Published on April 7, 2017 by Suraj Atreya
Acuity Knowledge Partners recently held a web seminar on “Quality of Earnings Review – Identifying the Fat Tail”. The webinar was highly interactive and brought together senior executives; including chief investment officers, heads of research, portfolio managers, and investment analysts, from the Asset Management industry to discuss the latest trends governing “Forensic Analysis” and “Quality of Earnings”.
Chanakya Dissanayake (Director/Country Head at Acuity Knowledge Partners, Sri Lanka) and Zohair Haiderally (Senior Vice President at Acuity Knowledge Partners) spoke on the importance of identifying the true earnings potential in the investment due diligence process and how to overcome the common tricks that companies use to distort earnings.
The speakers highlighted red flags (which act as early warning indicators) to watch out for and discussed about the different types of corporate frauds that made headlines, financial tricks used, and potential detection clues.
Please see the webinar recording for financial tricks and potential detection clues used in each of the cases. Case studies on how firms have been able to leverage our “quality of earnings” capabilities can also be found in the recording.
The Q&A session was highly engaging, and attendees had a broad range of questions such as:
1. How to identify the difference between frauds and smoothing of earnings via accounting gimmickry?
2. Is forensic analysis only applicable to emerging markets?
3. Is it possible to run screening tools to determine the “quality of earnings” of an acquisition target?
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Assistant Director, Marketing & Communications
I run solutions marketing for banking, research and lending business lines. I enable the marketing of technology and automation driven initiatives to supplement the services based model.
My work provides me an opportunity to be at the forefront of innovation and disruption impacting the financial services industry. I am excited about the application of emerging technology areas such as AI, ML, robotics and automation programs to fundamentally transform business models and inspire innovation across the ecosystem.
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