Jura: Towards Automatic Compliance Assessment for Annual Reports of Listed Companies
Published in CIKM, 2021
Recommended citation: Zhengqi Xu, Yixuan Cao, et al. Numerical Formula Recognition from Tables. In CIKM, 2021. https://dl.acm.org/doi/abs/10.1145/3459637.3481929
The initial public offering (IPO) market in Hong Kong is consistently one of the largest in the world. As part of its regulatory responsibilities, Hong Kong Exchanges and Clearing Limited (HKEX) reviews annual reports published by listed companies (issuers). The number of issuers has grown at a fast pace, reaching 2,538 as the end of 2020. This poses a challenge for manually reviewing these annual reports against the many diverse regulatory obligations (listing rules).
We propose a system named Jura to improve the efficiency of annual report reviewing with the help of machine learning methods. This system checks the compliance of an issuer’s published information against listing rules in four steps: panoptic document recognition, relevant passage location, fine-grained information extraction, and compliance assessment.
With the help of Jura, HKEX reports saving 80% of the time on reviewing issuers’ annual reports.