Credit intelligence for banks and funds · SEA

The intelligence layer
for private credit
in Southeast Asia

Independent bureau data. Automated deal ingestion. A prediction engine that learns from every deal you close. Supercash gives private credit fund managers the infrastructure institutional lenders take for granted — across P2P platforms, direct lending, supply chain finance, and bilateral deal flow.

Deal scoring — live Active
7
Markets covered
8 wks
Full deployment
9
Scoring factors
Day 1
Bureau data active
The problem

Fund managers are making
institutional decisions
with retail-grade data

01
Platform-only financials
Deal assessment relies on 12-month financial statements provided by the lending platform — unverified, unaudited, and the only data point available. No independent check exists.
02
No independent bureau access
Credit bureaus exist across SG, MY, TH, ID, AU, and NZ. Fund managers don't use them — not because they wouldn't want to, but because no one has built the integration layer.
03
Manual deal collection
Deal notifications arrive by email. Platform portals are logged into one by one. There is no unified view. Hours of operational overhead every week, per analyst.
04
Reactive portfolio monitoring
Deterioration is detected when payments are missed — not before. By the time a position is on the watchlist, the credit event is already in progress.
05
Allocation by spreadsheet
Country limits, platform concentration, FX exposure — managed manually. No systematic enforcement. No optimiser. No early warning when a limit is being approached.
06
Institutional cost to build
The technology exists — it lives inside Tier 1 banks. Building it in-house is a multi-year, multi-million dollar commitment. Most specialist fund managers have never tried.
07
Deal flow arrives from everywhere — and goes into a spreadsheet
Banks are pulling back from SME and mid-market lending across SEA, creating a structural referral pipeline to private credit funds. Direct bilateral deals, bank referrals, broker term sheets, supply chain receivables — deal flow now arrives from five different directions. No fund manager has a unified system to ingest, score, and track it all. Until now.
The platform

Six modules.
One platform.
Production-ready.

Supercash is modular by design. Deploy one module or all six. Each activates independently but they are built to compound — every module makes the others more powerful.

⟢
Deal origination
P2P platforms, direct bilateral deals, bank referrals, broker term sheets. API where it exists, email ingestion where it doesn't. Every deal from every source, in one place.
◈
Bureau integration
CBS, Equifax AU, illion, Experian, Centrix, Equifax NZ, SLIK (OJK). Independent borrower credit profiles triggered automatically on every deal.
⬡
AI decisioning
Your criteria encoded as rules on day one. ML default probability model activates as your deal history accumulates. Nine factors, four data sources, full SHAP explainability.
◎
Allocation optimiser
Hard concentration limit enforcement. Ranked rebalancing recommendations. FX-aware deployment suggestions. Your risk parameters, systematically enforced.
⟁
Loan management
Real-time repayment tracking. Overdue detection with recovery workflow triggers. Collection data feeds back into platform scoring automatically.
⊕
Automated reporting
Monthly LP report. Per-deal credit assessment. Daily risk snapshot. Generated automatically — no spreadsheet compilation, no manual assembly.
For banking institutions

A complete
AI banking stack.
Five products. One partner.

From the moment a customer contacts the bank to the moment a loan is repaid — or flagged for intervention — the full product suite covers every layer. Each product works standalone. Together, they compound.

