over Rule-Based Transaction Monitoring

8. Development of Machine Learning Algorithm using Python

9. Data visualization with Tableau

10. Introduction to MLNET and its application

There are a lot of concepts to cover, a wide variety of knowledge to gain. This course will benefit you immensely if you are either beginner, a data scientist, or just a compliance and AML/CFT professional.

I hope to see you in this course.

Who this course is for:

  • Beginners in Data Science , Data Scientist, AML/CFT and Compliance Professional

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