Each topic below explains the evidence, the business problem it creates, how GLOBEIR solves it, the benefits to your organisation, and how your data stays private and secure.
1. Branch Expansion
NBFCs use the same catchment and white-space analysis that banks use (see Banking & Finance): population and economic activity around each candidate location, existing competitor presence, road access and the performance of nearby branches. Mapping India's banking footprint, as Jan Dhan Darshak does for over 1.6 lakh branches and 4 lakh correspondents [10], shows how dense or thin financial coverage is in each area.
Business problem
Opening a branch commits rent, staff and years of fixed cost. Many NBFC expansion decisions still rest on local referrals and spreadsheets, so branches open too close to each other or to strong competitors while thinly served areas are missed. A weak location takes longer to break even and ties up capital that could fund lending.
Our solution
- Catchment analysis around each candidate site using population, economic activity, road access and travel time.
- White-space mapping that overlays existing branches, competitor presence and public banking-footprint data [10].
- Performance benchmarking of nearby existing branches to estimate potential for a new site.
- A ranked list of candidate locations delivered on a WebGIS map and as a report, with the NBFC Map as a ready starting point.
Benefits
- Expansion decisions backed by evidence rather than anecdote.
- Fewer overlapping branches and less internal cannibalisation.
- Earlier identification of underserved areas with lending potential.
- A repeatable method the strategy team can rerun every planning cycle.
Privacy & data security
- Catchment and white-space analysis runs on aggregated area-level data (population, activity, branch locations); individual borrower identifiers are not needed.
- Where existing branch performance is used, it is summarised at branch or area level and can be pseudonymised before analysis.
- Client data is used only for the agreed planning purpose and is not shared with or used for any other client.
2. Customer, Address and Collateral Verification
- Location-based KYC. RBI's KYC Master Direction requires the customer's live GPS coordinates in video-KYC recordings and the GPS coordinates on the watermarked photo in digital KYC, and connections from IP addresses outside India or spoofed IPs must be blocked [4]. These rules apply to RBI-regulated entities, including NBFCs.
- Address precision. India Post's DIGIPIN divides India into cells of about 4 m × 4 m, giving lenders an extra precise address attribute for KYC [11][12].
- Rural property as collateral. SVAMITVA has prepared more than 2.42 crore property cards from drone surveys, and the cards help rural owners use their property for bank loans [13]. This opens a geo-referenced collateral base for loans against property and rural housing finance.
- Field verification. Geotagged, time-stamped photos of the residence, business or asset at sanction and at end-use verification create an auditable record.
Business problem
NBFCs compete on turnaround time, but every loan still needs the customer, the address and the asset verified. Paper-based field reports are slow, hard to audit and easy to manipulate, and repeated visits add cost. At the same time, RBI requires GPS coordinates in video-KYC and digital KYC [4], so location evidence is a compliance requirement, not an option.
Our solution
- Geotagged, time-stamped verification visits for residence, business premises, vehicles and property through the My GLOBEIR app, with offline capture and sync.
- Automatic distance checks between the declared address and the captured location, with exceptions flagged for review.
- Support for precise address attributes such as DIGIPIN [11][12] in the geocoded customer and collateral database.
- Mapping of collateral, including geo-referenced rural property where SVAMITVA records are available [13], on a WebGIS map for credit and audit teams.
Benefits
- Faster verification with fewer repeat visits.
- An auditable evidence trail for each loan, useful for internal audit and regulatory inspection.
- Location evidence that supports RBI's GPS requirements for video-KYC and digital KYC [4].
- Access to a new geo-referenced rural collateral base for loans against property and rural housing [13].
Privacy & data security
- This topic handles highly sensitive data: customer addresses, GPS coordinates, KYC records and photos of homes and assets. Under the DPDP Act, location traces and geotagged photos of an identifiable person are personal data [14].
- Data is encrypted in transit (TLS 1.2 or higher) and at rest (AES-256), and access is limited by role (field officer, supervisor, branch, head office) with audit logs of access and changes.
- Where verification is part of a digital lending app, RBI's Digital Lending Directions allow only one-time access to camera, microphone or location for onboarding or KYC with explicit consent, forbid storage of biometric data and require data to be stored on servers in India [15]. GLOBEIR configures capture flows to fit these limits.
- Location tracking in the My GLOBEIR app applies to field staff, is optional and opt-in with a persistent notification, and is captured for work purposes only.
