AI Tools for Unbankable Customers: SME Playbook

A single stat should make any SME in Singapore sit up: about 58% of Indonesia’s workforce is “non-fixed income” and often excluded from mortgage financing because they can’t produce the usual salary slips and tax documents (reported in 2025). That’s not just a fintech problem—it’s a market-access problem. And it shows up everywhere: in how people buy homes, apply for credit, and even how they choose service providers.

MilikiRumah, a Jakarta proptech startup, is building a business around that gap. Their idea is straightforward: use AI and alternative data to score “unbankable” buyers fast, then route them to the right path—either a bank mortgage or a rent-to-own plan that creates a documented payment track record.

This matters for Singapore SMEs because the pattern is identical to marketing: your “unreachable customers” aren’t unreachable—they’re just invisible to your current filters. In this instalment of the AI Business Tools Singapore series, I’ll break down what MilikiRumah is really doing, then translate it into a practical digital marketing playbook you can run with.

What MilikiRumah gets right: alternative data beats old checklists

Answer first: MilikiRumah wins because it replaces slow, document-heavy eligibility checks with behavior-based signals.

Traditional lenders often rely on standard paperwork to infer repayment capacity. But for gig workers, small traders, freelancers, and cash-heavy microbusiness owners, those documents either don’t exist or don’t reflect reality. MilikiRumah’s platform reportedly uses 20+ alternative data points—including bank statements and cash flow patterns—to assess financial health and generate a predictive credit score within about an hour.

The operational impact is the real story: banks can take two to three weeks to process. If you’re a property developer, that delay kills momentum. If you’re an SME, that’s the equivalent of taking weeks to reply to a warm lead. Prospects move on.

The “credit score hospital” model (and why it’s smart)

MilikiRumah describes itself like a “hospital”: different treatments for different credit profiles.

• High score: send the buyer to a bank mortgage pathway.
• Near-miss but promising: enroll them in a 12-month rent-to-own (RTO) program to build a clean payment trail.
• Needs more time: use capital/funds to support offtake arrangements with developers (they’ve previously announced a large fund for this purpose).

That middle path is the key insight: don’t reject customers—rehabilitate them.

Singapore SMEs can apply the same thinking to marketing and sales: rather than writing off “not ready” leads, build a structured journey that turns them into qualified buyers.

The SME translation: stop marketing only to “bankable” customers

Answer first: Most SMEs aim their ads and content at people who already look like ideal customers. That’s safe—but it caps growth.

In marketing terms, “unbankable” doesn’t mean “unprofitable.” It usually means one of these:

• They don’t fit your usual persona (job title, company size, budget range).
• They don’t convert on your first offer (but may convert after education).
• They can’t prove intent in the ways your team expects (no form fills, no phone calls).

MilikiRumah’s advantage comes from finding proxy signals—real behaviors that correlate with future outcomes. SMEs can do this too using AI business tools and your existing data.

What “alternative data” looks like in digital marketing

You already have alternative data. You just don’t treat it as decision-grade.

Examples most Singapore SMEs can capture within a week:

• On-site behavior: time on key pages, return visits, product comparisons
• Content engagement: webinar attendance, PDF downloads, email click depth
• Chat signals: questions asked, objection patterns, urgency language
• Transaction breadcrumbs: partial checkouts, abandoned carts, repeat micro-purchases
• Response speed: how fast they reply after you follow up

A practical stance: lead forms are overrated as the only “intent signal.” If you’re only retargeting form-fillers, you’re ignoring the majority who are researching quietly.

Build your “marketing credit score”: a simple AI-led lead grading system

Answer first: You can create a “marketing credit score” by assigning points to behaviors that indicate readiness, then using AI to scale the routing.

You don’t need a complex data science team to start. The first version can be rules-based, then improved with AI as you collect outcomes.

Step 1: Define 6–10 behaviors that predict buying

Pick signals tied to revenue—not vanity metrics.

A B2B services SME might score:

• +10: visits pricing page twice in 7 days
• +8: views case study page
• +6: opens 2+ emails in a sequence
• +6: watches 50% of a demo video
• +5: asks about timeline or implementation in chat
• +3: visits “About” page (trust check)
• −5: only visits careers page

Then create three buckets:

• Ready now (hot): route to sales within 5 minutes
• Promising (warm): route to a nurture track
• Not yet (cold): route to education + retargeting

Step 2: Route like MilikiRumah—don’t treat everyone the same

MilikiRumah doesn’t push every buyer to a bank. It chooses the path.

