Auto-Lending Feature Adoption

The Challenge

P2P lending carries real risk (non-performing loans), and in 2017 only ~1% of Indonesians participated in the stock market — a savings-first culture, not an investing one. After two years of market education, the opportunity was to turn one-off lenders into habitual ones.

Solution & Process

I applied Nir Eyal’s Hooked framework and BJ Fogg’s Behavior Model (Behavior = Motivation × Ability × Trigger) to diagnose the blocker: users were motivated, but reviewing individual loan campaigns against their own risk criteria was too much friction — too little “ability.”

The fix, inspired by bank auto-debit: an auto-lending feature where users pre-set their own criteria (credit rating, interest rate, tenor), and available funds are matched automatically — the system never overrides their preferences, it just removes the manual review step.

• Onboarding drip campaign introducing auto-lending in the new-user email series
• Relationship managers trained to pitch it directly to high-value users
• Live demos featured at every lender event, online and offline
• Targeted re-engagement for high-value-but-inactive users (≤3 transactions in 90 days)