SuperOne CCR
Agentic AI
SuperGuard
SuperCoach + Train
Supercash
SuperOne CCROmnichannel contact centreOne agent desktop. All channels. Every customer interaction — inbound and outbound — on a single screen, connected live to core banking.
⊞
Unified omnichannel inbox
Voice, WhatsApp, Telegram, Facebook, Zalo, Instagram, web chat, and email — all channels in one agent desktop. No switching. Full customer context on every contact.
◎
Intelligent routing
Skills-based, priority, and emotion-aware routing. VIP customers, distressed contacts, and high-urgency signals surfaced automatically — without manual monitoring.
⟢
Outbound campaign engine
Predictive dialler, multi-touch sequencing across voice and digital channels, A/B testing, propensity scoring, and campaign analytics.
3.4×campaign conversion vs manual dialler
◈
Core banking integration — live, zero rekeying
T24 (Temenos) REST/SOAP connector. Balance and statement pull, loan status, card block/unblock, dispute lodgement, OTP trigger, identity verification — all executed live from the agent desktop.
⬡
Customer journey intelligence
Every touchpoint across all channels stitched into a unified journey timeline. AI-generated narrative summaries surfaced to agents at the start of every interaction.
SuperOne AgenticAutonomous AI agentsAI agents that complete full banking workflows end-to-end — planning, executing across core banking and connected systems, recovering from errors — without human intervention.
⟁
Customer-facing agents
Autonomous end-to-end handling of the workflows that currently consume agent time.
Loan applicationAccount onboardingDispute resolutionFraud alert response
◎
Outbound agents
Proactive outreach agents that operate 24/7 across the customer portfolio without agent involvement.
Collections negotiationLoan renewalCross-sell orchestration
⊕
Internal agents
Agents that work behind the scenes — supporting supervisors and operations without customer interaction.
Supervisor copilotEscalation triageShift briefing
⬡
Agentic orchestration — the coordination layer
A single trigger — fraud signal, NPL alert, compliance breach, campaign event — simultaneously fires multiple agents and modules as a unified response. Manages agent-to-agent handoffs, parallel execution, context preservation, and conflict resolution. Every orchestrated action produces a full audit trail.
71%of inbound queries resolved without an agent
SuperGuardAI compliance guardrailsReal-time guardrails on every AI output. Every bank running any LLM needs this — whether they use SuperOne or not.
◈
Hallucination blocking
Real-time scoring on every AI-generated response. Outputs that fail factual grounding checks are blocked before reaching the customer.
⟁
PII masking and financial advice fence
Automatic PII detection and masking in stored logs. Hard fence preventing AI from delivering personalised financial advice outside approved scope.
⟢
Sensitive topic routing
Keyword and intent detection for distress, legal disputes, fraud indicators, and regulatory-sensitive topics. Automatic escalation to human agents with full context transferred.
⬡
Automated QA and regression testing
Daily accuracy dashboard across all bots and agentic workflows. Weekly regression suite of 500+ test cases run automatically. Monthly model retraining triggered by QA findings.
◎
Immutable compliance audit trail
Every AI action, guardrail trigger, and escalation decision logged with timestamps. Full export in regulator-ready format. 3-year retention as standard.
SuperCoach + SuperTrainAgent intelligenceReal-time guidance for every agent interaction. Continuous training loops that improve both human agents and AI models from every conversation.
◈
Real-time in-conversation guidance
Next-best-action prompts, script adherence nudges, compliance alerts, sentiment-triggered empathy prompts, and instant knowledge retrieval — delivered live in the agent desktop during every interaction.
⟁
Emotion AI — live and longitudinal
Turn-by-turn customer emotion monitoring across voice and text. In-desktop alerts when a customer shifts toward distress or frustration. Escalation prediction before the customer asks for a manager.
⬡
Automated post-interaction coaching
Every conversation generates a coaching summary for the agent. Every QA finding automatically creates a coaching action or a bot retraining trigger. The loop is closed without supervisor intervention.
⊕
Supervisor intelligence dashboard
Live agent heatmap, compliance nudge frequency, guidance acceptance rate, emotion arc summary across the team, and automatic coaching handoffs.
Supercash Credit IntelligenceCredit intelligenceThe data and prediction layer for the lending side of the bank. Bureau integration, NPL early warning, loan origination scoring, and collections intelligence.
◈
Loan origination scoring
Bureau data pulled and scored at intake on every loan application. Independent credit profile before a credit officer reviews a single document.
Day 1bureau data on every application
⬡
NPL early warning
ML model monitors every active loan for deterioration signals — bureau score changes, cash flow decline, payment pattern shifts. Flags elevated risk before the first payment is missed.
30dadvance warning on predicted defaults
⟁
Collections intelligence
Recovery probability score on every overdue account. Ranked collections queue — which accounts to contact first, through which channel, and at what point in the delinquency cycle.
3.4×recovery conversion vs manual collections
⊕
Regulatory credit reporting — NBC, BNM, OJK, BOT, MAS
Every credit decision, bureau pull, and scoring output is audit-logged with timestamps. Supercash generates regulator-ready credit portfolio reports directly from live portfolio data.
◎
Deal referral network
Loan applications that don't meet credit criteria are referred — pre-scored and bureau-verified — to Supercash's network of private credit funds.
Bank→Supercash→Credit fund
Prediction engine

