Southeast Asia Lenders Use AI to Reach Unbanked, FICO Data Shows

Unlocking Southeast Asia's Credit Market

More than 70% of Southeast Asian adults remain unbanked or underbanked. This segment represents a $1.5 trillion financial services opportunity. Digital financial services in the region's six largest economies could generate $60 billion annually. They are currently on track for $38 billion. This $22 billion gap reveals the commercial cost of financial exclusion.

Aashish Sharma, FICO's Head of Digital Strategy & Innovation, notes over 1 billion people in Asia-Pacific lack access to formal financial services. Expanding credit responsibly, without increasing risk or cost, presents a significant challenge for lenders.

Credit Risk and Geographic Constraints

Fitch reveals that banks in the Philippines, India, and Vietnam demonstrate the highest risk appetite within Asia-Pacific. This partly stems from expanding financial inclusion into less traditional credit segments. Non-performing loan (NPL) ratios show this trend: Vietnam's NPL reached 5.4%, Cambodia's 7.0%, and the Philippines' 3.44% by May 2026, a nine-month high.

Many unbanked consumers lack formal credit histories, salary slips, or collateral. Traditional underwriting models cannot assess them, not due to uncreditworthiness, but due to unavailable data. Physical banking infrastructure also limits access. As of March 2025, 468 Philippine cities and municipalities lacked any bank, with 45% in Mindanao.

Regulatory Tension and AI Solutions

Regulators across Asia-Pacific seek broader financial inclusion, prudent lending, and tighter fraud controls simultaneously. This creates inherent tension in policy design. The Philippines' Bangko Sentral ng Pilipinas (BSP) has actively promoted digital payments, exceeding its own targets two years early.

Its June 2025 guidelines mandate validation frameworks for AI model risk management in supervised institutions. However, a new 2026 rule requires rural digital banks to keep 70% of customers within their physical operating area. This risks limiting digital banking's reach into underserved communities.

AI-facilitated credit scoring uses alternative data, such as spending patterns, payment velocity, and cash flow dynamics. This provides a more accurate view of creditworthiness than traditional credit files.

Operationalising AI for Inclusion

Lenders can implement rules-driven strategies at origination, expanding access while maintaining strong risk controls. These strategies adjust rapidly to market changes or segment needs. Grab Finance demonstrates this approach, deploying 22 AI decision workflows across six Southeast Asian countries in under eight months.

This increased credit offer eligibility by approximately 50% for previously ineligible users, according to FICO. Banks that successfully implement AI-led inclusion will capture a new generation of first-time borrowers in the region. Failure to do so risks building the next NPL crisis.

The $22 billion gap in digital financial services is a decisioning problem, not a technology issue. Rigorous, transparent, and consumer-protected applied intelligence can close it.