GLOBAL RESEARCH SYNDICATE
No Result
View All Result
  • Login
  • Latest News
  • Consumer Research
  • Survey Research
  • Marketing Research
  • Industry Research
  • Data Collection
  • More
    • Data Analysis
    • Market Insights
  • Latest News
  • Consumer Research
  • Survey Research
  • Marketing Research
  • Industry Research
  • Data Collection
  • More
    • Data Analysis
    • Market Insights
No Result
View All Result
globalresearchsyndicate
No Result
View All Result
Home Data Analysis

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

globalresearchsyndicate by globalresearchsyndicate
January 12, 2020
in Data Analysis
0
Egypt- The Investment Management Industry takes on AI and Big Data
0
SHARES
7
VIEWS
Share on FacebookShare on Twitter

(MENAFN – Daily News Egypt)

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

MENAFN1201202001530000ID1099540203

Related Posts

How Machine Learning has impacted Consumer Behaviour and Analysis
Consumer Research

How Machine Learning has impacted Consumer Behaviour and Analysis

January 4, 2024
Market Research The Ultimate Weapon for Business Success
Consumer Research

Market Research: The Ultimate Weapon for Business Success

June 22, 2023
Unveiling the Hidden Power of Market Research A Game Changer
Consumer Research

Unveiling the Hidden Power of Market Research: A Game Changer

June 2, 2023
7 Secrets of Market Research Gurus That Will Blow Your Mind
Consumer Research

7 Secrets of Market Research Gurus That Will Blow Your Mind

May 8, 2023
The Shocking Truth About Market Research Revealed!
Consumer Research

The Shocking Truth About Market Research: Revealed!

April 25, 2023
market research, primary research, secondary research, market research trends, market research news,
Consumer Research

Quantitative vs. Qualitative Research. How to choose the Right Research Method for Your Business Needs

March 14, 2023
Next Post
Rethinking Cybersecurity for the IIoT: Integrated, Automated and Adaptable – 2020-01-12 – Page 1

Rethinking Cybersecurity for the IIoT: Integrated, Automated and Adaptable - 2020-01-12 - Page 1

Categories

  • Consumer Research
  • Data Analysis
  • Data Collection
  • Industry Research
  • Latest News
  • Market Insights
  • Marketing Research
  • Survey Research
  • Uncategorized

Recent Posts

  • Ipsos Revolutionizes the Global Market Research Landscape
  • How Machine Learning has impacted Consumer Behaviour and Analysis
  • Market Research: The Ultimate Weapon for Business Success
  • Privacy Policy
  • Terms of Use
  • Antispam
  • DMCA

Copyright © 2024 Globalresearchsyndicate.com

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Cookie settingsACCEPT
Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Non-necessary
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.
SAVE & ACCEPT
No Result
View All Result
  • Latest News
  • Consumer Research
  • Survey Research
  • Marketing Research
  • Industry Research
  • Data Collection
  • More
    • Data Analysis
    • Market Insights

Copyright © 2024 Globalresearchsyndicate.com