Market monitoring by the EBA indicates that the use of such advanced applications is becoming increasingly prevalent, with two out of three EU credit institutions already having such solutions in production.

"In general, most institutions are currently using simpler algorithms, leveraging on their core banking data," the EBA notes in a new report. "However, the current landscape can evolve in a rapid pace in the next few years.

"The need for necessary competence is becoming increasingly important, raising an important challenge for institutions, supervisors and regulators. Training and development, as well as closer engagement between the relevant stakeholders, could be an appropriate starting point for addressing this challenge."

The EBA has identified four key pillars - data management, technological infrastructure, organisation and governance and analytics methodology - necessary to support the rollout of advanced analytics, along with a set of ‘elements of trust’ that need to be properly and sufficiently addressed.

Trusts based elements revolve around ethics, expalainability, advoidance of bias, data quality and consumer protection.

The EBA is of the view that additional efforts are need by banks to respect and integrate these capabilities into their application development programmes.

"Towards meeting this objective, a risk-based approach could apply on certain 'elements of trust' depending on the impact of each application," states the regulatory body. "For example, stricter requirements may apply on the 'explainability' element when there is a potential impact on business continuity or potential harm to the customer."

In the area of ethics, the Report refers directly to the “Ethics guidelines for trustworthy AI” developed by the EU High-Level Expert Group on AI set by the European Commission.