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“Artificial intelligence” (AI) has undoubtedly been the buzzword of the past two years, and it has inevitably penetrated the financial sector, significantly contributing to its digital transformation. Among the most intriguing applications of AI in finance is its capability to compile indices using AI models. This method offers a promise of more efficient and precise index design.

Passive investment products track the performance of a securities index based on selection criteria traditionally set once by experts and financial analysts and remain fixed over time. These criteria, including market capitalisation and sector affiliation, dictate which companies are included in the index. While this method has been effective for decades, it faces limitations due to the finite availability of company data and evolving market conditions.

On the other hand, actively managed investment products dynamically track market developments but typically require the time-consuming and costly involvement of a portfolio manager.

LIXX now provides a solution that meets both needs: a dynamic, rules-based index strategy that is cost-effective and can be implemented without the need for an active portfolio manager.

For instance, if an index aims to reflect the consumer behaviour of millennials and Gen Z, traditional methods typically identify only the large companies successfully targeting these demographics. However, trends in the B2C sector evolve rapidly, and newer, promising providers quickly become favourites among these consumer groups. Consequently, conventional index compilation methods often fall short in capturing these dynamic market shifts.

This is where AI proves invaluable. AI algorithms can process vast quantities of data, including financial statements, corporate news, and market sentiment. Utilising sophisticated machine learning models, these algorithms are capable of detecting patterns and trends that might elude human analysts. FinScience, a subsidiary of Datrix group, harnesses these AI models to perform precisely this function.

In a vast database continuously analysed by AI algorithms, consisting of approximately 1.5 million text elements from around 35,000 diverse data sources, the FinScience model identifies trends that often elude even the most seasoned financial analysts. The model monitors and dynamically analyses not only conventional financial information but also media reports typically unrelated to financial news. For over five years, FinScience has emphasised the importance of data quality and its relevance to the investment context.

Additionally, AI algorithms are able to consider complex relationships between various companies and sectors when constructing indices. This capability allows for a more dynamic index composition, optimised based on factors such as correlations, interactions and risk-return profiles.

LIXX customers can now utilise FinScience AI to develop indices on topics and market areas that previously appeared too vague for selecting appropriate securities. LIXX thereby provides an additional option for customers interested in creating their own indices and issuing related financial products.

The five exemplary indices crafted using the FinScience AI model stem from meticulous analysis of approximately 1.5 million text data entries from around 35,000 diverse sources, including company reports, news outlets, forums and specialised websites. This innovative approach is designed to offer investors a fresh and unique perspective on evolving trends and themes across various markets.

The five AI indices are:

• Finance & Banking of the Future Index (ISIN DE000A400A10)
• Agritech and Sustainable Agriculture Index (ISIN DE000A402WK1)
• Decarbonization Index (ISIN DE000A41C2L)
• Deep Learning Leaders Index (ISIN DE000A41C2M9)
• Stocks for the new Generations Index (ISIN DE000A41C2K3)

About FinScience: FinScience, a fintech company within Datrix group, was founded by former Google senior managers and specialists in AI and finance. This fusion of expertise enables FinScience to create innovative solutions for the investment ecosystem. Central to FinScience’s mission is the strategic application of AI-driven data and algorithms, enhancing the investment landscape’s intricacies and empowering financial institutions and analysts to make informed, data-driven decisions.