This report was first published by Oliver Wyman here.
Banks have been trying for years to implement artificial intelligence programs to improve their client experiences and fend off increasing competition from new entrants outside the traditional financial services industry. Most of these efforts have found only modest success so far — in large part because the programs haven’t cut broadly enough across the enterprise. Some of the biggest potential benefits of AI for banks are in revenue improvement, yet most firms aren’t capturing them.
But a small handful are making real progress. We call them AI trailblazers, and they are drawing a map for others to follow as they try to protect market share from potentially disruptive fintech and big tech rivals.
Exhibit 1: Pillars of the AI transformation
Source: Oliver Wyman analysis
We have identified four steps the most successful banks in AI deployment are following. First and foremost, they are seeking to develop AI everywhere — not just in client-facing applications but across their enterprises. Second, they are emulating the very tech companies they are trying to defeat: Instead of thinking like banks deploying technology, they are thinking like tech companies getting into banking. Third, they are committing full bore to improving and modernizing their data practices — not only by moving to the cloud but also by bolstering governance and data stewardship. Finally, the trailblazers are creating AI factories — internal centers of excellence brimming with talented workers — that they then can deploy across the enterprise.
Exhibit 2: Overview of 3-6-9 agile delivery approach followed by an AI-first trailblazer
Source: Oliver Wyman analysis
In this report, we share the secrets these trailblazers are revealing and create a new roadmap for banks to follow as they embark on, or begin to course-correct, their AI journeys.
Exhibit 3: The journey of our client, a leading GCC bank, in becoming an AI trailblazer
Source: Oliver Wyman analysis
