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Asset managers vs AI: what’s really happening?

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Asset Management AI

The confrontation between traditional asset managers and the rise of artificial intelligence is becoming increasingly apparent. 

With AI algorithms increasingly capable of analyzing vast amounts of data and making investment decisions in milliseconds, asset managers are facing both threats and opportunities.

So, what’s really happening? Are asset managers worried or happy with AI progress so far?

Over the past few years, asset managers have been exploring the integration of machine learning algorithms into their operations. Whether it involves portfolio management or risk optimization, AI has proven beneficial for asset managers. These algorithms can uncover insights at a higher speed and volumes and provide more precise analysis, which surpasses human capacity. Most of asset managers are taking advantage of this technology to improve their activity.

How exactly has AI been helping asset managers?

To answer this question, let’s go back to the AI first integration era. 

This technology has been introduced to asset managers in early 2010s and was used for Robo-Advisory and Fraud Detection. 

However, by the mid-2010s, many asset managers and financial institutions were implementing AI into portfolio optimization, risk assessment and client relationship management. 

While AI was becoming an important part of the business, engineers and developers kept digging deeper into this technology and found out new ways of exploiting it. As the data science industry grew, new algorithms were created to treat significant amounts of data, especially financial data. This new step helped asset managers in their financial analysis and market studies.

By the end of 2022, with the launch of ChatGPT, one of OpenAI’s products, the AI industry began the revolution. AI models grew very fast and the competition became fierce; Bard, Gemini, ChatGPT, Midjourney and many other platforms were developed. The success and the increased demand related to these platforms encouraged asset managers to include AI more and more into their business model.

Is AI also a threat for asset managers?

Although AI technology offers great advantages in terms of data analysis, risk management and portfolio optimization for asset managers, there is an important upcoming threat to anticipate: the independence of the private clients.

We all witnessed the rapid growth of Robo-Advisor technology. Private clients can access their portfolios through a platform at any time. Thanks to Robo-Advisors, they no longer need to contact their relationship manager for every transaction. This technology has indirectly fostered a sense of independence in financial decision-making. If we take the time to analyze the situation, it becomes clear that if this system is fueled with enough information, it can provide precise advice, thereby threatening the role of relationship managers.

Despite the growing presence of AI within asset management companies, we still have to wait for several years/decades before witnessing AI causing challenges for asset managers. 

In the coming years, we can expect to see continued advancements in AI technologies, driving further integration into asset management processes. Asset managers who integrate AI strategically are likely to be more successful.

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