LIVE INTERACTIVE WEBINAR
Utilise Data Analytics For Fraud Detection Without Complexity
31 Mar 2021 (Wednesday)
10:00am - 11:30am (Malaysia / Singapore Time) | 09:00am - 10:30am (Bangkok Time)
Most organizations are sitting on an ever growing ocean of data and it’s challenging for examiners to detect fraud in files of great size and complexity. In many cases, perpetrators of corporate fraud go undetected because of the limited ability to perform tests on data contained in multiple systems. This webinar explains various ways in which frauds may occur and how data can be analyzed to identify instances of possible fraud. In this webinar, you will learn:
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Current issues and impact of fraud
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Traditional approaches by fraud examiners
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Detecting fraud with data analytics
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Numeric analytics
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Implementation
Auditors and fraud investigators shall be able to develop or enhance a fraud detection program based on the learnings from this session.
Speaker:
Mr Michael Kano, ACDA
Data Analytics Consultant
Arbutus Analytics
Michael has 25 years of experience in data analytics and internal audit with organizations in the USA, Canada, and the Middle East. From 2015 to 2019, he was a senior member of the data analytics practice at Focal Point Data Risk, a US-based professional services firm.
Prior to Focal Point, Michael led eBay, Inc.’s data analytics program in the Internal Audit department. He was tasked with integrating data analytics into the audit workflow on strategic and tactical levels. This included developing quality and documentation standards, training users, and providing analytics support on numerous audits in the IT, PayPal, and eBay marketplaces business areas.
He also provided support to non-IA teams such as the Business Ethics Office and Enterprise Risk Management teams.
During his years at eBay, Michael supported audits throughout the organization in the IT, compliance, operations, vendor management, revenue assurance, T&E, and human resources areas.
Upcoming Events
Registration is closed
31 March 2021 (Wednesday)
10:00AM (Malaysia/Singapore Time)
09:00AM (Bangkok Time)
