KoreaLife insuranceScale · $100K
Samsung Life

Korea's largest in-force book, served one honorific conversation at a time — agentic policy servicing for Samsung Life

Samsung Life's scale means every servicing inefficiency is multiplied across the country's largest policyholder base; an agentic layer that resolves premium, policy-loan and claims-status conversations in careful honorific Korean — and feeds its huge agent channel instant product and underwriting answers — converts the industry's biggest servicing burden into its biggest automation dividend.

Entry use case
Policy servicing desk (premium, policy-loan, surrender and beneficiary inquiries)
Expected outcome
Resolve routine policy servicing in-conversation for an older phone-first base, cutting per-contact cost while claims and underwriting stay human.
Recommended next step
Dual-track scoping with policy operations and distribution leadership: baseline servicing and agent-desk volumes, then pilot the policy-servicing line with honorific voice-quality acceptance testing.
What we understand

Samsung Life's operating reality

Samsung Life is Korea's largest life insurer by assets and in-force business, a core Samsung Group financial affiliate with one of the country's largest exclusive-agent salesforces.

Public fact

Korea's life market is saturated and aging fastest in the OECD, shifting industry economics from new-business growth to in-force servicing efficiency and health-protection products.

Public fact

IFRS 17 and K-ICS regimes focus investor attention on CSM quality, capital ratios and cost discipline across Korean insurers.

Public fact

An older policyholder base is phone-first and honorific-sensitive: voice quality is the adoption bar for any servicing automation.

Reasoned inference

Policy-loan and surrender inquiries likely swing with rate moves and household-economy stress, creating demand spikes fixed staffing cannot track.

Seller hypothesis — validate

The exclusive-agent channel generates large internal support volume — product rules, underwriting status and commission questions daily.

Reasoned inference

Validate with the account team before outreach: Actual servicing and agent-desk volumes and wait times · Samsung Group AI-platform dynamics (Samsung SDS role, any group-mandated stacks) · FSS/cloud outsourcing route for insurance-conversation processing · Incumbent AICC vendors and contract windows

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: Samsung Life is a distribution-and-capital business whose IT runs through group vendors, with no public program for conversational-AI infrastructure; honorific-grade voice automation with FSS-auditable governance is a buy — navigated with sensitivity to Samsung Group affiliate preferences in procurement.

Why they won't build the full stack: An insurer managing IFRS 17 capital and the industry's largest in-force book has no strategic case for building voice-AI infrastructure; regulatory expectations favor a proven auditable platform with human gates, and the aging-book servicing curve rewards capacity deployed this year.

What management is signalling

Korean life insurers operate under IFRS 17/K-ICS with investor focus on CSM growth, capital ratios and cost discipline in a saturated, aging domestic market.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Tie servicing automation to CSM-quality and cost-discipline narratives — efficiency the market already scores Samsung Life on.

Samsung Life's investor story emphasizes shareholder returns and health-protection product growth as domestic saturation limits top-line expansion.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Position in-force servicing efficiency as the earnings lever that funds the protection-product pivot.

What already exists (don't pitch this)
  • Samsung Life app and web portal for policy lookup
  • Korea's largest exclusive-agent salesforce
  • Call centers with IVR routing
  • KakaoTalk notification channels
What customers still can't do end-to-end (pitch this)
  • →Transactional servicing depth — changes still need callbacks or agent visits
  • →Honorific-quality voice automation for the oldest customer base in Korean insurance
  • →Around-the-clock agent-channel support
  • →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; oldest callers get the shortest waits.
The largest in-force book in Korea generates the largest servicing volume — premiums, policy loans, surrenders, beneficiary changes.
Friction today: Older callers navigate IVR trees; routine changes require documents, callbacks or agent visits; wait times hit the most loyal customers hardest.
VoiceKakaoTalkApp chat
Agent-channel product and underwriting help desk
Instant grounded answers for the agent channel around the clock; internal desks refocus on complex cases.
Tens of thousands of exclusive agents lose selling time queuing for product and underwriting-status answers.
Friction today: Internal desks run business hours; product rules span systems; commission questions escalate slowly.
VoiceApp chat
Claims intake and status care
Compassionate structured intake any hour, proactive status at every stage; assessment and settlement decisions stay human.
Claims moments define insurer trust, and status inquiries recur for weeks when updates are not proactive.
Friction today: FNOL queues behind routine calls; document chases run by mail and callbacks; status calls dominate repeat volume.
VoiceKakaoTalkApp chat
Watch the change

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

Scenario: A 74-year-old policyholder calls about surrendering a policy to cover medical costs; the agent, in careful honorifics, verifies identity, explains the surrender value and the policy-loan alternative from the policy system, executes the loan she prefers within limits and books her assigned human agent for a coverage review — need met without losing the protection she has held for thirty years.
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 · Samsung 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 interactions1.2M
Seller assumption — replace in discovery
Current cost per interaction ($)$4.5
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$5.4M
Current operating cost / mo
$32.9M
Modelled gross benefit / yr
0.0 mo
Payback on Scale
1170%
3-yr ROI (modelled)
Automated/assisted interactions per month660K
Modelled AI run-cost per month (usage + cloud, system estimate)$231K
New monthly operating cost$2.7M

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 Samsung 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 Samsung Life: Policy servicing plus the agent-channel help desk are two bounded, high-volume workflows over shared policy-admin integrations — Scale scope with expansion into claims-status care once honorific voice quality is proven.

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, policy-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 market growing old faster than any in the OECD, the winner is whoever serves the largest aging book at the lowest cost without breaking trust; scale makes Samsung Life's automation dividend the industry's largest.”

CIO / CTO

“A governed agent platform over policy admin and underwriting systems gives one conversational layer for policyholders and the agent channel — architected to FSS outsourcing rules, benchmarkable against any group-internal alternative.”

COO

“Servicing demand rises with the age of the book while service labor grows scarcer; elastic honorific-quality capacity is the only model tracking both curves at your scale.”

Head of Distribution

“Your agents' selling hours leak into internal queues daily; instant product and underwriting-status answers at any hour is the cheapest productivity lever available to Korea's largest salesforce.”

Chief Risk / Compliance Officer

“Underwriting and claims decisions remain human; consumer-protection scripts run verbatim with 100% logging — conduct evidence at a depth sampled QA cannot reach, built for FSS review.”

CFO / Procurement

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

Outreach

Pre-built offer emails for Samsung 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 2 — high-potential incubation

Why this tier

Korea's largest life insurer holds the biggest in-force book in a saturated, rapidly-aging market — millions of policyholders skewing older and phone-first, a vast exclusive-agent channel, and IFRS 17-era investor scrutiny on cost discipline and CSM quality.

Recommended next step

Dual-track scoping with policy operations and distribution leadership: baseline servicing and agent-desk volumes, then pilot the policy-servicing line with honorific voice-quality acceptance testing.

Entry: Policy servicing desk (premium, policy-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.