Multiagent systems as key to AI-first banking: analysts

If implemented well, banks can see up to 60% productivity gains from credit analysts.

Multiagent systems are a key technology that can help banks achieve their AI-first goals, according to McKinsey & Co.

Orchestrated multiagent systems comprise various Al "agents" that can be thought of as virtual coworkers. These human-like agents have the capacity to eventually be able to plan– such as organizing a workflow– think, and then act using digital tools, according to McKinsey analysts from its Financial Services Practice.

If implemented well, such systems can “rewire” various domains of the bank, such as the possibility for between 20% to 60% productivity gains from credit analysts; and roughly 30% faster decision making.

“Beyond boosting productivity, the use of multiagent systems can form the basis of more engaging experiences for customers and bank employees. For instance, a multiagent system can help customers during a loan application process even if they don't have all the required documents,” the report stated.

For employees, a multiagent system could help a sales associate who is underperforming by creating a conversational experience that could offer the employee specific actions to secure the next sale, it added.

Currently, multiagent systems are in the nascent stage. McKinsey & Co. highlighted that there is still need for more technical development before they will be ready to deploy at scale across enterprises.

McKinsey & Co. analysts Carlo Giovine, Larry Lerner, Renny Thomas, Shwaitang Singh, Sudhakar Kakulavarapu, and Violet Chung, with Yuvika Motwani wrote the report “Extracting value from Al in banking: Rewiring the enterprise.”