Learning machines play an increasingly key role in our everyday lives. From search engines, to online recommendations, medical diagnoses, speech recognition, rapid translations, traffic management, self-driving cars, weather forecasting, fraud and crime detection/prevention, games strategy, etc. They transform the quality and efficiency of how we analyse information and help us to take smarter decisions.
Machines learn by analysing large sets of relevant data, identifying evolving patterns of behaviour and predicting future outcomes (what we do, what we like, what happens next). Whilst always trying to learn from mistakes and improve how we achieve our goals and manage risk.
Machines learn by analysing large sets of relevant data, identifying evolving patterns of behaviour and predicting future outcomes (what we do, what we like, what happens next). Whilst always trying to learn from mistakes and improve how we achieve our goals and manage risk.
Learning Machines are Transforming
Asset and Wealth Management
Case Study 01
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In March 2017, Sanlam, a 100 year old diversified financial services group with US$104 billion in AUM, US$10bn market capitalization and AA+ rated by Fitch appointed A.I. Machines as technology partner to operate the Sanlam AI Global Managed Risk Ucits Fund (GMR).
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A.I. Machines' PIE started powering GMR effective from June 2017, with no changes to the fund's existing objectives and guidelines, but using intelligent systems capable of adapting to changing market conditions. |
Market Reaction - Fund buyers' perspective
"GMR has exceeded expectations since adopting a fully fledged AI approach in 2017" |
Sanlam is delivering authentic, effective product and strategy differentiation in a sector where homogeneous products are the norm.
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Case Study 02
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In September 2018, Glacier, a South African provider of wealth management services with R281 bn (circa US$20 bn) in assets under administration, launched a retail multi-asset, flexible AI fund.
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The portfolio is fully powered by PIE and can invest across equities markets (developed and emerging), equity sectors (resources, financials, industrials, properties) and government bonds through exchange traded funds - ETFs.
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In a crowded multi-asset market place, the Glacier AI Fund provides a truly innovative and differentiated investment solution that stands out from the competition. |
Case Study 03
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In May 2015, A.I. Machines funded a Dynamic Asset Allocation (DAA) strategy fully powered by AI as a test case for PIE.
DAA is made of only 3 assets (equities, bonds and cash) and it is run unconstrained with a weekly forecasting horizon. PIE is free every week to decide how much needs to be to allocated to each asset based on a careful analysis of assets behavior and market conditions.
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As of December 31, 2021, DAA has significantly outperformed the Morningstar Flexible Allocation category, including BlackRock Global Allocation, a well known unconstrained asset allocation fund, in terms of both risk and return. |
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Today DAA is available as a white labelled solution for financial institutions of all sizes. |
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