ThailandBankingScale · $100K
Kasikornbank (KBank)

K PLUS put the bank in 20 million pockets; agentic service puts a banker in every conversation

Extend KBank's digital dominance from transactions to conversations: Thai-first agentic collections, SME servicing, and K PLUS support grounded in core systems, running on the cloud KBTG already builds on.

Entry use case
Retail & SME early-delinquency collections
Expected outcome
100% attempted day-1 coverage on early buckets with policy-bounded offers, measured against dialer-cohort roll rates
Recommended next step
Joint session with KBTG on a Thai-region reference architecture, then a control-group collections pilot on one retail portfolio.
What we understand

Kasikornbank (KBank)'s operating reality

KBank is one of Thailand's largest banks and its digital leader: the K PLUS mobile app is among the country's most-used banking apps with a base publicly reported around 20M+ users.

Public fact

KBTG, KBank's technology arm, is a published Google Cloud customer (the MAKE by KBank app case study) and publicly partners with AI Singapore and Google Research on Thai LLM development under Project SEALD.

Public fact

KBTG has publicly welcomed the new Google Cloud Thailand region for latency, cost, and Bank of Thailand compliance alignment.

Public fact

KBank's large SME lending franchise carries structurally elevated credit-cost exposure; collections effectiveness on small-ticket portfolios is an ongoing P&L lever.

Reasoned inference

LINE is the dominant conversational channel in Thailand; a LINE-first agentic layer would meet both retail and SME customers where they already talk.

Reasoned inference

A shared conversational platform could also serve regional ambitions (KBank's Vietnam and Indonesia presence) from one governance frame.

Seller hypothesis — validate

KBTG is a published Google Cloud customer (MAKE by KBank case study), publicly partners with Google Research on Thai LLMs (Project SEALD), and has publicly endorsed the Google Cloud Thailand region for BOT-aligned data residency.

Publicly reported Google Cloud relevance

Validate with the account team before outreach: Which portfolios KBank considers pilot-safe for agentic collections · KBTG's internal conversational-AI roadmap and where Tilicho complements it · LINE Official Account consent posture for outbound collections contact

Build vs buy

Why we have a right to win here

Partner-led target

Technically capable but needs industry workflows, integration, acceleration, or managed operations

Evidence: KBTG is one of the region's most capable bank technology arms, but its pattern is building customer-facing apps on bought platforms — it is a published Google Cloud customer, and its Thai LLM work with Google Research (Project SEALD) is research collaboration, not a service-stack build. Platforms are procured; KBTG integrates.

Why they won't build the full stack: KBank's differentiation lives in K PLUS and its credit franchise, not contact-center infrastructure. With BOT's governance bar and asset quality under active management, a hardened, auditable platform with KBTG owning integration beats a multi-year internal build.

What management is signalling

Management has publicly guided on elevated credit costs and balance-sheet clean-up, with asset-quality management a recurring theme in results briefings.

Reported factFY2024 results briefing · Jan 2025

GTM implication: Collections workflows attack the exact metric management is guiding the market on — lead with roll-rate economics on control cohorts.

What already exists (don't pitch this)
  • K PLUS app with roughly 20M+ users
  • KBTG engineering capacity and Google Cloud footprint
  • LINE-based customer engagement at scale
  • Established dialer-based collections operations
What customers still can't do end-to-end (pitch this)
  • →Policy-bounded collections negotiation with automatic PTP follow-through
  • →In-conversation actions executed in core and card systems
  • →Production-grade Thai voice automation
  • →100% interaction QA instead of sampled review
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Early-delinquency collections
Full attempted coverage on LINE/voice in Thai, offers from the approved matrix, automatic PTP follow-up, hardship routed to humans.
Small-ticket retail and SME buckets are exactly where human collection economics break and roll rates compound.
Friction today: Dialer capacity limits day-1 coverage; offers vary by collector; PTPs lack systematic follow-through.
LINEVoiceSMS
K PLUS service & dispute support
Grounded, in-conversation resolution with warm handoff; every interaction scored for quality.
At 20M+ users, even a small per-user contact rate is an enormous absolute volume; app-adjacent questions should resolve in-channel.
Friction today: Call center absorbs transfer, PromptPay, and dispute questions the app almost answers.
In-app chatLINEVoice
SME lending servicing & document chase
Proactive status, document checklists tracked conversationally, RM time returned to origination.
SME relationship managers spend selling time chasing documents and answering status questions.
Friction today: Application status and covenant queries flow through RMs by phone.
LINEVoiceEmail
Watch the change

