The retail banking industry is “fertile ground” for AI and AI agents, with potential additional profit of >$370 billion/year (>30% higher than baseline).
However, only 5% of businesses create value at scale from AI; 60% have not, hindered by legacy tech, culture, and compliance.
Bank revenue (2024–2029) forecast: only 2–4% growth/year.
2025 savings revenue: projected drop of nearly 35% vs. 2024 as interest rates fall.
Marketing cost/customer: increased >20% (2023–2024).
Cost/Income Ratio: Traditional banks are stuck at >60%; well-operated digital banks are at ~35%.
AI agents’ value share: 17% in 2025, expected to reach 29% by 2028, shifting AI from “passive advisor” to “operator.”
Early adoption case (Asian bank): Automated debt reminders cut costs by 30–40% and increased debt recovery rates by double digits.
Early adoption case (Virtual assistant): Increased pre-approved applications by 75%.
2024 Industry Snapshot: $2.9 trillion revenue, $900 billion pre-tax profit.
2030 Baseline Scenario: $3.8 trillion revenue, $1 trillion profit.
2030 AI-First Scenario: $3.1 trillion revenue, $1.3 trillion profit; cost/income ratio could fall to ~50%.
AI-first impact: Reduces structural costs by 30–40%, but reinvestment may cut potential revenue by 15–20% to gain market share.
Profit uplift: A typical bank’s profit could increase by ≥30% with AI at scale. Asia is leading the pace.
“AI leaders” value loop: 2028 value expected to be 3–7 times higher due to increased investment.
Transformation roadmap: Three phases (Deploy–Reshape–Invent), AI-first operations, flexible data/tech platform, and using R&C as a competitive advantage.
📌 BCG Report Key Takeaway: The opportunity for AI agents is open, driven by pressures (2-4% revenue growth, ~35% drop in 2025 savings revenue, 20% rise in marketing costs). AI-first can cut costs (30–40%), boost industry profit ($900B to $1.3T by 2030), and lower the cost/income ratio to ~50% (proven by cases cutting collection costs 30-40% and boosting pre-approvals >75%).
