Background

A major financial institution operating across banking, securities, and insurance divisions recognized that timely monitoring of market sentiment and risk signals is critical for effective risk management in a heavily regulated environment. With global financial markets moving rapidly, social media discourse and news coverage often serve as leading indicators of market volatility.

Increasingly stringent financial regulations require institutions to establish more robust risk early-warning systems. Traditional approaches relying on analysts to manually gather market intelligence can no longer meet the demands for real-time coverage and breadth. At the same time, large volumes of internal regulatory documents, research reports, and risk control records made it difficult for employees to quickly locate the information they needed.

Challenges Faced

• Tracking the public sentiment of thousands of listed companies and financial market developments daily involves an enormous volume of data
• Market risk signals are scattered across news outlets, social media, and research reports across different channels, making unified aggregation difficult
• Regulatory changes are frequent, requiring the compliance team to monitor domestic and international financial regulatory developments in real time
• Tens of thousands of regulatory documents and research reports have accumulated internally, resulting in low employee query efficiency
• Risk control alerts require real-time responsiveness, which traditional daily-report-based intelligence gathering methods cannot deliver

Industry Solutions

The institution simultaneously deployed LargitData's InfoMiner sentiment analysis platform and RAGi enterprise AI engine, building a comprehensive AI-driven risk management framework.

InfoMiner Sentiment Intelligence Risk Control Module

• Financial Market Sentiment Monitoring: real-time tracking of news and social media discussions related to listed companies, financial markets, and economic indicators
• Risk Signal Alerting: automatically detect risk signals such as surges in negative sentiment and abnormal discussion patterns using AI sentiment analysis
• Compliance Monitoring: track regulatory announcements and policy changes from domestic and international financial regulatory authorities
• Individual Stock Sentiment Dashboard: create dedicated monitoring dashboards for key investment targets, integrating multiple information sources

InfoMiner Social Listening →

RAGi Enterprise AI Retrieval-Augmented Generation Engine

• Regulatory Knowledge Base: import tens of thousands of regulatory documents, allowing employees to query relevant provisions using natural language
• Research Report Retrieval: quickly search historical research reports and market analysis documents, with source citations and summaries provided
• Risk Control Case Library: build a historical risk control event database for the risk management team to reference and learn from

RAGi Enterprise AI Retrieval-Augmented Generation Engine →

Implementation Results

• Risk signal detection advanced from next-day reporting to real-time alerts, successfully flagging market risks ahead of multiple volatility events
• Time for the compliance team to query regulatory provisions reduced from an average of 2 hours to just a few minutes, a 90% efficiency improvement
• Simultaneously monitoring sentiment dynamics for over 3,000 enterprises and investment targets, with greatly expanded coverage
• The RAGi knowledge base now contains over 50,000 internal documents, serving as the core information portal for employees' daily work
• Overall risk control operational efficiency improved by 60%, allowing human resources to be reallocated to higher-value strategic analysis work