Retail & SME early-delinquency collections: today vs the agentic model

Scenario: A small restaurant owner 8 days past due on a K SME loan gets a Thai LINE message, agrees a split payment from the approved matrix, and pays via QR in the same thread.
Today
same interaction, two worlds
Agentic layer
Day-1 contact coverage
capacity-limited
100% attempted, multi-channel
Platform capability
Roll-rate improvement
—
measured in pilot
Benchmark
Cost per contact
$13.50 median assisted
$1.84 median self-service
Benchmark
QA coverage
1–2% sampled
100% scored
Platform capability
Sources & assumptions
  • · Day-1 contact coverage: Coverage is a platform capability; contact success measured in pilot
  • · Roll-rate improvement: McKinsey: 20–25% NPL reduction among digital-first collections leaders
  • · 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
LINEVoiceSMSIn-app chatEmail

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 · Kasikornbank (KBank)
Collections platformCore bankingOffer matrixCard/dispute systemsCRMLoan originationDocument management

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

Trust & languages
ThaiEnglish

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 interactions4.0M
Seller assumption — replace in discovery
Current cost per interaction ($)$1.0
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$4.0M
Current operating cost / mo
$17.2M
Modelled gross benefit / yr
0.1 mo
Payback on Scale
185%
3-yr ROI (modelled)
Automated/assisted interactions per month2.2M
Modelled AI run-cost per month (usage + cloud, system estimate)$770K
New monthly operating cost$2.6M

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 Kasikornbank (KBank)'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 Kasikornbank (KBank): Collections plus K PLUS service and SME workflows across LINE, voice, and in-app channels — with KBTG as a capable integration counterpart — fit a multi-workflow Scale deployment immediately.

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: Collections platform, Core banking, Offer matrix
  • · A named business owner for retail & sme early-delinquency collections
  • · Security review counterpart and policy sign-off (Collections platform scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“KBank won Thai digital banking by moving first. Agentic service is the next first-mover window — and your KBTG-Google foundation means you can take it faster than any peer.”

CIO / CTO

“KBTG already builds on Google Cloud and co-develops Thai LLM capability with Google Research. Gemini Enterprise agents on the new Thai region extend that stack — BOT-aligned residency included.”

COO

“Collections coverage stops being a dialer-capacity problem, and K PLUS support absorbs volume elastically — your people move to the judgment work in both.”

Head of Retail Credit & Collections

“Every early-bucket account contacted on day one, every promise followed up automatically, every conversation scored against your playbook — with roll-rate impact measured on control cohorts.”

Chief Risk / Compliance Officer

“BOT market-conduct rules and Thai PDPA consent become enforced configuration: outreach windows, offer bounds, and full audit trails on 100% of interactions.”

CFO / Procurement

“Credit costs and service costs are your two heaviest operational lines; this attacks both with one platform, priced on implementation plus usage — not seats.”

Outreach

Pre-built offer emails for Kasikornbank (KBank)

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 1 — immediate strategic pursuit

Why this tier

Thailand's digital-banking leader with K PLUS at ~20M+ users, a huge SME lending franchise, and KBTG already a public Google Cloud customer working with Google Research on Thai LLMs — the warmest large-bank door in the country.

30 / 60 / 90-day plan
  • Day 0–30: Joint session with KBTG on a Thai-region reference architecture, then a control-group collections pilot on one retail portfolio.; confirm sponsor and baseline data access; validate: Which portfolios KBank considers pilot-safe for agentic collections
  • Day 31–60: architecture & security review with the platform team; Tilicho Labs scoping on LINE + Voice; pilot scope signed
  • Day 61–90: Scale package kickoff; retail & sme early-delinquency collections pilot in build; success thresholds locked with the Head of Retail Credit & Collections
Recommended next step

Joint session with KBTG on a Thai-region reference architecture, then a control-group collections pilot on one retail portfolio.

Entry: Retail & SME early-delinquency collections · 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.