Shinhan Financial Group's AI Leap Brings Copilot to Staff and Generative Bankers to Customers
Shinhan's AI plan: standardize M365 Copilot, fund key bets, and launch AI in branches, apps, and risk systems. A clear owner, quick pilots, and KPIs convert strategy into results.
How Shinhan Financial Group Is Building an AI Financial Group: A Playbook for Management
On July 1, Chairman Jin Ok-dong closed the group's mid-year management forum with a clear mandate: move decisively toward an AI-driven financial group. Shinhan is deploying AI across internal operations and customer touchpoints while aligning structure, talent, and capital to support the shift.
The approach is simple: standardize enterprise AI tools, invest where it matters, and bring AI to the front lines of banking, cards, securities, and insurance. Below is what they're doing-and what you can adapt in your own organization.
Enterprise Productivity: Standardize Tools, Scale Behaviors
Shinhan is rolling out a cloud-based collaboration stack with M365 + Copilot across major affiliates (holding, card, securities, life, DS). The goal: boost day-to-day productivity via AI-assisted document creation, data analysis, and meeting summaries.
- Manager takeaway: Pick one enterprise AI suite and commit. Define 5-7 "AI work patterns" (e.g., briefing prep, reporting, research synthesis) and train everyone to use them.
- Stage the rollout: leaders and high-impact teams first, then scale with KPIs tied to time saved and cycle-time reduction.
- Instrument usage data. Review adoption weekly for 90 days and remove friction fast.
Learn about Microsoft 365 Copilot
Capital Allocation: Fund the Future You Want
The group has invested a cumulative 77.5 billion KRW in AI-related companies. AI deals now account for roughly 15% of its strategic investments.
- Manager takeaway: Create an AI investment lane (build, buy, partner). Set thresholds for proofs of value and clear paths from pilots to production.
- Prioritize capabilities that compound: models, data pipelines, security, orchestration, and customer-facing automation.
AI at the Branch and in the App: Meet Customers Where They Are
Shinhan Bank launched an "AI Branch" with a Generative AI banker powered by its own LLM. Customers can open accounts, issue cards, exchange foreign currency, and file reports via interactive counseling-built to work even for seniors and financially vulnerable customers. The AI window expanded to the Sillim-dong branch in May.
Inside the "Shinhan SOL" app, the "AI Investment Mate" analyzes trends, market movements, and related news based on a customer's selected stocks and sectors, delivering insights in card format. It ran internally from December and opened to customers in April after validation and feedback.
- Manager takeaway: Start with high-friction services and make them AI-assisted, then expand. Design for accessibility upfront.
- Run employee-only pilots first, collect feedback, and open to customers after measurable improvements.
Operating Model: Formalize Ownership and Accountability
AI strategy sits under the bank's Digital Innovation Group with three core teams: AI Unit, AI Research Institute, and Data Planning Unit. Managing Director Lim Eun-taek leads the effort to embed AI technology across the bank and tie it directly to customer value.
- Manager takeaway: Centralize AI governance, decentralize delivery. Use a shared platform team with business-aligned pods.
- Publish clear standards for data, model lifecycle, security, and ethics. Review metrics at the executive level.
NIST AI Risk Management Framework
Cards: From Service to Security
Shinhan Card, with one of the largest data footprints in the industry, is pushing to operate as an AI company. Its A&D Research Institute has ~70 AI and data experts working on counseling, abnormal transaction detection, and automation.
"AI-SOLa" supports agents with real-time answers. An AI-driven Fraud Detection System (FDS) blocks unusual authentication attempts early to reduce financial fraud.
- Manager takeaway: Pair service augmentation (agent assist) with risk systems (FDS) to drive both revenue and protection. Share model features and outcomes across teams to improve continuously.
Securities: Advisory at Scale
Shinhan Investment & Securities launched an AI Private Bank (PB) that summarizes and visualizes investment information from verified data, with personalized content recommendations. A robo-advisor for retirement pensions is planned to automate long-term portfolio management.
- Manager takeaway: Use AI to productize advisory workflows-discovery, suitability, proposals, and monitoring-so PBs spend more time with high-value clients.
Insurance: Full-Stack Digitization
Shinhan Life is digitizing end-to-end insurance operations with AI. AI OCR speeds insurance claim processing while detecting forgery or alteration. "SMART+AI" supports personalized product design for sales, and the voice bot "Bori" handles loans, premium payments, and certificate issuance 24/7.
- Manager takeaway: Prioritize claims, underwriting, and sales support. Automate document workflows and add voice interfaces for always-on service.
What You Can Apply This Quarter
- Set a 90-day AI adoption goal for knowledge work: pick 5 use cases and measure time saved, error rates, and throughput.
- Fund two customer-facing pilots that remove friction in onboarding, advice, or claims-and build an internal review loop before launch.
- Stand up an AI governance cadence: risk review, model performance, incident response, and customer impact.
- Train managers on prompt quality, data hygiene, and decision rights. Track adoption weekly and clear blockers fast.
Bottom line: Shinhan's blueprint combines tooling, investment, operating structure, and front-line execution. As one executive put it, AI and digital aren't just cost moves-they reset the customer experience. The firms that operationalize this now will set the next standard for financial services.
