Global Institutional Investors To Increase Alternative Data Usage, Proficiency In Machine Learning Set For Growth

The majority of institutional investors globally, including pension funds, family offices, asset managers, private banks and hedge funds, are to increase their alternative data usage over the next 12 months, according to machineByte's White Paper in to Machine Learning & Alternative In Asset Management. Institutional investors are also expanding their proficiency in python and their use of machine learning tools and platforms.
By: machineByte
NEW YORK - Sept. 16, 2019 - PRLog -- The majority of institutional investors globally are to increase their alternative data usage over the next 12 months, according to machineByte's White Paper in to Machine Learning & Alternative In Asset Management. Institutional investors are also expanding their proficiency in python and their use of machine learning tools and platforms.

The White paper collected data points from more than 100 institutional investors globally from North America, Latin America, EMEA, Asia & Australia that are active or currently exploring alternative data or machine learning - more than 50% of those institutional investors from whom data points were collected have more than US$15 billion in AUM. More than 80% of institutional investors where data points were collected expect to increase their use of alternative data over the next 12 months. More than 65% of institutional investors are applying machine learning across a specific area of the firm.

"Through case studies as to how institutional investors apply machine learning and alternative data, to profiles, rankings, data and breakout sections on overcoming issues and taping in to opportunities, the machineByte White Paper provides a roadmap for those institutional investors beginning their exploration of alternative data, AI and machine learning in finance," said Robert McGlinchey, director & co-founder at machineByte. "We find that the majority of institutional investors globally are seeking to tap in to alternative data and apply machine learning over the next 12 months, yet barriers exist to growth, particularly around cost, proficiency, the risk of overfitting and an unwillingness from the wider financial services community to embrace open source."

Some of the findings of the machineByte White Paper, include:
  • ESG data ranks as the highest alternative dataset being primed for growth over the next 12 months;
  • Quandl is ranked as the leading alternative data provider among institutional investors;
  • AWS is ranked as the leading cloud provider among institutional investors;
  • DataRobot, Google AutoML and causaLens are currently finding usage among institutional investors. Platforms that are specifically catered to investment management are finding more traction among those investors exploring machine learning;
  • J.P.Morgan ranked as the leading bank in machine learning and alternative data research. Man Group as the leading hedge fund in machine learning research; Marcos Lopez de Prado as the leading academic;
  • The cost of alternative data sets and attracting talent are the challenges facing institutional investors exploring this space;
  • Barriers to entry include the lack of case studies of how alpha can be sourced / how portfolios can be optimised through alternative data and machine learning;
Through more than 100 pages, machineByte's White Paper provides a map of the market on how alternative data and machine learning is being used and explored by institutional investors. The full report includes:
  • Case studies on how machine learning and alternative data is being applied;
  • Rankings, data and profiles on alternative data companies/consultants/vendors being used or explored by institutional investors;
  • Rankings, data and profiles on cloud providers and AutoML platforms being used or explored by institutional investors;
  • In what data sets, in what markets and in what strategies alternative data is being used and explored;
  • What budgets are being allocated to alternative data;
Key findings of the report will be presented at machineByte Europe – The Machine Learning & Alternative Data in Finance Forum - at the Paris Marriott Rive Gauche on Sept. 17-18, a conference for institutional investors exploring machine learning and alternative data. For more information, visit www.machineByte.com.

About machineByte

machineByte, a sister platform of EQDerivatives, provides education, content and forums for investment professionals who are currently exploring or active in machine learning, AI and alternative data in financial markets.

Media Contact
machineByte: Chas Reese
***@machinebyte.com
+1 603-751-8248
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