Use case #0002

Product matching: how Cross-Sell AI recommends the next best loan product

A cross-sell recommendation that is wrong for the borrower is not just a missed sale — it is a relationship cost. A home loan borrower who receives a personal loan offer has been told, implicitly, that the institution does not know what kind of customer they are. A salaried borrower who receives an SME working capital offer has been told the institution does not know how they earn. The Cross-Sell Specialist AI recommends the next best product by matching the borrower's profile — income type, existing product, financial trajectory, and most recent signals — to the product that is most likely both to be approved and to genuinely serve the borrower's next financial need.

The product matching framework: four inputs to one recommendation

The Cross-Sell AI builds a product recommendation from four inputs processed simultaneously. The first is the borrower's current product and their behaviour on it — a borrower who makes prepayments on a home loan may be building equity towards a LAP; one who has never missed an SME instalment may be ready for a working capital enhancement. The second is the borrower's income and employment type — a salaried borrower's cross-sell path is different from a self-employed proprietor's, whose path differs from an SME's. The third is the borrower's financial trajectory — improving credit score, growing income credits, reducing TDSR (Total Debt Servicing Ratio) — which determines which products the borrower is now eligible for that they may not have been at origination. The fourth is the triggered signals — the specific combination of signals that crossed the readiness threshold determines which product fits the moment, not just the profile.

The output is not a single product name — it is a ranked product recommendation with a fit score for each, a specific loan amount range that the borrower's current profile supports, and the one or two reasons why this product fits this borrower at this moment, expressed in terms specific to their situation.

"The next best product is the one the borrower would have asked for themselves if they knew what was available and what they were eligible for. The Cross-Sell AI answers that question before they ask it."

Product recommendation for Orchard Buildworks: ranked matches

01
Recommended · Strongest fit · Act now

SME Working Capital Top-Up · SGD15–20 hundred thousand · 36 months

Orchard Buildworks has a 14-month track record of on-time repayment on their existing SGD28L SME term loan. GST revenue grew 34% YoY. A new GST registration in Philippines was filed last month — the expansion is underway. The SGD 150,000–SGD 200,000 working capital top-up gives the business the liquidity to fund the Philippines operations before revenues from the new territory come in. The instalment calculator use on Nov 12 suggests the proprietor is already modelling something in this range. Expected TDSR (Total Debt Servicing Ratio) post-top-up: 61% — within the 65% cap for SME borrowers.

94% fit
02
Alternative · Strong fit · If top-up declined

SME Term Loan (standalone) · SGD20–30 hundred thousand · 48 months

If the working capital top-up is not the right product for the Philippines expansion (e.g., if the borrower needs longer-tenor capital for machinery or infrastructure rather than working capital), a new standalone SME term loan at SGD20–30L for 48 months is the next match. The borrower's demonstrated repayment capacity on the existing loan supports this ticket. The longer tenor keeps the incremental instalment manageable at ~SGD55,000/month.

78% fit
03
Longer-term · 6–12 months out

Loan Against Property (LAP) · SGD40–60 hundred thousand · Against business premises

Orchard Buildworks owns the business premises (declared in loan documentation). If the Philippines expansion succeeds over the next 6–12 months, a LAP against the business premises at SGD40–60L would be the optimal capital structure for a larger phase 2 investment — secured, lower rate than an SME term loan, longer tenor. The Cross-Sell AI flags this as a future conversation, not an immediate offer.

58% fit · 6M horizon

The product-borrower fit matrix: what the Cross-Sell AI checks for each product

ProductBorrower profile fitKey eligibility checkDisqualifying signals
SME working capital top-up SME borrower with ≥12 months on-time, revenue growing, new market or product line visible Post-top-up TDSR (Total Debt Servicing Ratio) ≤65% · Existing loan at ≥60% repaid · No DPD in last 6 months GST filing irregularity · Revenue declining · Outstanding >85% of original
Home loan top-up HL borrower with ≥18 months on-time, property value appreciated, or income significantly grown Post-top-up LTV ≤75% · Income supports additional instalment · No DPD in last 12 months DPD in last 12 months · LTV would exceed 75% · Property in disputed jurisdiction
Loan Against Property (LAP) Borrower with clear property ownership, income to service, needing larger ticket than SME term allows Property valuation current · Clear title · LTV ≤60% · TDSR (Total Debt Servicing Ratio) post-instalment ≤60% Property in co-name without co-borrower · credit bureau <650 · DPD in last 6 months
Personal loan (top-up) Salaried borrower with strong repayment history, credit bureau improvement, personal financial need Salaried income confirmed · Post-instalment TDSR (Total Debt Servicing Ratio) ≤50% · credit bureau ≥700 · No missed instalment ever TDSR (Total Debt Servicing Ratio) already above 40% · SME borrower (not appropriate product) · Any DPD in last 6 months
Education loan (new) Salaried borrower nearing home loan maturity, income strong, dependent child approaching higher education age (17–20) Life stage signal · Income supports education instalment · Loan nearly closed = capacity freeing up No dependent child in profile · Loan still in early stage

The opportunity score panel: what the Cross-Sell AI shows the relationship manager

Cross-Sell Opportunity — Orchard Buildworks · LA-2024-1844 · Nov 14, 2025
Readiness score: 87/100 · Recommended: SME WC top-up SGD 150,000–SGD 200,000 · Outreach: today
Active signals contributing to 87-point score
14 consecutive on-time monthly instalments (last instalment: Nov 5) — zero DPD+30 pts
instalment calculator used Nov 12 — modelled a SGD15L loan at 13% over 36M+28 pts
GST outward supply Q3 FY2025: SGD1.84Cr — +34% vs Q3 FY2024+20 pts
Philippines GST registration filed Oct 28, 2025 — new state expansion+15 pts
Outstanding balance SGD16.8L vs original SGD28L — 60% repaid+20 pts → adjusted −26 pts (capped)
Total readiness score
87 / 100
Above 70-point outreach threshold · Category: SME expansion
Recommended outreach
WhatsApp today · RM call by Nov 16
Personalised message drafted · Specific to Philippines expansion context
● 94% product fit: SME WC top-up · Estimated new disbursement: SGD17.5L midpoint · Commission (referral partner Arjun): SGD21,875 at 1.25% · Expected decision: within 7 days of outreach
4Inputs to each recommendation — current product, income type, financial trajectory, triggered signals · All combined into a ranked fit score
94%Orchard Buildworks fit for SME top-up — 5 concurrent signals all pointing to the same need · Working capital for TN expansion
3Products ranked — #1 WC top-up now · #2 SME term if top-up declined · #3 LAP in 6–12 months when TN revenue established
SGD17.5LExpected disbursement at midpoint — SGD21,875 commission for referral partner Arjun · 7-day expected decision timeline post-outreach

The recommendation that is right for the borrower and right for the institution is the only recommendation worth making

A cross-sell recommendation that produces a disbursement the borrower cannot service is a disbursement that will become an NPL in 6 months. The institution earned the commission and lost the relationship — and the net credit cost exceeds the commission earned. The Cross-Sell AI's product matching explicitly checks post-disbursement TDSR (Total Debt Servicing Ratio), post-disbursement LTV, and current credit bureau before recommending any product — not because the institution is conservative, but because a loan that fits the borrower is the only loan that stays performing. A 94% fit score means the product is right for the borrower. It does not mean the borrower will accept — but if they do, both parties benefit.

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