Master of Science in Computer Science
Department of Computer Science
Faculty / School
School of Mathematics and Computer Science (SMCS)
Date of Submission
Dr. Zaheeruddin Asif, Assistant Professor, Department of Computer Science, Institute of Business Administration (IBA), Karachi
MSCS Survey Report
Information extraction, Automated regulatory compliance, Financial institution ontologies, Automated rule extraction, Automated risk assessment, Governance risk and compliance, Text to model conversion, Semantic knowledge representation
Regulatory Compliance is organization’s conformation to some laws and regulations relevant to its business. These laws are created by regulatory authorities like State Bank of Pakistan creates regulatory laws for financial authorities in Pakistan. Currently, all financial institutions create compliance programs to handle the compliance of the organizations where manual work is done for identifying non-compliance and controlling it.
To automate this, we can use the Natural Language processing which is a branch of Artificial Intelligence through which computer can understand human language and speech. RegTech is the application of emerging technologies in field of regulatory processes to make it more enhanced and automated.
This research focuses on one of the applications of Natural Language Processing in the field of RegTech i.e. information extraction techniques to enhance regulatory compliance. Information Extraction is the branch of natural language processing used to find relevant information in unstructured text. To find the relevant part that what one organization need to comply can be achieved by using information extraction techniques i.e. Sentiment Analysis, text summarization etc.
Lalwani, R. K. (2021). Regulatory compliance enhancement using information extraction techniques (Unpublished MSCS survey report). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/survey-reports-mscs/21
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