Are you turning away some of the most creditworthy borrowers?
A tailor hoping to start a home-based business in Sri Lanka applies for a loan with two years of steady monthly transfers from her husband in Riyadh. But because she lacks a standard corporate payslip or a credit bureau record, the underwriting guidelines classify her cash flow as unverified and rejects the file.
Across South Asia and Africa, millions of households depend on remittances from the Gulf and other major corridors. They have reliable, recurring inflow, but lenders lack the operational tools to verify and underwrite it.
Why remittances have stayed out of credit
Historically, banks have treated remittances as a transactional service. Exchange houses competed on transfer fees and turnaround times, while credit risk teams viewed incoming wire transfers as personal deposits rather than qualifying signals.
There were practical operational reasons for this:
· Fragmented and multi-lingual documentation: A household’s remittance history is often spread across exchange house receipts, SMS alerts in local languages, wallet statements, and physical passbooks.
· Review costs exceeding loan margins: Small-ticket personal loans operate on thin interest margins. If a credit officer must spend hours translating receipts, matching cross-border names, and reconciling ledger lines, the operational cost of processing the application exceeds the revenue the loan generates.
· Regulatory frameworks: Credit policies and regulatory expectations have long been built around familiar proof of income: payslips, tax returns and bureau records. Income that arrives from abroad, in someone else's name, doesn't fit neatly into those checklists.
As a result, excluding remittances from credit models was a standard risk mitigation strategy. Given the current scale of these flows, that strategy leaves substantial lending volume unserved.
Sizing the lending opportunity
According to IFAD’s Sending Money Home report, migrants sent $728.6 billion to families in low- and middle-income countries in 2025. These funds do not arrive in sporadic, large sums. They typically move as transfers of $300 to $400 sent nine or ten times a year.
In Sri Lanka, remittance inflows surpassed a record $8 billion in December 2025. Nigeria recorded $22.8 billion, and Ethiopia reached $7.1 billion. The primary source regions for these corridors remain Saudi Arabia, the UAE, Kuwait, and Qatar.
Many remittance recipient can afford the repayments; lenders just lack a scalable way to confirm the money. That friction costs retail lenders millions in lost originations.
Early models (and their limitations)
A few institutions have introduced remittance-linked loan products, though most focus on the sender rather than the recipient:
· Sri Lanka’s Manusavi Scheme: This program provides loans to migrant workers, requiring repayments to be routed directly through foreign currency accounts.
· Ethiopian Diaspora Loans: Commercial Bank of Ethiopia (CBE) and Awash Bank offer diaspora mortgages and credit packages, but they evaluate the overseas worker's earnings rather than the domestic family's cash flow.
Most existing frameworks lend to the migrant worker abroad and use the remittance stream as a repayment mechanism. Another significant opportunity lies in underwriting the household receiving the funds, using their verified transaction history as a proxy for creditworthiness.
What remittance-ready underwriting requires
Building a functional underwriting process for remittance households requires specific data extraction and risk assessment capabilities:
1. Ingesting unstructured, multi-Language documents
Underserved borrowers rarely present clean digital statements. An effective system should be able to ingest and parse photos of exchange house receipts, passbooks, and digital wallet records across languages such as Arabic, Amharic, Tamil, and Malayalam, extracting sender details, dates, and amounts without manual intervention.
2. Evaluating household cash flow dynamics
Traditional scorecards check for a single domestic employer. Remittance underwriting evaluates the cadence and stability of the corridor: transaction frequency, seasonal dips, and variance. A transfer that goes through within a consistent five-day window for 18 consecutive months provides a clearer risk signal than an irregular lump-sum deposit.
3. Using device signals for alternative scoring
For many remittance recipients, a smartphone contains a more complete financial footprint than physical paperwork. Remittance deposits generate bank SMS alerts that accumulate over time.
With the borrower's explicit consent, an on-device risk engine like DeviceConnect can analyse transactional SMS data. This data provides strong predictive value:
· Layering alternative data onto traditional scores can make risk models 5-20 percent more predictive
· An IFC report highlighted device data as an established input for alternative scoring models.
Solving the intake bottleneck
The infrastructure gap in remittance underwriting mirrors the broader shift toward alternative data in emerging markets.
Tools like Atlas Origin handle the document layer by capturing, classifying, and verifying unstructured financial paperwork directly at intake, while Atlas Flow structures the application into an guided conversation via instant messaging apps. Combining this with privacy-safe device analytics turns fragmented cross-border transactions into an objective risk profile.
Many remittance households already receive steady money from abroad, month after month. With better intake and verification tools, lenders could start assessing these households on what that money shows.
Until next time,
Srijan
Co-founder
FinBox
