Banks and financial-services brands use catalog.xmap.ai to map branch and ATM density against competitors, spot overlap worth consolidating, and find underserved areas for a digital-first expansion.
catalog.xmap.ai is a self-serve database of 140M+ real business locations across 40+ countries. Every record is an actual, physically-located business (not an estimate) with up to 36 structured fields: name, full address, latitude/longitude, category (three levels deep), brand and chain affiliation, hours of operation, phone and website, star rating and review count, open/closed status, and more.
You filter the catalog by category, brand, or geography in a live web interface, watch the matching record count update as you narrow the search, and export the results as a clean CSV file, ready to open in a spreadsheet, load into GIS software, or join against your own data.
The dataset refreshes every 30 days, so an export reflects recent openings, closures, and changes rather than a static snapshot from years ago.
Rationalizing a network means knowing exactly what coverage a closure would remove.
Digital-first challengers compete for the same customer without showing up on a map of branches.
Branch decisions increasingly face questions about equitable access to financial services.
See your own and competitor branch coverage across a market in one export.
Identify overlapping branches within a short distance of each other as consolidation candidates.
Find neighborhoods with population but no branch or ATM within a reasonable distance.
Monitor a rival bank's branch openings and closures as a signal of market strategy.
Scout retail partners for in-store banking counters based on existing foot traffic.
Rank alternative sites for a branch being relocated by traffic, access, and coverage impact.
Branch count across four districts, own and competitor combined.
Every export carries 36 columns; these are the ones banking teams use most.
| Field | Type | Why it matters here |
|---|---|---|
| category_level_3 | string | Distinguishes full branches, ATM-only locations, and in-store counters |
| brand_name / chain_flag | string / boolean | Separates your network from competitor banks |
| latitude / longitude | float | Drives every coverage and overlap calculation |
| open_status | string | Flags branch openings and closures for monthly monitoring |
| hours_of_operation | string | Reveals extended-hours or weekend-access gaps |
| traffic_score / dwell_time | numeric | Signals footfall potential for a relocation or in-store partnership |
| venue_hierarchy | string | Shows in-store banking counters and their host retailer |
| rating / review_count | numeric | A read on customer sentiment toward nearby branches |
A bank is reviewing which branches to keep ahead of a lease renewal cycle. The team exports its own and competitor branches across the region, identifies two branches four blocks apart with near-identical coverage, and proposes consolidating them while redirecting the savings toward an underserved suburb.
We'll pull a live sample for your category and market.