Concepts
What are the business audiences?
Define the category, name and operational meaning of the object, so that the same term is consistent in different systems.
Client/ Account/ ProductFintology · Enterprise ontology and knowledge graph
Unify business concepts and relationshipsHelp AI understand your business and connect its data
Fintology organizes concepts, attributes, relationships and rules from systems, documents and expert knowledge into one business model. Connect customers, accounts, products and orders to their data sources and supporting knowledge, giving search, analytics and agents a consistent understanding of the business.
Business information and dataSystem records Business files Expert experience
FintologyA shared enterprise business model
ConceptsAttributesRelationshipsRule
Knowledge and business applicationsKnowledge Retrieval Business Analysis Position
Defining operational implicationsAssociation Real DataRetain source and version
What's the body?
Define business concepts and relationships
Create a shared business vocabulary
An ontology explicitly defines the concepts, attributes, relationships and constraints of a business domain. It gives people, systems and agents a shared understanding of terms, entities and their connections.
Attributes
How do you describe these objects?
To clarify the characteristics of the object, the meaning of the field and the type of data, and to reduce the differences in synonyms and calibres.
Client number / product typeRelationships
How does it connect with the object?
Connecting objects with a clear business relationship to provide a path for cross-system queries and linkage analysis.
Client - Holds accountsConstraints
What requirements should records meet?
The field requirements, the range of values to be taken and the associated conditions are clearly stated as the basis for data verification and expert review.
Status take value / association condition(c) The definition and linkages of the subject of the business are clearly defined in this context; Knowledge maps organize specific objects and records by these relationships. The two complement each other by matching business implications with actual data.
Conceptual reference: W3C OWL 2Business models and knowledge mapping
Connect records across systems
See the full business context
Connect business data through consistent definitions while retaining the source of each relationship. Follow a business question to the relevant entities, connections and evidence.
Connect customers, accounts and products
Linking client information, account records and product information with harmonized business definitions reduces the cost of cross-system understanding and reconciliation.
Clients
• Classification of business
Account
Account number. Account status
Products
Product number · Product type
Relationship manager
Number of employee
Transaction records
· The amount of the transaction
Operational systems
Scope of application. Version of information
Explore data mapping and business queries
Body Definition
Clarify the meaning of objects, attributes and relationships.
Operational data
Links specific records to these definitions.
Knowledge mapping
Connect objects and sources by business relationship.
Link records across systems by business entity
CRM Client InformationClients
Client_id · Client number
Accounts system recordsAccount
act_no · account number
Product Master DataProducts
product_code · Product number
View links around business issues
Which customers hold a given product, and where do the records come from?
- Clients A-102
- Account AC-071
- Products P-03
Search for records along the "Customs-Account-Product" relationship and link the data sources of the systems.
How to build a business.
Start with a business question
Build a reusable business model
Define the scope and questions first, then align terminology, model relationships, connect data and validate the results. Business and technical teams maintain the model as needs change.
01 Define the business scope
List the questions that need to be answered and clearly use the scene and maintenance responsibilities.
Phased outputsOperational issues and scope02 Collect business terminology
Summarizing data dictionaries, systems and trade vocabulary and collating synonyms and definitions.
Phased outputsList of terms and definitions03 Define concepts and relationships
Establishment of conceptual hierarchies, attributes, relationships and necessary constraints.
Phased outputsBody Model04 Link actual business data
Connect business examples and sources, keep cross-system identification maps.
Phased outputsOperational data and relationships05 Validate with domain experts
Using a model for validation of operational issues, data are checked and reviewed by experts.
Phased outputsValidation and audit records06 Publish and maintain
Record changes in models and definitions of sources and continuously refine business models.
Phased outputsVersion and Change Record
Modelling methodology referenceStanford University's Ontology Development 101
Connecting knowledge, data and business
Align business meaning
Connect knowledge with agent applications
The business model defines entities and relationships; the knowledge base supplies source material; agents use both to complete business tasks.
FinLore
There's a source on the source.
Organizational systems, manuals and operational information to inform concepts and rules in their original language.
Explore FinLoreFintology
Coherence of business implications
Harmonization of concepts, attributes, relationships and rules, linking knowledge and business records.
Business business modelFinClaw
Use of knowledge in tasks
In conjunction with business models, access to relevant audiences and information is provided to assist staff in completing analysis and processing.
Explore FinClawYOUR NEXT STEP
Discuss Fintology
Product demos and integration guidance
Tell us about your business needs, existing systems and deployment environment. Our team can provide a product demo and discuss integration.
Fintology
Frequently asked questions
How do ontologies, knowledge graphs and knowledge bases differ?
An ontology defines business concepts, attributes, relationships and constraints. A knowledge graph connects actual entities and relationships. A knowledge base stores source material for search and citation. Together they link business data, definitions and supporting sources.
Must all enterprise data be organized before building an ontology?
Start with one question and its relevant data, such as a customer-account query or order-material trace. Define scope, entities and relationships, validate the model against real questions, then expand to other departments and use cases.
Why add an ontology when databases and data dictionaries already exist?
Database schemas define storage; data dictionaries explain fields. An ontology aligns concepts across systems—for example, whether two customer records refer to the same entity and how accounts relate to products. Existing data dictionaries provide a starting point.
Do ontology rules directly execute system operations?
An ontology describes business meaning and relationships; constraints validate data. Agents invoke tools for system changes, with FinGuard handling authorization, approvals and execution records. Modeling and action execution remain separate responsibilities.