Webinar: How to identify and detect financial statement fraud in the digital age
Event Code : 20201112

Highlights

Leading businesses are investing in new technologies and business models. The approaches in identifying and detecting financial statement fraud continues to evolve in the digital age. This session will highlight recent financial statement fraud trends and share real case studies. The session will also share red-flag identification as well as new approaches in financial statement fraud detection such as forensic data analytics, machine learning, and alternative data.

Speaker(s)

Mr. Jacky Lai 
Jacky is the Assurance Partner at Ernst & Young. He has extensive experience in providing professional services to clients from different markets and in a wide range of industries, including retail and consumer products, food and beverage, environmental energy, entertainment, construction, and manufacturing. He has extensive experience with Initial Public Offerings, including advising on cross border listing procedures, as well as assisting state-owned enterprises with pre-IPO restructuring.

Jacky is currently the committee member of the HKICPA’s Professional Development Committee, Professional Conduct Committee, and Registration and Practising Committee.  He is a regular speaker at seminars and forums on various topics such as financial reporting and capital market development.

Chairman

Mr. Kim Man Wong

Mr. Kim Man Wong  is currently the Chief Financial Officer of Hong Kong Electric Investments. He has over 30 years of experience in financial management and accounting in Hong Kong and other countries. He holds a Bachelor’s and Master’s degree in Business Administration. He is also a member of HKICPA.

He has actively involved in accounting education and professional development all these years. He is currently the Chairman of Accountancy Advisory Board of Lingnan University. He is also a Panel Convenor of the Financial Reporting Review Panel of Financial Reporting Council.

Language:
Cantonese
CPD Hours:
2.0 Hours
Fee:
HK$100
Deadline:
2020-12-12
Registration period expired

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