WeLab and Google team up to bring AI-driven banking to 500 million users across Asia by 2032

WeLab partners with Google to scale AI-first digital banking across Asia Pacific

WeLab and Google have entered an AI-focused partnership to speed up digital banking across the region. The goal: deliver AI-powered financial services to 500 million users by 2032, while strengthening WeLab's position as a technology leader.

The collaboration spans product development, core operations, and marketing efficiency. WeLab will use Google's AI models and agents along with Google Cloud to launch new solutions faster, enter new markets, and stay compliant across jurisdictions.

Why this matters for product leaders

• Speed to value: AI agents will compress research and decision cycles across investment insights, marketing, and service delivery.
• Proven rollout pattern: WeLab already operates on Google Cloud in Indonesia, creating a blueprint for scaling with performance, compliance, and security.
• Measurable impact: WeLab projects a 42.4% efficiency gain over five years based on internal data - a clear target for product and platform OKRs.
• Customer personalization: Agents will support FX, lending, and wealth use cases with instant, personalized recommendations.

Key architecture moves

WeLab will deploy AI agents built on Google Cloud, starting with an internal AI Investment Research Agent. Employees can query it for near-instant insights from trusted external sources combined with WeLab's internal data.

These agents will be built with Gemini models on Vertex AI and Google's Agent Development Kit (ADK) to coordinate tasks reliably and work together. This sets the foundation for customer-facing agents that deliver timely guidance in everyday banking flows.

As these capabilities embed directly into user experiences, WeLab expects faster market entry while aligning with local regulations and responsible AI practices.

What the leaders said

"Our AI vision at WeLab is to enhance the adoption and diffusion of AI technology to amplify human potential… we estimate to deliver a 42.4% efficiency gain in the next five years," said Simon Loong, WeLab Founder and Group CEO. "Partnering with Google lets us deploy tools faster, focus teams on higher-value work, drive cost savings, and deliver more value for customers."

Google highlighted the opportunity for Hong Kong's fintech sector and its support for WeLab's growth with secure, personalized services, marketing acceleration, and regional expansion.

Execution checklist for product teams

• Define agent charters: Start with one internal agent (e.g., research, credit ops, fraud triage) with clear scope and success metrics.
• Data plan: Map trusted external sources and governed internal datasets; set strict permissions and audit trails.
• Model + tooling: Standardize on Vertex AI, Gemini family models, and an agent framework; instrument evaluation and observability from day one.
• Safety + compliance: Configure policy checks, PII redaction, and human-in-the-loop for sensitive decisions; align with local regulations per market.
• Rollout blueprint: Pilot with a small group, measure cycle time and quality lift, then expand; reuse the Indonesia playbook for new regions.
• Cost controls: Track unit economics per interaction; set budgets, caching, and fallback flows for resiliency and spend discipline.

Go-to-market and operations

Beyond product, AI will support channel optimization and creative testing for marketing. Internally, ops teams can reduce manual analysis and improve response times across service and risk functions.

Using Google Cloud as a preferred partner helps standardize infrastructure, security, and compliance while keeping launch cycles short across markets.

Risks to manage

• Quality drift: Establish continuous evaluation, red-teaming, and prompt/version control.
• Explainability: Provide citations for research outputs and clear reasoning steps where possible.
• Data leakage: Enforce strict isolation between environments; use encryption, anonymization, and access policies.
• Latency and reliability: Add graceful degradation and human takeover for high-stakes flows.

What to watch next

• Rollout of customer-facing agents across FX, lending, and wealth.
• Localization and compliance patterns for new markets based on the Indonesia blueprint.
• Evidence of the projected 42.4% efficiency lift in specific workflows and KPIs.

For teams building on similar stacks, explore Vertex AI and Google's agent tooling to evaluate fit and speed up POCs. For a curated view of AI learning paths by leading platforms, see this resource: AI courses sorted by leading AI companies.