TAYLLORCOX > Akademie > SAS > Anti Financial Crime – Applied Analytics Training

Anti Financial Crime – Applied Analytics Training

The Anti Financial Crime – Applied Analytics Training helps you understand and interpret the current regulation and requirements for the anti-money laundering (AML) area. This program is designed to support you in transforming your organization to become data driven and enable you to obtain business value with analytics. We have created an eight-month learning framework where we give you the capacity to learn and reflect on critical analytics skills connected to AML. Rather than feeding you only technical knowledge that can quickly become obsolete, we cover other critical skills to succeed with analytics to create a permanent behavioral change. The program includes 10 days of mandatory training to translate new knowledge into real business issues and cases. Optional days for deeper tool and lab sessions during the period are available, both for the individual and in plenum.

Termíny
Target group
Course structure
Prerequisites

Virtual Training nebo e-Learning?

Máme dostatečnou flexibilitu, takže vybírat můžete jak prezenční termíny, tak online kurzy.

Zkuste živý kurz virtuálně

Target group

AML investigators (data exploration, data visualization, analytic analysis, report creation, report consumption, domain expertise); compliance officers, AML officers, and risk controllers (domain experts, decision makers); quantitative analysts and data scientists (exploratory analysis, descriptive segmentation, predictive modeling); and IT professionals such as administrators, coders, DBA, ETL personnel, and enterprise architects

Course structure

Session 1

Introduction to analytics methods.
Segmentation.
Threshold tuning.
Leadership perspective.
Create value.
Personal communication.
Introduction to AML.
Codes and Definitions.
Prospective view.

Session 2

Unsupervised learning.
Predictive modelling.
Business model.
Decision-making process.
Identifying stakeholders.
Core of transaction monitoring.
Improve efficiency and effectiveness.

Session 3

Text analytics.
NLP/NLG.
QKB – Match codes.
Contextual analysis.
Preparing meetings.
Interviewing techniques.
Building trust.
Sanctions.

Session 4

Entity resolution.
Entity consolidation.
Dynamic networks.
Data collection.
Interact with stakeholders.
Impact business.
Explaining with simplicity.
TBML, CB, capital markets.
Terrorism financing.

Session 5

RPA, Deep Learning.
Agents, auto learning.
Challenges with change.
Human stages – transition model.
Eight-step model.
AI next gen.

Prerequisites

A high engagement to learn more about the drivers for analytics success is the main requirement. You need to have the willingness to change your mindset, and you should be looking forward to having an impact on the further development of your department. There are no formal technology prerequisites for this program. You are working on the mission to solve AML challenges in your organization.