Design of a Financial Indicators Analysis System Based on AI Technology

The study designs an intelligent financial analysis system. Through requirements analysis, three user roles has been identified- visitors, registered users, and system administrators. Visitor functions include browsing pages, performing decision-tree intelligent classification of listed companies, and obtaining single-company financial indicator analysis data. Registered users gain additional capabilities for trend analysis and industry comparative analysis of listed companies beyond visitor functions. System administrator functions encompass user information management and data maintenance. The system adopts object-oriented design methodology and has implemented three core modules- single-company financial indicator analysis, single-company financial indicator trend analysis, and listed company financial indicator industry analysis. It employs web crawling technology, text parsing techniques, and decision tree models to achieve automated collection, parsing, classification, and presentation of financial statement information for Shanghai and Shenzhen listed companies based on user-defined criteria. On this basis, it calculates various financial indicators. Specific implementations include- Intelligent data acquisition using Selenium components for automated extraction of financial reports from target websites; Text extraction and data parsing utilizing PDF processing libraries such as Camelot and Pdfplumber; Database management and operations through SQLAlchemy with SQLite.