Interactive analysis of where agentic AI can drive operating-efficiency and expense-productivity gains across Citi's wholesale businesses, with financial estimates grounded in Citi's disclosed FY2025 figures and external benchmarks.

Wholesale Banking · Operations Technology

Turning Citi's proven AI momentum into measurable operating-efficiency gains.

An opportunity map for agentic AI across Services, Markets and Banking — grounded in Citi's disclosed FY2025 financials and real industry benchmarks.

$1.5–3.0B
est. AI-attributable run-rate at maturity
~3–5%
of the $55.1B expense base
8
prioritized opportunities · 2026–2028
▼ Scroll to explore
The mandate

Drive AI strategy, operating efficiency, and expense productivity.

Citi delivered record FY2025 revenue and positive operating leverage across all five businesses — while committing to keep bending the cost curve. The wholesale franchise, with its scale and process intensity, is where AI compounds fastest.

$0B
FY2025 total operating expense
0%
FY2025 efficiency ratio
target ≈ 60% in 2026
$0B
run-rate savings still to capture (≈$2–2.5B)
0%
2026 RoTCE target (10–11%)
The wholesale franchise

Three businesses, one operations spine.

Services — the engine

Treasury & Trade Solutions (cross-border / international payments, USD clearing) + Securities Services. FY2025 revenue $21.3B · opex $10.8B · cross-border value $416B.

Markets

Fixed Income + Equities (incl. Prime). High-volume, low-latency. FY2025 revenue $22.0B · opex $14.1B.

Banking

Investment Banking (M&A, ECM, DCM) + Corporate Banking. FY2025 revenue $8.2B · opex $4.5B.

Shared spine: onboarding/KYC, reference & client data, trade & payment processing, reconciliations, settlement, controls, and regulatory reporting — where most addressable expense (and AI opportunity) concentrates.

The opportunity map

Eight opportunities, ranked by impact & feasibility.

Each estimate is built bottom-up from a disclosed segment cost pool × an addressable share × a conservative AI savings rate — and anchored to a documented "quantum-leap" benchmark. Click any card to expand.

Live ROI model

Pressure-test every assumption.

Pick an opportunity and adjust the addressable cost pool and AI savings rate. The financial impact and the portfolio total recompute live. Defaults reflect the conservative ranges in the analysis.

$0.2B$6B
0%40%
This opportunity → / yr run-rate
Portfolio run-rate potential (all 8, at maturity)
Not strictly additive (KYC & controls overlap segment rows). AI is one lever within Citi's ~$2–2.5B savings target. Benchmarks suggest these ranges are conservative.
See it in action

Agentic AI on a live wholesale case.

From copilot to autonomous multi-step agent — grounded in Citi data and bank-grade governance. Pick a scenario and run the agent.

Before · manual
After · agentic
Basis

Ready
Prioritization

Impact vs. feasibility.

Bubble size = estimated annual run-rate impact. Hover any bubble for detail. Sequencing weighs ROI certainty, cost-pool size, and data/regulatory dependencies.

Sequencing

A 2026–2028 delivery roadmap.

The basis

Every estimate has a documented quantum leap behind it.