Institutional asset allocation processes have changed little in the past 25 years. Yes, there are new asset classes, sub-asset classes and investment opportunities. However, the investment decision and allocation process has not changed much. Excel still dominates investment processes as the tool-of-choice.  Humans gather data, verify, transform, analyze and make decisions.  This entire chain of data & knowledge management is fairly manual at many asset allocator and asset owner institutions.  We need the right data, at the right time, in front of the right people to ultimately make the right investment decisions

Technology as a force for innovation is ubiquitous in nearly every industry, except perhaps the world of the asset allocator.  Asset allocators who fund technological advancements through their investment allocations, limited partners (LPs) in venture capital (VC) investments, don’t get to benefit much from the advancements created by their own investments.

Cloud computing, data science, and machine learning have transformed entire industries.  Institutional asset allocation industry is at the beginning of a major technology adoption curve over the next 5 years.  One of the key conclusions of the Thinking Ahead Institute’s (Willis Towers Watson) 2021 Global Pension Assets Study, is ‘People plus Technology will be the dominant investment model over the next 5-10 years’.  McKinsey’s North American Wealth Management in 2030 report expects financial services firms to act more like tech firms as they seek data-driven, AI-enabled investment decisions, and improve operational effectiveness.

At Osyte [‘O-Sight’], we call this ‘Human-Machine collaboration in Investment Management’ and we are building that future now.   Automation of investment data management, machine assisted investment decisions, machine led portfolio monitoring, alerts and implementation are a reality today.  It’s time to reap the benefits of technological advancements funded by your own investment allocations.