Hanwha Life's Global AI Strategy Reimagines Customer Experience in Insurance

Hanwha Life's AI Playbook for Insurance Leaders

Hanwha Life Insurance is building AI into the core of its business to deliver better service, smarter risk decisions, and stronger economics. Dedicated teams-an AI Room, the Hanwha Life AI Research Institute, and the Hanwha AI Center (HAC) in San Francisco-turn research into production systems that serve customers and the business.

The strategy is simple: combine AI's intelligence with finance's purpose-serve customers well. The outcome is a richer experience, faster decisions, and capabilities that scale.

From Research to Deployment

Since 2014, Hanwha Life has invested in AI, forming the first big data task force among Korean insurers. The team introduced machine learning and deep learning across underwriting, claims, and service.

A machine learning risk assessment model helped launch products suited for elderly customers by enabling more granular risk views. Integrated risk scoring and AI-driven auto-screening improved payment accuracy and sped up low-risk cases. The company also brought deep learning-based OCR into insurance workflows-accelerating document intake and reducing manual errors.

For context on OCR technology and benchmarks, see NIST's overview of OCR research and evaluation programs: NIST OCR.

AI Contact Center (AICC): Faster Responses, Consistent Quality

The AICC uses natural language processing, voice recognition, and text analytics to streamline customer calls. AI agents reduce waiting times while keeping answers consistent.

New counselors train through mock sessions with AI, speeding up proficiency. AI also supports end-to-end sales monitoring, improving customer convenience and frontline productivity.

Three Specialized AI Pillars

• AI Room: Engineers embed AI into financial workflows and ship production-grade services and products.
• Hanwha Life AI Research Institute: Studies AI's impact across the economy, policy, and society to set strategy and inform market moves.
• Hanwha AI Center (HAC), San Francisco: A global base that partners with the local AI ecosystem to develop and commercialize technology, enable open innovation, and incubate new businesses-building global competitiveness.

What This Means for Insurers

• Start with outcomes: Prioritize use cases that change customer experience and cost: claims triage, OCR-based document intake, contact center automation, and risk scoring for underserved groups.
• Build a dual-track structure: A production-focused AI engineering team plus a research function that scans policy, tech, and market shifts.
• Modernize the contact center: Use NLP and speech tech to cut wait times, improve first-contact resolution, and automate QA coverage.
• Govern models: Establish clear policies for data quality, drift monitoring, fairness, and audit trails. Reference frameworks such as the NIST AI Risk Management Framework.
• Get your data right: Create high-quality labeled datasets (claims docs, call transcripts), manage consent, and secure PII. Track OCR accuracy and exception handling end to end.
• Invest in people: Train frontline staff with AI-driven simulators and embed coaching into daily workflows. Use AI to support sales compliance without adding friction.
• Scout globally: A small outpost near technology hubs (like HAC in San Francisco) helps validate partners early and bring proven solutions home.

Next Steps

Pick one high-impact workflow (e.g., document intake or claims triage), define success metrics, and run a 90-day pilot with strong governance. Scale only after the metrics hold in production.

If you're mapping skills and tools for your team, this curated list can help: AI tools for finance.