Like the industry it regulates, the UK’s Financial Conduct Authority is turning towards machine learning and other AI-based technologies to spur its productivity and improve its effeciency.

The regulator also has been working with its international counterparts to discover other areas in which they can benefit from regulatory technology beyond its current use in manual reporting and compliance reporting.

It is still “early days” for implementing such technology, according to one FCA official.

The FCA is investigating using supervised machine-leaning for speech-to-text applications, social media analytics, and media analytics as well as unsupervised analytics for detecting financial irregularities.

“We’re looking at these underlying technology approaches and regtech solutions to try and see how we can employ them internally to be more efficient and to better identify which solution (works) for the financial markets,” Nick Cook, head of data and information operations at the FCA to CNBC.

One of the initial use cases could be making unambitious portions of regulator’s handbook machine readable and ultimately fully machine executable.

“The idea being that we can put out rules which are written manually in ways that can be fully and unambiguously interpreted by machines,” he explained.