Data Analytics For Fraud Detection, Prevention and Investigation

1 Day Workshop/ $450

This course will expose the participants to various quantitative and qualitative data analysis techniques to detect fraud and errors. Participants will also learn how to use data analytics to add value to organization, as well as gain insight to digital forensic and digital surveillance.


Programme Objective

With today intensive use of integrated systems storing gigantic amount of financial and non-financial data, hardly can any accounting, auditing or investigation work be conducted without data analysis. Valuable evidence may be staring at the accountant and auditor but not picked up if they do not know how to mine and connect the seemingly unrelated data to make sense out of it. The irreversible trend of Big Data and pressure to remain competitive have compel organization to make use of data analysis and continuous monitoring to understand business trend and consumer behaviours, as well as to detect fraud.

Knowing how to pick up data profile and pattern in data analysis to identify red flags have become indispensable skills of today accountant and auditors. Knowing what tool to use to acquire admissible digital evidence and how to search through pile of electronic files and email certainly is a must have skill for today’s auditors. This course will expose the participants to various data analysis techniques, tools and templates in the conduct of audit or investigation.

A data analysis tool will be given FREE to participants of this course for self-use.

On completion of this program participants will: • Acquire the overall concept of data analysis in detecting fraud • Better equipped to identify irregularities in data trend and data profile • Able to perform qualitative data analysis • Understand rules governing digital evidence, digital forensic and online investigation • Understand about procedures in digital forensic and continuous monitoring • Gain knowledge on common detection techniques of fraud/ wrongdoing

Programme Outline

  1. Data Analysis – Overview • What is data analysis? • Three Reason Data Analysis is Must • Data Analysis in Auditing vs Investigation • What can Data Analysis do and can’t

  2. Common Analysis Procedures • Financial Ratio, Variance, Percentage, Aging, Average • Common analysis functions

- Filter / Sort/ Join / Append/ Pivot/ Trend / Regression / Ratio - Vlookup/ Eye-lookup/ Grouping/ Summarization/ Stratification

  1. Two type of Data Analysis • Quantitative – Sorting, Category, Relationship, Profiling • Qualitative – Contextual, Behavioural

  2. Performing Data Analysis • Gap analysis • Duplicate analysis • Fuzzy duplicate • Orphan transactions • Timing analysis • Limit and Reasonableness • Trend and Outlier • Unwanted match • Aging, Stratification, Sampling

  3. Performing Data Profiling • Frequency tests • Intensity tests • High risk tests • Relative Size tests • Digit Frequency tests (Benford) • Concentration test (GEL)

  4. OLAF Approach in Data Analysis • Object Locate Analyse Follow • Understand “Miscarriage of Justice” and “Impurity of Finding”

  5. Beyond Data analysis and Digital Forensic – What Next? • Finding confirmation • Determine root cause • Develop Hypothesis • Move on to interview and interrogation

Target Audience

  • Anyone who interested in doing data analysis and digital investigation
  • CFO, Financial controllers, finance manager and accountant
  • Procurement and HR professionals
  • Auditor, audit manager, forensic auditor
  • Compliance and internal control professional

Training Methodology

Presentation, group discussion, and case study. Multimedia, game and templates sharing

Programme Facilitator

Kent Hoh

Kent Hoh is a prolific trainer in audit, fraud investigation, corporate governance and personal effectiveness. Kent Hoh has wide ranging experience in leading compliance and audit functions in Asia Pacific as well as forensic investigation team globally.

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