Regtech Clausematch has released a knowledge graph in open source to help speed up the way regulators and financial companies digitise their policies and procedures as well as address regulatory change management.
The graph is the result of a two-year digitalisation project with the regulatory authority of Abu Dhabi Global Market (ADGM). The project utilises advanced AI models to automatically categorise regulatory requirements, creating tags focused on regulatory concepts, obligations and expectation.
The aim of extracting the understanding of regulations and embedding it in a structured, dynamic, machine-executable form is to help more financial institutions gain better contextual understanding of legislation and apply requirements more effectively and efficiently.
Regulators or companies can take the data set and apply it to their own models.
Clausematch’s mission
Evgeny Likhoded, founder and CEO at Clausematch, explains: “Our goal was to address how we can help companies to consume regulations, especially when the number of regulations is increasing and the complexity of regulations is increasing. We wanted to train a machine learning model to think like a regulator and understand the context of regulation.
“We’re hoping that by providing this data set, we can speed up the road to automation and speed up the structured regulation adopted across the entire industry rather than by select regulators.
“We understand that the industry needs to evolve and to get to a place where it’s easy to consume regulation and not a single company in the world can do it purely because of the manpower required to digitise the entire regulation.
“So this is an attempt to help the industry to go forward. Whether we have competitors who want to apply this data set or regulators, we just want the regulatory world to become better. It will reduce a massive burden from the industry by applying and publishing regulations in this way. We want to enable faster, better, easier compliance for regulated entities.”
Clausematch has also published a scientific paper on the application of knowledge graph technologies for regulations.
