Moody’s hosted a webinar on June 2 with senior banking leaders to discuss what banks need to consider today to build for the future. The panel, which featured Moody’s Head of Banking Andrew Bockelman, Head of Industry Practice Leads Americas James Partridge, alongside practitioners Eray Guven, Tim Kocher and senior adviser Arindam Mukhopadyhay, discussed data from our banking study, The Intelligence Edge.
The conversation focused on how competitive advantage is defined by how quickly and confidently banks make decisions. The institutions pulling ahead are connecting data, artificial intelligence (AI), and workflows to enhance their decision-making capability. However, many banks remain constrained by fragmented data and disconnected systems.
According to our survey, 40% of banks have ambitious data and technology plans, yet a staggering 80% are challenged by fragmented data and legacy infrastructure, and only 12% feel confident using their data to act quickly.
How can banks act on their technology ambitions to enhance their decisioning capability, support value creation through optimized workflows and drive a sustainable competitive advantage? Our panel shared four practical steps.
1. Understand where AI can unlock value
The panel discussed how banks should have a clear view of where AI can materially improve outcomes and where human judgment still remains essential. This requires leaders to have a deep understanding of end to end processes, underlying architecture, and close collaboration with domain experts. Our research shows that 39% of banks are hiring AI and data specialists to build this capability.
With this foundation, institutions can better target investment where it delivers near term impact whilst supporting longer term transformation.
2. Define a clear data strategy
Successful AI implementation hinges on a well-defined banking data strategy. Banks must define what data they need, how it’s governed, and how it supports priority use cases. Architecture, analytics, and business objectives should align around the bank's value creation strategy.
A clear data strategy ensures that investment is focused, scalable, and directly linked to faster and better decision-making.
For more reading on building a data strategy, visit: Good AI without good data? Don’t bank on it
3. Invest in AI governance for scale
Scaling AI safely requires strong governance, yet Moody’s 2026 research found that only 35% of banks are investing in their AI governance frameworks.
Clear standards for explainability, traceability, and accountability are essential across AI in banking to meet regulatory expectations and build trust, enabling AI to be deployed responsibly and consistently across the enterprise.
4. Embrace progress over perfection
The main takeaway from our panelists? Start now. If banks wait for perfect data or fully aligned systems to invest in their technology strategy, they risk falling behind.
Leading banks are taking a pragmatic approach, applying AI in focused areas, improving workflows, and automating routine tasks while strengthening their data foundations over time.
The opportunity is there, the time to move is now
The industry is in a pivotal moment. Banks have a clear opportunity to differentiate and build a competitive edge, and the leading institutions are already working to modernize banking decision-making.
Strategic investment in data, AI, and integration goes beyond a technology upgrade. It transforms decision making across the organization.
The opportunity to differentiate is open but will narrow as adoption accelerates. The most crucial step is to start.
To discuss your next steps, contact us today.
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