KoreaLife insuranceScale · $100K
Hanwha Life

Arming 20,000 agents, serving millions of policyholders — an agentic service layer for Hanwha Life's distribution machine

Hanwha Life's competitive weapon is distribution — a massive exclusive-agent salesforce selling into a saturated market — which means two frontlines to feed: policyholders who call about policies, and agents who call about products, underwriting and commissions; an agentic layer that serves both in proper honorific Korean lets the distribution machine scale without the back-office scaling with it.

Entry use case
Policy servicing desk (premium, loan, surrender and beneficiary inquiries)
Expected outcome
Resolve routine policy-servicing calls in-conversation and cut agent-support queue times, freeing specialists for underwriting and advice-grade work.
Recommended next step
Dual-track scoping with policy operations and Hanwha Life Financial Services: baseline both servicing and agent-desk volumes, then pilot the policy-servicing line first.
What we understand

Hanwha Life's operating reality

Hanwha Life is one of Korea's largest life insurers, part of Hanwha Group, and spun its exclusive salesforce into Hanwha Life Financial Services — one of Korea's biggest insurance distribution organizations.

Public fact

Korea's life market is saturated and aging: new-business growth is hard-won, shifting economics toward in-force servicing efficiency and health/protection products.

Public fact

Korean insurers face IFRS 17/K-ICS capital regimes that put public focus on CSM quality and cost discipline.

Public fact

A distribution-heavy model generates large internal support volume — product, underwriting-status and commission questions from thousands of agents daily.

Reasoned inference

Policyholder demographics skew older and phone-first; honorific-register voice quality is a hard adoption bar for servicing conversations.

Reasoned inference

Policy-loan and surrender inquiry volume likely spikes with rate moves and economic stress, straining fixed servicing capacity.

Seller hypothesis — validate

Validate with the account team before outreach: Actual servicing and agent-desk contact volumes and current wait times · FSS/cloud compliance route for LLM processing of insurance conversations · Hanwha Group AI initiatives and any mandated internal platforms · Incumbent AICC vendors (Korean telcos sell competing stacks into insurers)

Build vs buy

Why we have a right to win here

Buy-led target

Limited internal ability or appetite to build the core platform — strong candidate for the packaged solution

Evidence: Hanwha Life is a distribution-led insurer, not a technology organization: group-level AI activity exists at Hanwha, but the insurer's own change capacity is vendor-led and committed to IFRS 17-era systems work — honorific-quality conversational AI with FSS-grade governance is a buy, sold with sensitivity to any group-platform preferences.

Why they won't build the full stack: An insurer competing on distribution cannot divert engineering into voice-AI infrastructure; regulatory expectations (FSS outsourcing, consumer-protection scripts) favor a proven, auditable platform with human gates, and the agent-productivity clock rewards capacity this year over a multi-year internal program.

What management is signalling

Korean life insurers operate under the IFRS 17/K-ICS regime, with public reporting focused on CSM growth, capital ratios and cost discipline in a saturated domestic market.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Tie servicing automation directly to reported cost-discipline and CSM-quality narratives — efficiency the market already rewards.

Hanwha Life continues investing in distribution scale (Hanwha Life Financial Services) and overseas expansion as domestic growth saturates.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Pitch the agent help desk as a distribution-productivity investment — the same strategic lane the company is already funding.

