GenAI Use Cases: Asset Management
Asset managers are professional firms and institutions that invest and manage capital on behalf of individuals, corporations, and governments to achieve specific financial goals. These managers allocate assets across a range of vehicles—such as mutual funds, ETFs, pension funds, and hedge funds—balancing risk and return to maximize value for their clients.
Key players: Global Asset Managers (BlackRock, Vanguard, Fidelity Investments), Investment Banks with asset management arms (Goldman Sachs Asset Management, Morgan Stanley Investment Management), Boutique and Alternative managers (Invesco, PIMCO), Private Equity Funds (Blackstone, KKR, Carlyle Group), Hedge Funds (Bridgewater Associates, Citadel),
Today, AI is deeply integrated across asset management operations, from portfolio construction to client service. Large asset managers use ML models to optimize trading (e.g. choosing the best venue and timing for a trade) and to forecast risk scenarios (such as stress-testing portfolios with AI-generated simulations). Risk management systems like BlackRock’s Aladdin have incorporated machine learning to better predict defaults or market shocks using diverse data (SmartDev). A significant development in 2023 was the creation of domain-specific large language models such as BloombergGPT, a 50-billion parameter model trained on financial data. BloombergGPT can handle specialized financial NLP tasks – answering questions about market conditions, interpreting financial documents, and even generating plausible news headlines. This reflects the industry’s growing need to digest textual information at scale.
On the sell-side, investment banks and research firms are deploying generative AI to draft portions of research reports, summarize company filings, or produce first drafts of client communications (McKinsey). On the buy-side, one of the first high-profile uses of generative AI has been in wealth management advice. For example, Morgan Stanley Wealth Management partnered with OpenAI to integrate GPT-4 into its advisor workflow, creating an internal chatbot called the “AI @ Morgan Stanley Assistant” that helps human financial advisors quickly retrieve information and analyses from the firm’s knowledge base (OpenAI). By 2023, 98% of Morgan Stanley advisor teams were actively using this AI assistant to answer client questions faster and to generate concise summaries of research – effectively augmenting human expertise with AI (OpenAI). Such tools improve productivity and consistency, allowing advisors to tap the firm’s collective intelligence via a simple query. Looking ahead, asset managers are exploring generative AI to customize client reports, generate scenario narratives (e.g. “what if” market stories), and even ideate new trading strategies by analyzing vast data for hidden patterns.