Your SME version:

• Hot: sales call + strong offer + proof (case studies)
• Warm: “credit-building” journey: credibility content + low-risk offer
• Cold: awareness ads + value content + retargeting based on engagement

Here’s the mindset shift: nurture isn’t a newsletter. It’s a structured conversion rehab program.

Step 3: Use AI business tools to scale the workflow

You can apply AI without pretending it’s magic:

• AI chat to capture objections and tag intent (pricing, timeline, requirements)
• AI summarisation for sales: turn chat + email threads into a one-paragraph lead brief
• AI segmentation: cluster leads by the questions they ask (not just demographics)
• Predictive scoring (lightweight): many CRMs and marketing platforms now offer it; start small and validate against closed-won deals

If you do one thing in Q1 2026: connect your lead scoring to real outcomes (won/lost, deal size, time to close). Otherwise, you’ll optimise for noise.

The rent-to-own parallel: “credit-building” offers that convert hesitant leads

Answer first: Rent-to-own works because it reduces risk while building a proof trail. SMEs can mirror that with offers that create commitment and measurable progress.

MilikiRumah’s 12-month RTO program creates a documented payment history that improves mortgage approval chances. The marketing equivalent is a low-friction entry product that demonstrates value and creates proof.

Examples SMEs in Singapore can run this quarter

• Marketing agencies: a paid audit + 30-day pilot (instead of a 12-month retainer pitch)
• B2B SaaS: a guided onboarding package or assisted trial with success milestones
• Tuition/enrichment: diagnostic assessment + 4-lesson starter plan
• Renovation/home services: paid site inspection + concept preview + transparent costing

The rule: the starter offer must produce a concrete artifact—report, roadmap, prototype, before/after metrics—so the customer gains confidence.

A good “credit-building” offer makes the next purchase feel inevitable, not risky.

Practical January 2026 playbook: reach underserved segments with AI marketing

Answer first: If you want more leads in 2026, design for the segment your competitors ignore, then use AI to run the journey efficiently.

January is when many SMEs reset targets, budgets, and vendor lists. Buyers are active, but cautious. That’s the perfect time to tighten your funnel and build a lead “rehab” system.

A 14-day implementation checklist (realistic for SMEs)

1. Day 1–2: Audit your last 90 days of leads
   • What % were “not ready”? What happened to them?
2. Day 3–4: Define your 3 lead buckets (Hot/Warm/Cold)
3. Day 5–7: Create one “credit-building” offer
   • Pilot, assessment, starter package
4. Day 8–10: Implement tracking for 6–10 behaviors
   • Page visits, content engagement, chat tags
5. Day 11–12: Build 2 nurture sequences
   • Warm: proof + process + offer
   • Cold: education + problem framing + retargeting
6. Day 13–14: Add AI support
   • Chat intent tagging + auto summaries + basic lead routing

What to measure (so you don’t fool yourself)

Track these four numbers weekly:

• Lead-to-meeting rate (by bucket)
• Meeting-to-close rate (by bucket)
• Time-to-first-response (aim for minutes, not days)
• Cost per qualified lead (not cost per lead)

If your “unbankable” segment starts moving from Cold → Warm → Hot with improving conversion rates, you’re doing it right.

What this means for Singapore SMEs watching Southeast Asia

Answer first: Southeast Asia’s growth is increasingly coming from customers who don’t fit old definitions of “qualified.” AI helps you see them clearly.

MilikiRumah is reportedly preparing a Series A round in the first half of 2026 to scale its model. Funding aside, the underlying lesson is bigger: platforms win when they turn exclusion into onboarding.

If you sell across Singapore and the region—especially into Indonesia—this is also a reminder to localise your assumptions:

• Documentation norms differ.
• Income patterns differ.
• Trust signals differ.

Marketing that works in Singapore’s highly banked environment can underperform elsewhere unless you adapt the journey and proof points.

Next steps: build your own “unbankable-to-qualified” engine

The practical takeaway from MilikiRumah isn’t “use AI.” It’s: design a system that upgrades people from not-yet-qualified to ready-to-buy. That’s how you get more leads without endlessly raising ad budgets.

If you’re running a Singapore SME and you want 2026 growth, start by asking a sharper question than “How do we get more leads?” Ask: “Which customers are we accidentally filtering out, and what would it take to bring them in responsibly?”

That’s where AI business tools shine—scoring intent, automating follow-up, and keeping the journey personal enough to convert.