Hong KongInsurance / retirement (MPF)Scale · $100K
Manulife Hong Kong

Serving Hong Kong's retirement savings at scale — agentic MPF and policy servicing for Manulife's million-member base

Manulife touches more Hong Kong retirement savers than any other provider through MPF, layered on a large life and health book — a service estate where contribution questions, fund-switch requests, claims and the eMPF transition generate trilingual contact volume that agency and hotline capacity absorb expensively; an agentic frontline that resolves member and policyholder questions natively in Cantonese turns scale from a service liability into a retention advantage as the MPF market reshuffles.

Entry use case
MPF member servicing desk (contributions, fund switches, consolidation, eMPF transition)
Expected outcome
Resolve routine MPF member inquiries in-conversation and guide members through the eMPF transition, cutting hotline queues and protecting scheme retention.
Recommended next step
Workshop with the retirement business and operations leadership: baseline MPF hotline volumes and transition-driven contact forecasts, then scope a Scale pilot on the member servicing desk.
What we understand

Manulife Hong Kong's operating reality

Manulife is the largest MPF scheme provider in Hong Kong by assets and members, alongside a major life, health and wealth insurance business.

Public fact

Hong Kong's eMPF platform — the government-driven centralization of MPF scheme administration — is progressively onboarding providers, resetting fee structures and administration economics across the industry.

Public fact

MPF servicing is inherently high-volume and low-margin: contribution records, employer changes, fund switches and consolidation requests from millions of members.

Reasoned inference

The eMPF transition itself generates a wave of member confusion and status questions that providers must absorb while their per-member economics compress.

Reasoned inference

Manulife globally has publicly invested in generative AI for advisor and service productivity, giving the local business air cover for AI-led service transformation.

Public fact

Members skew across every demographic in Hong Kong's workforce; Cantonese-first phone service remains the binding channel for older members and small-employer HR contacts.

Seller hypothesis — validate

Validate with the account team before outreach: eMPF onboarding timeline for Manulife schemes and the projected contact wave · Actual MPF hotline volumes and cost per member contact · Global Manulife AI program scope and whether Asia service automation is already claimed · MPFA constraints on automated member conversations

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: Manulife's global GenAI investment targets advisor productivity and internal tooling, not Cantonese contact-center voice infrastructure; the Hong Kong business runs on vendor-led administration and channel systems, and trilingual regulated-conversation AI is a capability it will buy and govern locally.

Why they won't build the full stack: Local engineering capacity is consumed by the eMPF migration and policy-system change; building voice AI for MPF servicing in-house during the industry's biggest administration reshuffle is unfundable, while a bought platform with human gates delivers retention-grade service through the transition window that decides market share.

What management is signalling

Hong Kong's eMPF platform migration is progressively onboarding providers industry-wide, compressing administration fees and resetting MPF servicing economics.

Reported factpublic MPFA / industry disclosures · 2025-2026

GTM implication: Every provider faces the same margin squeeze; sell the servicing frontline as the market leader's way to win the reshuffle on service quality at lower cost.

Manulife has publicly emphasized generative-AI adoption for productivity across its global operations.

Reported factrecent investor communications · 2025

GTM implication: AI-led service transformation in Hong Kong is on-message with global strategy — position as local execution of a stated group direction.

