Financial DSS components	Sub-components	Definitions and Functions
Database management subsystem [5] [15]	database	Collect and store relevant data.
	DBMS	Get and extract data from the database, update (add, delete, edit, modify) data records and documents. Provide comprehensive data security for queries and reports, handle personal and informal data, perform complex data processing tasks on a query basis, record data usage, and manage data.
	data catalog	Data accessibility of the answer; Answer data sources; The exact meaning of the answer data; Add, delete items, and fix feature objects.
	query facility	Query data; Processing data; Display data results.
data warehouse [7] [8] [9] [10] [16] [23]	source data	Source data is provided for the data warehouse, such as various production system databases, operational data of online transaction processing system (OLTP), external data sources, etc.
	Extraction, transformation and load tools	Data is extracted from the data source, tested and sorted out. According to the design requirements of the data warehouse, data is reorganized and processed and loaded into the target database of the data warehouse.
	data modeling tool	Model information for the source database of the data warehouse and the target database.
	central repository and data mart	Store data models and metadata. Includes metadata, data models, and data marts.
	target database	Store tested, sorted, processed, and reorganized data.
	Data warehouse management tools	Provide management means for data warehouse operation, including security management, storage management and other aspects.
Model base management subsystem [24] [25] [26]	model base	Storage strategy, tactics, operations, analysis models.
	model building blocks	Data analysis tools, including model infrastructure and programs, can be applied directly as models or as components of large models.
	modeling tool	Deals with semi-structured or unstructured issues such as programming tools and language programming models. Typical examples are spreadsheets (Excel).
	MBMS	Easily and quickly create the model; Storing, acquiring, and managing multiple different types of models in a logical and integrated manner; Use and integrate infrastructure components; Categorize and display model catalogs; Record model data and application usage; Link integration database and model library; Manage and maintain model libraries: store, use, run, update, connect, categorize, and query; Use multiple models to support problem solving.
	model catalog	Model classification; Model definition; Answer model feasibility and function.
	Execution, composition and instructions	Control the actual running process of the model; Accept and interpret instructions from the user interface section and send them to the MBMS, model execution.
Knowledge management subsystem (expert system) [6] [21] [27]	knowledge acquisition	Explain and integrate answers to questions through knowledge engineering. Create clear concept of analogy and construction counterexample.
	knowledge base	Understand and expound knowledge; Knowledge required to solve problems.
	inference engine	Reasoning information in knowledge base and blackboard structure, controlling structure and rule interpreter.
	user interface	Provide communication between users and computers.
	blackboard	Describe specific problems; Document assumptions and decisions.
	explanation subsystem	Source of follow-up conclusions; Explain expert system behavior.
	knowledge-refining system	Analyze the knowledge and application, generate more accurate knowledge base and effective reasoning method.