During my recent visit to India, I had the good fortune of meeting several startups and scale ups and was rather surprised to see the amount of emerging Unicorns in the space who leverage LLMs. I must say I was partial to the LLMs that we use extensively in Financial Services from FinGPT, FinBot, InvestLM, BloomGPT, FinLlama etc .
So when these companies said they were better than some of the companies that have hundreds of billions of recent funding, I did not believe them. When I explored further it was very clear that these companies (LLMs and SLMs) that were locally originated was more suited to financial analysis of India based companies when you deployed more local intel, more recent financials, more channel checks and so on.
So upon return I looked at what LLM models are really making the difference. While there are the large Banks that experiment with many LLMs, hedge funds and private equity had an opportunity to move the needle in this area..
What models are gaining traction in the market? Here is a summary of some of the interesting models that are helping with better revenue generation and deal closures. In writing this article during Tech week I met with Industry CIO Sreej Menon, who has a lot of technology experience at multiple banks such as JPMC, UBS, Santander, Credit Suisse who validated some of the thinking in this area and helping me thinking through what lies ahead and which agents are delivering value. Here is a summary of the top 10:
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AI research Analyst LLM
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Live agent that continuously analyses market data such as 10 K, 10Q and updated disclosures and helps risk management teams and pricing teams enabling sales teams to close quicker by giving a read in seconds versus what used to take weeks
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AML Agent
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Analyses Financial Transactions and calculates risk scores and subtle risk indicators that enables better compliance
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Auction Management
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This agent manages the complaex lifecycle of OTC contracts auctioning , bid management and seamless automation of novation and closeouts
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Breaking News agent
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Helps Portfolio Managers personalize client recommendations based on how a breaking news event impacts a portfolio positively or negatively especially when a “tweet” can move markets
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Corporate Actions agent
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Automates end to end processing of corporate actions and maintains complete audit trail
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ISDA legal docs analyzer
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Agent attracts key clauses and derivatives from OTC derivatives dox including ISDA, credit support annexes and credit amendments and makes it easy to identify risks
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Research Agent
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This agent surfaces data from multiple sources and creates a daily digest that can be customized by client
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Sell Side Recommendation agent
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Personalized agent for customizing a thesis relevant to a client for faster revenue acceleration
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Term Sheet Agent
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This agent automates and interprets OTC derivative term sheets, Combines structured, unstructured and live market data for accuracy.
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Trade Surveillance agent
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Agent monitors equity, bond and options trading activity and detects violations and automates red flags and exceptions for investigation by analysts
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In addition we discussed agents that help with due diligence for private equity transactions that are getting very popular at some of the larger PEs around the World.
So when David Solomon says that 95% of core IPO documents are now AI generated versus Six bankers grinding away for several weeks, it is further validation for the potential in this area.
2025 may well be the golden year for LLMs and given that Quantum is not far behind a lot of limitations of current day processing are likely to change in the medium term.
All opinions expressed by the writers are solely their current opinions and do not reflect the views of FinancialColumnist.com, TET Events.
