The Quickstart Guide to AI Augmented Investment Decisions

Asset managers around the world today are coping with a difficult investment environment. From a tentatively recovering economy to global uncertainty in markets, new levels of risk in the system are driving investors to take new and adaptive approaches to increase the predictive accuracy of their decisions. Traditional methods of diligence and analysis are insufficient for the scope and speed required in today’s competitive and rapidly changing landscape.

Although many investment decisions are ever more ‘data driven’, many large asset managers continue to rely on human judgement, for better and for worse. At their best, the most senior leaders in an organization are experts in an asset class and have years of accumulated knowledge from which to base a decision. However, as small elite teams make big decisions they also introduce human bias and receive biased inputs often taken as ‘ground truths’. Moreover, very few have the opportunity or software available to model what-if scenarios and back-test key aspects of the decision in the time required to capture the best deals. 

So how can investors handle the modern demands of investment decisions and not just survive, but thrive? How can AI augment the decision processes of our most talented teams and help us make our decisions more quickly, efficiently, and accurately?

The answer? Human-empowered artificial intelligence (AI). In just the next few years, the global AI market is predicted to snowball, reaching a $190.61 billion market value in 2025, which is no doubt fueled by the machine learning application industry receiving $37 billion of funding in the U.S. just two years ago. 

Some asset managers are still hesitant to explore AI, which makes sense as a large proportion of AI is focused on replacing human judgment with algorithms. However, with new types of AI on the horizon, this sentiment is changing quickly. New AI technologies like CrowdSmart combine the unparalleled strength of human reasoning with the unmatched scale and processing speed of AI.  With human-empowered AI, funds can augment an investment team’s capabilities in multiple aspects of their work, reducing groupthink and human bias, and increasing the speed and accuracy of their decisions. As funds battle to demonstrate superior performance,  human-empowered AI creates proprietary data and powerful knowledge models that form the foundation of faster and more accurate decisions across the organization. According to Forbes, 43% of enterprises believe that their AI and Machine Learning (ML) initiatives matter “more than we thought,” with one in four saying AI and ML should have been their top priority sooner. Furthermore, 83% of investment funds have increased their budgets for AI and machine learning year-over-year from 2019 to 2020.

As more and more investors begin to unlock the benefits of AI to support their investment teams, it’s crucial not to get left behind. That’s why we’re sharing exactly what you need to know about augmenting your investment decisions with AI. With Decision Performance Management software, you can improve the investment decision processes for any team, reduce risk, create proprietary data, and build institutional knowledge that can be leveraged across your organization to improve over time.

 

The Modern Pressures of Investment Decision Making

From market volatility to increasingly complex investment strategies, chief investment officers face numerous challenges today—all of them more complex and time-sensitive than ever. Under the continued pressure to maximize both returns and efficiency, more and more chief investment officers are turning to AI. Although some asset classes lend themselves to systematic approaches with machine learning and AI, others remain heavily dependent on cumbersome, inefficient, and biased human processes. Before you move on and optimize these asset classes, however, you should be aware of these modern decision process challenges:

  1. Reducing or eliminating cognitive biases from investment decisions
  2. Finding the balance of data vs intuition when so many decisions require deep expertise and human judgement
  3. Moving beyond historical data analysis and applying AI to improve investment decisions across all asset classes
  4. Creating new, proprietary data to give you a sustainable advantage

Each of these issues makes it difficult to unlock the countless benefits that AI can yield. Although we turn to AI to eliminate human bias from investment decisions, this doesn’t mean we want to ignore human knowledge altogether and rely on a data-only approach. In fact, the best AI models are able to leverage the deep expertise of your team and tap into the knowledge of your external managers while also improving their performance. 

In addition, there is also growing pressure on chief investment officers to apply AI to internal issues, such as solving the ongoing challenge to become more nimble, creating the ability to unlock the expert knowledge in one part of their organization and use it to inform other strategies, as well as future-proof the investment office, identifying potential internal talent for succession planning. 

So with all of these modern pressures, where does that leave investors who are hoping to use AI to drive better decisions?

 

The New Wave of AI

Many scientists believe that the next breakthrough in AI will come from the human brain itself. Ongoing research at institutions such as MIT, Stanford, and UC Berkeley is advancing the frontier of how humans use knowledge to solve problems and make predictions. This new wave combines AI models with collective intelligence, enabling the aggregate predictions of a diverse group to be transformed into quantitative and predictive data. Human-empowered AI provides the capability to make smarter decisions than any person, group, or computer could do alone. Human-empowered AI tackles the top modern decision process challenges mentioned above by:

  1. Building trust through explanation and integration with human cognitive processes
  2. Leveraging collective human skills of reasoning and judgement
  3. Providing a framework for contextual adaptation

For investors who struggle to stay clear of the biases and blind spots as they invest billions of dollars in new opportunities, human-empowered AI brings a much higher degree of accuracy in predicting which investments will generate alpha. Better yet, the technology supports continuous improvement so any investment team will become smarter and even more accurate at predicting success as they work together with the AI system over time. 

 

The CrowdSmart Solution

Unlike many forms of AI that are trained using historical data, CrowdSmart learns from human interactions and converts opinions into computational models that generate new data. 

Battle-tested, CrowdSmart was originally created as a technology platform for an AI-driven venture fund. A team of 2,500 investment experts used CrowdSmart technology to collectively create 80% accuracy in predicting follow-on funding momentum for a cohort of 150 companies. CrowdSmart is effective with groups as small as eight people, and becomes even more predictively accurate with more people and diverse participation, including the addition of ODD personnel or ‘outside’ experts in the collaborative discussion.

With each use of CrowdSmart in your firm, the accuracy of your investment decisions and your institutional knowledge grows in depth and intelligence over time, creating an engine of constant improvement and better returns.

Ready to level up? Let’s schedule a demo today and see how we can help your firm make better investment decisions by combining the best of human and artificial intelligence.

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