PaisaMaps for businessObjectiveChoose the next branch locations
With PaisaMapsRank pincodes by spend, banking depth and enterprise density, then check distance to your existing branches.
OutcomeA branch list where each site has a catchment that can carry it.
For NBFCs: gold loan, MSME, microfinance, vehicle and consumer finance
Open the next branch where the book can grow.
An NBFC grows branch by branch, and every branch has to earn its cost from the pincodes around it. PaisaMaps ranks those pincodes by household income and spend, banking depth and local enterprise, so the next branch, agent or campaign goes where the demand is.
Area-levelnever about an individual borrower
One map, five kinds of lender
Read the same pincodes the way your product needs
Each kind of NBFC leans on a different mix of signals. Pick yours.
Gold loans
Reach where branches are thin
Gold-loan branches compete on reach. Read household spend against bank branches per lakh people to find areas with spending power and few branches nearby.
- Household spend by pincode
- Bank branches per lakh (district level)
- Distance rings around your own branches
MSME lending
Follow the small businesses
MSME registrations per lakh people show where small enterprise clusters, district by district. Pair it with household spend to find trading towns worth a branch.
- MSMEs per lakh people (Udyam, district level)
- Purchasing power by pincode
- Factories per lakh (state level) for context
Microfinance
Rank districts, then blocks
Read cropping intensity, enterprise density and banking depth together. Most rural pincodes carry a district estimate, and the map labels them, so rank districts and blocks rather than villages.
- Cropping intensity (state level)
- Bank branches and deposits (district level)
- Every estimate labelled as one
Vehicle finance
See who is ready to move up
The car-to-two-wheeler mix and car ownership show where an area is still two-wheeler-led, and income shows whether it can afford the step up.
- Car to two-wheeler ratio (VAHAN, district level)
- Cars per 1,000 people
- Household income by pincode
Personal & consumer-durable loans
Size the market by pincode
Purchasing power and household spend size the market for small-ticket personal and consumer-durable loans, and show where dealer and retailer tie-ups will see the most demand.
- Purchasing power and spend by pincode
- UPI value per person (district level)
- Exports to plan tie-ups
What you can achieve
Branches, agents and campaigns pointed at demand
ObjectivePhase a new-state entry
With PaisaMapsExport every scored pincode in the state with its signals and level, and rank them in your own model.
OutcomeA year-one and year-two plan, with the reasons written down.
ObjectivePoint sourcing and DSA effort
With PaisaMapsRead your branches against the strength of their areas, and spread field teams by market size.
OutcomeSourcing effort that follows the market, not the org chart.
ObjectiveAdd an area feature to your models
With PaisaMapsPull signals by pincode with an API key and join them to your book.
OutcomeA documented area input next to bureau and customer data, reviewed under your own governance.
In the workspace
Planning the next branches, screen by screen
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01
Read a candidate
Click a pincode: its opportunity score, how it compares with its district and state, and the signals behind it.
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02
Score your branches
Upload branches with a performance figure. Each is scored against its area, and the profile of your best branches surfaces.
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03
Compare the finalists
Line up to five candidates on opportunity, income, spend and risk.
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04
Track the pipeline
Every candidate carries a status and notes, so the expansion committee sees one list.
Use it the right way
Where to grow, not whom to lend to
Good for
- Choosing branch and agent locations
- Phasing a new state or region
- Sizing a product by region
- An area feature next to your own customer data
Not for
- Approving or declining an individual
- Replacing bureau data or your credit policy
- Anything that needs household-level income
- Telling two villages apart where both carry an estimate
A business case, start to finish
A gold-loan NBFC plans 20 branches in a new state
- Rank the stateEvery scored pincode on household spend, bank branches per lakh people and deposits per person.
- Find the gapsKeep pincodes with solid spend where branch density sits below the state's typical level.
- Learn from homeUpload the home-state branches with monthly disbursement to see which area profile the best ones share.
- Space them outDistance rings around each candidate rule out pairs that would draw on the same customers.
- PhaseThe top ten open first; the next ten wait for the first six months' results.
The decision
Twenty branch locations in two phases, each with its catchment and ranking saved to the project for the credit and expansion committees.
What the team walks away with
- A phased branch list with reasons
- Area signals joined on pincode for the NBFC's own model
- A PDF for the expansion committee
Who's involved
Who uses it, who reads it, who pays for it
Uses it every week
- Branch expansion manager
- Business strategy analyst
- Credit or sourcing analytics
Ranks pincodes, uploads branch performance, compares candidate locations and exports area signals.
What they getA branch shortlist with reasons, and area features ready to join to the book.
Reads and decides
- Head of distribution / branch banking
- Chief business officer
- Expansion and credit committees
Approves which states, districts and branch sites come next, and which area features enter the model.
What they getOne document per expansion decision, with every signal's source and level.
Pays for it
- Chief business officer
- Chief risk officer
- CTO (for API use)
Owns the expansion, analytics or data budget.
What they getBranches opened where the book can grow, and fewer that never break even.
- Built for branch networks
- Distance rings, side-by-side comparison and a saved-location pipeline, not just a data file.
- Honest granularity
- Banking and enterprise signals are published by district; we say so, and never present them as pincode measurements.
- Joins to your MIS
- Pincode is the key. Export as CSV, Excel or JSON, or pull it with an API key.
- Area-level only
- Nothing about any individual applicant, so it sits alongside your credit policy rather than inside it.
Before you buy
Questions we hear
Can this be used for individual credit decisions?
No. It's an area-level signal, the same for everyone in a pincode. Use it for where to grow, alongside your own customer-level data and credit policy.
How good is it in rural areas?
Most rural pincodes don't have data of their own yet, so they carry a district or state estimate, labelled as one. Use it to rank districts and blocks; don't read differences between two villages into it.
Can we see our own branches on the map?
Yes. Upload a CSV or Excel file with branch, pincode and a performance figure such as monthly disbursement. Each branch is scored against its area, and the file stays in your company, encrypted.
Where do the banking signals come from?
RBI branch and deposit statistics, and PhonePe Pulse for UPI value, all at district level. The signals page lists each source and level.
Keep exploring
Where to go next
Site selection
Shortlist candidate pincodes by purchasing power, check each catchment, compare up to five sites side by side and send a…
Explore →Credit & affordability
Use pincode income, spend and banking depth to prioritise sourcing and size products by region, joined to your own data on…
Explore →
Workspace
A shared workspace for expansion decisions: projects, location intelligence, site comparison, saved-location pipeline, your…
Explore →Tell us the state you're entering
We'll rank its pincodes with you on income, spend and banking depth, in about 20 minutes.