3. Collections Efficiency
Collection cases can be allocated by days past due, risk profile and customer location, and agents' routes optimised [16]. Collections and visits recorded with GPS stamps provide proof of visit, and larger lenders already use the GPS location of a transaction to flag suspicious activity [17].
Business problem
Collections are one of the largest field costs for an NBFC. When cases are allocated without regard to location, agents criss-cross territories, complete fewer visits per day and cannot always prove a visit happened. Supervisors lack a live view of field activity, which makes it hard to act quickly on overdue accounts.
Our solution
- Location- and delinquency-based case allocation so each agent receives a geographically compact set of cases [16].
- Daily route planning and GPS-stamped proof of visit and collection, through the My GLOBEIR app.
- Supervisor dashboards with Live Tracking of field teams and visit status.
- Collection and overdue heatmaps by branch and area on the NBFC Map and Heatmap views.
Benefits
- More visits and resolutions per agent day, with lower travel cost.
- Verifiable proof of visit that reduces disputes and false reporting.
- Faster supervisor intervention where collections are falling behind.
- Industry example: location-, risk- and overdue-based allocation with route optimisation is already used by Indian lenders to organise field collections [16].
Privacy & data security
- Two kinds of location data are involved: borrower addresses and the movement trails of collection staff. Both are personal data under the DPDP Act [14].
- Staff tracking is optional and opt-in with a persistent notification on the device, and is limited to work purposes.
- Supervisors see only their own teams and territories through role-based access; all access is logged.
- Borrower-level detail is visible only to users who need it; dashboards for management can run on aggregated data.
4. Fraud and Anomaly Detection
Common location red flags include an application address far from the device location at onboarding, several unrelated applicants at the same coordinates, collections recorded away from the customer's location, and dense clusters of early defaults in one locality. Spatial analysis brings these anomalies to the surface for investigation [4][17].
Business problem
Organised fraud, such as fake addresses, staged applications and fabricated collection records, often shows up first as a location pattern. Without spatial analysis these patterns are buried across separate origination, collection and default systems, and are found only after losses occur.
Our solution
- Rule-based checks on location evidence: distance between declared and captured locations, multiple applications at one point, and collections logged away from the customer's location.
- Cluster detection of early defaults and exceptions by locality and branch.
- Exception reports and map views for risk, audit and vigilance teams on WebGIS.
- All checks use the location of applications, visits and transactions; they do not use personal characteristics of borrowers.
Benefits
- Earlier detection of suspicious patterns, before losses build up.
- Investigators can focus on a short, ranked list of exceptions.
- Evidence packs (maps, coordinates, timestamps) that support internal action.
- Industry example: larger lenders already use the GPS location of transactions to flag suspicious activity [17].
Privacy & data security
- Fraud analytics combine KYC, device location and transaction location, which is among the most sensitive data an NBFC holds.
- Analysis can run on pseudonymised identifiers, with re-identification limited to authorised investigators.
- Audit logs record who accessed which exception and when.
- Analysis is based on locations and events only, never on the personal characteristics of individuals.
5. Portfolio Risk and Climate Disclosure
- NPA and delinquency hot spots mapped by branch, district and product show where stress is concentrated.
- Climate disclosure. Top-layer and upper-layer NBFCs are covered by RBI's draft Disclosure Framework on Climate-related Financial Risks, which asks for assessment of physical risk and geographic exposure [18].
Business problem
Management often sees NPAs as a single number or a branch table, which hides where stress is concentrated and why. Upper-layer NBFCs also face the prospect of reporting the geographic exposure of their portfolios to physical climate risk under RBI's draft framework [18], which needs every loan and collateral to be geocoded and linked to hazard data.
Our solution
- NPA and delinquency heatmaps by branch, district, product and vintage on the NBFC Map and Heatmap.
- Portfolio geocoding and overlay with flood, cyclone, heat and other hazard layers.
- Exposure metrics (outstanding by hazard zone, by district and by product) in a format ready for disclosure work.
- Periodic refresh so risk committees see trends, not one-off snapshots.
Benefits
- Recovery and credit policy can be targeted at specific areas rather than applied across the board.
- Early warning of geographic concentration of stress.
- Exposure metrics prepared in advance of climate disclosure requirements [18].
- Better-informed board and risk committee discussions.
Privacy & data security
- Portfolio hot-spot and hazard-exposure analysis works on aggregated, area-level data; individual borrower identity is not needed.
- Risk analysis is location- and hazard-based only; it does not use personal characteristics of borrowers.
- Geocoded loan data is held in India-hosted infrastructure or the NBFC's own environment, under role-based access.