Mapping the Missing Signal
Mapping the Missing Signal

Locating millions of scorable micro-enterprises Indonesia's credit system cannot see.

Mapping micro-enterprise digital readiness and financial access at national population scale across 38 provinces and 500+ kabupaten, making visible what the credit system has never measured.

Nur Jihad Albar · UC Berkeley · Goldman School of Public Policy · 2026
Prepared for the interview process, Office of Staf Khusus Presiden Bidang UMKM dan Teknologi Digital
What this study does

A national-scale classification of every micro-enterprise household.

Indonesia has 20 million micro-enterprise households. Of these, only 19.3% (3,876,810 households) have any formal credit access. The remaining 80.7% operate entirely outside the formal financial system.

This study classifies all 20 million along two dimensions: whether the business operator is digitally active (uses internet for selling or e-banking) and whether the household has formal credit (KUR, bank, BPR, or koperasi). The most actionable finding: 2,621,446 households are digitally visible but financially invisible — generating the exact digital footprints that alternative credit scoring (PKA) could use, yet completely excluded from formal credit. Of these, 76.2% are Upgraders with savings accounts and no debt. 98.2% receive zero government programs.

Read the full paper (PDF) →

All figures are based on BPS SUSENAS March 2025 and SAKERNAS February 2025. This is a point-in-time snapshot. The framework is designed to be re-run on future survey waves.

Findings

Every micro-enterprise household falls into one of four groups.

20,063,735 micro-enterprise households classified by digital activity and formal credit access. Of these, only 19.3% have any formal credit. Click each group to see its full profile.

Digital activity
Formal credit access
Yes
No
Yes
No
Data Explorer

Province and Kabupaten Explorer

How digital readiness and financial exclusion concentrate across Indonesia.

Lower share
Higher share
No data / insufficient sample
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