Transforming the Data Landscape

In the ever-evolving landscape of financial services, the integration of Artificial Intelligence (AI) and Large Language Models (LLMs) has emerged as a game-changer, especially in the realm of financial data generation such as:

• Reference data

• Research

• ESG

• Fundamental data sets

The accuracy in which AI, particularly LLM’s can extract data points from unstructured sources, such as Exchange filings and Disclosures, is reshaping how FinTech’s and Data Vendors approach Data production and Operations, providing a potent catalyst for

• Improved accuracy
• Accelerated speed to market for new product offerings.
• Improved accuracy

Some key operational benefits that the integration of AI and LLM’s can deliver include:

1. Complementing Internal Operational Processes

Financial institutions rely heavily on data vendors for comprehensive and timely information. Integrating AI and LLMs into existing operational processes enhances the capabilities of these vendors. By automating data extraction and analysis, these models help eliminate manual errors, reduce processing times, and ensure a more consistent and reliable flow of information. This strategy can open the door for data vendors to extend the scope and simplify the integration of their data sets without additional large capital investment in data operations.

2. Enhancing ESG Data Accuracy

ESG factors have become integral to investment decision-making, reflecting a growing awareness of sustainability and responsible investing. AI and LLMs contribute significantly by automating the extraction and analysis of ESG-related information from diverse sources, including news articles, social media, and official company disclosures. This process not only improves the accuracy of ESG data but also significantly improves speed-to-market for updates data points within days of a company material ESG disclosures.

3. Accelerating Speed to Market

One of the primary advantages of leveraging AI and LLMs within data generation operations is the acceleration of speed to market for new product offerings. These models can quickly analyze, extract and maintain datasets, assuming the models can be exposed to the official underlying sources of data. It is worth noting that, in our view, there will always be a need for human involvement in the data generation process, especially for performing delta checks where business rules have been triggered. Overall the combination of AI and human within data operations can deliver the speed-to-market, which is critical in an industry where timely information can make the difference between seizing market opportunities and missing out.

4. Market Validation and Adoption

Market trends affirm the growing importance of AI and LLMs in financial services. According to a report by EY in October 2023*, Wealth and Asset Manager senior executives rated ‘Data Ingestion to drive alpha generation’ as the top area in which GenAI could have the greatest impact on their organization. The report emphasizes the positive impact on data accuracy and the ability to uncover previously inaccessible insights, aligning with the themes discussed in this blog.

In conclusion, the integration of AI and Large Language Models highlights how positive an impact GenAI can have on data generation within financial services – detailed thought needs to go into how these GenAI models are deployed, as well as the controls and QC processes that are built around them. By enhancing accuracy, increasing scope, and accelerating speed to market, these technologies could empower services providers to stay ahead in a dynamic and competitive landscape.

As the industry continues to embrace this transformation, the power of GenAI models could prove to be a disruptive force within financial data generation.

Orbit Financial Technology focuses on harnessing AI models to make sense and structure from millions of unstructured data sources – Contact Us to see how our platform is creating positive disruption in data production and operations as well as investment research and ESG due diligence.

Generative AI transforming wealth and asset management | EY - US