- Artificial intelligence (AI) is transforming financial instrument management and expanding investment opportunities by supporting strategic decision-making, according to FlexFunds.
- These technologies enable asset managers to become more efficient and comply with regulations, facilitating the hyper-personalization of financial vehicles and portfolio diversification.
- AI is also driving the distribution and growth of investment products, although human oversight remains necessary in this process.
- Supported by technology, FlexFunds facilitates the global creation and distribution of financial products, structuring independent investment vehicles through an asset securitization program.
The global rise of artificial intelligence is having direct repercussions in the financial world, contributing to the management of various instruments and assets, identifying opportunities for value creation, and providing greater support for strategic decision-making. FlexFunds explains the key elements of adopting these technologies in asset management.
The race within the asset management universe has intensified in recent years due to industry trends pointing toward hyper-personalization of financial vehicles and more diversified portfolios, while technological solutions like AI allow asset managers to become more efficient and compliant with different regulations.
In a report titled How technology empowers success in the alternative assets market, consulting firm Deloitte explains that regulatory pressures are driving the adoption of automation in response to the demand for robust processes that reduce human error. According to this analysis, published alongside AlterDomus, automation becomes essential for risk management and ensuring compliance, thereby avoiding rising operational costs1.
Likewise, liquid assets and alternative instruments are benefiting from these tools in portfolio structuring to enhance performance in options such as stocks, bonds, investment funds, and other financial securities.
Concepts like algorithmic trading, a mode of operation in financial markets based on automation, or robo-advising, which provides investment solutions through digital tools, are gaining prominence in this scenario.
In this context, technological solutions are also contributing to the distribution and growth of investment products for asset managers, though the activity still requires significant human oversight, explains FlexFunds, a leading provider of services for asset securitization.
On its platform, FlexFunds offers solutions to fund managers through the setup of independent investment vehicles, enabling the management of strategies and global distribution to non-US investors. Through an asset securitization program, FlexFunds creates exchange-listed products (ETPs) that facilitate global distribution.
FlexFunds uses advanced technologies to setup independent investment vehicles, enabling effective global distribution of financial products. In their view, AI could be a determining factor for the future of asset management and investment structuring in the coming years.
FlexFunds analysts note that thanks to the management of large volumes of data and its subsequent analysis, tools like artificial intelligence allow for the identification of value-creation opportunities in asset transactions. Liquid and alternative investments benefit from AI applications in multiple fields, ranging from identifying potential opportunities to risk management and the personalization of different instruments.
According to Mercer Investments’ 2024 Global Manager Survey2, 91% of managers currently use (54%) or plan to use (37%) AI in their investment strategy or asset class analysis. “At the asset class level, there is clearer consensus regarding the AI-driven value creation opportunity in equities, hedge funds, and digital assets,” the report states.
In the midst of the global AI boom and its adoption in the financial industry, these technologies could contribute to generating efficiency, managing risk, and improving decision-making by asset managers, according to a report from BlackRock. As noted in the document titled Artificial intelligence and machine learning in asset management3, these technological solutions can enhance user experience and interfaces, operational efficiency, and investment processes.
These solutions allow better adaptation of financial products to clients’ needs based on their risk profile and investment horizon. At the same time, they improve the quality of data on financial instruments managed by asset managers through machine learning techniques.
Regarding investment processes, these tools aid decision-making by identifying patterns and perspectives. For example, in the case of an ETF (exchange-traded fund), AI models can help decide how to weigh allocations within a given index, facilitating its management and enabling a more precise replication of the index.
AI facilitates the growth and distribution of investment products, though significant human oversight is still required to avoid systemic errors.
The AI race in the global financial sector
Consulting firm International Data Corporation (IDC) estimates that global spending on AI solutions will grow to over US$500 billion by 20274, as organizations in multiple sectors benefit from adopting AI-enhanced products and services.
The financial sector could be one of the most benefited by this AI wave, as despite challenges, it could experience gains in fraud detection and financial forecasting, with up to 40% of financial services companies “primarily relying on machine learning for both use cases,” according to a report by S&P Global Market Intelligence TMT5.
S&P projections indicate that, initially, generative AI solutions will help enhance human response capabilities through the implementation of chatbots or virtual assistants. On another level, the correct adoption of these tools and extensive use of the vast volumes of data they manage will lead to the creation of hyper-personalized products and services, while entities advance in technological modernization in other areas.
Emerging technologies enable greater efficiency in the personalization of financial products and portfolio diversification, helping asset managers meet regulatory requirements.
One of the main benefits is that generative AI, capable of creating original content from existing data, could add up to US$340 billion annually in value to the global banking sector due to, among other factors, increased productivity, according to figures from the McKinsey Global Institute (MGI)6. The value creation in the industry could equal between 2.8% and 4.7% of the industry’s total revenues.
Tech company IBM indicates that current uses of AI in finance7 include customer service, cybersecurity prevention, financial planning, fraud detection, loan eligibility, and trading.
The success of AI in asset management
A report from the CFA Institute Research Foundation8, titled Artificial intelligence in asset management, concludes that the success of AI in asset management primarily stems from its ability to detect complex patterns in high-dimensional data that humans cannot perceive, improving forecast accuracy.
Secondly, these technological solutions can process large volumes of unstructured data, such as articles and reports, without manual intervention, ultimately enriching financial analysis.
And thirdly, CFA refers to AI’s self-improving capability, automatically adjusting based on data, eliminating the need for manual reconfigurations common in traditional methods. However, its ability to process data unsupervised can be a weakness if the data quality is low or the task is too complex, which could result in systemic errors, they warn.
Given the significant role of human management in the activity, CFA believes that the success of AI currently hinges on a range of capabilities, from “the ability to solve portfolio optimization problems with specific conditions” to creating “fully automated algorithmic trading systems.”
In conclusion, FlexFunds highlights that although AI presents challenges, its ability to process large volumes of data and continually improve its performance is redefining the way asset managers structure and distribute their financial products in an increasingly competitive global market. In this scenario, AI and other technological tools are promoting greater efficiency, diversification, and personalization in investments, while enhancing strategic decision-making.
Sources:
1 https://www.deloitte.com/lu/en/Industries/investment-management/perspectives/technology-empowers-success-in-the-alternative-assets-market.html
2 https://www.mercer.com/assets/global/en/shared-assets/global/attachments/pdf-2024-Mercer-AI-integration-in-investment-management-2024-global-manager-survey-report-03212024.pdf
3 https://www.blackrock.com/corporate/literature/whitepaper/viewpoint-artificial-intelligence-machine-learning-asset-management-october-2019.pdf
4https://www.idc.com/getdoc.jsp?containerId=prUS51335823
5https://www.spglobal.com/en/research-insights/special-reports/ai-in-banking-ai-will-be-an-incremental-game-changer
6 https://www.mckinsey.com/industries/financial-services/our-insights/scaling-gen-ai-in-banking-choosing-the-best-operating-model
7 https://www.ibm.com/topics/artificial-intelligence-finance
8https://www.cfainstitute.org/-/media/documents/book/rf-lit-review/2020/rflr-artificial-intelligence-in-asset-management.ashx
