Data forensics - Workshop 2019

This workshop aims to provide you with an overview on forensic analytics and its application of specialised analytical knowledge and techniques. Learn how to identify patterns and activities such as potential fraud, misappropriation, and corruption.

My Offerings

Overview

Forensics Data Analysis (FDA) examines the structured financial data in connection to the financial crime. The aim of FDA is to unveil and analyse the patterns of fraudulent activities. Technologies like data science and analytics, and even machine learning often play a vital role in the investigation.

This workshop aims to provide you with an overview on forensic analytics and its application of specialised analytical knowledge and techniques. Learn how to identify patterns and activities such as potential fraud, misappropriation, and corruption.


Key topics covered:

  • Common patterns in fraudulent activities
  • Forensic analytics application and process
  • Mini-cases in Forensic Data Analysis


Trainer profile:

Walter Lau, MSc Finance, BBA (Hons) Accountancy, FCCA, FRM

Walter is an Adjunct Lecturer at The University of London and HKU School of Professional and Continuing Education and has more than ten years lecturing experiences in wide range of topics in business, accounting and finance, including business strategies, corporate finance and strategic management accounting, financial and business risk management, financial portfolio management, etc. covering both corporate and academic levels at HKU SPACE and other institutions. Walter is a regular speaker at different investment and educational seminars organised by various professional bodies in Hong Kong.

Objectives

  • Develop an investigative process for the data forensic investigation
  • Explain the methods of focusing investigations through analysis of multiple evidence sources

Audience

This workshop is suitable for anyone who are actively involved in internal control and auditing, accounting and assurance services.

Details

100031777

3 hours

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