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The Investment Management Industry takes on AI and Big Data - Daily News Egypt

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The Investment Management Industry takes on AI and Big Data

In the words of many industry heavyweights, artificial intelligence (AI) is the “new electricity”.  Researchers have made tremendous strides in building the ultimate “seeing, hearing, and understanding” machine in recent years. But, while many are referring to AI as the new electricity, others are calling big data the “new oil.” Big data is often referred …


In the words of many industry heavyweights, artificial intelligence (AI) is the “new electricity”.  Researchers have made tremendous strides in building the ultimate “seeing, hearing, and understanding” machine in recent years. But, while many are referring to AI as the new electricity, others are calling big data the “new oil.” Big data is often referred to as “structured data” and “unstructured data” or “alternative data”. Unstructured data is from sources that are not currently used or not yet mainstream. And, in comparison to structured data, which is data that is digitized and stored in relational databases, unstructured data often uses images or voice formats and are readily processable.

CFA Institute published a report called “AI Pioneers in Investment Management” which explains how investment managers are beginning to use AI and big data as part of their day-to-day work.

William Tohmé

The survey results indicate that, in fact, few investment professionals are currently using programs typically utilized in machine learning (ML) techniques. Most portfolio managers continue to rely on Excel (indicated by 95% of portfolio manager respondents) and desktop market data tools (three quarters of portfolio manager respondents) for their investment strategy and processes. Moreover, only 10% of portfolio manager respondents have used AI/ML techniques in the past 12 months, and the number of respondents using linear regression in investment strategy and process outnumbers those using AI/ML techniques by almost five to one.

The big takeaway is that the investment industry is still in the very early stages of adoption of AI techniques and related technologies. That said, approximately one fifth of analysts and portfolio managers report participating in AI/big data training, so we can expect to see changes coming soon.

So, what is holding investment professionals and investment firms back from realizing the full power of AI and big data? We identified five major hurdles, which form a pyramid for investors to overcome.

Hurdle #1: Cost.  Launching an AI and big data capability can involve significant upfront cost as well as ongoing maintenance costs. Small firms may find it increasingly difficult to compete in the age of AI and big data.

Hurdle #2: Talent. College graduates with basic programming and statistics training, not to mention those with advanced degrees in AI or related fields, are already very popular with employers in the age of AI. It seems very few of the top AI talents want to work in the investment industry, and companies need to develop compelling opportunities for people with these skills to attract them from the big tech companies.

Hurdle #3: Technology. We are at the beginning of the AI revolution, and technology is still fast evolving. Staying current with the latest developments is a real challenge.

Hurdle #4: Vision. There will likely be sweeping changes in the investment industry driven by advances in AI and big data technologies in the coming decades. Strategic vision, leadership commitment, and collective ownership of IT deployment will be essential for firms to succeed in the future.

Hurdle #5: Time. Any progress, no matter how small, often takes a significant investment of time, among other things.

The technology function in future investment teams will likely require different skill sets than those required today. In particular, data scientists, in addition to computer engineers, will become important.

To recap, we have identified three key uses of AI in investment management: (1) using natural language processing (NLP), computer vision, and voice recognition to efficiently process text, image, and audio data; (2) using machine learning (ML), including deep learning, techniques to improve the effectiveness of algorithms used in investment processes; (3) using AI techniques to process big data, including alternative and unstructured data, for investment insights. CFA Institute believes that successful investment firms of the future will be those that strategically plan on incorporating AI and big data techniques into their investment processes. And successful investment professionals will be those who can understand and best exploit the opportunities brought about by these new technologies.

By William Tohmé, Regional Head of Middle East and North Africa at CFA Institute, and Larry Cao, Senior Director of Industry Research, Asia Pacific, CFA Institute

Caption: Hurdles in Ascending the Fintech Pyramid

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