Industry Solutions

The financial sector faces increasingly complex market risks and regulatory demands. LargitData combines InfoMiner sentiment analysis with the RAGi enterprise AI decision engine to deliver real-time market risk monitoring, compliance alerting, and intelligent investment research solutions for banks, securities firms, insurers, and asset managers.

Industry Challenges

Global financial markets shift rapidly and regulations grow ever stricter, leaving financial institutions facing multiple challenges in risk management and compliance:

• Insufficient Real-Time Market Risk Visibility：Traditional risk-control systems rely heavily on structured data and historical indicators, making it difficult to capture real-time market risk signals embedded in unstructured sources such as social media and news coverage.
• Increasing Regulatory Compliance Pressure：Regulations from the FSC, central bank, and international frameworks such as Basel III and MiFID II are continuously updated, requiring organizations to track regulatory changes in real time and assess their impact.
• Investment Research Efficiency Bottlenecks：Analysts must read through massive volumes of research reports, financial statements, earnings-call transcripts, and industry news every day — a manual process that is slow and prone to missing critical information.
• Enterprise Reputation Risk：The reputation of financial institutions directly affects client trust and share-price performance, making real-time monitoring of negative sentiment and media coverage essential.
• Activate Internal Knowledge with AI：Compliance documents, internal control policies, and historical cases are scattered across different systems across departments, making it difficult for staff to retrieve the information they need quickly.

Industry Solutions

LargitData offers financial institutions a combined solution built on two core AI tools:

InfoMiner — Market Sentiment Intelligence and Risk Monitoring

• Real-time monitoring of over 100,000 channels covering financial news, social media discussions, and regulatory announcements.
• AI sentiment analysis automatically gauges market sentiment trends and delivers quantifiable market confidence indicators.
• Abnormal volume detection and real-time alerts notify risk management teams before negative events spread.
• Sector and individual stock sentiment trend analysis to support investment decision-making.

Learn MoreInfoMiner Social Listening

RAGi - Enterprise Generative AI Platform

• Consolidates compliance documents, internal controls, and regulatory databases into an AI-powered enterprise knowledge base.
• Employees can quickly retrieve regulatory clauses, historical cases, and internal policies through natural language queries.
• Supports on-premise deployment to ensure sensitive financial data never leaves your environment, meeting financial industry security requirements.
• AI automatically summarizes research reports and financial statements, significantly boosting investment research efficiency.

Learn MoreRAGi Enterprise AI Retrieval-Augmented Generation Engine

Diverse application scenarios

Scenario 1: Real-Time Market Sentiment Monitoring and Early Warning

The risk-control division of a securities firm used InfoMiner to set up sentiment monitoring projects for individual stocks and industry sectors. When negative sentiment around a specific stock surged abnormally within a short timeframe, the system automatically sent alerts to the trading floor and Chief Risk Officer, enabling the team to initiate risk assessment and hedging operations before market prices reacted.

Scenario 2: Regulatory Change Tracking and Compliance Assessment

A bank's compliance department used InfoMiner to monitor announcements and news from the FSC, central bank, and international regulators. In parallel, RAGi was used to build an internal compliance knowledge base. When new regulations were issued, compliance staff could ask the AI directly — for example, "How does this new rule affect our current KYC process?" — and RAGi would instantly cross-reference internal policy documents to provide analytical recommendations.

Scenario 3: Intelligent Investment Research Analysis

The research team at an asset management company loaded thousands of research reports, financial statements, and earnings-call verbatim transcripts into the RAGi knowledge base. Analysts simply ask questions in natural language — such as "Compare TSMC and Samsung's capital expenditure trends over the past three quarters" — and the AI automatically extracts relevant data from the documents and produces a summary report, compressing what previously took hours of data gathering into just minutes.

Scenario 4: Enterprise Reputation Risk Management

A large financial holding company used InfoMiner to continuously monitor media coverage and social media discussions for each of its subsidiaries. AI sentiment analysis automatically flagged negative reports, enabling the risk-management team to track the reputational risk index of each business unit in real time and incorporate sentiment data into the annual risk report.

Expected Outcomes

• Risk Detection Advanced by 2–4 Hours：Real-time sentiment monitoring across social media and news sources surfaces potential risks earlier than traditional structured data.
• Compliance Assessment Efficiency Improved by 70%：The RAGi AI knowledge base reduces regulatory queries and impact assessments from days to near-instant results.
• Investment Research Report Production Time Reduced by 50%：AI auto-summarization and cross-document comparison dramatically accelerate the research workflow.
• Reputation Risk Event Response Rate Improved to 95%：Comprehensive monitoring and real-time alerts ensure nearly all negative events are addressed immediately.
• Zero Data Leakage：RAGi supports on-premise deployment, keeping all sensitive financial data within the corporate intranet in full compliance with financial industry data security regulations.