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PORTFOLIO ANALYTICS
Financial ServicesA Leading Asset Management Firm · AUM 5B+

10x Improvement in Investment Research Processing Efficiency

Building an AI-Powered Investment Research Information Hub

20 minutes/day
Information Processing Time
100+ reports/day
Research Report Coverage
Within 5 minutes
Critical Information Response
Unified knowledge base
Cross-Team Knowledge Sharing

背景与挑战

This asset management firm manages over RMB 5 billion in assets and has a 12-person investment research team. Each day the team must track market developments across Shanghai, Shenzhen, and Hong Kong, process sell-side research reports, monitor portfolio company announcements, and follow macroeconomic policy changes. Before adopting AI, researchers spent an average of 3–4 hours per day on information gathering, summarization, and organization — accounting for 40–50% of their productive working hours. Delays in processing information meant the team often finished internal distribution only after the market had already priced in a given piece of news, missing the optimal window for decision-making. In addition, each analyst had different habits for collecting research reports, creating severe information silos: the same report was frequently read by multiple people, while critical data points circulated internally with very low efficiency.

璟知科技解决方案

JingMind Technology built an investment research information hub for the firm, comprising three core modules:

Intelligent Information Aggregation Layer — Automatically connects to 30+ major sell-side research channels, exchange announcement systems, and financial news feeds. Every day it completes content ingestion, deduplication, classification, and summary generation automatically, delivering a morning research brief to the entire team before 7:30 AM.

Semantic Search & Q&A — All historical research reports and internal investment notes are vectorized into a knowledge base spanning three years of history. Analysts can ask questions in plain language — e.g., "Were the EV penetration rate forecasts from the past two years accurate?" — and the system retrieves relevant reports and synthesizes an answer with an average response time of 8 seconds.

Real-Time Monitoring & Alerts — Key-word monitoring is set up for each portfolio holding. Announcement releases, abnormal price movements, and management changes are pushed to the responsible analyst within 5 minutes.

落地成果

Information Processing Time
3–4 hours/day→20 minutes/day

Morning brief automation + intelligent summarization reduces manual information work by 90%

Research Report Coverage
10–15 reports/day→100+ reports/day

The system processes more than 10x the volume handled manually

Critical Information Response
T+1 discovery→Within 5 minutes

Real-time alerts for abnormal portfolio events; decision timeliness dramatically improved

Cross-Team Knowledge Sharing
Email forwarding→Unified knowledge base

3 years of investment research content is structured and searchable; new hire ramp-up time reduced by 60%

“We used to be overwhelmed by information. Now information serves us. AI filters out 80% of the noise, leaving us only with things that truly require judgment. This is not just an efficiency gain — it is a systemic upgrade to our investment research capability.”

— Chief Investment Officer

项目实施周期

Week 1–2

Requirements gathering and data interface integration; mapping the investment research team's information flow

Week 3–4

Knowledge base construction: import 3 years of historical research reports and complete vector indexing

Week 5–6

Automated morning brief system goes live; team pilot and feedback iteration

Week 7–8

Real-time alert system launches; full system goes into production

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