What already exists (don't pitch this)
  • Manulife HK app and MPF member web portal
  • Hotline servicing in Cantonese, English and Mandarin
  • Agency and broker channels handling informal servicing
  • Global GenAI productivity investments announced publicly
What customers still can't do end-to-end (pitch this)
  • →Transactional depth — fund switches, consolidations and record fixes still queue for humans
  • →Proactive eMPF transition guidance at member scale
  • →Patient trilingual voice automation for older members and small-employer HR
  • →Cross-channel context between agents, hotline, app and eMPF
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
MPF member servicing desk
Routine member servicing resolved in-conversation with fund switches executed within policy; hotline queues decompress.
Contribution, balance, fund-switch and consolidation questions from millions of members are the structural volume of the retirement business.
Friction today: Members queue on hotlines for record-level questions; employer HR contacts chase contribution issues by phone and fax-era processes.
VoiceApp chatWeb
eMPF transition guidance and outreach
Proactive, plain-language transition guidance in the member's language; retention through the migration measured.
The industry migration confuses members exactly when switching providers becomes easiest — a retention moment disguised as an admin project.
Friction today: Transition letters go unread; confused members flood hotlines or disengage entirely.
VoiceSMSWhatsApp
Insurance policy servicing and claims status
Routine servicing and proactive claims status in-conversation; human adjusters on every assessment.
The life and health book generates the same servicing tide as every major insurer — premiums, beneficiaries, claims status.
Friction today: Servicing routes through agents and hotlines; claims status drives repeat calls.
VoiceApp chat
Watch the change

MPF member servicing desk (contributions, fund switches, consolidation, eMPF transition): today vs the agentic model

Scenario: A 58-year-old member calls about consolidating three old MPF accounts before retirement; the agent, in patient Cantonese, verifies identity, retrieves her accounts, explains the consolidation steps and eMPF changes in plain language, initiates the transfer within policy and books a retirement-planning call with a licensed advisor for the drawdown question.
Today
same interaction, two worlds
Agentic layer
First-contact resolution
deferred via tickets
in-conversation actions
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
  • · First-contact resolution: Process design: agent acts in systems of record
  • · 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
VoiceApp chatWebSMSWhatsApp

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 · Manulife Hong Kong
MPF administration / eMPFMember recordsCRMeMPF platformPolicy administrationClaims platform

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

Trust & languages
CantoneseEnglishMandarin

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 interactions600K
Seller assumption — replace in discovery
Current cost per interaction ($)$5.5
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$3.3M
Current operating cost / mo
$20.4M
Modelled gross benefit / yr
0.1 mo
Payback on Scale
1435%
3-yr ROI (modelled)
Automated/assisted interactions per month330K
Modelled AI run-cost per month (usage + cloud, system estimate)$115K
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 Manulife Hong Kong'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 Manulife Hong Kong: MPF member servicing plus insurance policy servicing and claims-status care are multi-workflow scope across distinct systems — the integration breadth Scale is designed for.

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: MPF administration / eMPF, Member records, CRM
  • · A named business owner for mpf member servicing desk (contributions, fund switches, consolidation, empf transition)
  • · Security review counterpart and policy sign-off (MPF administration / eMPF scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“The eMPF era compresses administration economics for every provider; an agentic servicing frontline is how the market leader defends share with better service at lower cost while rivals absorb the same squeeze with headcount.”

CIO / CTO

“A governed agent layer over MPF administration and policy systems rides the eMPF transition instead of fighting it — bounded integrations, full auditability, and a conversation layer that outlasts the plumbing change beneath it.”

COO

“Transition-driven contact waves plus structural member volume exceed any hotline staffing plan; elastic trilingual capacity absorbs both without carrying peak cost year-round.”

Head of Retirement / MPF Business

“Members can switch providers more easily than ever; the provider whose service answers in seconds in Cantonese keeps the assets — that's the retention math this deployment measures.”

Chief Risk / Compliance Officer

“MPFA- and PDPO-aligned deployment: human gates on advice moments, approved-language enforcement, 100% logging — regulated-conversation evidence your audit team can inspect.”

CFO / Procurement

“Per-member servicing cost is the number the eMPF era punishes; the pilot measures cost per resolved member contact against your baseline in one quarter.”

Outreach

Pre-built offer emails for Manulife Hong Kong

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

Hong Kong's largest MPF provider plus a major life and health insurer — millions of scheme members and policyholders generating structural servicing volume, right as the industry-wide eMPF platform migration resets retirement-servicing economics.

Recommended next step

Workshop with the retirement business and operations leadership: baseline MPF hotline volumes and transition-driven contact forecasts, then scope a Scale pilot on the member servicing desk.

Entry: MPF member servicing desk (contributions, fund switches, consolidation, eMPF transition) · 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.