  Regulatory compliance is an organization's adherence to laws, regulations,
guidelines and specifications relevant to its business. Compliance officers
responsible for maintaining adherence constantly struggle to keep up with the
large amount of changes in regulatory requirements. Keeping up with the changes
entail two main tasks: fetching the regulatory announcements that actually
contain changes of interest, and incorporating those changes in the business
process. In this paper we focus on the first task, and present a Compliance
Change Tracking System, that gathers regulatory announcements from government
sites, news sites, email subscriptions; classifies their importance i.e
Actionability through a hierarchical classifier, and business process
applicability through a multi-class classifier. For these classifiers, we
experiment with several approaches such as vanilla classification methods (e.g.
Naive Bayes, logistic regression etc.), hierarchical classification methods,
rule based approach, hybrid approach with various preprocessing and feature
selection methods; and show that despite the richness of other models, a simple
hierarchical classification with bag-of-words features works the best for
Actionability classifier and multi-class logistic regression works the best for
Applicability classifier. The system has been deployed in global delivery
centers, and has received positive feedback from payroll compliance officers.
