Cognitive Compliance: Assessing Regulatory Risk in Financial Advice Documents

Authors

  • Wanita Sherchan IBM Research Australia
  • Sue Ann Chen IBM Research Australia
  • Simon Harris IBM Research Australia
  • Nebula Alam IBM Research Australia
  • Khoi-Nguyen Tran IBM Research Australia
  • Christopher J. Butler IBM Research Australia

DOI:

https://doi.org/10.1609/aaai.v34i09.7105

Abstract

This paper describes Cognitive Compliance - a solution that automates the complex manual process of assessing regulatory compliance of personal financial advice. The solution uses natural language processing (NLP), machine learning and deep learning to characterise the regulatory risk status of personal financial advice documents with traffic light rating for various risk factors. This enables comprehensive coverage of the review and rapid identification of documents at high risk of non-compliance with government regulations.

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Published

2020-04-03

How to Cite

Sherchan, W., Chen, S. A., Harris, S., Alam, N., Tran, K.-N., & Butler, C. J. (2020). Cognitive Compliance: Assessing Regulatory Risk in Financial Advice Documents. Proceedings of the AAAI Conference on Artificial Intelligence, 34(09), 13636-13637. https://doi.org/10.1609/aaai.v34i09.7105

Issue

Vol. 34 No. 09: Issue 9: EAAI-20 / AAAI Special Programs

Section

Demonstration Track