Forty-five percent of banks and other financial institutions are looking to automation technologies to help contain the expected rise in their risk management spend in the next two years.

Half of the 57 financial institutions queried for a new Deloitte Insights report said “efficiency tools” such as cognitive analytics, robotics processing automation (RPA), natural language processing, machine learning, and digital tools will be “extremely high” or “very high” priority in the coming years.

The 57 global FIs polled included banks, investment managers and insurers surveyed between March and September 2020. Of those, 51% reported offering banking services. The 12th edition of Deloitte’s “Global Risk Management Survey” also incorporates approximately two dozen interviews with chief risk officers or their equivalents, and recommendations from the author, J.H. Caldwell, a global financial services risk advisory leader and a partner at Deloitte, a “big four” accounting organization.

While the majority of FIs polled plan to adopt automation tools, few of those surveyed currently use them. Although 46 % of organizations reported using cloud computing, only 29% reported using RPA, compared to 42 % who said they plan to adopt RPA. Twenty-seven percent said they currently use machine learning, with 38% saying they plan to use it. A mere 13% said they use cognitive analytics, with 39% planning adoption.

But automation adoption can do much more than reduce operating costs for financial institutions.

“While these technologies can reduce operating costs by automating manual processes, their benefits go far beyond cost reduction to offer substantial improvements in effectiveness and quality,” Caldwell said in the report.

Specifically, Caldwell stated that RPA, AI and other digital tools can be used to:

• build controls directly into processes for risk management;
• prioritize areas for testing and monitoring;
• review all transactions, as opposed to relying on sample tests; and
• identify potential risk events in real time.

But while automation can reduce risk, it does introduce factors FIs will need to manage, including new points of failure and potential bias.

“Failures of automated processes could have even deeper and more extensive impacts than would result from a problem in a manual process,” Caldwell stated. “Machine learning systems, where the application learns and makes individual decisions on its own rather than being explicitly programmed, have the potential to create inadvertent bias, rogue programs, or inaccurate results.”

AI applications powered by machine learning can create a “black box,” in which decisions based on personal data cannot be explained, potentially leading lenders to run afoul of legislation such as the General Data Protection Regulation in the European Union.

“Institutions will need to demonstrate to regulators and the public that their model risk management frameworks have been enhanced to be able to identify and manage these risks in their IT systems, as well as broader data ethics implications,” the report warned.

Bank Automation Ignite, taking place March 2-3, 2021 as a virtual experience, is the event for inspiring automation initiatives and investment in financial services. Formerly the Bank Innovation Ignite conference, this new focus creates an event where financial services professionals can discover new use cases and technologies that are accelerating automation in banking. Learn more and register for the event at www.BankAutomationIgnite.com.