Accelerating Digital Transformation Of Capital Markets With Generative AI
Ravi Dharmavaram is Founder and CEO of Exafluence, an IT services and data analytics firm utilizing Gen AI to transform data into decisions.
Capital markets have reached an inflection point around the utilization of data, the pace of which has significantly increased with the advent of generative technologies. From its initial popularization just over 18 months ago, the industry-focused conversations occurring today around the technology’s practical applications have rapidly changed. Last year alone private equity firms nearly doubled their investments in generative AI compared to 2022, reaching an announced value of $2.18 billion according to S&P Global Market Intelligence. While retail banking has been able to capitalize on user data and generate hyper-personalized product recommendations and experiences, behind the closed doors of firms operating in capital markets, a different scene is unfolding. Even with billions of shares exchanging hands daily in the U.S. alone, capital markets have yet to digitally transform many operations, leaving them to rely on legacy systems that aren’t capable of the automation standards of today.
The Current State Of Digital Transformation Within Capital Markets
A decade ago, analysts were still refining their recommendations on the strategic development of digitalized capital markets and the potential benefits to front-end traders and portfolio managers. While digitalized trading across the industry has optimized the transfer of funds and assets, other aspects of firm operations such as data management, market intelligence and reporting have yet to be automated. The result? Capital markets are playing catch up in the middle and back office, leaving executives without a simple, singular viewpoint of data from fund managers.
Where Is Generative AI Most Likely To Make An Impact?
Generative AI’s steep innovation curve has caught the eye of leaders across industries, but the seemingly “endless” number of applications for GenAI may be overwhelming for many. Two of GenAI’s key benefits that will assist capital markets to digitally transform are scalability and automation. Here are a few of the many areas where these benefits have started to be seen in capital markets:
Data Management: The advent of GenAI has opened the eyes of capital markets such as private equity and venture capital to nontraditional data sources that have traditionally been considered difficult to integrate into existing data pools such as social media or news feeds. In practice, generative AI can capture these data sources, as well as clean and prepare existing unstructured data streams, significantly cutting down on the amount of time analysts and portfolio managers spend checking for data accuracy.
Analytics: Over the next three years, KPMG reports that 71% of financial reporting leaders expect to use AI extensively in their daily functions, citing accuracy and efficiency as the main drivers of transformation. Concerns remain about the transparency of models and the potential for hallucinations often seen in conversational applications of generative technology, but the overall time saved in generating reports will still be notable even if more time is necessary to double-check results.
Cybersecurity: Cyberattacks are anticipated to cause over $10 trillion worth of damage to government and enterprises annually by 2025, and experts believe generative AI will play a significant role in this, especially for attacks reliant on social engineering. Protecting millions or billions of dollars of assets in today’s market will necessitate that firms turn to GenAI for defensive measures, such as anomaly detection, malware detection and analysis, and phishing detection.
Talent Management: Even as capital markets continue to undergo digital transformation, a high priority will be kept on the development and acquisition of top talent from the executive suite to the analysts. Just as fund managers seek to utilize generative technology to improve their understanding and the best next step for managing capital, HR teams will implement generative AI to help them assess talent better and focus more heavily on skills-based hiring.
What’s Preventing Total Adoption Across The Industry?
Given the number of business areas where GenAI is clearly able to make transformation, it’s fair to ask why the adoption rate for this technology is lagging behind interest and investment in its development. Some concerns, especially around GenAI’s potential to hallucinate and be used for fraud reasonable, especially considering the scope of transactions handled by capital markets daily. As with any emerging technology, there is an adoption curve that takes time to build momentum. As GenAI continues to make waves throughout all industries, decision-makers in capital markets must keep their finger on the pulse.
The Digital Future Of Capital Markets
Digital transformation sometimes feels like a catch-all, encompassing any new technology that helps businesses operate online. For industries such as capital markets already leaning into new technology, it’s important to look at processes from a higher level to see where GenAI can make a meaningful impact. Digital transformation today in capital markets focuses on upgrading existing tools and processes to build a more connected workplace that can automate unnecessary administrative tasks such as data entry, allowing employees to focus on creative tasks that help managers make better-informed decisions. While this will likely mean targeting generative technology toward processes such as report creation, which at the surface may seem noncritical, the result will be a competitive advantage that propels firms above the competition.
The advancement of openly available GenAI may fascinate consumers, but practical applications of computational and conversational AI should draw the attention of business leaders. By approaching the integration of computational AI in a similar fashion as new employee onboarding, capital markets can, in essence, upskill AI to handle functions that require a level of learning many consumer-facing AI models are not capable of handling today. Integrating a chatbot that focuses on both internal and external audiences can investigate and understand data models for each stakeholder’s specific needs. The real-world applications of GenAI are nearly endless, but the onus is on the experts in capital markets to realize the potential.
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