What already exists (don't pitch this)
  • Hanwha Life app and web portal for policy lookup
  • Large exclusive agent salesforce via Hanwha Life Financial Services
  • Call centers with IVR routing
  • KakaoTalk notification channels
What customers still can't do end-to-end (pitch this)
  • →Transactional depth — servicing changes and policy loans still require callbacks or agent visits
  • →Instant grounded answers for the agent channel outside desk hours
  • →Honorific-quality voice automation for an older, phone-first base
  • →Proactive claims-status and maturity outreach
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Policy servicing desk
Routine servicing resolved in honorific conversation with documents guided in-flow; wait times drop for the oldest callers.
Premium, policy-loan, surrender and beneficiary questions are the structural volume of a large in-force book in an aging market.
Friction today: Older policyholders navigate IVR trees; routine changes need documents, callbacks or an agent visit.
VoiceKakaoTalkApp chat
Agent-channel product and underwriting help desk
Instant grounded answers for the agent channel around the clock; internal desk capacity refocuses on complex cases.
Agent productivity is the business model; every minute an agent waits on a product or underwriting-status answer is selling time lost.
Friction today: Agents queue on internal lines for product rules, underwriting status and commission questions answered from multiple systems.
VoiceApp chat
Claims intake and status care
Structured compassionate intake any hour with proactive status at every stage; assessments stay human.
Claims moments define insurer trust; status inquiries recur for weeks when updates aren't proactive.
Friction today: FNOL queues behind routine calls; document chases run by mail and callbacks.
VoiceKakaoTalkApp chat
Watch the change

Policy servicing desk (premium, loan, surrender and beneficiary inquiries): today vs the agentic model

Scenario: A 69-year-old policyholder calls about borrowing against her policy before a medical procedure; the agent, in careful honorifics, verifies identity, explains her policy-loan terms and tax implications from the policy system, executes the loan within policy limits and books her assigned human agent for the coverage-review conversation — resolved in one call, no branch visit.
Today
same interaction, two worlds
Agentic layer
Status-call volume
dominant inbound driver
suppressed by proactive updates
Platform capability
Cost per contact
$13.50 median assisted
$1.84 median self-service
Benchmark
QA coverage
1–2% sampled
100% scored
Platform capability
Sources & assumptions
  • · Status-call volume: Process design; measured in pilot
  • · Cost per contact: Gartner customer service cost benchmarks, 2024
  • · QA coverage: Platform capability: every interaction logged and evaluated
  • · Gartner, customer service cost benchmarks (2024): $13.50 median assisted vs $1.84 self-service per contact
  • · McKinsey, digital-first collections research: 20–25% NPL reduction among leaders; up to 40% opex reduction with gen AI
  • · Baymard Institute: ~70% average cart abandonment (meta-analysis)
  • · IAMAI–Kantar via IBEF (2025): 900M+ Indian internet users; 98% consume Indic-language content
  • · LeadSquared and vendor funnel studies: 78% of students choose the first institution to respond (directional, vendor data)
  • · HDI / ITSM operator benchmarks: $15–25 per L1 ticket; 40–60% of L1 volume is resets/status (validate per customer)
  • · Conventional-flow wait times and volumes are typical operator patterns — assumptions to replace with the customer's own baseline
  • · Agentic-flow behaviors (context retention, 100% logging, in-line policy checks) are platform capabilities, not projections
Recommended solution

One integrated stack, opinionated for this account

Channels · Tilicho Labs
VoiceKakaoTalkApp chat

Voice & channel orchestration, telephony, conversational execution, session/state, routing, integration build. Capability coverage validated during implementation.

Intelligence · Google Cloud
Gemini reasoningEnterprise groundingWorkflow agentsMulti-agent orchestrationGoverned actionsEvaluation & analytics
Systems · Hanwha Life
Policy administrationCRMDocument managementProduct rules engineUnderwriting workflowCommission systemsClaims platform

API access to these systems is the critical-path dependency.

Trust & languages
KoreanEnglish

Identity-bound sessions, policy-bounded actions, 100% audit logging, human approvals at defined points, in-tenant intelligence.

Business case

The economics, with your numbers

Addressable monthly interactions700K
Seller assumption — replace in discovery
Current cost per interaction ($)$4.5
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$3.1M
Current operating cost / mo
$19.2M
Modelled gross benefit / yr
0.1 mo
Payback on Scale
1160%
3-yr ROI (modelled)
Automated/assisted interactions per month385K
Modelled AI run-cost per month (usage + cloud, system estimate)$135K
New monthly operating cost$1.6M

All figures are modelling estimates from the labeled inputs above — nothing here is customer-provided yet. The pilot's first job is replacing these assumptions with Hanwha Life's measured baseline. Package price covers implementation only; recurring usage billed separately.

