IndiaCredit cards — monoline issuerScale · $100K
SBI Card

Two crore cardholders, every due date covered: collections and card service in the cardholder's own language

Deploy an agentic layer across SBI Card's early-bucket collections and high-volume service line, giving a mass-market national base day-1 due-date coverage and grounded card servicing at a cost per contact the current model cannot match.

Entry use case
Pre-due & early-bucket collections outreach
Expected outcome
Improved early-bucket roll rates and full pre-due coverage within RBI conduct and TRAI window norms.
Recommended next step
Propose a bucket-0/1 pilot on one portfolio segment: conversational due-date coverage for 60 days, roll-rate delta versus dialer-only control.
What we understand

SBI Card's operating reality

India's largest pure-play credit-card issuer (SBI-promoted, listed), with a mass-market portfolio spanning deep into tier-2/3 India.

Public fact

Industry-wide unsecured-credit stress in FY24–FY26 pushed credit costs up across card issuers — collections effectiveness is a publicly discussed earnings driver for SBI Card.

Public fact

RBI recovery-agent conduct norms and TRAI DND rules tightly constrain human collections calling; digital-first conduct-perfect outreach is a structural advantage.

Public fact

A mass-market national base likely calls in a dozen languages while IVR and agents cover far fewer well; statement, limit, and dispute intents likely dominate.

Reasoned inference

The SBI-linked brand likely brings PSU-influenced procurement rhythms — pilots need government-grade documentation and clear conduct audit trails.

Seller hypothesis — validate

Validate with the account team before outreach: Current early-bucket contact and roll-rate baselines · Collections BPO structure and dialer stack · Procurement route: direct or via SBI-group empanelment

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: A monoline issuer whose technology (processing, dialers, the ILA virtual assistant) is vendor-run, with PSU-influenced procurement rhythms; there is no internal AI-platform engineering franchise.

Why they won't build the full stack: Card-system integration, RBI-conduct-bounded collections dialogue, and multilingual speech must arrive as a governed, documented platform — exactly the shape SBI-grade procurement is structured to buy.

What management is signalling

Credit costs moderated through FY26 after the industry's unsecured stress cycle, with management guiding further normalization

Reported factQ4 FY26 earnings call · May 2026

GTM implication: Collections effectiveness remains the earnings lever — a conduct-perfect early-bucket coverage pilot lands on-message

Management has set out a cost-to-income improvement path for FY27

Reported factQ4 FY26 earnings call · May 2026

GTM implication: Service-line deflection in eight languages gives the cost-to-income target a measurable operational lever

What already exists (don't pitch this)
  • SBI Card app with statements and EMI conversion
  • ILA virtual assistant for FAQs
  • WhatsApp servicing notifications
  • Large outsourced dialer-led collections estate
What customers still can't do end-to-end (pitch this)
  • →Assistant is informational; disputes and actions go to agents
  • →Two-language IVR for a dozen-language base
  • →Early-bucket coverage is dialer-capacity-bound
  • →PTP follow-through is manual
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Pre-due & early-bucket collections
100% pre-due and day-1 attempts with matrix-bounded plans and in-channel payment; PTPs auto-followed.
With elevated industry credit costs, stopping bucket-0-to-1 rolls on a two-crore-card base is the single biggest earnings lever.
Friction today: Dialer capacity misses due-date coverage; conduct norms cap attempts; payment follow-through drops between call and app.
WhatsAppVoiceSMS
Card service line deflection
Top-15 intents resolved in-conversation in 8+ languages; humans reserved for disputes and complaints.
Statement, limit, reward, and dispute-status intents flood the line from a base that spans metros to small towns.
Friction today: Two-language IVR for a multilingual base; agents re-authenticate and read card screens.
VoiceWhatsAppApp chat
EMI-conversion & revolver engagement
Consent-governed EMI-conversion conversations with transparent cost explanation and in-channel confirmation.
Converting large purchases to EMIs is core fee income and reduces delinquency risk on stretched cardholders.
Friction today: EMI-eligible transactions get one SMS; conversion needs a conversation about tenure and cost.
WhatsAppVoice
Watch the change

Pre-due & early-bucket collections outreach: today vs the agentic model

Scenario: A first-jobber in Coimbatore is 4 days past due on a 38,000-rupee card bill and screens unknown numbers during office hours
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
WhatsAppVoiceSMSApp 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 · SBI Card
Card management systemCollections platformPayment gatewayDispute workflowCRMCard systemOffer engine

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

Trust & languages
HindiEnglishTamilTeluguBengaliMarathiKannadaGujarati

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 interactions2.5M
Seller assumption — replace in discovery
Current cost per interaction ($)$1.1
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$2.8M
Current operating cost / mo
$12.4M
Modelled gross benefit / yr
0.1 mo
Payback on Scale
212%
3-yr ROI (modelled)
Automated/assisted interactions per month1.4M
Modelled AI run-cost per month (usage + cloud, system estimate)$481K
New monthly operating cost$1.7M

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 SBI Card'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 SBI Card: Collections plus service deflection are two proven workflows on card-system integrations; scale scope fits, with expansion into EMI-conversion sales after credit-cost pressure eases.

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: Card management system, Collections platform, Payment gateway
  • · A named business owner for pre-due & early-bucket collections outreach
  • · Security review counterpart and policy sign-off (Card management system scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“Credit costs are the story the street asks about every quarter; conduct-perfect, full-coverage early-bucket outreach is the fastest operational answer you can point to.”

CIO / CTO

“The agent grounds on your existing card and collections systems — a bounded integration with complete audit logging that fits an SBI-grade governance review.”

COO

“Due-date coverage stops being a seat-capacity question; evening and weekend windows your rosters miss become your best-performing contact slots.”

Head of Collections

“Every due account attempted on day 1 in its own language, every settlement inside the approved matrix, every PTP chased automatically — with 100% scored calls.”

Chief Risk / Compliance Officer

“RBI recovery-conduct norms are embedded as hard constraints — windows, disclosures, escalation rules — with transcripts as standing audit evidence.”

CFO / Procurement

“Roll-rate improvement on a two-crore-card base plus service deflection gives a two-engine business case; a control-cohort pilot prices both before commitment.”

Outreach

Pre-built offer emails for SBI Card

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

India's largest pure-play card issuer with ~2 crore cards; industry-wide unsecured stress has pushed collections intensity up while a mass-market, multilingual base strains service capacity — strong fit, PSU-linked procurement pace.

Recommended next step

Propose a bucket-0/1 pilot on one portfolio segment: conversational due-date coverage for 60 days, roll-rate delta versus dialer-only control.

Entry: Pre-due & early-bucket collections outreach · 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.