Affordable Housing - Branch Visit Note
- Priyanka Deepak Saraf
- 2 days ago
- 6 min read
Three Lenders, Three Moats
Home First Finance · Aadhar Housing Finance · Aavas Financiers
QUICK VIEW All three lenders target the same customer earning roughly ₹40,000–50,000/month with loan sizes of ₹15–25 lakh. The similarities end there.
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Visible in the Field
Macro tailwinds are one thing; ground-level conviction is another. My recent field visits across affordable housing lenders spanning branch networks, DSA ecosystems, and borrower profiles point to a demand environment that is structurally better than the headline numbers capture. Ticket sizes are inching up, first-time buyer intent remains strong, and PMAY 2.0 is beginning to show up in application pipelines. The housing super-cycle thesis, built on urbanisation, formalisation, and policy support, is no longer theoretical it is visible in the field.
Snapshot: Key Metrics Across The Three Lenders
Metric | Home First Finance | Aadhar Housing | Aavas Financiers |
Avg borrower income | ₹45–50k/month | ₹40–50k/month | ₹40–50k/month |
Average ticket size | ₹18–22 lakh | ₹15–20 lakh | ₹20–25 lakh |
Monthly branch disb. | ~₹5 cr | ~₹7 cr | ~₹8 cr |
Login → Sanction | ~80–85% | 60–70% | ~35% |
Sanction TAT | ~2 days | ~2 days (salaried) | 3–4 days |
Bounce rate | ~12% | ~14% | N/A |
90+ DPD | ~1.9% | N/A | N/A |
BT-out ratio | 4–5% | N/A | ~7% |
Yield | ~12.2% | N/A | ~12% |
DSA / connector payout | 0.3–0.4% (sole-sellers) | 0.6–1.0% DSA; 0.4% Mitra | N/A |
Core moat | Speed + connector loyalty | Branch replication + distribution | Gov-scheme collateral edge |
Field view | ● POSITIVE | ○ NEUTRAL | ○ NEUTRAL |
Home First Finance (Kalyan Branch)
Metric | Value |
Monthly leads | 120-130 |
Lead → Login | Login → Sanction | ~30% | ~80-85% |
Overall lead conversion | ~25-30% |
Monthly disbursements | ~₹5 crore |
Average ticket size | ₹18-22 lakh (up from ₹13 lakh pre-builder onboarding) |
Branch AUM | ₹86 crore | YoY growth ~65% |
Relationship Managers | 7 RMs (up from 3–4 a year ago) |
RM productivity | ~5 property discussions/day; 3–4 new builder additions/month |
New property legal + tech TAT | Sanction TAT | 4-5 days | ~2 days (independently verified by channel partner) |
Bounce rate | ~12% |
30+ DPD / 90+ DPD | ~2.6% / ~1.9% (improved from 2.1% QoQ) |
SARFAESI (last 12 months) | 67 properties repossessed and sold; zero principal losses |
BT-out rate | ~4-5% |
Co-lending share (Mumbai region) | ~20% | Partners: CBI, UBI, Axis |
Pricing: regular / co-lend | ~12.2% / ~11.75% (end-customer range: 8.9–10.25%) |
Portfolio mix | 97% home loans (apartments) / 2% LAP |
Key Takeaways
Connector exclusivity is real, not claimed. 70% of connectors are sole sellers who route business exclusively to Home First. At 0.3–0.4% payout versus industry DSA rates of 1%+, the economics are compelling. The 16-year channel partner visited acts as a pre-screening filter effectively outsourced first-pass credit. This cannot be easily replicated.
Speed is embedded in the process, not the pitch. 2-day sanctions validated independently by both branch staff and channel partner. Account aggregators, PAN/GST/UAN validation and geo-tagged field visits run in parallel. Soft approvals issue within minutes of login. In affordable housing, where customers risk losing property bookings on delays, TAT is a structural moat.
RM incentive alignment reduces origination risk. Variable pay: ~45% disbursements / ~50% collections / ~5% builder onboarding. The originator has a direct economic stake in repayment. The 67 SARFAESI recoveries with zero principal losses are the output of this structure.
Builder ecosystem is scaling with ticket-size implications. ~65 formal builder relationships in Kalyan alone. Average ticket has risen from ₹13L to ₹18-22L. Portfolio remains 97% apartments. Monitor builder concentration and construction finance exposure as the book scales.
Co-lending is structural, not opportunistic. ~20% share in Mumbai region across CBI, UBI and Axis. ~45 bps rate arbitrage is a cost-of-funds lever neither Aadhar nor Aavas is deploying at comparable scale.
Auto-prepayment product drives stickiness. Customers can set up an additional monthly ACH above EMI with a rate benefit for opt-in. Channel partner described it as among the easiest features to sell. Product differentiation of this kind matters in a commoditized mortgage market.
THE REAL TEST: Can connector loyalty, SARFAESI discipline and 80–85% login-to-sanction be sustained across a materially larger network? The Kalyan evidence is encouraging. The risk is builder concentration as construction finance grows. |
Aadhar Housing Finance (Thane Branch)
Branch Type | Monthly Disb. Threshold | Team Configuration |
Ultra Micro Branch | ₹30 lakh/month | 3–4 sales people |
Micro Branch | ₹50 lakh/month | 3–4 sales people |
Small Branch | ₹75 lakh+/month | Credit + collection officer added |
Main Branch | ₹1 crore+/month | Full credit, legal, technical |
Sales Role | Monthly Target | Max Incentive |
BSM (manages 3 DSTs) | ₹1 crore/month | ₹5 lakh |
TSM (SM + DST team) | ₹1.2 crore/month | ₹6 lakh |
ASM (large team) | ₹1.5 crore/month | ₹7 lakh |
Operating Metric | Value |
Branch disbursements | ~₹7 crore/month |
Salaried sanction TAT | ~2 days |
Login → Sanction | 60–70% | Sanction → Disbursement: 50–60% |
LTV (sub-₹30L / sub-₹75L) | 90% / 80% |
DSA payout / Mitra payout | 0.6–1.0% / 0.4% |
Bounce rate | ~14% |
Sales attrition | ~20% annualized |
RPUs in MMR | 2 (model operational since 2018) |
Key Takeaways
Capex-efficient expansion by design. Branches are upgraded only after crossing defined volume thresholds. Infrastructure investment follows proven demand. Smaller locations share credit and technical resources with the hub Main Branch. This limits cost drag during ramp-up.
