How Multi-Strategy Hedge Funds Scale to Prevail with AI

Spotlight on the portfolio manager (PM)     

The hedge fund talent war has been well-documented, and some say it is a “full-blown arms race for alpha.”ⁱⁱⁱ There are bidding wars and $100 million compensation packages, while at the same time multi-manager platforms are demanding performance, some installing hard stop-loss thresholds. A BlackRock executive told Spears Magazine that in the current environment, there’s a widening gap between good managers and average ones, and “if you can identify those good managers, there’s more potential reward than in the past.”^iv Therefore, PMs are under the microscope, both in terms of keeping them happy and retained and also tracking their performance and overseeing risk exposures.

Technology-forward PMs want AI

Savvy young PMs expect their firms to give them the tools they need to succeed. They do not want to chase other departments or IT to get data they need; they do not want to work in a place where they cannot trust the integrity and accuracy of data; and they expect their firms to be deep into the development of AI agents. They will jump quick if they bump up against operational barriers to their day-to-day business of driving alpha. PMs, as well as other departmental staff, will soon be using AI agents to execute key tasks. They already can use natural speech with AI to navigate searchable data catalogs to find and track data assets — in a fraction of the time they used to expend.

This is made possible by automated data management processes working in the background, in which AI-powered data quality and governance engines ensure insights are up to date, precise, and easy to understand. Moving a step farther, AI will be helping to not only gain swift access to the right information but also add depth and speed to financial analysis, making it even easier to surface actionable insights.

AI for intelligent multi-strategy operations

Arcesium’s Aquata platform includes AI capabilities that solve the perilous problem of dealing with unstructured data. It can ingest and harmonize diverse, previously unusable information from documents like PDFs that contain valuable business intelligence. For example, managers and analysts can use unstructured proxy vote data, consumer loan terms, and capital call notices data to inform their governance quality screening, relative value/arbitrage strategies, or liquidity timing and stress signals, respectively. And in doing so, they incur fewer errors and can scale without sweating about adding large or unwieldy datasets. Business users can ask natural language questions about their data and have the AI generate the relevant visualizations like graphs, charts, and dashboards automatically.

The Opterra platform unlocks efficiencies for operational users, and our agentic AI capabilities will soon be helping human colleagues execute tasks across the investment lifecycle like trade processing, reconciliation, and collateral management. In the first part of our two-part series on multi-strategy funds, we noted that tools like universal book of record (UBOR), an innovative combination of IBOR and ABOR, help funds thrive in complex multi-manager structures, offering them separate strategy views, allocations, and performance, allowing them to extend capital to the best strategies and asset classes.  

Funds with benefits: make the most of the multi-manager model

A major benefit of the multi-manager hedge fund structure is its capability to gain capital deployment and margin efficiencies with the diversification of managers and strategies. However, if the fund accountant is unable to accurately track that across the different PMs, that would-be benefit becomes an operational albatross. If you're running a highly diversified overall portfolio, then you need to capture where you're gaining those efficiencies to justify the multi-manager approach. Armed with the advantage of an accurate and speedy house view into the fund’s liquidity and cash flow, as well as fully loaded P&Ls of each manager and portfolio, managers ensure optimal allocations to the best-performing PMs and strategies and subsequently can generate margin efficiencies.

AI-powered real-time reporting and risk transparency

The precise tracking of sophisticated P&L allocations and structures across all portfolios empowers managers to produce real-time risk reports that help better manage liquidity and counterparty risk. The Aquata data platform’s AI-powered, self-service financial data analysis tools help funds slice and dice data, personalize and visualize reports, and automate and schedule delivery of client, regulatory, and management reports.

The Aquata data platform offers out-of-the-box partner and vendor integrations with OMS, trading systems, execution venues, and market data vendors. Upcoming AI capabilities will further accelerate data integration by automatically detecting schemas, generating custom data models, and building intelligent data pipelines. Armed with a deeper well of investment data, PMs can react deftly when market changes require quick pivots.