The ORIGIEN Knowledge Graph Construction and Analysis Platform is a one-stop solution that provides full lifecycle management capabilities for designing, building, integrating, and analyzing knowledge graphs. It supports the rapid construction of business graphs from structured data and unstructured data such as text, with key applications in knowledge retrieval, anti-money laundering, intelligent auditing, and industry chain analysis. It can serve as an enterprise-level knowledge middle platform.
Difficult Knowledge Graph DesignThe business nature of knowledge graphs requires extensive communication between technical and business personnel. The final design of business entities, relationships, and schemas only applies to the current scenario, requiring a redesign when the scenario changes, which is time-consuming and labor-intensive.
High Cost of Graph Construction and UpdatesThe source data is diverse and voluminous, with rapid update frequencies. Each update requires manually running programs to input data, which is cumbersome, error-prone, and unable to keep up with timely data updates.
Difficult Graph ApplicationGraph analysis requires the use of business rules, machine learning models, and graph algorithms to mine large amounts of data. The integration of business platforms and the resource scheduling for graph computations are highly resource-intensive.
The ORIGIEN Knowledge Graph Construction and Analysis Platform provides end-to-end capabilities encompassing knowledge modeling, knowledge extraction, knowledge fusion, and knowledge analysis. It effectively supports knowledge retrieval needs in general domains as well as business graph analysis applications in the financial sector, including marketing, risk control, auditing, and anti-money laundering.
Knowledge graphs can be applied in various business areas:
Knowledge Retrieval for Document Information| Through technologies like NLP and OCR, the platform quickly realizes text understanding and information extraction, enabling structured information to support precise business knowledge retrieval. For example, a regulatory knowledge graph built with regulatory rules and penalty information helps compliance officers in efficient information retrieval.
Anti-Money Laundering Visualization Investigation| Focused on transaction data, the system integrates internal and external data to build a comprehensive view of funds. Using techniques such as community discovery, pattern matching, and model determination, the platform effectively identifies anti-money laundering patterns and criminal groups.
Intelligent Auditing| Builds a complete graph of personal, corporate, institutional, account, transaction, and behavioral data, integrating rules, graph algorithms, and machine learning to effectively mine audit clues hidden within vast amounts of customer information and business data.
Industry Chain Analysis| Integrates internal and external data across industry supply chains, corporate equity, and investments to build a panoramic map of industries and business networks. It provides in-depth business analysis capabilities for investment research, asset management, and investment banking, such as relationship analysis, event propagation, customer acquisition marketing, and sentiment risk control.
Quickly extract information and structure knowledge, achieving efficient compliance information retrieval through the construction of regulatory knowledge graphs.
- Fast Graph Construction
Built-in common business entities, relationships, and graphs; flexible construction methods: mapping, extraction, and incremental; graphical and readable interactive mode improves construction efficiency by 25%.
- Accurate Graph Construction
Powerful NLP model capabilities, built-in financial domain information extraction models for more accurate entity and relationship extraction; active learning reduces text data labeling by over 30%.
- Comprehensive Business Graph Analysis Capabilities
Smooth graph visualization experience, seamless integration of rule engines and machine learning models, complete variety of graph algorithms, and rich reporting features. It supports various integration methods with business systems: page embedding, API, and full data integration.
- Rich Business Scenario Accumulation
Incorporates best practices for financial graph applications, with built-in business entities and blueprints for anti-money laundering, intelligent auditing, and more, ready to use out-of-the-box. For scenarios such as industry chain analysis, it provides unique third-party data.
