Whether in business processes, software applications or apps – expert knowledge such as decisions, calculations or checks is defined in the form of business rules. Business rules management (BRM) allows companies to define, centrally manage, and automate expert knowledge, independent of program code and business processes, as a set of graphical rules – consistent across processes, applications, and channels.
Business rules are managed centrally at a single-point-of-truth and deployed to all processes and applications – consistent and error-free.
Instead of using code or process models, rules are graphically defined, securely managed, and quickly adapted as needed for maximum business agility.
By reducing coordination loops between business and IT, business rules management ensures high efficiency and optimum use of resources.
Changes to business rule models are documented as well as the execution of the rules in day-to-day operations. This ensures audit-proof traceability.
Business rules are policies and statements about how to deal with a situation depending on certain criteria. Examples include lending or pricing guidelines, compliance checks, process control specifications, calculations, and more. Most business rules exist as knowledge in the minds of subject matter experts.
Digital transformation requires more knowledge to be embedded in the software systems, which is done with the help of rule models, among other things. Subject matter experts use decision tables or decision trees to formalize their business rules. The rule models can be understood and processed by business and IT experts, but also by computers.
A business rule engine is a software component that automatically executes business rules. A rule engine aims to separate the frequently changing business logic (business rules) from the rather static process logic (business processes) in order to enable higher independence and thus agility and flexibility for business departments.
A business rules management system (BRMS) is a software that supports business and technical users throughout the entire process of defining, managing, automating and adapting business rules. A graphical modeling approach is easy to understand for business users and enables them to quickly change business rules when they need to – without coding.
Many rules: BRM allows companies to optimize the organization and structuring of their business rules.
Complex business logic: BRM helps companies bring IT and business expertise together by directly involving business domain experts.
Frequent changes: BRM empowers business users to quickly change business rules and thus, speed up time to market.
Maximum transparency: BRM provides optimum transparency and traceability for auditing requirements and other activities.
Faster development: Companies break out of endless development cycles and use BRM as a collaborative platform for business and IT.
Dispersed rules: Companies centralize their business rules and optimize their reusability for consistency across all applications and processes.
BRM is an integral part of corporate-wide decision management. It can be applied to control processes and workflows within business process management. In business intelligence, BRM is used to calculate KPIs and apply analytical results. Besides, BRM even supports the legacy modernization and data transformation.
Business departments apply business rules management for all kinds of application scenarios such as ensuring product, client and investment suitability, underwriting, account auditing, pricing or fraud detection. Rules-based advisory processes can be digitized and master data management can be automated by using BRM technology.
With ACTICO Rules, companies manage and automate rules-based business logic. Business professionals benefit from the intuitive graphical approach and maintain business logic independent from IT release cycles. Discover our market-leading business rules management system now!
ACTICO Machine Learning is an integrated software platform for intelligent decision automation. It offers a well-aligned toolset for modeling, managing and automating operational decisions and apply machine learning technology.