Unlock the Potential of AI in Banking

Setting a Bold, Bankwide Vision for the Value AI Can Create

McKinsey's experience with hundreds of companies shows that capturing value from digital and AI transformations requires a fundamental rewiring of how a company operates. This involves six critical enterprise capabilities: a business-led digital road map, talent with the right skills, a fit-for-purpose operating model, technology that's easy for teams to use, data that's continually enriched and easily accessible across the enterprise, and adoption and scaling of digital solutions. Leading banks view AI not just as a cost-efficiency driver but as a tool to enhance revenues and improve customer and employee experiences.

They embed AI in the strategic planning process, requiring every business unit to set bold financial and customer goals. By prioritizing high-impact areas and investing in enabling scalability, leading banks ensure that major AI initiatives are business-led. This means business executives take ownership and hold joint accountability with technology leaders to deliver outcomes.

Rooting the Transformation in Business Value

Launching isolated AI endeavors like chatbots or document summarizers leads to incremental results and rarely drives material financial changes. To significantly boost business value, banks need to choose the right scope of transformation by rewiring entire domains and subdomains. Instead of having many disparate, siloed projects, leading banks reimagine entire business domains and subdomains using a full range of AI and digital technologies.

When selecting subdomains for transformation, banks consider business impact, technical feasibility, end-user adoption, and solution priority. Once selected, each subdomain is deconstructed into executable modules that drive business value. For example, transforming the customer underwriting subdomain involves multiple AI and digital technologies working together.

Enabling Value through an AI Stack Powered by Multiagent Systems

To embed AI seamlessly across the enterprise, banks implement a comprehensive capability stack. This includes the engagement layer, decision-making layer, data and core tech layer, and operating model layer. The decision-making layer, the brain of the AI-first bank, orchestrates thousands of AI-powered decisions.

Orchestrated multiagent systems represent a major advancement. These systems comprise various AI "agents" that can plan, think, and act. When combined with predictive AI models and digital tools, they can rewire several domains, boosting productivity and creating more engaging experiences for customers and employees.

For example, in credit underwriting, agents can handle most tasks, with human intervention for the final steps. Multiagent systems can automate complex decisions and workflows, enhancing the work of both credit risk teams and employees.

Investing in the Foundations to Enable AI Value Creation

Banks that unlock value from AI make balanced investments across the entire AI capability stack. The industrial AI/machine learning sublayer provides reusable tools for deploying and running LLMs. The enterprise data sublayer stores and accesses large unstructured data sets for training multiagent systems.

Building AI capabilities at scale requires investing in these crucial sublayers to ensure the right capabilities and innovations are in place.

Sustaining and Scaling Value from AI

A successful AI transformation balances near-term financial impact with building lasting capabilities. After choosing domains and subdomains for transformation, banks focus on executing at scale and delivering value from reusable components.

For example, a large bank is transforming to improve performance and deliver analytics at scale. They built reusable assets and an end-to-end analytics pipeline, with early results showing promising revenue increases.

To sustain value, banks set up teams that create value, not just models. They also establish a central AI control tower and governance council to oversee the transformation, track value, and ensure reusability of assets.