Woori Puts AI in Charge of 2026 Strategy, Rolling Out 344 Use Cases

Woori puts AI at the core, rolling out 344 use cases across banking and affiliates. The plan ties productivity with consumer protection and targets 20% growth from non-banks.

Woori puts AI at the center of its digital finance push

Woori Financial Group is repositioning itself as an AI-first financial platform, making the technology the core operating logic for growth and competitiveness. The focus is clear: shift from balance sheet expansion to technology-led productivity across the group.

At the group's 2026 management strategy workshop in Seoul, Chairman Yim Jong-yong said the past three years built the foundation - full privatization, stronger capital ratios, and a completed portfolio spanning banking, insurance, and securities. The next phase ties productive and inclusive finance with a group-wide AI transformation (AX) to generate deeper synergies.

AX as operating logic: 344 AI use cases

Central to the plan is AX. Woori will roll out 344 AI use cases by next year - 200 in banking and 144 across non-bank affiliates. AI will sit inside management decisions, daily operations, and risk control, not as add-ons but as default workflows. As Yim put it, leadership in finance will be determined by how quickly and credibly organizations adopt AI-driven decision-making.

Productive finance meets scale and inclusion

Woori is leaning into its strength in corporate finance while wiring AI through banking, insurance, and securities. The group said it will "strengthen synergies" across units, seeking to achieve a growth of 20 percent generated by non-bank businesses.

Consumer protection and inclusive finance are positioned alongside AX, with the group emphasizing it aims to be both technologically advanced and socially credible. That framing matters: growth with controls, access, and trust built in from the start.

What executives should take from this

Treat AI as operating logic, not a side project. Budget, governance, and P&L ownership should reflect that.
Run a portfolio of use cases with clear business owners. Track time-to-production, lift against KPIs, and model monitoring performance.
Invest in data quality and access. Shared metadata, lineage, and standardized features reduce cycle times across affiliates.
Tighten controls. Build on model risk management, bias testing, and human-in-the-loop review. The NIST AI Risk Management Framework and MAS FEAT principles are useful anchors.
Use AI to unlock cross-entity wins. Pricing, underwriting, servicing, and distribution can benefit when banking, insurance, and securities share signals and incentives.
Upskill fast. Stand up an AI excellence hub, and put frontline training on a schedule, not a wish list.

Signals to watch

Number of AI use cases live in production, not pilots.
The share of decisions materially influenced by AI in credit, risk, and service.
Drift, fairness, and stability metrics reported to risk committees.
Cost-to-income and loss rates as AI scales, plus the portion of growth coming from non-bank units.

Why this matters for banking, insurance, and securities

This is a clear shift from project-level experimentation to enterprise-wide adoption. If Woori executes on AX while holding the line on consumer protection and inclusion, it sets a practical template for financial groups that need growth without losing credibility with regulators or customers.