Recommended package

Scale — $100K implementation

Scale · $100K · A multi-channel production deployment10–14 weeks to production across priority workflows

Why this package for Hanwha Life: Policyholder servicing plus the agent-channel help desk are two distinct, well-bounded workflows over shared policy-admin integrations — natural Scale scope for a major insurer.

Included
  • 4–6 channels
  • 2–3 priority workflows
  • Multiple enterprise integrations
  • API credential & security setup
  • Advanced orchestration
  • Multilingual support
  • Agent Assist / human escalation
  • Production analytics
  • Expansion roadmap
Not included
  • ✕Usage & consumption (billed separately)
  • ✕Enterprise-wide governance build-out
  • ✕Multi-BU rollout
Recurring costs (separate from the package)

Packages cover implementation and integration only. Recurring costs are billed separately: Tilicho Labs platform usage (~$0.15/call-min indicative, usage only), Google Cloud consumption, telephony/carrier charges, managed operations, and support & optimization. No package includes unlimited usage.

Customer resources required
  • · API access + credentials for: Policy administration, CRM, Document management
  • · A named business owner for policy servicing desk (premium, loan, surrender and beneficiary inquiries)
  • · Security review counterpart and policy sign-off (Policy administration scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“In a saturated market the winners are decided by distribution productivity and servicing cost; an agentic layer that feeds both frontlines is a structural advantage competitors staffing call centers cannot match.”

CIO / CTO

“A governed agent platform over policy admin, underwriting and commission systems gives one conversational layer for policyholders and the salesforce — architected to FSS cloud and outsourcing expectations from day one.”

COO

“Servicing demand rises with the age of the book while Korean service labor grows scarcer and costlier; elastic honorific-quality capacity is the only model that tracks both curves.”

Head of Distribution (Hanwha Life Financial Services)

“Your agents lose selling hours to internal queues; instant product and underwriting-status answers at any hour is the cheapest productivity lever available to a 20,000-agent force.”

Chief Risk / Compliance Officer

“Underwriting and claims decisions stay human; consumer-protection scripts are enforced verbatim, every conversation logged and scored — stronger conduct evidence than sampled QA under FSS scrutiny.”

CFO / Procurement

“Under IFRS 17, servicing cost discipline flows straight to CSM quality; the pilot measures cost per servicing contact and agent-desk wait times against your own baseline, usage billed on consumption.”

Outreach

Pre-built offer emails for Hanwha Life

Written from this account's own research — the strategic signal, the capability gap, the entry workflow, and the modelled economics — not a mail-merge template. Pick the moment and the persona, edit anything, then copy or open in your mail client.

Moment in the deal
Cold outreach — no prior conversation
Who it's addressed to
Cares about: The workflow itself and its daily failure modes
Register
Length
Draft — edit freely before sending
Open in mail client

Customer-safe by construction: drafts are composed only from customer-facing fields. Account tier, build-vs-buy classification, priority score, internal routing, and partner-commercial detail are not inputs to the composer, so they cannot appear in a draft. Money figures are always framed as modelled from the customer's own volumes. Read before sending — you own what goes out.

The pursuit

Tier 3 — longer-term / partner-led

Why this tier

Korea's second-tier life major runs one of the country's largest agent-distribution networks (via Hanwha Life Financial Services) and a big in-force book in a saturated, aging market — heavy policy-servicing and agent-support volume with structural cost pressure.

Recommended next step

Dual-track scoping with policy operations and Hanwha Life Financial Services: baseline both servicing and agent-desk volumes, then pilot the policy-servicing line first.

Entry: Policy servicing desk (premium, loan, surrender and beneficiary inquiries) · Scale package · 10–14 weeks to production across priority workflows. Human fallback throughout; success thresholds agreed before build.

Start the pursuit

Research-based priority-account universe assembled from public information, market scale, communication volume, and solution fit. This is NOT an authoritative list of top Google Cloud customers; existing Google Cloud relationships are noted only where publicly reported. Validate every account with the account team before outreach.