By Andrew Bockelman, Head of Banking, Moody’s
Banks worldwide are deploying artificial intelligence (AI) to support and accelerate risk-assessment processes and inform decision-making amidst growing competition from new rivals. Our recent survey of 348 banking leaders across the United States, the European Union (EU) and the Asia-Pacific (APAC) suggests that successful AI adoption depends on more than technology alone. Banks that are reporting the greatest progress are also investing in the people, skills and organizational changes needed to support it.
The prevailing narrative around AI adoption in the banking industry over the past few years has been simple: Banks that integrate the technology fastest across their organizations will gain the greatest advantage. However, the findings from our survey suggest that the story is a little more nuanced. The banks reporting stronger progress are combining AI adoption with organizational transformation to reshape their organizations and reinforce new ways of working throughout the business.
APAC banks provide a strong illustration of this trend. Banks in the region report deploying agentic AI across some or most teams at a rate of 82 percent, compared with 74 percent in the US. They also recognize that technology provides greater value when employees, processes and operating models are prepared to use it effectively.
Across the APAC region, three strategies are shaping that response.
Across the APAC region, three strategies are shaping that response. Banks are upskilling their existing workforces, hiring specialized talent to support transformation efforts and blending in-house capabilities with strategic external partnerships. All three approaches are more common in APAC than in the US or Europe.
The survey found that 38 percent of APAC banks were making cultural changes to move their organizations toward a more technology-enabled data business, compared to 32 percent in the US and 30 percent in Europe. This involves role-specific training for frontline staff as well as recruiting AI and data specialists to help steer technology use. “Everyone is not an IT engineer; everyone is not an AI guy; so you need to invest in your people, down to the people who are in the branches; they should know what AI is and how it works,” said a senior executive at one APAC bank that we surveyed. “Investing in AI is for people and for data.”
Forty-two percent of APAC banks were hiring senior staff with data and AI experience to drive strategic change, compared with 31 percent in the US and 32 percent in Europe. A further 43 percent were hiring AI and data specialists, compared to 37 percent in the US and 38 percent in Europe. Recruitment that once focused on generalists is increasingly targeted at specific specialist categories, particularly in areas such as digital lending.
New positions are being created around data and emerging technologies. The prevailing view, however, is that AI should augment human judgment rather than replace it. “More and more roles—data scientists, data analysts—are coming over,” said a senior executive at a bank in the region. “The decision-making power should stay with the human.”
Behind both the upskilling and hiring is a deliberate approach. APAC banks are combining in-house development with carefully selected external partnerships, determining where to build, where to partner and where to bring capabilities in-house. Thirty-two percent of APAC banks were forming partnerships with organizations in adjacent sectors, compared to just 24 percent in the US and 22 percent in Europe. This mix of internal build and external partnerships is deliberate. The result is a coherent philosophy: train broadly, hire selectively, partner where it accelerates, and keep critical capabilities inside the perimeter.
Survey respondents cited three main reasons for this approach:
- First, to maintain strict control over sensitive data and support regulatory compliance. A partnership lead for payments and platforms at an APAC bank explained, “We never want to go outside and collaborate with Google, Gemini or any other player. We try to build that in-house.” The respondent added, “There is a regulatory aspect as well—that’s the reason the bank decided to have an in-house AI capability.”
- Second, to gain and sustain a competitive advantage through customized solutions that may be difficult to achieve using off-the-shelf products. “For large international banks, most of [the business] is built on third-party and internal systems combined,” observed one senior executive at an APAC bank. “That’s the way it’s done, because otherwise the competitive advantage is gone.”
- Third, to internalize technology capabilities developed initially through fintech (financial technology) collaborations, without forsaking trust. “Banks are closing collaborations with fintechs because they have now understood the technology and deployed it on their own platforms. At the end of the day, the customer trusts a bank over a fintech—that is the advantage banks always have,” said a product sales lead at an APAC bank.
The survey results suggest that this strategy may be contributing to stronger implementation outcomes among APAC banks compared to their US and European peers. Thirty-two percent of APAC banking leaders strongly agreed they were succeeding operationally in implementing technological and data-change directives, compared with 25 percent in the US and 29 percent in Europe.
In commercial lending, connecting functions that were previously working from different data sets is beneficial. “We’ve cut our time to decision in half—not because the model has changed, but because we have finally connected data from origination, credit and risk in one place,” said an executive at an APAC bank. “That visibility gives us the confidence to move faster.”
In credit risk, one benefit is improving the speed of daily decision-making. AI helps assemble the data picture across portfolios, geographies and markets, while human committees translate that information into decisions. “For the credit committee package, we hold daily meetings to discuss regionally and globally all data issues—geopolitical risk, country risk and market risk across the equity, bond and commercial paper markets,” an executive explained.
The findings suggest that those banks that develop cultures, talent strategies and operating models to support AI may be better positioned to respond to evolving customer needs, strengthen decision-making and build deeper customer relationships in an increasingly competitive market.
This byline article was drafted based on insights from a recently published white paper that can be found HERE
Andrew Bockelman is the Global Head of the Banking Segment at Moody’s. He is responsible for Moody’s overall business with banks around the world. As a seasoned executive with over 30 years of experience, Andrew has a proven track record of driving growth, efficiency, and performance in both public and private companies. His career has been mostly dedicated to serving large financial institutions, leveraging his strong international experience across 40+ countries to lead global organizations with 2,000+ people.