Distribution extends beyond real estate channels. The Aadhar Mitra network includes India Post, Common Service Centres, JK Cement and Gram Haat. These channels reach informal-income borrowers that traditional DSAs cannot, at 0.4% payout, well below standard DSA economics.
RPU model preserves local underwriting intelligence. RPUs keep credit decisions close to the market. For informal-income borrowers, local market knowledge is the underwriting edge.
20% sales attrition is the primary structural watch item. Sales managers are on-roll (positive), but 20% annualized attrition implies the branch team turns over meaningfully every five years. In a relationship-driven model this is a recurring drag. A 60–70% login-to-sanction (vs. 80–85% at Home First) reflects the conversion cost of this churn.
THE REAL TEST: Aadhar’s story is operational compounding, not near-term catalysts. The push question: can per-employee productivity improve materially as headcount scales, given 20% attrition? |
Awarding Bonus Point for higher payout to Mahila Aadhar Mitra 😊 |
Aavas Financiers (Thane Branch)
Metric | Value |
MMR AUM (13 branches) | ₹250 crore |
Monthly disbursements | ~₹8 crore | Q1 FY26 peak: ~₹15 crore |
FY26 disbursements (MMR) | ₹70-80 crore |
Two-year trend | ₹4.5–5 cr (2 yrs ago) → ₹6.5–7 cr (1 yr ago) → ₹8 cr (current) |
Average ticket | ₹20–25 lakh | Borrower income: ₹40,000–50,000/month |
Lead → Login | ~30% | Login → Sanction: ~35% |
Sanction TAT | 3–4 days (self-employed: 4-5 days) |
Yield | ~12% |
BT-out rate | ~7% (elevated vs. Home First at 4-5%) |
Banking data via aggregator | ~70% automated pull |
The MHADA / CIDCO Collateral Angle
The most analytically material observation from the Aavas visit is not visible in the financial statements: government-scheme properties in MMR are allotted at prices substantially below open-market value, creating embedded equity for both borrower and lender from day one.
Project Type | Allotment Price | Est. Market Value | Effective LTV vs. Market |
CIDCO scheme (illustrative) | ₹27–28 lakh | ~₹50 lakh | ~48% LTV to market (vs. 90% to cost) |
MHADA scheme (illustrative) | ₹15–21 lakh | ~₹40–41 lakh | ~44–51% LTV to market |
Company-provided examples. Market values per company; not independently verified.
Key Takeaways
Headline LTV systematically overstates credit risk. A 90% LTV on a CIDCO allotment at ₹27 lakh equals ~48% LTV to market value of ~₹50 lakh. Recovery outcomes likely benefit structurally from embedded equity that most models do not price in.
35% login-to-sanction is a deliberate design choice, not a process weakness. Mandatory physical verification for cash-income customers, multiple valuations on larger tickets (lowest used for underwriting), conservative rental income assumptions. For the informal self-employed segment, this is the right trade-off.
Supervisor mandate is a material productivity lever. ~1,100 supervisors now required to source ≥1 disbursement/month personally. Per-RM target: ~5 logins/disbursements per month. On a 4,000-4,200 RM base, every ₹20L of per-employee improvement implies ~₹80–100 crore of incremental monthly disbursements network-wide.
7% BT-out is elevated and warrants monitoring. Compared with 4–5% at Home First. In a competitive or rising-rate environment BT-out can accelerate. Track alongside net AUM growth disclosures.
Disbursement trajectory is the central diligence question. ₹8 crore/month now versus ₹15 crore in Q1 FY26. Medium-term trend from ₹4.5-5 crore two years ago remains upward.
THE REAL TEST: Is the current ₹8 crore/month MMR disbursement run-rate a cyclical trough (post Q1 spike) or a structural deceleration? The answer drives the near-term earnings revision story. |
WHAT I'M TAKING BACK
Physical verification cannot be digitized away. All three companies have deployed account aggregators, digital document collection and mobile underwriting. All three still conduct physical verification for self-employed borrowers. Dairy farmers during business hours; newspaper vendors at different times. This is why affordable HFC is not a bank digital-lending play and why branch density remains a genuine moat.
Property beats borrower in a stressed recovery. Legal title, technical quality and collateral marketability came up independently across all three discussions. Home First’s 67 SARFAESI recoveries without principal loss and Aavas’s MHADA/CIDCO embedded equity reflect the same principle: loss-given-default in affordable housing is determined by the property, not the income.
Sourcing channel discipline is a leading indicator of NPA. Home First at 0.3-0.4% with 70% sole-seller loyalty versus Aadhar at 0.6–1.0% DSA payouts. Lower-cost, higher-loyalty channels produce higher-quality files. Distribution economics show up in NPA with a lag.
A housing super-cycle does not lift all boats equally. It separates the franchises that are built to scale from those that are built to survive. What our field visits confirmed is that the best lenders in this segment do not just originate loans; they build ecosystems: of connectors, builders, verifiers, and repeat borrowers that become harder to displace with every passing quarter. The ground-level conviction we set out to test has been strengthened. The thesis is intact. The differentiation is clearer.
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