Contact us
Overview

From AI ambition to profit and risk advantage

The 2026 Global AI Report for Banking and Financial Services reveals how AI leaders convert strategy into measurable profit, growth, and risk advantage. Based on global executive research, the findings show that strategic alignment, centralized governance and disciplined operating models separate leaders from laggards. Financial institutions that embed AI across revenue, risk, and compliance functions are widening the performance gap — scaling innovation with regulatory confidence.

Access the playbook

Highlights

FAQ

What defines an AI leader in banking and financial services?
AI leaders in financial services fully align AI strategy with business strategy and measurable profit outcomes. 84.1% of fully aligned institutions report at least a 5% profit uplift from AI. Leaders move beyond experimentation, embedding AI across revenue generation, risk management, and compliance functions — with centralized governance and executive accountability in place.
Why is AI investment accelerating among leading financial institutions?
65.0% of financial services AI leaders report very significant AI investment. More importantly, leaders tie investment to measurable business impact and reinvest based on proven results. Institutions that convert early profit uplift into disciplined reinvestment widen the competitive gap, particularly in personalization, underwriting, fraud prevention, and workflow automation.
What separates leaders in banking from laggards?
Leaders prioritize growth-driving front-office use cases (75.0% vs. 40.3% of laggards), move faster to production (52.5% vs. 23.6%), and adopt centralized governance (65.0% vs. 36.1%). Laggards often remain constrained by fragmented pilots, unclear decision rights, and diffused risk ownership.
Why is centralized governance critical in financial services?
In regulated banking environments, governance enables scale. 65.0% of AI leaders use centralized governance models. Structured oversight ensures consistent model validation, clear risk accountability, and faster supervisory approvals, allowing institutions to innovate without increasing regulatory exposure.
Where is AI creating the most value in banking?
AI delivers the strongest impact when applied to revenue and high-risk workflows. 75.0% of leaders prioritize front-office use cases such as personalization and advisory, while 85.0% redesign back- and mid-office processes end to end. Concentrating AI in growth and risk-sensitive domains drives measurable profit, cost efficiency, and resilience.

Key findings

  • AI leaders align AI initiatives directly to profit pools and P&L outcomes.
  • Centralized governance enables AI to scale safely in regulated environments.
  • Revenue-first use cases in personalization and advisory drive competitive advantage.
  • End-to-end workflow redesign turns AI pilots into enterprise-grade execution.
  • 84.1% of fully aligned financial institutions report ≥5% profit uplift from AI.
  • 75.0% of AI leaders prioritize front-office, revenue-driving use cases.
  • 65.0% follow centralized AI governance to scale with control.
  • 52.5% of leaders move fast vs. 23.6% of laggards.
  • 50.0% of leaders prioritize structured change management vs. 23.6% of laggards.

The AI advantage in financial services belongs to institutions that operationalize it at the core, linking growth, risk, and governance into a single disciplined engine.”

Niraj Singhal
Group Senior Vice President, NTT DATA, Inc.
Insights

 Additional insights for business leaders 

  1. Strategic Profit Alignment
    AI leaders in financial services align AI initiatives directly to profit pools, revenue growth, and risk-adjusted returns, not isolated innovation agendas.

  2. Revenue-First Deployment
    Leaders prioritize front-office use cases such as personalization, advisory augmentation, and dynamic decisioning to drive competitive advantage.

  3. Governance as an Accelerator
    Centralized governance and executive risk ownership enable faster scaling in regulated environments while maintaining supervisory confidence.

  4. End-to-End Workflow Reinvention
    AI leaders redesign underwriting, fraud detection, compliance, and operational workflows to unlock measurable productivity and control gains.

  5. Investment Discipline
    Early profit impact fuels disciplined reinvestment, creating a compounding advantage across growth, efficiency, and resilience.

  6. Actionable Next Steps
    Download the report to benchmark your AI maturity and scaling strategy.

Download

Get your copy of the 2026 Global AI Report: A playbook for AI leaders in banking and financial services

Ready to accelerate your journey to an AI-native state? Get your copy of the playbook and discover how to turn AI strategy into business strategy for growth.
Download the playbook

Copyright © 2024 NTT DATA, Inc.