An AI Regulatory Roadmap

Posted on March 20, 2020 by Editor

A recent Centre for Finance Technology and Entrepreneurship (CFTE) paper develops a regulatory roadmap for addressing the increasing role of AI in finance, focusing on how human involvement can deal with ‘black box’ issues.

The paper identifies three regulatory challenges from AI in finance. Firstly, AI algorithms increase information asymmetries between various users and developers. Secondly, AI increases data dependencies as different data sources can alter operations. Thirdly, AI enhances system dependencies.

All of these issues are summarised as the ‘black box’ problem: accountability is reduced as the nature of AI obscures why and how it operates.

The authors of the paper suggest external regulators insist on strengthened internal governance – specifically, keeping a human in the loop in order to review the AI and shed some light into the ‘black box’.

Read the paper here.

Other Posts


Would you like
to learn more?

Join our Newsletter mailing list to
stay plugged in to the latest
information about XBRL around the world.

By clicking submit you agree to the XBRL International privacy policy which can be found at xbrl.org/privacy