A model that gets
more accurate
with every deal you close

LAYER 01
Rules engine
Active day 1
Your existing scoring criteria encoded as a weighted rules framework. Fully deterministic, fully explainable. Composite score on every deal from the first day of deployment.
LAYER 02
Default probability model
Activates month 6–9
Gradient-boosted model (XGBoost) trained on your resolved deal outcomes. Outputs P(default) per incoming deal. SHAP explainability on every prediction — MAS FEAT compliant by design.
LAYER 03
Early warning system
Activates month 12+
Monitors every active position for deterioration signals: bureau score changes, cash flow decline, platform behaviour shifts, macro FX triggers.
Deal SC-2026-0847 · Meridian Logistics Model recommends: Approve
82
Composite score / 100
P(default) = 0.08
Coverage

Seven markets.
Every bureau.
All connected.

🇸🇬
Singapore
Primary market
Credit Bureau Singapore (CBS)MAS-compliant disclosurePDPA consent framework
Platforms
Funding SocietiesValidus Capital
🇲🇾
Malaysia
BNM regulated
CCRIS (BNM)CTOS Data SystemsExperian MY
Platforms
Funding Societies MYCapBay
🇹🇭
Thailand
BOT regulated
NCB (Nat. Credit Bureau)Digital bank alt-dataPromptPay data feeds
Platforms
FinnomenaInnovestX
🇮🇩
Indonesia
OJK regulated
SLIK (OJK)Digital bank alt-dataFintech credit scores
Platforms
AmarthaInvestree
🇦🇺
Australia
Positive data sharing
Equifax AustraliaillionExperian AU
Platforms
Plenti
🇳🇿
New Zealand
Full credit history
CentrixEquifax NZ
Platforms
Harmoney
🌏
Expanding
Vietnam · Philippines · Cambodia
Bureau coverage mappedPlatform integrations in scopingContact us for roadmap
Data ingestion

API where it exists.
Email parsing
where it doesn't.

Every deal reaches the platform structured and scored — regardless of how the originating platform sends it.

Method A — Direct API
Authenticated platform connection
Where P2P platforms publish investor APIs, Supercash connects directly and polls for new deals, book-building updates, and repayment events in real time.
01OAuth authentication with platform investor portal
02Real-time polling for new deals and status changes
03Repayment events trigger collection tracking updates
04Bureau pull and scoring pipeline triggered automatically
Method B — Email ingestion
Automated email extraction
Where platforms don't expose APIs, Supercash reads your deal notification inbox (read-only OAuth) and extracts structured deal data from originating emails automatically.
01Read-only OAuth connection to PAM's notification inbox
02Platform identified by sender domain and email template
03Deal fields extracted from HTML body and PDF attachments
04Low-confidence fields flagged for one-click confirmation
05Corrections improve platform extraction model over time
Compliance

Built for the
regulatory environment
you operate in

◈
MAS FEAT compliant
Every model prediction includes SHAP value attribution — which factors drove the score and by how much. Explainability is not optional; it is built into the architecture.
◉
PDPA consent framework
Consent verification before personal data is processed. Withdrawal support built into the data pipeline. Bureau pulls triggered only after consent confirmation.
⟁
Immutable audit trail
Every deal decision, bureau pull, score calculation, and model recommendation is audit-logged with timestamps. Full export in MAS report format, JSON, or CSV.
⊕
Data ownership
Your deal data, credit reports, scoring history, and model outputs are your property. Supercash does not use client outcomes to train models serving other clients without explicit written consent.
⬡
Human-in-the-loop
Supercash recommends. Your team decides. Every investment requires a human approval action. The platform never auto-approves, auto-commits capital, or acts without instruction.
⟢
3-year log retention
Configuration changes, guardrail triggers, and decision logs retained for three years as standard. SIEM export available for integration with compliance platforms.
◎
Multi-regulator framework
Reporting formats and audit trail structures built for NBC (Cambodia), BNM (Malaysia), OJK (Indonesia), BOT (Thailand), and MAS (Singapore). One platform, every regulator.

The platform is
live.
Would you like
a walkthrough?

We demonstrate the working platform — including a live bureau pull on a consented test borrower — not slides. Bring your deal flow. We'll show you what it looks like scored.

Singapore · Private credit fund managers · Banking institutions · Confidential enquiries welcome