TECH TUESDAY is a weekly content series covering all aspects of capital markets technology. TECH TUESDAY is produced in collaboration with Nasdaq.
Artificial intelligence continues to draw attention and make headlines as the emerging technology that many expect will transform how capital markets firms operate.
The development of generative artificial intelligence, the newest iteration of AI, is considered to be in its early stages, with few bounds on potential capabilities. But AI is driving value today by automating the data extraction, quantitative analysis and regulatory reporting that historically have absorbed an enormous allocation of person-hours.
BlackRock, the world’s largest investment manager, outlined its approach to AI and machine learning in a July 2024 blog post. “We leverage these capabilities with the goal of continually shifting from the realm of qualitative to quantitative, increasing the breadth of what we’re able to measure in pursuit of more precise and differentiated investment outcomes,” the blog stated.
In the financial industry’s latest AI deployment to increase automation and efficiency, Nasdaq has integrated AI to simplify and accelerate bank and insurance risk calculations.
Nasdaq noted that market volatility and tighter regulation enacted after the global financial crisis of 2007-2008 are forcing institutional firms that trade over the counter (OTC) derivatives to conduct complex and computationally intensive risk calculations. Specifically, X-value adjustment (XVA) sensitivity analysis can require more than 1 trillion calculations per day; Nasdaq’s recently announced AI-based machine learning functionality, provided through its Calypso platform, can process risk calculations up to 100 times faster.
Gil Guillaumey, Senior Vice President and Head of Capital Markets Technology at Nasdaq, commented on the utility of Nasdaq Calypso’s XVA Accelerator functionality:
“Maintaining the necessary infrastructure and systems can be outrageously expensive, inefficient, and increasingly impractical regardless of cloud elasticity strategies,” Guillaumey said in an October 17 press release. “The sheer scale of computing power required to meet the most demanding regulations, alongside the strategic benefits of more accurate real-time analytics, is driving a profound rethink about how we can leverage AI to reduce the cost of compliance.”
Nasdaq’s XVA Accelerator uses a mathematical approach known as Chebyshev Tensors. Importantly, this approach recalibrates each time an XVA calculation is launched and adapts immediately to changing market conditions – the end results are significantly improved execution times, lower costs, and more empowerment for financial institutions to manage risk.
Such results tie in with the current landscape for AI, in which firms need to see the technology move the needle on the bottom line. In Deloitte’s State of Generative AI in the Enterprise Q3 2024 report, the consultancy cited an overarching theme of moving from potential to performance.
“In the rapidly evolving landscape of artificial intelligence (AI), the connection between technology and value has become increasingly apparent,” the report stated. “Technology application on its own is not enough. Results and business outcomes matter. The real measure of success for GenAI will be how it enables enterprise strategies and drives tangible value.”
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