The increasing use of artificial intelligence (AI) and machine learning by financial firms could enhance the efficiency of the financial system, but it also creates the potential for new systemic risks by intensifying interconnectedness and increasing firms’ reliance on opaque models, says a report from the Financial Stability Board (FSB) released on Wednesday.

There are a number of possible risks and benefits stemming from the increasing use of these sorts of technologies that “should be monitored” as the technology evolves and as more data on its use becomes available, the report says.

In terms of new risks, the use of AI and machine learning could result in “new and unexpected forms of interconnectedness between financial markets and institutions,” the report says. For instance, it suggests that the use of previously unrelated data sources by various financial firms could create a new form of interconnectedness.

As well, the growing use of these sorts of technologies could make financial firms increasingly dependent on third-party firms, which could, in turn, “lead to the emergence of new systemically important players that could fall outside the regulatory perimeter,” the report says.

In addition, the growing technical sophistication of these technologies makes them increasingly difficult to oversee. “The lack of interpretability or auditability of AI and machine learning methods could become a macro-level risk,” the report adds. “Similarly, a widespread use of opaque models may result in unintended consequences.”

These potential new sources of risk are in addition to the more easily foreseeable threats to customer privacy, the challenge of cybersecurity, and ever-present conduct risks.

On the upside, the report notes that more efficient information processing may also help create a more efficient financial system, and regulators may be able to use AI and machine learning to help improve compliance and to increase their supervisory effectiveness.