WEBINAR: Career Insights - Research and analytics in the era of AI

Natalie Yiu    Suresh Krishnamurthy, CFA, Biharilal Deora, CFA, CIPM
17 Jul 2019
Category: Other

Country or region: Asia Pacific (Overall)

Machine learning and artificial intelligence are about to revolutionise the financial services industry. How can skilled finance personnel participate in this revolution? What are the opportunities for CFA charterholders and candidates? (Video: 1 hr)



This webinar qualifies for 1 CE credit under the guidelines of the CFA Institute Continuing Education Program. 
We encourage CFA Institute members to log in to the CE tracking tool to self-document these credits.

The investment banking industry has been going through massive changes and is struggling hard to combat cost pressure and increased regulatory changes. Banks are now increasingly leveraging technology. The research function cannot lag. Core analytical functions of research firms (in equity research, fixed income research, credit risk) have largely remained untouched by technology over the past decades. While research analysts continue to dominate analytical functions by leveraging their experience to deliver deep insights about stocks, industry and economy, cognitive automation is a disruptive threat for research. From using excel sheets and PowerPoint presentations for client pitches, there is a paradigm shift in the way research is expected to be delivered to clients today. Machine learning (ML) and artificial intelligence (AI) are among the most talked about areas at global corporations and the financial services industry is at the forefront of the revolution. The growing applicability of ML and AI is driven by three key factors of growth in computational power, increasing availability of digital data (both structured and unstructured data), and the falling cost of data infrastructure.

Within the financial services industry, asset management firms are building teams of data scientists and data engineers as extensions of the quantitative research teams or as separate distinct teams. Sell side research houses are training their research analysts in programming, typically Python, so that they can incorporate fresh insights from unstructured data to produce distinguished investment themes. Similarly, credit risk management teams of global banks are investing in cognitive solutions that tap into new age data or alternative data to generate early warning signals for any potential stress on their portfolio of borrowers. There exists a huge scope for skilled finance personnel to participate in this industry evolution and build out distinct research offerings and products based on deep knowledge of data, processes, and required outcomes. This webinar aims to create broader awareness of trends and discuss opportunities for CFA® charterholders and candidates.


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WEBINAR: Career Insights - Research and analytics in the era of AI

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