A closer look at AI: business rules management systems

2019-11-17T18:33:08-08:00January 14th, 2017|
Artificial intelligence business rules management systems

Business rules management systems (BRMS) are one of the most popular tools in artificial intelligence and machine learning.  BRMS enable companies to easily define, deploy, monitor, and maintain new regulations, procedures, policies, market opportunities, and workflows.  One of the main advantages of business rules is that they can be written by business analysts without the need of IT resources.  Rules can be stored in a central repository and can be accessed across the enterprise.  Rules can be specific to a context, a geographic region, a customer, or a process.  Advanced Business Rules Management systems offer role-based management authority, testing, simulation, and reporting to ensure that rules are updated and deployed accurately.

Limits in Business Rules Management Systems

Business rules represent policies, procedures, and constraints regarding how an enterprise conducts business.  Business rules can, for example, focus on the policies of the organization for considering a transaction as suspicious.  A fraud expert writes rules to detect suspicious transactions. However, the same rules will also be used to monitor customers whose unique spending behavior are not accounted for properly in the rule set and this results in poor detection rates and high false positives.  Additionally, risk systems based only on rules detect anomalous behavior associated with just the existing rules; they cannot identify new anomalies which can occur daily.  As a result, systems based on rules are outdated almost as soon as they are implemented.

Smart Agents technology works with legacy software tools to overcome the limits of the legacy machine learning technologies to allow personalization, adaptability and self-learning.