Artificial Intelligence is no longer a futuristic concept but a crucial tool in shaping today’s investment strategies. In an industry where data-driven decisions determine success, AI is giving fund managers and selectors a competitive edge over rivals. It’s doing this in many ways: automating repetitive tasks, analysing data more effectively, and providing insights into how performance can be improved.

In this article, we share our findings from deploying AI in fund management and explain how it can be used in the pursuit of better returns, improved margins, and higher Assets Under Management (AUM).

Main takeaways

AI can provide an edge: fund managers and selectors using AI have better prospects of outperforming their rivals.

Data lies at the heart of AI: investing is data-driven, and AI excels in drawing conclusions from complicated datasets.
Greater efficiencies: AI will lead to cost reduction and efficiency gains. Automating tasks will free up time for fund managers to focus on their priorities.
The human element remains important: investment needs are complex, so AI is unlikely to replace human expertise – at least for the time being.
Ignoring AI is a risk: fund managers must embrace advanced analytical tools – or risk losing clients who will use AI themselves.
Boost AUM: AI can help fund managers refine their strategies, which is a necessary step in driving greater assets under management.

AI gives investors a competitive edge

Having an information advantage over rivals has always been important in the investment world, but the rise of AI is changing how this competitive edge is perceived. In our experience, success no longer depends solely on getting hold of this data but on harnessing AI tools to analyse it more effectively in the pursuit of superior investment decisions.

The most useful AI tools can digest performance figures, detailed sector reports, management comments and economic forecasts, and then produce conclusions to influence future action.

AI is tailor made for fund management

Successful investing depends on striking the right balance between information, data points and human judgement calls, but this isn’t always easy to achieve. We believe AI can play an important role in this respect, as its main strength lies in the ability to analyse complicated datasets, identify trends and draw meaningful conclusions.

Here, we outline how AI tools can be used to help improve investment skills, boost returns generated and increase AUM.

Improving investment skills: spotting how investment decisions have been made and their outcomes, as well as highlighting unintentional biases and style drift.
Providing unbiased insights: AI helps managers mitigate the effects of behavioural biases by grounding decisions in numerical evidence. This ensures a more objective approach and reduces the risk of repeating past mistakes.
Freeing up time: AI’s machine learning, Natural Language Processing (NLP), and predictive analytics can also automate routine tasks and free up time to hone other skills.
Available 24/7: AI systems don’t need sleep. This means their data analysis can be carried out constantly to ensure investors receive real-time insights.

In our experience, when trained with high-quality data on evaluating investment skills, AI has demonstrated remarkable efficiency, delivering insights comparable to those of a human expert, only much faster.

Beyond speed, AI can systematically analyse every aspect of an investment, minimising the risk of overlooking critical details that a human expert might miss due to reliance on mental shortcuts.

Improve investment skills with AI

We see AI as the perfect investment coach because it can even help portfolio managers at the very top of their game to increase their skills and make better decisions. In the same way that elite athletes constantly train, AI can give investment professionals non-judgemental feedback to help them understand their strengths and pinpoint areas for improvement. The use of objective, data-driven feedback is easier to accept because it can’t be dismissed as being simply someone’s opinion.

Of course, AI is not just about minimising adverse factors. We have found it’s equally useful for fact-checking a manager’s narrative. For example, when uploading a manager’s strategy documentation, our AI expert can identify inconsistencies and provide the necessary investigative questions to clarify claims being made.

How AI can improve fund selectors’ decisions

A comprehensive AI toolkit can also help fund selectors who often spend a large part of their working day evaluating investment teams. Taking an unbiased, data-driven approach to manager expertise ensures their performance is more driven by skill than simply luck. AI systems can efficiently screen extensive data sets to uncover blind spots often missed in traditional research. This is especially useful for fund selectors, helping to offset their own behavioural biases, such as confirmation or recency bias when choosing external managers.

In our discussions with fund selectors, a common theme is the constant pressure and time constraints they face. AI’s powerful automation in analysing complex data—particularly in assessing investment skills—has the potential to transform their daily workflow. By streamlining analysis and highlighting key insights, AI can free up valuable time, allowing selectors to focus on high-impact decision-making.

The future of AI

AI is already having a major impact on the world of fund management, even though many of these tools are still very much in their infancy. It’s still to be seen how AI will be affected by unpredictable events, such as black swan occurrences and natural disasters. However, AI systems are constantly being improved to correct the errors that have been spotted, which are proving to be a hindrance to wider deployment. There’s little doubt that a constant wave of updated AI tools will become available over the next couple of years as its use becomes more commonplace among investors.

From our experience implementing AI systems, we’ve observed significant advancements that we believe will transform investment skills, and we anticipate much more future progress.

Data v human interaction: what will happen?

It’s the question that’s often asked: will AI replace the need for humans? As far as investing is concerned, we believe this possibility is still a long way off. While AI is virtually untouchable when it comes to data analysis, there are plenty of qualitative human factors at play when it comes to fund management. Understanding political nuances, assessing the impact of economic factors, and gauging other elements still require that element of human intuition that’s more difficult to replicate. The human element is still needed to help build and maintain client relationships, as AI systems can’t yet replace personalised advice and address the unique needs of individuals. All this means is that it's unlikely AI will directly replace portfolio management, but rather, it will serve as a compliment that frees up time for more critical decisions.

Conclusion

In this report, we discovered

AI can analyse complicated datasets and draw conclusions
Unbiased insights can help improve investment skills
AI can help improve margins and assets under management
Human interaction will still be needed in the future.

About:
SkillMetrics® revolutionises investment expertise by providing advanced behavioural insights tailored for portfolio managers. Our cloud platform identifies strengths, weaknesses, and behavioural biases, leading to improved performance. CIOs/CEOs can coach teams to enhance results by focusing on the investment process. Fund Selectors benefit from skill monitoring and behavioural diversification.

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