Investment research teams are under pressure to cover more funds and asset classes, faster, without compromising on quality. When analysts spend most of their time pulling data from databases and spreadsheets to draft reports by hand, output is capped by capacity. A global consulting firm faced this constraint in its wealth business. LTM helped the firm reimagine research report creation with an LLM-powered Fund Researcher Co-Pilot, showing how generative AI in investment research can multiply analyst productivity.
New Productivity Paradigms
LTM infused generative AI into the firm's research workflow through an AI co-pilot that automatically produces first drafts of fund viewpoint reports so analysts can focus on insight and judgment.
We owned outcomes
Enabled higher volumes of fund viewpoint reports across asset classes within the year
Drove a substantial improvement in profitability for the research function
Our Client
The client is a global consulting firm delivering expertise across talent, health, retirement, and investment solutions to organizations worldwide. Its wealth business relies on a dedicated investment research team to produce fund viewpoint reports that guide advice and investment decisions.
Industry Trends
Wealth and investment advisory firms are embracing generative AI in investment research to scale research and advice. Leading firms are increasingly:
Using generative AI for research report automation, creating first drafts of reports and commentary
Automating data gathering and synthesis from structured and semi-structured sources
Expanding research coverage across asset classes without proportional headcount growth
Keeping analysts in the loop to review, refine, and approve AI-generated content
Treating research productivity as a lever for profitability
Challenges
The firm's research process faced several constraints that limited output and efficiency.
Manual report creation: The investment research team produced fund viewpoint research reports manually, making each report time-consuming to create.
Fragmented data sources: Analysts had to review and synthesize data stored in databases and Excel sheets completed by fund managers.
Limited capacity to scale: The manual approach capped the number of reports the team could produce across asset classes each year.
These constraints limited research coverage, weighed on profitability, and made a clear case for research report automation.
LTM's Solution
LTM developed the Fund Researcher Co-Pilot, an end-to-end application of generative AI in investment research that uses an LLM to generate research reports.
End-to-end report generation: The co-pilot delivers research report automation by drawing on fund data from databases and fund manager spreadsheets to generate complete fund viewpoint reports.
Multi-asset coverage: The solution supports different asset classes, including Fixed Income and Global Equity.
Analyst-ready first drafts: Each generated report serves as an initial draft for the wealth business's investment research team, who review and refine it before publication.
Business Benefits
The AI co-pilot delivered measurable gains in research productivity and business performance.
Increased report generation efficiency by 50%.
Enabled the team to produce higher volumes of reports across asset classes within the year.
Delivered a substantial improvement in profitability, driven by higher research output.
Freed analysts from manual drafting through research report automation, so they could focus on analysis, insight, and quality review.
Conclusion
With an AI co-pilot at the center of its research workflow, the consulting firm shifted fund viewpoint reporting from a manual, capacity-bound task to a faster, scalable, and more profitable process. LTM's solution shows how generative AI in investment research gives teams a strong foundation to extend AI-assisted research to additional asset classes and report types.
Ready to Outcreate manual research reporting and scale your investment insights across asset classes?
Contact us at info@ltm.com
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