By Laurent Louvrier, VP of Product, Artificial Intelligence at Confluence
The SEC’s introduction of new regulations over the last few years, including the Shareholder Reporting Rule, has meant increased reporting obligations for firms without a corresponding increase in the time, money, and human capital required to meet these obligations.
Firms are under pressure to have the right data and systems in place, leading to rising costs and resources at a time when many firms are also grappling with an overwhelming volume of unstructured data. To source, structure, arrange and report on this data is a significant undertaking given the amount of data teams need to parse. It’s becoming unfeasible for firms to tackle this using their traditional technologies.
New technologies like Gen AI and LLMs allow the automation of manual tasks like checking, reconciling, translating, and reasoning about information that cannot be easily handled by traditional technologies due to the nature of unstructured data. To use the SEC’s Tailored Shareholder Report requirements as an example, manual reconciliation to meet this requirement on or after July 24 may take a typical manager hundreds of business days to reconcile the reports each time. Firms must do this within a 60-day window, which becomes operationally impossible.
Advanced AI models are now capable of mining and pinpointing discrepancies in language and numeric information between financial reports and the TSR, automatically parsing data from third-party financial reports, and interrogating and reconciling it within seconds leading to a 90% increase in efficiency. This directly addresses the key challenges our clients face with data reconciliation and compliance validation under tight deadlines. These solutions convert complex unstructured data into valuable insights, reducing what would typically take weeks of manual work into a streamlined process that delivers significant efficiency and cost savings. While there’s still human oversight needed in all of this, AI can radically improve the efficiency of information and dissemination in financial reporting and compliance.
So, what’s holding firms back from using AI? Largely it has been resistance to change and the perceived risks regarding data privacy and security. To ease any concerns, I would first say companies should examine their business processes to evaluate where they allocate their time and resources and how AI can transform these areas to gain efficiency. A better understanding of business priorities and processes will help make decisions on where to start to leverage AI. While some organizations may have the capability to develop AI solutions internally, it often makes more sense to partner with established vendors who have the business process and AI expertise that can bring proven immediate business value.
As new regulations with more arduous reporting requirements arise, demanding greater time and resources, it will be especially important for firms to replace tedious manual validation processes and embrace productivity-enhancing technologies or risk being left behind. By leveraging AI, investment compliance operations can streamline SEC reporting processes, enhance compliance, and mitigate regulatory risks more effectively.
