Days to Minutes: AI-Powered Fund Analysis Processing

The Challenge

Financial services firms managing fund analysis face significant operational hurdles. A 12b-1 fee — a recurring charge built into mutual fund expenses for marketing and distribution, typically ranging from 0.25% to 1% of assets — requires careful scrutiny. Under Section 15(c), fund boards must annually review adviser contracts to examine costs, performance, and services.

One Quantiva client providing fund analytics struggled with scale during peak filing seasons, requiring analysts to manually process thousands of prospectuses, SAIs, and annual reports. This manual approach consumed hours per fund while clients awaited critical comparative analysis for board meetings.

Building an AI That Speaks "Fund" Language

Fund documents present extraction challenges due to inconsistent formatting. Fee tables vary widely, performance metrics use different calculations, and governance changes hide in boilerplate text.

Quantiva developed an AI pipeline trained on thousands of historical fund documents, enabling the system to:

• Extract multi-tier fee structures from any table format
• Normalize performance data for peer comparisons
• Identify strategic and governance changes
• Automatically generate comparative analytics for 15(c) reviews

Delivering Intelligence at the Speed of Business

The platform enables analysts to query documents using natural language, generate board-ready reports automatically, create peer group analyses with consistent methodology, and monitor fee trends across the fund universe.

The Results That Matter

• Processing: Fully automated extraction versus hours of manual work
• Accuracy: 98% for fee and performance data
• Analyst Productivity: 5x increase
• Throughput: 30% increase in client capacity

Better intelligence means better decisions. By embedding AI into review workflows, compliance becomes a strategic advantage.