The rise of ‘regtech’ will enable businesses to navigate complex compliance and keep the global economy stable. Via WIREDUK WIREDWorld2022
Unlike haiku and Stephen King novels, financial regulation isn’t quick or easy reading. To take one example, chapter 1 of title 12 of the US Code of Federal Regulations is 1,114 pages long and contains more than 600,000 words. If you had a reading rate of 300 words per minute, it would take in excess of 33 hours to finish. And that’s just chapter one. There are 18 chapters in title 12, and 50 titles in total.
Regtech firms use AI to help financial institutions keep up with regulations and monitor client activity for regulatory violations. Up until now, machine learning and natural language processing techniques have been employed to organise, classify and extract requirements from regulatory documents. Three key factors have created this opportunity in regtech AI. The first is data availability and quality. For the past decade, native digital versions of many regulations have been produced and enriched. Mass digitisation has allowed regulatory texts – and their metadata – to be structured at scale.
The third factor is the technology, which is broadly represented by semantic AI. Regtech AI draws on vast volumes of regulatory and user data – the latter including comments, annotations and “implicit feedback”, which is communicated through the usage of a system. The combination of such data with big advances in deep transformer-based models such as BERT, GPT-3 and Wu Dao 2.0 is the key to machine understanding.
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