Financial Analysis Agent

The Financial Analysis Agent is a sophisticated AI system designed for comprehensive financial analysis by coordinating multiple specialized tools. The agent integrates document-based analysis for SEC filings (10-K reports), SQL database queries for customer holdings, real-time market data, and automatic PII protection. The system enables natural language queries that are intelligently routed to appropriate tools and synthesized into actionable financial insights.

Problem Statement

Financial analysis requires coordination across multiple data sources:

• Complex SEC filings (10-K reports) need detailed analysis
• Customer holdings stored in SQL databases require querying
• Real-time market data needed for current valuations
• PII protection critical for regulatory compliance
• Need for intelligent tool selection based on query intent

Solution

Built a comprehensive financial agent featuring:

• 6 Specialized Tools: 3 document-based and 3 function-based tools
• Natural Language to SQL: Converts queries to SQL automatically
• 10-K Document Analysis: Extracts insights from SEC filings
• Real-Time Market Data: Integration with Yahoo Finance API
• Automatic PII Masking: Protects sensitive customer information
• Intelligent Tool Selection: LLM-based routing to appropriate tools
• Response Synthesis: Combines results from multiple tools

Architecture

The agent coordinates six specialized tools:

Document-Based Tools (3):

1. 10-K Document Analyzer:

   • Processes SEC 10-K filings
   • Extracts financial metrics and insights
   • Answers questions about company performance

2. Financial Report Parser:

   • Structured extraction of financial data
   • Table parsing and normalization
   • Year-over-year comparisons

3. Risk Analysis Tool:

   • Identifies risk factors from documents
   • Summarizes risk sections
   • Highlights material changes

Function-Based Tools (3):

1. SQL Query Tool:

   • Natural language to SQL conversion
   • Queries customer holdings database
   • Returns structured results

2. Market Data Tool:

   • Real-time stock prices via Yahoo Finance
   • Historical price data
   • Market indicators and trends

3. PII Protection Tool:

   • Automatic detection of personally identifiable information
   • Masking and redaction capabilities
   • Compliance with financial regulations

Key Technologies

• LLM-Based Tool Selection: Intelligently routes queries to appropriate tools
• Natural Language to SQL: Converts user questions to database queries
• Yahoo Finance API: Real-time market data integration
• Document Processing: Advanced parsing and analysis of SEC filings
• PII Detection: ML-based identification and masking of sensitive data

Tool Coordination Workflow

1. Query Analysis: LLM analyzes user query to determine intent
2. Tool Selection: Identifies which tools are needed for the query
3. Parallel Execution: Runs multiple tools simultaneously when appropriate
4. Result Synthesis: Combines results from different tools into coherent response
5. PII Check: Ensures no sensitive information leaks in final output

Challenges & Resolutions

Challenge: Converting natural language to accurate SQL queries
Resolution: Fine-tuned LLM with SQL schema context and validation logic

Challenge: Ensuring real-time market data accuracy
Resolution: Implemented caching with TTL and fallback data sources

Challenge: PII detection across different data formats
Resolution: Multi-layer detection using regex patterns, ML models, and rule-based checks

Challenge: Synthesizing results from multiple tools
Resolution: Structured prompt engineering for LLM-based synthesis

Challenge: Maintaining data freshness for financial analysis
Resolution: TTL-based cache invalidation and scheduled data refresh

• 95% accuracy in natural language to SQL conversion
• Real-time market data integration with <500ms latency
100%
[object Object], in production ( detection rate)
90%
[object Object], achieving accuracy
500+
Successfully analyzed 10-K documents
1000+
Processed customer holding queries

This project highlighted the importance of tool coordination in AI agent systems. The integration of document analysis, database queries, and real-time APIs demonstrated how to create comprehensive analysis capabilities. The PII protection tool showed the critical need for security considerations in financial AI systems. The natural language to SQL conversion proved that careful prompt engineering and schema context can achieve high accuracy without fine-tuning. The parallel tool execution significantly improved response times for complex queries requiring multiple data sources.